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Abstract Under the influence of diapir structure, the formation pressure system is complicated. The characteristics of high temperature and high pressure are obvious, the prediction is difficult, and complex accidents such as well kick and leakage are frequent, which seriously restrict the efficient development of oil and gas resources. Therefore, taking Yinggehai Basin in China as an example, combined with the evolution characteristics of diapir structure, the influence of diapir structure on abnormal high-pressure, wellhole collapse and fracture is analyzed. Three pressure calculation methods are selected, and the distribution rules of pressures and safety density window are analyzed, too. The results show that the diapir structure and its associated fault not only constitute the fluid transport system, but also make the deep overpressure transfer upward and accumulate into high pressure in the shallow formation, and the development of the associated fault destroy the integrity of the formation rock and reduce the strength of the rock. The upwelling of hot fluid changes the local geothermal conditions, reduces the hydrocarbon generation threshold of shallow source rocks, promotes the evolution of clay minerals, causes hydrothermal expansion, and enhances the shallow high pressure. In high-temperature environment, the cooling effect of drilling fluid will produce heating stress, change the stress distribution around the wellhole, and increase the risk of wellbore instability. Additionally, under the influence of diapir structures, the pore pressure in deep formations increases, while the fracture pressure decreases, resulting in a significantly narrowed safe density window. The safety density window width generally presents a half-spindle shape, and with the increase of depth, the window width increases first and then decreases.

Abstract In order to address the problem of data heterogeneity, in recent years, personalized federated learning has tailored models to individual user data to enhance model performance on clients with diverse data distributions. However, the existing personalized federated learning methods do not adequately address the problem of data heterogeneity, and lack the processing of system heterogeneity. Consequently, these issues lead to diminished training efficiency and suboptimal model performance of personalized federated learning in heterogeneous environments. In response to these challenges, we propose FedPRL, a novel approach to personalized federated learning designed specifically for heterogeneous environments. Our method tackles data heterogeneity by implementing a personalized strategy centered on local data storage, enabling the accurate extraction of features tailored to the data distribution of individual clients. This personalized approach enhances the performance of federated learning models when dealing with non-IID data. To overcome system heterogeneity, we design a client selection mechanism grounded in reinforcement learning and user quality evaluation. This mechanism optimizes the selection of clients based on data quality and training time, thereby boosting the efficiency of the training process and elevating the overall performance of personalized models. Moreover, we devise a local training method that utilizes global knowledge distillation of non-target classes, which combined with traditional federated learning can effectively address the issue of catastrophic forgetting during global model updates. This approach enhances the generalization capability of the global model and further improves the performance of personalized models. Extensive experiments on both standard and real-world datasets demonstrate that FedPRL effectively resolves the challenges of data and system heterogeneity, enhancing the efficiency and model performance of personalized federated learning methods in heterogeneous environments, and outperforming state-of-the-art methods in terms of model accuracy and training efficiency.

Abstract Corticosteroids have always been recommended for severe cases of COVID-19. However, the efficacy of treatment with corticosteroids for COVID-19 during the SARS-CoV-2 omicron outbreak in China has not been reported. Clinical data from 406 patients hospitalized for severe/critical COVID-19 from December 2022 to January 2023 at six hospitals in Chongqing were retrospectively analyzed. The primary outcome was all-cause mortality at 28 days in the groups with and without corticosteroids treatment after propensity score matching (PSM). Secondary outcomes were to compare in-hospital mortality and length of survival time with corticosteroids and those without corticosteroids. This study included 406 patients with severe or critical COVID-19, divided into the corticosteroids group (231, 56.9%) and non-corticosteroids group (175, 43.1%). After PSM, the use of corticosteroids did not reduce all-cause mortality at 28 days (42.5% vs. 39.1%). Univariate analysis showed that corticosteroids were not associated with improved all-cause mortality at 28 days [hazard ratio (HR), 1.019; 95% confidence interval (CI), 0.639–1.623; p = 0.938]. Multivariate analysis showed similar results (HR, 1.047; 95% CI, 0.633–1.732; p = 0.858). Among non-survivors, the survival time was significantly larger in those who received corticosteroids compared with the non-corticosteroid users [median 13 (IQR 6.5–15.5) vs. 6 (4-11.25), p = 0.007]. The use of systemic corticosteroids in severe/critical COVID-19 may provide certain potential survival benefits but does not improve prognosis.

Abstract Epidermal growth factor receptor wild type lung adenocarcinoma (EGFRWT LUAD) still has limited treatment options and unsatisfactory clinical outcomes. Ferroptosis, as a form of cell death, has been reported to play a dual role in regulating tumor cell survival. In this study, we constructed a 3-ferroptosis-gene signature, FeSig, and verified its accuracy and efficacy in predicting EGFRWT LUAD prognosis at both the RNA and protein levels. Patients with higher FeSig scores were found to have worse clinical outcomes. Additionally, we explored the relationship between FeSig and tumor microenvironment, revealing that enhanced interactions between fibroblasts and tumor cells in FeSighigh patients causing tumor resistance to ferroptosis. To address this challenge, we screened potential drugs from NCI-60 (The US National Cancer Institute 60 human tumour cell line anticancer drug screen) and Connectivity map database, ultimately identifying 6-mercatopurine (6-MP) as a promising candidate. Both in vitro and in vivo experiments demonstrated its efficacy in treating FeSighigh EGFRWT LUAD tumor models. In summary, we develop a novel FeSig for predicting prognosis and guiding drug application.

Abstract Lung adenocarcinoma (LUAD), a prevalent type of non-small cell lung cancer (NSCLC), was known for its diversity and intricate tumor microenvironment (TME). Comprehending the interaction among human immune-related genes (IRGs) and the TME is vital in the creation of accurate predictive models and specific treatments. We created a risk score based on IRGs and designed a nomogram to predict the prognosis of LUAD accurately. This involved a thorough examination of TME and the infiltration of immune cells in both high-risk and low-risk LUAD groups. Furthermore, the examination of the association between characteristic genes (BIRC5 and BMP5) and immune cells, along with immune checkpoints in the TME, was also conducted. The findings of our research unveiled unique immune profiles and interactions among individuals in the high- and low-risk categories, which contribute to variations in prognosis. LUAD demonstrated significant associations between BIRC5, BMP5, immune cells, and checkpoints, suggesting their involvement in disease advancement and resistance to medication. Furthermore, by correlating our findings with a multidrug database, we identified specific LUAD patient subsets that might benefit from tailored treatments. Our study establishes a groundbreaking prognostic model for LUAD, which not only underscores the importance of the immune context in LUAD but also paves the way for advancing precision medicine strategies in this complex malignancy.

Abstract The high‐voltage pulse discharge technology, which is based on the electrohydraulic effect, can generate powerful, controllable, and repetitive electrohydraulic shock waves (EHSWs) in underground confined space, so it has been applied in the petroleum industry to improve the permeable of the reservoir. In this paper, a numerical model based on LS‐DYNA is built to study the damage analysis of the cement sheath and rock subjected to EHSWs during perforation completion. The results show that the stress state of the cement sheath and rock surrounding the perforation hole is determined by the shock pressure from both the perforation hole and the wellbore; the damage of the cement sheath and rock is mainly caused by tensile stress; the damage zone of the cement sheath is mainly distributed on the inner surface and near the perforation hole, while the damage zone of rock is distributed near the perforation hole; after multiple discharges, the damage of cement sheath and rock gradually accumulates, and the damage zone eventually forms a vertical plane along perforation holes. Overall, these results provide guidance for the safe application of the high‐voltage pulse discharge technology in the oil field.

