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Abstract Background The relationship between the biological pathways related to deep learning radiomics (DLR) and lymph node metastasis (LNM) of breast cancer is still poorly understood. This study explored the value of DLR based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in LNM of invasive breast cancer. It also analyzed the biological significance of DLR phenotype based on genomics. Methods Two cohorts from the Cancer Imaging Archive project were used, one as the training cohort (TCGA-Breast, n = 88) and one as the validation cohort (Breast-MRI-NACT Pilot, n = 57). Radiomics and deep learning features were extracted from preoperative DCE-MRI. After dual selection by principal components analysis (PCA) and relief methods, radiomics and deep learning models for predicting LNM were constructed by the random forest (RF) method. A post-fusion strategy was used to construct the DLR nomograms (DLRNs) for predicting LNM. The performance of the models was evaluated using the receiver operating characteristic (ROC) curve and Delong test. In the training cohort, transcriptome data were downloaded from the UCSC Xena online database, and biological pathways related to the DLR phenotypes were identified. Finally, hub genes were identified to obtain DLR gene expression (RadDeepGene) scores. Results DLRNs were based on area under curve (AUC) evaluation (training cohort, AUC = 0.98; validation cohort, AUC = 0.87), which were higher than single radiomics models or GoogLeNet models. The Delong test (radiomics model, P = 0.04; GoogLeNet model, P = 0.01) also validated the above results in the training cohorts, but they were not statistically significant in the validation cohort. The GoogLeNet phenotypes were related to multiple classical tumor signaling pathways, characterizing the biological significance of immune response, signal transduction, and cell death. In all, 20 genes related to GoogLeNet phenotypes were identified, and the RadDeepGene score represented a high risk of LNM (odd ratio = 164.00, P

Abstract Background C‐reactive protein to albumin ratio (CRP/Alb ratio, CAR) has been suggested as a potential prognostic biomarker in lung cancer. This updated systematic review and meta‐analysis aimed to assess the association between CAR and lung cancer prognosis in current literature. Methods A systematic search of databases was conducted to identify relevant studies published up to April 2023. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to assess the association between CAR and overall survival (OS) and progression‐free survival (PFS) and recurrence‐free survival (RF) in lung cancer patients. Results This meta‐analysis includes 16 studies with a total of 5337 patients, indicating a significant association between higher CAR and poorer OS, PFS, and RFS in lung cancer patients, with a pooled HR of 1.78 (95% CI = 1.60–1.99), 1.57 (95% CI = 1.36–1.80), and 1.97 (95% CI = 1.40–2.77), respectively. Conclusions This updated meta‐analysis provides evidence for the potential prognostic role of CAR in lung cancer, suggesting its utility as an effective and noninvasive biomarker for identifying high‐risk patients and informing treatment decisions in a cost‐effective manner. However, further large‐scale studies will be necessary to establish the optimal cut‐off value for CAR in lung cancer and confirm the present findings.

Abstract To reduce the high burden of disease caused by air pollution, the World Health Organization (WHO) released new Air Quality Guidelines (AQG) on September 22, 2021. In this study, the daily fine particulate matter (PM2.5) and surface ozone (O3) data of 618 cities around the world is collected from 2019 to 2022. Based on the new AQG, the number of attainment days for daily average concentrations of PM2.5 (≤ 15 µg m−3) and O3 (≤ 100 µg m−3) is approximately 10% and 90%, respectively. China and India exhibit a decreasing trend in the number of highly polluted days (> 75 µg m−3) for PM. Every year over 68% and 27% of cities in the world are exposed to harmful PM2.5 (> 35 µg m−3) and O3 (> 100 µg m−3) pollution, respectively. Combined with the United Nations Sustainable Development Goals (SDGs), it is found that more than 35% of the world's cities face PM2.5‐O3 compound pollution. Furthermore, the exposure risks in these cities (China, India, etc.) are mainly categorized as “High Risk”, “Risk”, and “Stabilization”. In contrast, economically developed cities are mainly categorized as “High Safety”, “Safety”, and “Deep Stabilization.” These findings indicate that global implementation of the WHO's new AQG will minimize the inequitable exposure risk from air pollution.