Abstract Background This study aims to evaluate the effect of various background reference regions on spinal 18F-FET PET imaging, with a focus on distinguishing between spinal tumors and myelitis. To enhance diagnostic accuracy, we investigated the pons and several other spinal cord area as potential references, given the challenges in interpreting spinal PET results. Results A retrospective analysis was conducted on 30 patients, 15 with cervical myelitis and 15 with cervical tumors, who underwent O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) PET/MR imaging. The stability of uptake across four regions, including the pons, C2, C2–C7, and T1–T3, was compared. The standardized uptake value ratio (SUVR) was then evaluated using various background regions, and their effectiveness in differentiating between spinal tumors and myelitis was compared. Additionally, we correlated the SUVR values derived from these regions with the Ki-67 proliferation index in tumor patients. The study found no significant difference in SUVmax (U = 110, p = 0.93) and SUVmean (U = 89, p = 0.35) values at lesion sites between myelitis and tumor patients. The pons had the highest average uptake (p

Abstract The current extension limit prediction model for offshore extended-reach well (ERW) in mudstone does not consider the formation collapse, which poses a huge risk to offshore drilling construction. To address this problem, this paper presents new open-hole extension limit prediction model for ERW. By considering formation collapse, rate of penetration (ROP), and annular pressure loss, the extension limit models during normal drilling and tripping were derived. The sensitivity of geological and engineering factors was evaluated by analyzing limits for wells 1H and 2H. The research results showed that: (1) The extension limit increases with the ROP and formation collapse duration, but decreases with the increase in mud weight, plastic viscosity, and flow rate. (2) In ERWs, the mud flow rate has a significant impact on the extension limit than the plastic viscosity of mud fluid. However, mud weight has the least impact compared to the two. (3) Considering various parameters, the predicted extension limit of well 1H, when the mud weight is 1.16 g/cm3 [9.67 ppg], is 1593.28 m [5225.96 ft] less than the limit when the collapse period is not considered.

Abstract Background In HBV-associated HCC, T cells often exhibit a state of functional exhaustion, which prevents the immune response from rejecting the tumor and allows HCC to progress. Moreover, polymerase-specific T cells exhibit more severe T-cell exhaustion compared to core-specific T cells. However, whether HBV DNA polymerase drives HBV-specific CD8+ T cell exhaustion in HBV-related HCC remains unclear. Methods We constructed a Huh7 cell line stably expressing HA-HBV-DNA-Pol and applied co-culture systems to clarify its effect on immune cell function. We also examined how HBV-DNA-Pol modulated PD-L1 expression in HCC cells. In addition, HBV-DNA-Pol transgenic mice were used to elucidate the underlying mechanism of HBV-DNA-Pol/PD-L1 axis-induced T cell exhaustion. Results Biochemical analysis showed that Huh7 cells overexpressing HBV-DNA-Pol inhibited the proliferation, activation, and cytokine secretion of Jurkat cells and that this effect was dependent on their direct contact. A similar inhibitory effect was observed in an HCC mouse model. PD-L1 was brought to our attention during screening. Our results showed that the overexpression of HBV-DNA-Pol upregulated PD-L1 mRNA and protein expression. PD-L1 antibody blockade reversed the inhibitory effect of Huh7 cells overexpressing HBV-DNA-Pol on Jurkat cells. Mechanistically, HBV-DNA-Pol interacts with PARP1, thereby inhibiting the nuclear translocation of PARP1 and further upregulating PD-L1 expression. Conclusions Our findings suggest that HBV-DNA-Pol can act as a regulator of PD-L1 in HCC, thereby directing anti-cancer immune evasion, which further provides a new idea for the clinical treatment of liver cancer.

Purpose This investigation leveraged the SEER database to delve into the progression patterns of PTC when left untreated. Furthermore, it aimed to devise and authenticate a nomogram for prognosis prediction for such patients. Methods We extracted data from the SEER database, focusing on PTC-diagnosed individuals from 2004-2020. To discern disease progression intervals, median survival times across stages were gauged, and the disease progression time was estimated by subtracting the median survival time of a more severe stage from its preceding stage. Prognostic determinants in the training set were pinpointed using both univariate and multivariate Cox regression. Using these determinants, a prognostic nomogram was crafted. Results In untreated PTC patients, those in stages I and II had a favorable prognosis, with 10-year overall survival rates of 86.34% and 66.03%, respectively. Patients in stages III and IV had a relatively poorer prognosis. The median survival time of stage III, stage IVA, stage IVB and stage IVC patients was 108months, 43 months, 20 months and 8 months, respectively. The deduced progression intervals from stages III-IVC were 65, 23, and 12 months. In the training set, age, tumor stage, gender, and marital status were identified as independent risk factors influencing the prognosis of untreated PTC, and a nomogram was constructed using these variables. Conclusion In the absence of treatment intervention, early-stage PTC progressed slowly with an overall favorable prognosis. However, in mid to advanced-stage PTC, as tumor stage increased, disease progression accelerated, and prognosis gradually worsened. Age, tumor stage, marital status, and gender were independent risk factors influencing the prognosis of untreated PTC, and the nomogram based on these factors demonstrated good prognostic capability.

CD36 is a scavenger receptor that has been reported to function as a signaling receptor that responds to pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) and could integrate metabolic pathways and cell signaling through its dual functions. Thereby influencing activation to regulate the immune response and immune cell differentiation. Recent studies have revealed that CD36 plays critical roles in the process of lipid metabolism, inflammatory response and immune process caused by Mycobacterium tuberculosis infection. This review will comprehensively investigate CD36’s functions in lipid uptake and processing, inflammatory response, immune response and therapeutic targets and biomarkers in the infection process of M. tuberculosis. The study also raised outstanding issues in this field to designate future directions.

Abstract Background Aquaculture plays an important role in global protein supplies and food security. The ban on antibiotics as feed additive proposes urgent need to develop alternatives. Gut microbiota plays important roles in the metabolism and immunity of fish and has the potential to give rise to novel solutions for challenges confronted by fish culture. However, our understanding of fish gut microbiome is still lacking. Results We identified 575,856 non-redundant genes by metagenomic sequencing of the intestinal content samples of grass carp. Taxonomic and functional annotation of the gene catalogue revealed specificity of the gut microbiome of grass carp compared with mammals. Co-occurrence analysis indicated exclusive relations between the genera belonging to Proteobacteria and Fusobacteria/Firmicutes/Bacteroidetes, suggesting two independent ecological groups of the microbiota. The association pattern of Proteobacteria with the gene expression modules of fish gut and the liver was consistently opposite to that of Fusobacteria, Firmicutes, and Bacteroidetes, implying differential functionality of Proteobacteria and Fusobacteria/Firmicutes/Bacteroidetes. Therefore, the two ecological groups were considered as two functional groups, i.e., Functional Group 1: Proteobacteria and Functional Group 2: Fusobacteria/Firmicutes/Bacteroidetes. Further analysis revealed that the two functional groups differ in genetic capacity for carbohydrate utilization, virulence factors, and antibiotic resistance. Finally, we proposed that the ratio of “Functional Group 2/Functional Group 1” can be used as a biomarker that efficiently reflects the structural and functional characteristics of the microbiota of grass carp. Conclusions The gene catalogue is an important resource for investigating the gut microbiome of grass carp. Multi-omics analysis provides insights into functional implications of the main phyla that comprise the fish microbiota and shed lights on targets for microbiota regulation. Video Abstract

Abstract Managed pressure cementing (MPC) is a new technology based on managed pressure drilling, which has a greater advantage in facing narrow density window formations. However, the existing pressure prediction models during MPC injection stage consider fewer factors and have lower accuracy. To this end, combined with the characteristics of the injection stage, a predictive model of the distribution of annular fluid type was first proposed. Then, based on the experimental results, fluid density and rheology as a function of temperature and pressure were fitted. The governing equation of temperature‐pressure field was established. Eventually the fluid performance parameters–temperature–pressure coupling prediction model was developed in this paper. By comparing the predicted pump pressure with the measured pump pressure, the maximum relative error is not more than 10%. Using this model, the fluid type distribution, temperature field distribution, and pressure field distribution were investigated. The results indicated that the distribution of fluid types in the wellbore presented a complex variation, with up to 10 fluids in the casing and up to five fluids in the annulus. The trend of temperature field is complex, with three turning points. The larger the formation temperature gradient, the higher the fluid temperature in the annulus. The influence law of fluid heat conduction coefficient is reversed at 6750 m. Decreasing drilling fluid density will trigger gas channeling, while increasing drilling fluid density will increase the risk of fracturing formation, and safe operation can be realized by MPC. The variation of the static pressure in the casing is more complicated than in the annulus and the annular circulation pressure in the eccentric casing is smaller than that of the concentric casing, which is due to the smaller annular friction pressure. This study can provide a theoretical basis for the prediction of hydrodynamic parameters during the MPC injection stage.

Abstract Background Breast fibroadenoma poses a significant health concern, particularly for young women. Computer-aided diagnosis has emerged as an effective and efficient method for the early and accurate detection of various solid tumors. Automatic segmentation of the breast fibroadenoma is important and potentially reduces unnecessary biopsies, but challenging due to the low image quality and presence of various artifacts in sonography. Methods Human learning involves modularizing complete information and then integrating it through dense contextual connections in an intuitive and efficient way. Here, a human learning paradigm was introduced to guide the neural network by using two consecutive phases: the feature fragmentation stage and the information aggregation stage. To optimize this paradigm, three fragmentation attention mechanisms and information aggregation mechanisms were adapted according to the characteristics of sonography. The evaluation was conducted using a local dataset comprising 600 breast ultrasound images from 30 patients at Suining Central Hospital in China. Additionally, a public dataset consisting of 246 breast ultrasound images from Dataset_BUSI and DatasetB was used to further validate the robustness of the proposed network. Segmentation performance and inference speed were assessed by Dice similarity coefficient (DSC), Hausdorff distance (HD), and training time and then compared with those of the baseline model (TransUNet) and other state-of-the-art methods. Results Most models guided by the human learning paradigm demonstrated improved segmentation on the local dataset with the best one (incorporating C3ECA and LogSparse Attention modules) outperforming the baseline model by 0.76% in DSC and 3.14 mm in HD and reducing the training time by 31.25%. Its robustness and efficiency on the public dataset are also confirmed, surpassing TransUNet by 0.42% in DSC and 5.13 mm in HD. Conclusions Our proposed human learning paradigm has demonstrated the superiority and efficiency of ultrasound breast fibroadenoma segmentation across both public and local datasets. This intuitive and efficient learning paradigm as the core of neural networks holds immense potential in medical image processing.

Abstract Background Developing biomarkers for early stage AD patients is crucial. Glucose metabolism measured by 18F-FDG PET is the most common biomarker for evaluating cellular energy metabolism to diagnose AD. Arterial spin labeling (ASL) MRI can potentially provide comparable diagnostic information to 18F-FDG PET in patients with neurodegenerative disorders. However, the conclusions about the diagnostic performance of AD are still controversial between 18F-FDG PET and ASL. This study aims to compare quantitative cerebral blood flow (CBF) and glucose metabolism measured by 18F-FDG PET diagnostic values in patients with Alzheimer’s disease (AD) and amnestic mild cognitive impairment (aMCI) using integrated PET/MR. Results Analyses revealed overlapping between decreased regional rCBF and 18F-FDG PET SUVR in patients with AD compared with NC participants in the bilateral parietotemporal regions, frontal cortex, and cingulate cortex. Compared with NC participants, patients with aMCI exclusively demonstrated lower 18F-FDG PET SUVR in the bilateral temporal cortex, insula cortex, and inferior frontal cortex. Comparison of the rCBF in patients with aMCI and NC participants revealed no significant difference (P > 0.05). The ROC analysis of rCBF in the meta-ROI could diagnose patients with AD (AUC, 0.87) but not aMCI (AUC, 0.61). The specificity of diagnosing aMCI has been improved to 75.56% when combining rCBF and 18F-FDG PET SUVR. Conclusion ASL could detect similar aberrant patterns of abnormalities compared to 18F-FDG PET in patients with AD compared with NC participants but not in aMCI. The diagnostic efficiency of 18F-FDG-PET for AD and aMCI patients remained higher to ASL. Our findings support that applying 18F-FDG PET may be preferable for diagnosing AD and aMCI.

Drilling into fractured formations can easily lead to mud loss, which significantly affects drilling efficiency and increases drilling costs. In high-temperature and high-pressure environments, changes in mud properties render mud loss more uncontrollable. On the basis of a mud performance test in a high-temperature and high-pressure environment, and considering the time-varying characteristics of wellbore temperature and pressure and the distribution law of fracture temperature and pressure, a coupling model of temperature and pressure in the wellbore and fracture was established in this study. The developed model was solved numerically using the finite difference approximation, and the characteristics of the mud loss were analyzed. The effects of geothermal gradient, fracture parameters (fracture width, fracture length, and deformation capacity), mud properties (viscosity, yield value, and specific heat capacity), and operating conditions on mud loss were investigated. The model was validated using field measurement-while-drilling tool data of the LD1 well in the South China Sea. The results show that the average errors between the calculated temperature and pressure results of the numerical model and the actual data are 2.45% and 0.57%, respectively, which proves that the model has high accuracy in the prediction of the bottom hole temperature and pressure. A comparison of the predicted data of mud loss with the actual measured data indicates that the average error of the mud leakage model is 4.23%. This also demonstrates that the model has a high accuracy in predicting mud loss. In addition, the results show that the mud performance changes significantly under high-temperature and high-pressure conditions, which has a significant influence on mud loss. The geothermal gradient affected the mud properties and thus significantly affected the mud loss characteristics. The larger the mud pumping rate, the larger the bottomhole pressure difference and the more serious the mud loss. Blindly increasing mud viscosity is not advisable because it may lead to more serious losses. With an increase in the mud yield value, the mud flow resistance in the fractures can be significantly increased to inhibit mud loss. The larger the mud-specific heat capacity, the less mud loss is affected by the temperature. With an increase in the fracture width, the degree of mud loss gradually decreased. The larger the fracture length and deformation capacity, the more serious the mud loss. The fracture length and width could be inverted using the developed model.

A multiphase flow model is an important foundation for well control simulation. In this paper, a multiphase variable mass flow model considering sudden density change was developed for variable gradient managed pressure drilling (MPD) and it was solved by finite difference method (FDM). Further, the model was used to simulate the whole process of well control based on constant bottom-hole pressure for variable gradient MPD. In this way, the advantages of the new gas kick detection method compared with the mud pit increment detection method and the variation laws of key parameters in the whole well control process were investigated. The results indicate that under the condition of small gas rate, the new gas kick detection method is better than the mud pit increment detection method because of its time savings. In the process of gas discharge, the wellbore pressure fluctuates due to the influence of gas expansion, sudden density changes at the separator position and annulus diameter changes at the casing shoe and mud line. The time when the back pressure reaches the maximum lags behind the time when the gas front reaches the wellhead. The mud pit increment increase rate when the gas front reaches the separator position is significantly higher than that in the early stage of gas kick detection.