Abstract CD8+ T cells are the executor in adaptive immune response, especially in anti-tumor immunity. They are the subset immune cells that are of high plasticity and multifunction. Their development, differentiation, activation and metabolism are delicately regulated by multiple factors. Stimuli from the internal and external environment could remodel CD8+ T cells, and correspondingly they will also make adjustments to the microenvironmental changes. Here we describe the most updated progresses in CD8+ T biology from transcriptional regulation to metabolism mechanisms, and also their interactions with the microenvironment, especially in cancer and immunotherapy. The expanding landscape of CD8+ T cell biology and discovery of potential targets to regulate CD8+ T cells will provide new viewpoints for clinical immunotherapy.

The X-type strike-slip fault system and weathering crust karst fracture-cave and channel reservoirs were developed in the Halahatang area of the northern Tarim Basin. However, the relationship between the reservoir and the strike-slip fault remains controversial. Based on the core data, and taking an NE-striking strike-slip fault as an example, this paper dissects the karst reservoir from wells along the strike-slip fault damage zone and analyzes the control of scales, properties, and segmentation styles of strike-slip faults on karst reservoirs. The results show that (1) the scale of the strike-slip fault controls the distribution of the reservoir—the wider the fault damage zone, the wider the fracture-cave reservoirs; (2) the transtensional segments of the strike-slip fault are more likely to produce karstification, and the buried-hill area and the interbedded area are controlled by different hydrodynamic conditions to form different types of karst reservoirs; (3) six different parts of the strike-slip fault are conducive to the formation scale of fault fracture zones. This research provides new insight into recognizing karst reservoirs within strike-slip fault damage zones, which can be further applied to predict karst reservoirs controlled by strike-slip faults.

Pore structure is the key element of tight sandstone reservoirs, which restricts the accumulate and flow of oil and gas in reservoirs. The pore structure is one of the key and difficult point of unconventional oil and gas exploration and development. In this paper, ten dense core samples from the Upper Triassic Yanchang Group 7 section in the Heshui area of the Ordos Basin are selected to carry out experiments, including high-pressure mercury pressure and X-diffraction. Fractal theory is used to analyze the characteristics of pore throats, then the relationship between fractal dimension and reservoir physical properties, pore structure and mineral content is analyzed. The results show that according to the mercury pressure curve and pore structure, the reservoir is divided into categories Ⅰ, Ⅱ and Ⅲ, its reservoir performance and seepage capacity decrease in turn, and the microheterogeneity is enhanced. Different types of reservoirs have different fractal characteristics: according to the inflection points of fractal curves 0.05 and 0.02 μm. The pore size of class Ⅰ reservoirs is divided into large pores (> 50 nm) and medium pores (50-6 nm) by combining the actual situation with the standard of pore size division proposed by IUPAC. According to the inflection point, the reservoirs of classes Ⅱ and Ⅲ can be divided into medium pores a (50-20 nm) and mesoporous B (20-6 nm). The average fractal dimension increased, which was 2.619 3, 2.745 4 and 2.852 6, respectively, and the heterogeneity gradually increased. The main permeability is contributed by fewer large pores, and the fractal dimension mainly reflects the heterogeneity of pore size. The fractal dimension is related to some minerals. Mineral composition and content are the internal factors that determine the fractal dimension and then affect the quality and pore structure of reservoirs.

With the rapid development of unconventional oil and gas resources, the demand for corresponding evaluation methods is increasing. At present, the evaluation methods for unconventional oil and gas resources are divided into analogy, statistical and genetic method. While constantly innovating evaluation methods, how to improve conventional methods and apply them to unconventional resource evaluation is also a focus and difficulty in current research. Taking a well as an unit and the EUR of the well as the unit's oil or gas reserves, a Pareto distribution model was established, and a program was compiled according to the principle of random sampling and skew sampling to analyze the sensitivity of number N, shape parameter and exploration coefficient E to the model. This method was applied to the shale oil resource evaluation in the X230 well block in Heshui area of Ordos Basin. Results show that the number of discoveries affects the size and dispersion of the parameters for oilfield distribution. The distribution model tends to be stable when the number is more than 300. Exploration coefficient has little influence on the sensitivity of distribution model, which is the limitation of taking EUR as evaluation unit. According to the variation of number N with shape parameter β, the number corresponding to cut-off point can be determined, that is, the sum of EUR of all wells is the recoverable resource of the area, which is 6.72×106 t. The result is consistent with the evaluation of oil and gas resource abundance. This method can provide guidance for unconventional oil and gas resources evaluation.