In order to improve the backward-facing radar stealth capability of the engine exhaust system, five coating schemes for afterburner, which is radar wave strong scattering source, are formulated. The influence of afterburner coating absorbing materials on the horizontal polarization and vertical polarization RCS distribution pattern of the exhaust system in the range of -30°~+30° azimuth of the typical frequency point in the S-band and X-band is analyzed by using the shooting and bouncing rays, also SAR imaging of typical frequency points in the X-band at an azimuth angle of 0° is simulated.The results show that the distribution of strong scattering sources in S-band and X-band is basically the same, and the influence of different coating schemes of absorbing materials on the RCS reduction effect of two bands is similar. The flame stabilizer is the strongest scattering source of radar characteristic signal, and coating it with radar absorbing materials has the greatest benefit on reducing the radar characteristic signal of the exhaust system. Coating absorbing materials in the four parts of afterburner inner cone, flame stabilizer, lobe mixer and afterburner cylinder is the best absorbing material coating scheme for the reduction effect of RCS in the two wave bands. The average RCS reduction effect of horizontal polarization and vertical polarization in S band is 92.3% and 92.0%, and the average RCS reduction effect of horizontal polarization and vertical polarization in X-band is 90.2% and 88.4%.

Abstract Background Pancreatic ductal adenocarcinoma (PDAC) is a devastating disease that requires precise diagnosis for effective treatment. However, the diagnostic value of carbohydrate antigen 19 − 9 (CA19-9) is limited. Therefore, this study aims to identify novel tumor-associated autoantibodies (TAAbs) for PDAC diagnosis. Methods A three-phase strategy comprising discovery, test, and validation was implemented. HuProt™ Human Proteome Microarray v3.1 was used to screen potential TAAbs in 49 samples. Subsequently, the levels of potential TAAbs were evaluated in 477 samples via enzyme-linked immunosorbent assay (ELISA) in PDAC, benign pancreatic diseases (BPD), and normal control (NC), followed by the construction of a diagnostic model. Results In the discovery phase, protein microarrays identified 167 candidate TAAbs. Based on bioinformatics analysis, fifteen tumor-associated antigens (TAAs) were selected for further validation using ELISA. Ten TAAbs exhibited differentially expressed in PDAC patients in the test phase (P

Tropical cyclones (TCs) are associated with severe weather phenomena, making accurate wind field retrieval crucial for TC monitoring. SAR’s high-resolution imaging capability provides detailed information for TC observation, and wind speed calculations require wind direction as prior information. Therefore, utilizing SAR images to retrieve TC wind fields is of significant importance. This study introduces a novel approach for retrieving wind direction from SAR images of TCs through the classification of TC sub-images. The method utilizes a transfer learning-based Inception V3 model to identify wind streaks (WSs) and rain bands in SAR images under TC conditions. For sub-images containing WSs, the Mexican-hat wavelet transform is applied, while for sub-images containing rain bands, an edge detection technique is used to locate the center of the TC eye and subsequently the tangent to the spiral rain bands is employed to determine the wind direction associated with the rain bands. Wind direction retrieval from 10 SAR TC images showed an RMSD of 19.52° and a correlation coefficient of 0.96 when compared with ECMWF and HRD observation wind directions, demonstrating satisfactory consistency and providing highly accurate TC wind directions. These results confirm the method’s potential applications in TC wind direction retrieval.

There is still a great challenge to reveal the micro-macro dynamic mechanical behavior of initial coal failure induced by mining stress field in working face as a necessary condition for the outburst occurrence. The multivariate stress loading paths for the damage and instability of mining coal were constructed based on the typical coal and gas outburst accident of mining face. PFC3D discrete software was used to carry out the visual simulation of damage and instability of coal under multiple working conditions and scales. The dynamic response law of damage and instability of mining coal was revealed, the dynamic evolution behavior of cracks in mining coal was clarified, and the prospect of outburst prevention technologies was put forward based on the initial failure process of coal induced by in-situ stress under mining. The results shown that the failure type and strength of the mined coal varied significantly with the loading and unloading rate of the principal stress. In the process of gradual unloading of stress, the macroscopic fracture surface of coal presented the form of single inclined plane or conjugate shear plane, and the failure strength of coal decreased with the increase of unloading rate. With the gradual loading in both directions of stress at the same rate, unidirectional sudden unloading or a certain residual stress maintaining state presented a macro fracture surface parallel to the direction of the intermediate principal stress. And the failure strength of coal decreased with the increase of the unloading degree or the decrease of the residual stress. Under different stress loaded, the tension-shear failure process of coal appeared successively with shear and tension cracks. In the process of instability caused by mining coal damage, the dynamic evolution of cracks presented intermittent, progressive and paroxysmal composite characteristics. The overall development process of cracks can be characterized as the initial appearance of new cracks (intermittent-sudden increase stage), crack expansion (gradual-slow increase stage), penetration and expansion (paroxysmal-slow increase stage), and the overall tearing process of coal (sudden increase stage). The mechanical strength of coal was regarded as one of the main controlling factors affecting the occurrence of outbursts. The difficulty of initial failure of coal induced by in-situ stress depended critically on the stress loading and unloading path. The coal was most prone to initial failure when the unidirectional principal stress was suddenly unloaded or the bidirectional principal stress was gradually unloaded. Based on this mechanical law, the “ideal mining mode of outburst prediction in mining working face” was proposed to represent the most dangerous state of coal in the working face.

Plant dyes have the advantages of green environmental protection and high safety, but due to the shortage of resources, high cost and low color fastness, the industrial application of plant dyes is limited. Baiyi people have the traditional custom of plant dyeing in Heqing, Yunnan Province, and there are rich local dye plant resources and traditional dyeing technology. In order to investigate, record and study Baiyi people plant dyeing and related traditional knowledge, expand plant dye resources and promote the development and utilization of plant dyes, this study conducted ethnobotanical investigation on plant dyeing and related traditional knowledge of Baiyi people in Liuhe Yi Township, Heqing County, Dali Prefecture. From September 2019 to March 2020, 288 informants were interviewed by semi-structured interviews from four villages in Liuhe Yi Township, Heqing County, Dali Prefecture; local dye plants were investigated by field research; traditional plant dyeing crafts were recorded by participatory observation; traditional knowledge of plant dyeing was analysed through quantitative analysis (f value, CIIs value, ICF value). The results are as follows: (1) The Baiyi people use 11 species of dye plants in Heqing, belonging to 10 families and 11 genera. (2) People of different regions, ages and genders have different cognitions of traditional knowledge of plant dyeing. (3) The use frequency and cultural importance index of Viburnum cylindricum and Buddleja officinalis are higher, and the cognition of Baiyi people is highly consistent on dye plants of blue. (4) Baiyi people often use dye plants to dye their own traditional cloth (folk cloth made from Gerbera delavayi). This research reveals that Baiyi people have a relatively complete knowledge system of traditional plant dyeing in Heqing, but it has gradually lost with the development of the times. This study provides scientific clues for the exploitation of dye plant resources and the research of traditional plant dyeing technology, promotes the industrial application of dye plants of minority, and has a great significance and application value for the economic development in minority areas.

In light of the low yields and complex reaction routes of some well-known 5,5-fused and 5,6-fused bicyclic compounds, a series of 5,7-fused bicyclic imidazole-diazepine compounds were developed with high yields by only two efficient steps. Significantly, the seven-membered heterocyclic ring has a stable energetic skeleton with multiple modifiable sites. However, the 5,7-fused bicyclic energetic compounds were rarely reported in the area of energetic materials. Three neutral compounds 1, 2 and 4 were synthesized in this work. To improve the detonation performances of the 5,7-fused neutral compounds, corresponding perchlorate 1a and 2a were further developed. The physicochemical and energetic performances of all newly developed compounds were experimentally determined. All newly prepared energetic compounds exhibit high decomposition temperatures (Td: 243.8–336 °C) and low mechanical sensitivities (IS: >15 J, FS: >280 N). Among them, the velocities performances of 1a (Dv = 7651 m/s) and 4 (Dv = 7600 m/s) are comparable to that of typical heat-resistant energetic material HNS (Dv = 7612 m/s). Meanwhile, the high decomposition temperature and low mechanical sensitivities (Td = 336 °C; IS = 32 J; FS > 353 N) of 4 are superior to that of HNS (Td = 318 °C; IS = 5 J; FS = 250 N). Hence, the 5,7-fused bicyclic compounds with high thermostability, low sensitivities and adjustable detonation performance have a clear tendency to open up a new space for the development of heat-resistant energetic materials.

The recovery of tellurium and bismuth from bismuth telluride waste is of great significance in improving the utilization levels of renewable resources, protecting the ecological environment and alleviating the problem of resource shortages. In this paper, tellurium and bismuth were recovered from bismuth telluride waste by selective sulfidation–vacuum volatilization. The Gibbs free energy, phase diagram and thermodynamic equilibrium diagram for the core reaction were calculated and analyzed to determine the possible reactions and the conditions required for the stability of bismuth telluride during the sulfidation process. After calculating the saturated vapor pressures, it was concluded that tellurium and bismuth sulfide could be separated by vacuum volatilization. The thermogravimetric analyses and differential scanning calorimetry were then used to analyze the reaction between bismuth telluride and sulfur. The results indicated that the temperature range for the sulfidation reaction should be 491–620 K. The volatilization temperature of tellurium should be greater than 695 K. The evaporation kinetics for tellurium and bismuth sulfide showed that the evaporation rate of tellurium was much higher than that of bismuth sulfide. Furthermore, experiments were conducted to verify the reliability of the theoretical analysis, and these were in good agreement with the thermodynamic and kinetic results. The direct yields of tellurium and bismuth were 99.65% and 99.49%, respectively. These results confirmed that the selective sulfidation-vacuum volatilization method is a feasible alternative for recovery of tellurium and bismuth from bismuth telluride waste.

Rhinoviruses (RVs) are major causes of the common cold and are related to severe respiratory tract diseases, leading to a considerable economic burden and impacts on public health. Available and stable viral resources of rhinoviruses for laboratory use are important for promoting studies on rhinoviruses and further vaccine or therapeutic drug development. Reverse genetic technology can be useful to produce rhinoviruses and will help to promote studies on their pathogenesis and virulence. In this study, rhinovirus A89, an RV-A species that has been found to be highly involved in hospitalization triggered by RV infections, was selected to construct an infectious clone based on its sequence as a representative. The viral mRNA produced by a T7 RNA transcript system was transfected into H1-HeLa cells, and the rescued RV-A89 viruses were harvested and confirmed by sequencing. The rescued RV-A89 induced a similar cytopathic effect (CPE) and shared almost identical growth kinetics curves with parental RV-A89. Moreover, 9A7, a prescreened monoclonal antibody against the parental RV-A89, had a good and specific reaction with the rescued RV-A89, and further characterization showed almost the same morphology and protein composition of both viruses; thus, recombinant RV-A89 with similar biological characterization and virulence to the parental virus was obtained. In summary, the infectious clone of RV-A89 was successfully established, and the development of reverse genetic technology for rhinovirus will provide a framework for further studies on rhinoviruses.

Summary: Determining novel biomarkers for early identification of chronic thromboembolic pulmonary hypertension (CTEPH) could improve patient outcomes. We used the isobaric tag for relative and absolute quantitation approach to compare the serum protein profiles between CTEPH patients and the controls. Bioinformatics analyses and ELISA were also performed. We identified three proteins including heparanase (HPSE), gelsolin (GSN), and secreted protein acidic and rich in cysteine (SPARC) had significant changes in CTEPH. The receiver operating characteristic curve analysis showed that the areas under the curve of HPSE in CTEPH diagnosis were 0.988. Furthermore, HPSE was correlated with multiple parameters of right ventricular function. HPSE concentrations were significantly higher in patients with a low TAPSE/sPAP ratio (≤0.31 mm/mmHg) (65.4 [60.5,68.0] vs. 59.9 [35.9,63.2] ng/mL, p

Efficient multiple target tracking (MTT) is the key to achieving green, precision, and large-scale aquaculture, marine exploration, and marine farming. The traditional MTT methods based on Bayes estimation have some pending problems such as an unknown detection probability, random target newborn, complex data associations, and so on, which lead to an inefficient tracking performance. In this work, an efficient two-stage MTT method based on a YOLOv8 detector and SMC-PHD tracker, named EMTT-YOLO, is proposed to enhance the detection probability and then improve the tracking performance. Firstly, the first detection stage, the YOLOv8 model, which adopts several improved modules to improve the detection behaviors, is introduced to detect multiple targets and derive the extracted features such as the bounding box coordination, confidence, and detection probability. Secondly, the particles are built based on the previous detection results, and then the SMC-PHD filter, the second tracking stage, is proposed to track multiple targets. Thirdly, the lightweight data association Hungarian method is introduced to set up the data relevance to derive the trajectories of multiple targets. Moreover, comprehensive experiments are presented to verify the effectiveness of this two-stage tracking method of the EMTT-YOLO. Comparisons with other multiple target detection methods and tracking methods also demonstrate that the detection and tracking behaviors are improved greatly.

Background: Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation. Purpose: To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis, myelitis, and spinal tumors. Methods: This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal–Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements. Results: FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA’s superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in myelitis patients (r = −0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = −0.71, p = 0.0002). Conclusion: DTI indicators, especially FA, have the potential in distinguishing spondylosis, myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.

This study investigated Earth science students’ experiences with online education during the COVID-19 pandemic at the University of Tennessee, Knoxville, in the US. We used an existing survey from the online education literature, the Online Learning Environment Survey (OLES), which consists of three instruments: (a) community of inquiry (CoI), (b) Institutional Support (IS), and (c) Self-Directed Online Learning Scale (SDOLS). The survey rating subscales ordered from highest to lowest are autonomous learning, asynchronous online learning, institutional support, teaching presence, social presence, and cognitive presence, respectively, indicating interest for the online learning environment. Among all of the subscales, the asynchronous online category was rated the highest by the students. The data were then analyzed using Rasch modeling. According to the Rasch analyses, asynchronous online teaching represents the most favorable course delivery technique for geoscience education. Overall, the survey data show a general interest in online delivery and the effectiveness of the modality, thus indicating potential for evolving into an online Earth science program. Finally, also discussed are possible future extensions of the research (e.g., extending the research to other introductory online geoscience courses).