Anisotropic plasmonic metasurfaces have attracted broad research interest since they possess novel optical properties superior to natural materials and their tremendous design flexibility. However, the realization of multi-wavelength selective plasmonic metasurfaces that have emerged as promising candidates to uncover multichannel optical devices remains a challenge associated with weak modulation depths and narrow operation bandwidth. Herein, we propose and numerically demonstrate near-infrared multi-wavelength selective passive plasmonic switching (PPS) that encompasses high ON/OFF ratios and strong modulation depths via multiple Fano resonances (FRs) in anisotropic plasmonic metasurfaces. Specifically, the double FRs can be fulfilled and dedicated to establishing tailorable near-infrared dual-wavelength PPS. The multiple FRs mediated by in-plane mirror asymmetries cause the emergence of triple-wavelength PPS, whereas the multiple FRs governed by in-plane rotational asymmetries avail the implementation of the quasi-bound states in the continuum-endowed multi-wavelength PPS with the ability to unfold a tunable broad bandwidth. In addition, the strong polarization effects with in-plane anisotropic properties further validate the existence of the polarization-resolved multi-wavelength PPS. Our results provide an alternative approach to foster the achievement of multifunctional meta-devices in optical communication and information processing.

Pore structure restricts the reservoir capacity and flow capacity of oil and gas in the reservoir, which is the key factor of studying tight sandstone reservoir, and also the key and difficult problem of current research. Taking the Chang 7 tight reservoir of Upper Triassic Yanchang Formation in Heshui area of Ordos Basin as an example, the relationship between pore structure and movable fluid parameters was studied by combining high-pressure mercury injection and nuclear magnetic resonance (NMR) analysis techniques. The main results are as follows: ① when using the conventional method and linear least square method to convert the NMR T2 spectrum into pore radius, the pore structure can be divided into two parts, The correlation coefficient is (0.87-0.98)/0.92. The inflection point of the mercury injection curve is calculated by fractal theory, and the corresponding T2 is converted. The T2 spectrum is converted by segments. After the conversion, the curve has a high degree of overlap, and the number of phase relations is (0.97-0.99)/0.98. ② By analyzing the influencing factors of fluid mobility, it is found that there is a direct relationship between rock physical properties, in which porosity is more suitable to characterize the size of reservoir space, the correlation is 0.9, and the correlation with movable fluid saturation is better; The characteristic parameters of pore structure have a good correlation with the parameters of movable fluid, and the tight pore structure restricts the mobility of fluid. The proportion of dead pores is related to SMFS φ The negative correlation coefficients of MFS were 0.5371 and 0.3775, respectively φ MFS has little effect, but it has no effect φ MFS is more suitable to characterize the micro pore structure.

Abstract The monthly and hourly climatology of Saharan dust layer height over the Atlantic, at a spatial resolution of ∼10 km, is obtained for the first time, via a passive remote sensing technique. The technique is applied to multiple years of Earth Polychromatic Imaging Camera (EPIC) data collected at the Lagrange‐1 point, generating a climate data record (CDR) of aerosol optical centroid height (AOCH). This CDR offers unprecedented spatial coverage and diurnal sampling compared to spaceborne lidars (CALIOP and CATS). Our results show high correspondence with CALIOP data in domain‐averaged monthly variations and with CATS data in diurnal variations, respectively. A principal component analysis (PCA) reveals the dominant role of dust transport in regulating AOCH variation, whereas the impact of the boundary layer is less significant. MERRA‐2 and satellite retrievals respectively display zero and 200–1,000 m of diurnal variation of AOCH, highlighting the uniqueness of EPIC AOCH CDR in constraining climate models.

BackgroundRemarkably, the anti-cancer efficacy of immunotherapy in lung adenocarcinoma (LUAD) has been demonstrated. However, predicting the beneficiaries of this expensive treatment is still a challenge.Materials and methodsA group of patients (N = 250) diagnosed with LUAD and receiving immunotherapy were retrospectively studied. They were randomly divided into a training dataset (80%) and a test dataset (20%). The training dataset was utilized to train neural network models to predict patients’ objective response rate (ORR), disease control rate (DCR), responders (progression-free survival time > 6 months), and overall survival (OS) possibility, which were validated by both the training and test datasets and packaged into a tool later.ResultsIn the training dataset, the tool scored 0.9016 area under the receiver operating characteristic (AUC) curve on ORR judgment, 0.8570 on DCR, and 0.8395 on responder prediction. In the test dataset, the tool scored 0.8173 AUC on ORR, 0.8244 on DCR, and 0.8214 on responder determination. As for OS prediction, the tool scored 0.6627 AUC in the training dataset and 0.6357 in the test dataset.ConclusionsThis immunotherapy efficacy predictive tool for LUAD patients based on neural networks could predict their ORR, DCR, and responder well.