Colorectal cancer (CRC) is one of the most prevalent malignant tumors of the digestive tract worldwide. Despite notable advancements in CRC treatment, there is an urgent requirement for preclinical model systems capable of accurately predicting drug efficacy in CRC patients, to identify more effective therapeutic options. In recent years, substantial strides have been made in the field of organoid technology, patient-derived organoid models can phenotypically replicate the original intra-tumor and inter-tumor heterogeneity of CRC, reflecting cellular interactions of the tumor microenvironment. Patient-derived organoid models have become an indispensable tool for investigating the pathogenesis of CRC and facilitating translational research. This review focuses on the application of organoid technology in CRC modeling, tumor microenvironment, and guiding clinical treatment, particularly in drug screening and personalized medicine. It also examines the existing challenges encountered in clinical organoid research and provides a prospective outlook on the future development directions of clinical organoid research, encompassing the standardization of organoid culture technology and the application of tissue engineering technology.

BackgroundBreast cancer endocrine therapy research has become a crucial domain in oncology since hormone receptor-positive breast cancers have been increasingly recognized, and targeted therapeutic interventions have been advancing over the past few years. This bibliometric analysis attempts to shed light on the trends, dynamics, and knowledge hotspots that have shaped the landscape of breast cancer endocrine therapy research between 2003 and 2022.MethodsIn this study, we comprehensively reviewed the scientific literature spanning the above-mentioned period, which included publications accessible through the database of the Web of Science (WOS) and the National Center for Biotechnology Information (NCBI). Next, a systematic and data-driven analysis supported by sophisticated software tools was conducted, such that the core themes, prolific authors, influential journals, prominent countries, and critical citation patterns in the relevant research field can be clarified.ResultsA continuous and substantial expansion of breast cancer endocrine therapy research was revealed over the evaluated period. A total of 1,317 scholarly articles were examined. The results of the analysis suggested that research on endocrine therapy for breast cancer has laid a solid basis for the treatment of hormone receptor-positive breast cancer. From a geographical perspective, the US, the UK, and China emerged as the most active contributors, illustrating the global impact of this study. Furthermore, our analysis delineated prominent research topics that have dominated the discourse in the past two decades, including drug therapy, therapeutic efficacy, molecular biomarkers, and hormonal receptor interactions.ConclusionThis comprehensive bibliometric analysis provides a panoramic view of the ever-evolving landscape of breast cancer endocrine therapy research. The findings highlight the trajectory of past developments while signifying an avenue of vast opportunities for future investigations and therapeutic advancements. As the field continues to burgeon, this analysis will provide valuable guidance for to researchers toward pertinent knowledge hotspots and emerging trends, which can expedite the discoveries in the realm of breast cancer endocrine therapy.

AbstractObjective To investigate the histopathological findings and follow-up outcome of focused ultrasound ablation surgery (FUAS) treatment of multiple fibroadenomas (FA).Methods A total of 20 patients with 101 multiple FAs were enrolled. After one session FUAS ablation, 21 lesions (≥15.0 mm) were surgically removed within one week for histopathological analysis, including 2, 3, 5-triphenyltetrazolium chloride (TTC) staining, H&E staining, nicotinamide adenine dinucleotide (NADH) -flavretin enzyme staining, Transmission electron microscope (TEM) and scanning electron microscope (SEM). The remaining 80 lesions were followed up at 3, 6 and 12 months after treatment.Results All ablation procedures were performed successfully. Pathologic findings showed that irreversible damage of FA was confirmed. TTC, H&E and NADH staining and TEM/SEM demonstrated tumor cell death and tumor structural destruction at the gross, cellular, and subcellular levels, respectively. The median shrinkage rate at 12 months post-FUAS was 66.4 (43.6, 89.5) %.Conclusion Histopathological analysis for FAs after FUAS treatment proved that FUAS could effectively induce irreversible coagulative necrosis of FA, and the tumor volume would gradually shrink in follow-up. FUAS was safe and effective to treat multiple FAs with good cosmesis.Key pointsThis study was the first study of detailed histopathological analysis for FAs after FUAS treatment.FUAS can effectively induce irreversible coagulative necrosis of fibroadenoma cells.FUAS ablation of multiple fibroadenomas is safe and effective.

Peer-to-peer (P2P) lending is a fintech innovation that provides loans to individuals and businesses without the need for additional intermediaries. However, if the borrower fails to repay the loan on time, the bank suffers a financial loss due to the borrower's default. At present, many studies are trying to improve the accuracy of credit default risk prediction models to reduce the risk of financial institutions' loan business, but it is also a meaningful study to focus on improving the recall rate of model prediction results. In the related research field of credit default risk prediction, improving the recall rate is crucial for banks and other lending institutions. The recall rate refers to the proportion of all true positive examples that are correctly identified as positive examples. In credit default risk prediction, true positive cases refer to the cases where borrowers default, while being correctly identified as positive cases means that the model can accurately predict which borrowers may default. If banks' risk prediction models can improve recall rates, this can help them better assess risk, formulate appropriate lending policies, and minimize default losses. This study aims to further improve the recall and AUC metrics (area under the ROC curve) of P2P credit default prediction using the lending dataset from Lending Club using an improved machine learning model fusion algorithm. Our proposed algorithm consists of two machine learning algorithms. The improved LightGBM algorithm and the improved XGBoost algorithm are used for model fusion to obtain the LGB-XGB-Stacking model. By optimizing the evaluation metrics in the training phase of these two algorithms, we have achieved significant improvement in results, especially in the recall rate of defaulted customers and the overall AUC metrics. After comparing the predictive performance of the models, our proposed predictive model is improved in the following aspects. First, the recall of our proposed prediction model is significantly better than other models. Second, it also outperforms other machine learning models on the AUC metric. Among them, the recall rate of the positive sample (default customer) is 24.43% higher than that of the XGBoost model, and the overall AUC index is 6.71% higher. In the end, it was found that XGBoost, LightGBM, and CatBoost models performed very well in terms of accuracy rate improvement. The accuracy rates of these three models are very close, and they are all higher than other models. Therefore, it is found that machine learning models are still an effective method for credit default prediction research, especially tree models. Although the accuracy of our model is slightly lower than the above models, our proposed model outperforms the above models in identifying defaulting customers. Our model can more accurately identify defaulting customers and minimize the risk of bad debts for financial institutions.

Abstract Purpose To explore pediatric nurses’ challenges and effective coping strategies in caring for dying children. Methods A descriptive qualitative study was adopted. Data were collected using a semi-structured interview with ten nurses from the pediatric, pediatric emergency, and neonatology departments. Results Three themes were generated: stressors, consequences, and coping strategies. Ten sub-themes were generalized: negative emotions; helplessness; questioning rescue behavior; fear of communication; lack of workforce for night rescue; compassion fatigue; burnout; changes in life attitudes; self-regulation; leadership approval and no accountability. Conclusions Through qualitative research, nurses’ challenges and effective coping strategies in caring for dying children were found, which provides information for nurses’ career development and related policy formulation in China. Clinical relevance While there are many articles in China on hospice care, there is little research on the nurses’ experience of caring for dying children. Many studies have mentioned the adverse consequences of caring for dying children in foreign countries, leading to post-traumatic stress disorder (PTSD). However, domestic discussion of such problems is rare, and no corresponding coping strategies exist. This study explores pediatric nurses’ challenges and effective coping strategies in caring for dying children.