The Cenozoic in the western Qaidam Basin is rich in oil and gas resources and has good prospects for exploration. The maturity, sedimentary environment, and biological source of the crude oil in the western Qaidam Basin are discussed based on the composition characteristics of biomarkers in crude oil and source rocks. The above is performed to classify the genetic types of crude oil and determine the oil source relationship. It is found that the crude oil shows the characteristics of low mature–mature and is formed in the reducing environment with high salinity. The organic matter is from the mixed source with dominant aquatic plants input. According to the sedimentary environment, parent material types, and maturity characteristics, the crude oil in the western Qaidam Basin can be classified into four types. (1) Type I is from the Shizigou-Yuejin areas, which have a high content of gammacerane, a low value of Pr/Ph, C27 sterane predominance, and “tail-upwarping” phenomenon. (2) Type II is from the Qiekelike-Zhahaquan and Nanyishan-Youquanzi areas, which have C27 sterane predominance and no “tail-upwarping” phenomenon. Its content of gammacerane is lower than type I. (3) Type III is from the Dafengshan and Huangguamao areas, which have C29 sterane predominance and no “tail-upwarping” phenomenon. (4) Type IV is from the Kaitemilike area, which has a C27 sterane predominance, no “tail-upwarping” phenomenon, and lower content of gammacerane than that of others. The result of the oil-source correlation shows that the crude oil is dominantly derived from source rocks of the lower Ganchaigou Formation (E3) and the upper Ganchaigou Formation (N1).

A series of huge smoke plume events from the largest wildfire season recorded in California’s modern history has occurred in 2020. Here, a research algorithm was modified to retrieve the aerosol optical centroid height (AOCH) and aerosol optical depth (AOD) from Earth Polychromatic Imaging Camera (EPIC) measurements. The research focus is to gain insights of the algorithm’s feasibility in heavy smoke conditions to study the diurnal variation of AOCH; this is only made possible via EPIC due to its unique position at Lagrange-1 point and its equipment of O2 B-band at which the vegetated surface reflectance is low. Vicarious calibration is applied to the EPIC 443, 680 and 688 nm channels based on the Tropospheric Monitoring Instrument (TROPOMI) observation. This new calibration leads to a better agreement of AOCH values between EPIC retrievals and the counterparts derived from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol extinction vertical profile. The hourly variation of AOCH up to 0.45 km on September 7 is shown to have important implications for estimating hourly change of surface PM2.5, although more quantitative studies are needed in the future.

Concentrations of particulate aerosols and their vertical placement in the atmosphere determine their interaction with the Earth system and their impact on air quality. Space-based lidar, such as the Cloud–Aerosol Transport System (CATS) technology demonstration instrument, is well-suited for determining the vertical structure of these aerosols and their diurnal cycle. Through the implementation of aerosol-typing algorithms, vertical layers of aerosols are assigned a type, such as marine, dust, and smoke, and a corresponding extinction-to-backscatter (lidar) ratio. With updates to the previous aerosol-typing algorithms, we find that CATS, even as a technology demonstration, observed the documented seasonal cycle of aerosols, comparing favorably with the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) space-based lidar and the NASA Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2) model reanalysis. By leveraging the unique orbit of the International Space Station, we find that CATS can additionally resolve the diurnal cycle of aerosol altitude as observed by ground-based instruments over the Maritime Continent of Southeast Asia.

Lung cancer is the principal cause of leading cancer-related incidence and mortality in the world. Various studies have excavated the potential prognostic biomarkers for cancer patients based on gene expression profiles. However, most of these reported biomarkers lack independent validation in multiple cohorts. Herein, we collected 35 datasets with long-term follow-up clinical information from TCGA (2 cohorts), GEO (32 cohorts), and Roepman study (1 cohort), and developed a web server named OSluca (Online consensus Survival for Lung Cancer) to assess the prognostic value of genes in lung cancer. The input of OSluca is an official gene symbol, and the output web page of OSluca displays the survival analysis summary with a forest plot and a survival table from Cox proportional regression in each cohort and combined cohorts. To test the performance of OSluca, 104 previously reported prognostic biomarkers in lung carcinoma were evaluated in OSluca. In conclusion, OSluca is a highly valuable and interactive prognostic web server for lung cancer. It can be accessed at http:// bioinfo.henu.edu.cn/LUCA/LUCAList.jsp.

Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan–Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp.