Abstract Background Although the pressure of pulmonary vein increases before pulmonary artery in pulmonary hypertension due to left heart disease (PH-LHD), only a few studies have assessed pulmonary vein smooth muscle cells (PVSMCs) because of the lack of a simple and feasible isolation method. Methods In this study, we introduced a simple method to obtain PVSMCs. Primary pulmonary veins were removed by puncture needle cannula guidance. Then, PVSMCs were cultured by the tissue explant method and purified by the differential adhesion method. The cells were characterized by hematoxylin-eosin (HE) staining, immunohistochemistry, western blotting, and immunofluorescence to observe the morphology and verify the expression of alpha-smooth muscle actin (α-SMA). Results The HE staining results showed that the pulmonary vein media was thinner than the pulmonary artery, the intima and adventitia of the pulmonary vein were removed by this method, and the obtained cells with good activity exhibited morphological characteristics of smooth muscle cells. In addition, higher α-SMA expression was observed in the cells obtained by our isolation method than in the traditional method. Conclusion This study established a simple and feasible method to isolate and culture PVSMCs that might facilitate the cytological experiments for PH-LHD.

Objective To investigate the effects of Quanduzhong Jiaonang(QDZJN) and pinoresinol diglucoside (PDG) on microcirculatory blood perfusion in intestinal wall and its spectral characteristics in spontaneously hypertensive rats (SHRs). Methods SHRs were randomly divided into SHR, SHR+QDZJN, SHR+PDG (L), SHR+PDG (M) and SHR+PDG (H) groups with 6 in each group. The control group consisted of 6 WKY rats. All treatment groups were given intragastric administration of QDZJN, PDG, or pure water. After 2 month continuous administration, rats' intestines were exposed by surgery. The wall microcirculatory blood perfusion of was measured by laser Doppler flowmetry (LDF) and laser Doppler perfusion imaging (LDPI). Wavelet transform analysis was performed, and the amplitudes of NO-independent endothelial and NO-dependent endothelial oscillators were compared among six groups. Results Compared with the control group, blood perfusion level of intestine wall was significantly decreased in SHRs group (P＜0.001). After two months of treatment with QDZJN and PDG, the blood perfusion level of SHRs was significantly elevated (P＜0.001). The amplitudes of NO-dependent and -independent endothelial activity in SHRs group were significantly lower than those in the control group (both P＜0.01). QDZJN and PDG significantly enhanced the amplitude of NO-dependent and -independent endothelial activity of intestine wall perfusion in SHRs (P＜0.0001 and P＜0.01). Conclusions Treatment with QDZJN and PDG for two months may significantly improve the microhemodynamics and endothelial function of intestine wall in SHRs.

The rapid development of hydrogen energy requires the use of natural gas infrastructure for hydrogen transportation. It is very important to study hydrogen-added natural gas transportation technology, which is a key way to rapidly develop coal-based gas and renewable energy. This study aims to study the influence of X80 pipeline steel's fatigue performance in hydrogen environment, and perform fatigue tests on notched round rod specimens under different hydrogen concentration. The experimental results show that hydrogen seriously affects the fatigue life of pipeline steel. After reaching a certain hydrogen concentration, as the hydrogen concentration continues to increase, the fatigue life decreases gradually. Combined with SEM analysis of fracture morphology, the decrease in the size and density of the dimples reduces the displacement amplitude, while the increase in the planar area increases the displacement during fatigue fracture due to accelerated crack propagation. From this study, we can know the influence of hydrogen concentration on the fracture morphology of pipeline steel, which provides an understanding of the effect of hydrogen on fatigue fracture morphology and a broader safety analysis.

In this study, a novel peroxydisulfate (PDS) activator (CF-nZVI-JE) was prepared via in-situ loading nano zero-valent iron (nZVI) on Juncus effusus (JE) followed with wrapping a layer of cellulose film (CF). The CF-nZVI-JE had the same 3D structure as the JE, being easy to separate from aqueous solution. The loaded nZVI existed single nanoparticles with a size of 60–100 nm except chain-type agglomeration of nanoparticles due to the stabilization of JE fibers. The activation performance of the CF-nZVI-JE for PDS was evaluated with Rhodamine B (Rh B) as a representative pollutant. Under the optimal activating conditions, the degradation rate of Rh B reached 99% within 30 min in the CF-nZVI-JE/PDS system. After five cycles, the degradation rate of Rh B was still over 85%, suggesting that the CF-nZVI-JE had good reusability. More interestingly, SO4·− and ·OH radicals were simultaneously detected in the CF-nZVI-JE/PDS system, but only SO4·− existed in the JE-ZVI/PDS system, suggesting the different activation mechanism. Meanwhile, the introduction of CF not only facilitated to the mineralization of Rh B but also significantly reduced the release amount of iron ions. Hence, the CF-nZVI-JE can be employed as a promising PDS activator for the treatment of organic wastewater. HIGHLIGHTS The prepared CF-nZVI-JE had the same 3D structure as JE, which can stabilize nZVI.; nZVI existed as single nanoparticles and chain-type agglomeration of nanoparticles.; Rh B degradation was involved in SO4−· and HO· in the CF-nZVI-JE/PDS system.; CF-nZVI-JE facilitated the mineralization of Rh B compared with the nZVI-JE.; CF prevented the leakage of nZVI and reduced the release amount of iron ions.;

Landfill leachate, because of its complex components, may cause pipe clogging during its collection and transportation, and pose a threat to the environment. This study considers two typical drainage pipe materials, i.e., polypropylene-random (PPR) and acrylonitrile-butadiene-styrene (ABS), to discriminate their anti-scaling performances through a landfill leachate immersion experiment. The results show that both PPR and ABS pipe materials immersed in the younger-aged leachate are prone to scaling. The mass concentrations of Ca2+ in the leachate play a key role in scale formation, followed by Mg2+, pH, oxidation–reduction potential (ORP), dissolved oxygen (DO), and Cl−. In particular, Ca2+, pH, and DO show a positive relationship in scaling, while Mg2+ acts in a negative relationship. Calcium carbonate is the major constituent of the scales, accounting for 72.3% of the total. The scaling on the surface of the PPR pipe material is more serious than that of the ABS pipe material, revealed by the corresponding weight increment that is 33% higher than that related to ABS during the experimental period. It is thus indicated that ABS has better anti-scaling performance, which may be an optional material selected for the system design of leachate collection and transportation. HIGHLIGHTS Two typical drainage pipe materials are discriminated by their anti-scaling performances.; Key factors regarding leachate water quality that may give rise to scaling are identified.; Ca2+ plays a dominant role in scale formation.; Younger-aged leachate is more prone to scaling than older-aged leachate.; ABS has better anti-scaling performance than PPR.;

Objective To investigate the factors influencing the sonication dosage and efficiency of ultrasound-guided high intensity focused ultrasound (USgHIFU) for breast fibroadenomas.Materials and Methods Forty-nine patients with 78 breast fibroadenomas who underwent USgHIFU were retrospectively analyzed. The energy efficiency factor (EEF) was set as dependent variable, and the factors possibly influencing the sonication dosage, including age, body mass index (BMI), fibroadenoma size, distance from the shallow margin of the fibroadenoma to skin, distance from the deep margin of the fibroadenoma to pectoralis major, types of near field acoustic pathway, and Adler blood flow classification of ultrasound, were set as independent variables. The correlation between EEF and these independent variables were analyzed, and an optimal scaling regression model was established.Results Fibroadenoma size, distance from the shallow margin of the fibroadenoma to skin and type of near field acoustic pathway had significant correlation with EEF (p

To solve the contradiction between multiple wearable sensor features and the limited computing power and storage capacity of embedded devices, feature engineering is used to select the best features for predicting physical activity energy expenditure (PAEE) on the basis of data fusion of multiple sensors (accelerometer and gyroscope sensors). In the data preprocessing stage, time-domain and frequency-domain features of the sensor are extracted by using sliding window technology, and sinusoidal curve fitting is used for dataset at three velocity levels, finally hypothesis testing is carried out to check data outliers. A WEKA experimental platform is constructed based on filtering, warpper and embedded feature selection algorithms and machine learning prediction models such as multiple linear regression, regression tree, support vector machine and neural network. Finally, the optimal model is selected by evaluating the correlation coefficient and mean absolute error of each model during the decision level fusion. The dataset with jitter is used as the test data, which shows that feature selection can mitigate model overfitting and improve the model’s generalization ability and robustness. Embedded feature selection adopts classical elastic network algorithm. Experimental results show that the features extracted from accelerometer sensors play a more decisive role than those from gyroscope sensors in PAEE and the neural network model of multi-sensor feature fusion based on correlation coefficient method is the optimal model.