Abstract The evolution of gas hydrates influenced by the seawater environment is unknown. We present a model of structural transformation from sI hydrate to sII hydrate due to the influence of seawater environment and vent fluid in nature through in situ experiments of gas hydrate formation in the Haima cold seep area. The in situ experimental results indicate that gas hydrates preferentially form as sI hydrates even in cold seep environments where C2+ hydrocarbons are present. During subsequent evolution, the sI hydrates could restructured at the effect of seawater environment and vent fluid, causing transformation to sII hydrates under the influence of hydrate stability. The supply of gas and direct contact with seawater environment are critical factors for structural transformation. Such structural transformation is the result of gas hydrates seeking thermodynamic stability and may be common in active cold seep areas.

The main objective of this paper is to reduce the dimensionality of unknown coefficient vectors of finite-element (FE) solutions in two-grid (CN) FE (TGCNFE) format for the nonlinear unsaturated soil water flow problem by using a proper orthogonal decomposition (POD) and to design a new reduced-dimension iteration TGCNFE (RDITGCNFE). For this objective, a new time semi-discrete CN (TSDCN) scheme for the nonlinear unsaturated soil water flow problem is first designed and the existence, stability, and error estimates of TSDCN solutions are demonstrated. Subsequently, a new TGCNFE format for the nonlinear unsaturated soil water flow problem is designed and the existence, unconditional stability, and error estimates of TGCNFE solutions are demonstrated. Next, a new RDITGCNFE format with the same FE basis functions as the TGCNFE format is built by the POD method and the existence, unconditional stability, and error estimates of RDITGCNFE solutions are discussed. Ultimately, the rightness of theory results and the superiority of the RDITGCNFE format are verified by two sets of numerical tests. It is worth noting that the RDITGCNFE format differs completely from all previous reduced-dimension methods, including the authors’ previous works. Therefore, the study of this paper can not only provide a new theoretical method for the dimensionality reduction of numerical models for nonlinear problems but also provide an algorithm implementation technology for the numerical simulation of practical engineering problems.

Abstract Zooplankton can affect and regulate the biological carbon pump in the biogeochemical cycles of marine ecosystems through diel vertical migration (DVM) behaviour. The diel vertical distribution and migration of a zooplankton community were studied at a continuous survey station in the Caroline Seamount area of the western tropical Pacific Ocean. Using a MultiNet sampling system, 346 zooplankton species/taxa were collected and identified. The vertical distribution patterns of abundance and composition of the zooplankton community differed between daytime and nighttime. The highest biodiversity index occurred in the 100–200-m ocean depth layer, but some zooplankton species remained in the deep-water layer below 300 m. The DVM patterns of the various dominant species differed, even when the species belonged to the same order or family. Dissolved oxygen and seawater temperature were the main environmental factors affecting the diel vertical distribution of the zooplankton community. The oxygen minimum zone was identified as performing the dual role of “ecological barrier” and “refuge” for zooplankton. The active carbon flux mediated by the zooplankton DVM in the Caroline Seamount area was 14.5 mg C/(m2·d). Our findings suggest that zooplankton DVM can affect and mediate the biological carbon pump in the Caroline Seamount area.

Abstract Hydrothermal H2S is an important energy source for hydrothermal ecosystems. However, it is difficult to obtain accurate hydrogen sulfide concentrations in high‐temperature hydrothermal fluids because they are highly susceptible to oxidation and compositional variability with mixing. In this study, a new in situ approach for measuring H2S, HS− and pH in hydrothermal fluids was developed and applied to the detections of Okinawa Trough hydrothermal activities. The in situ total H2S concentrations in the Jade and Biwako fluids were determined to be 31.4 and 76.7 mmol/kg, respectively. The in situ measured pH of the Jade fluids was determined to be 6.3, which has exceeded that of a neutral fluid at a specific temperature and pressure, indicating that the pH of Jade fluids is weakly alkaline. The pH transition of hydrothermal fluids from alkaline to acidic may be attributed to the thermal decomposition of organic matter and sulfide precipitation.