Objective To explore the learning curve of high intensity focus ultrasound (HIFU) treatment for breast fibroadenoma.Methods A database of 110 patients with 255 breast fibroadenomas who underwent HIFU treatment at two different clinical centers (Center 1 and 2) were retrospectively analyzed. The learning curves of HIFU treatment for breast fibroadenoma were drawn by CUSUM analysis in two centers, respectively. According to the inflection point of the learning curves, the treatment was divided into two groups: initial phase and consolidation phase. HIFU treatment parameters were compared between two groups. The effectiveness and safety results were also evaluated.Results The inflection points of the learning curves were the 60th treatment in Center 1 and the 65th treatment in Center 2. The screening time, treatment time, sonication time and hyperechoic scale change time were significantly shorter in consolidation phase than those in initial phase of the two centers (p

The aim of this study was to identify predictive immunity/hypoxia/ferroptosis/epithelial mesenchymal transformation (EMT)-related biomarkers, pathways and new drugs in allograft rejection in kidney transplant patients. First, gene expression data were downloaded followed by identification of differentially expressed genes (DEGs), weighted gene co-expression network analysis (WGCNA) and protein–protein interaction (PPI) analysis. Second, diagnostic model was construction based on key genes, followed by correlation analysis between immune/hypoxia/ferroptosis/EMT and key diagnostic genes. Finally, drug prediction of diagnostic key genes was carried out. Five diagnostic genes were further identified, including CCR5, CD86, CD8A, ITGAM, and PTPRC, which were positively correlated with allograft rejection after the kidney transplant. Highly infiltrated immune cells, highly expression of hypoxia-related genes and activated status of EMT were significantly positively correlated with five diagnostic genes. Interestingly, suppressors of ferroptosis (SOFs) and drivers of ferroptosis (DOFs) showed a complex regulatory relationship between ferroptosis and five diagnostic genes. CD86, CCR5, and ITGAM were respectively drug target of ABATACEPT, MARAVIROC, and CLARITHROMYCIN. PTPRC was drug target of both PREDNISONE and EPOETIN BETA. In conclusion, the study could be useful in understanding changes in the microenvironment within transplantation, which may promote or sustain the development of allograft rejection after kidney transplantation.

Based on the metal elements contained in crude zinc, the evaporation kinetic experiments of the Cd-Zn, Bi-Zn and Bi-Sn-Zn systems in vacuum distillation were carried out. The Langmuir formula was used for theoretical prediction of evaporation rate. The results are in good agreement with the experimental data. It indicates that the method of evaporation rate calculation is applicable. The condensation coefficients of zinc in the alloys were calculated. The relationship between the interaction and the evaporation rate of components in the alloys was discussed. It will be helpful to the separation and purification of crude zinc and the optimization of experimental equipmentby vacuum distillation.

The special temperature-pressure environment and narrow safety density window of the deepwater formation pose a great challenge to wellbore pressure control during drilling. The downhole variable-gradient drilling method is an effective idea to solve this challenge. However, previous studies mainly focused on the theoretical adaptability analysis of this method, while the experimental feasibility verification has not yet been reported. In this paper, based on the segmental control principle of wellbore fluid density, we set up an indoor physical experiment system to investigate the feasibility of variable-gradient drilling method based on downhole cyclone separator. Using this experimental system, we investigated the effect of drilling fluid physical parameters, hollow glass microsphere (HGMS) performance parameters and engineering parameters on the separator separation efficiency, wellbore pressure gradient and HGMS slip rate. The experimental results revealed that the separator could separate the HGMSs into the annulus from the fluid mixture in the drill pipe. The separation efficiency increased with the increase in the HGMS diameter, HGMS concentration and flow rate, while decreased with the increase in the HGMS density and fluid viscosity. The HGMS density and HGMS concentration were the key factors affecting the annulus pressure gradient value, and the separator separation efficiency was the main factor determining the difference of the annulus pressure gradient. The HGMS slip rate was highly sensitive to its diameter and fluid viscosity, and a combination of optimal HGMS diameter and fluid viscosity could avoid the drilling risk caused by the HGMS slippage. Therefore, the variable-gradient drilling method based on downhole separator is feasible, which is able to create two or more pressure gradients in the annulus. This study could provide guidance for the optimization of key parameters and the development of equipment related to the variable-gradient drilling.

Knowledge of wellbore multiphase flow characteristics is important for early gas invasion identification and treatment, especially in oil-based drilling fluid. The wellbore multiphase flow law in downhole dual-gradient drilling (DDGD) is more complex than that in conventional single-gradient drilling. There was no relevant literature report at present. In this paper, considering the synergistic feedback relationship of multiphase flow, interphase mass transfer, and wellbore temperature, a fully transient wellbore multiphase flow model was established based on oil-based drilling fluid in deepwater DDGD. The model also coupled the variable temperature–mass flows caused by the dynamic transfer of hollow glass balls and formation gas. The bubble interface mass transfer theory was adopted to describe the interphase mass transfer rate. The model was verified through the experimental measurement data. The calculated results indicated that the dynamic transfer of hollow glass balls varied the wellbore pressure gradient and flow rate in DDGD, resulting in a sudden decrease in gas fraction and gas solubility along the flow direction at the separator. Additionally, the transient interphase mass transfer and wellbore temperature had large impact on the wellbore multiphase flow behaviors. Moreover, the model based on bubble interface mass transfer theory could more accurately characterize the development of the wellbore multiphase flow. This research could provide a certain theoretical basis for the detection and treatment of gas invasion in deepwater DDGD.

The borehole breathing observed when drilling into natural fractured formations is often erroneously identified as leakage or kick. The main reason for this phenomenon is that the fractures around the well have opened and closed after being affected by the wellbore pressure fluctuations. In this paper, a three-dimensional geological model is established for simulating fractured borehole breathing based on the Cohesive unit method, and the full three-dimensional simulation of fractured borehole breathing is realized for the first time. Based on this model, this paper studies the dynamic response characteristics of the fractured borehole breathing mechanism in detail, and analyzes a variety of parameters that may affect borehole breathing. The research results show that: increasing the viscosity of drilling fluid can effectively inhibit the occurrence of borehole breathing and extend its duration; formation elastic modulus is inversely correlated with borehole breathing; borehole breathing is not sensitive to changes in formation Poisson’s ratio and porosity; horizontal geostress affects the severity of borehole breathing by determining the reopening pressure of the fracture; changes in the original width of the fracture will not affect the total volume of backflow, but will affect the amount of mud lost in the early stage.