Gas production from several metabolic pathways is a necessary process that accompanies the growth and central metabolism of some microorganisms. However, accurate and rapid nondestructive detection of gas production is still challenging. To this end, gas chromatography (GC) is primarily used, which requires sampling and sample preparation. Furthermore, GC is expensive and difficult to operate. Several researchers working on microbial gases are looking forward to a new method to accurately capture the gas trends within a closed system in real-time. In this study, we developed a precise quantitative analysis for headspace gas in Hungate tubes using Raman spectroscopy. This method requires only a controlled focus on the gas portion inside Hungate tubes, enabling nondestructive, real-time, continuous monitoring without the need for sampling. The peak area ratio was selected to establish a calibration curve with nine different CH4–N2 gaseous mixtures and a linear relationship was observed between the peak area ratio of methane to nitrogen and their molar ratios (A(CH4)/A(N2) = 6.0739 × n(CH4)/n(N2)). The results of in situ quantitative analysis using Raman spectroscopy showed good agreement with those of GC in the continuous monitoring of culture experiments of a deep-sea cold seep methanogenic archaeon. This method significantly improves the detection efficiency and shows great potential for in situ quantitative gas detection in microbiology. It can be a powerful complementary tool to GC.

We here employ a proper orthogonal decomposition (POD) to reduce the dimensionality of unknown coefficient vectors of finite element (FE) solutions for the fractional Tricomi-type equation and develop a reduced-dimension extrapolating FE (RDEFE) method for the fractional Tricomi-type equation. For this purpose, we first develop an FE method for the fractional Tricomi-type equation and provide the existence, unconditional stability, and error analysis for the FE solutions. We then develop the RDEFE method for the fractional Tricomi-type equation by means of the POD technique and analyze the existence, unconditional stability, and errors for the RDEFE solutions by using the matrix analysis. Lastly, we provide two numerical examples to verify our theoretical results and to explain the advantages of the RDEFE method.

A cold seep is one of the typical deep-sea chemical energy ecosystems and a hotspot for studying unique life processes and biogeochemical cycles in the deep sea. Macrofauna, which is one of the most important components of the cold seep ecosystem, has not been thoroughly studied. We examined the macrofauna community at Site F using images collected in 2016 by an imaging and laser profiling system and biological samples collected in 2020 and 2021 by TV grab and a remotely operated vehicle. In total, 41 species were found. The overall number of macrofauna identified at Site F (20,000 m2) reached 252,943 individuals, and the biomass reached 726.15 kg by dry weight. As the dominant species, Gigantidas platifrons and Shinkaia crosnieri reached their highest densities of 629 and 396 individuals/m2, respectively. The comparisons between different stations revealed that the diversity and density, even the biomass of dominant species, were much higher in the south than in the north at Site F in 2020. Correlation analysis showed that methane had a positive effect on macrofauna density. Compared with S. crosnieri, G. platifrons seems to be more adapted to the harsh cold seep environment. Methane consumption rates of the dominant species show that macrofauna are important in influencing seafloor methane fluxes. Our findings provide valuable insights into the ecology, community structure, and biota-environment interaction in the cold seep at Site F.

Aiming at maritime infrared target detection with low contrast influenced by maritime clutter and illumination, this paper proposes a Modified Histogram Equalization with Edge Fusion (MHEEF) pre-processing algorithm in backlight maritime scenes and establishes Local-Contrast Saliency Models with Double Scale and Modes (LCMDSM) for detecting a target with the properties of positive and negative contrast. We propose a local-contrast saliency mathematical model with double modes in the extension of only one mode. Then, the big scale and small scale are combined into one Target Detection Unit (TDU), which can approach the “from bottom to up” mechanism of the Visual Attention Model (VAM) better and identify the target with a suitable size, approaching the target’s actual shape. In the experimental results and analysis, clutter, foggy, backlight, and dim maritime scenes are chosen to verify the effectiveness of the target detection algorithm. From the enhancement result, the LCMDSM algorithm can achieve a Detection Rate (DR) with a value of 98.26% under each maritime scene on the average level and can be used in real-time detection with low computational cost.

Confocal Raman microscopy (CRM) is a powerful tool for biological research, which can provide information regarding the composition and distribution of biomolecules in an in situ, label-free, non-destructive manner and with high spatial resolution. Sample preservation is often an unavoidable step, especially for symbiotic deep-sea samples. Moreover, protocols for the preservation of samples for CRM have not been established and specific effects of different preservation methods on biomolecules have not been studied for relevant samples. In this study, we used deep-sea mussel Gigantidas platifrons, an ideal model in the study of deep-sea symbiosis and investigated the effect of four common preservation methods on the results of CRM imaging and signals. The methods included snap-freeze (SF), SF followed by rapid fixation in methanol (SF-MeOH), 2.5% glutaraldehyde and 2% paraformaldehyde fixation (SF-GP), and 4% paraformaldehyde and alcohol fixation (PS-PA). The results of this study indicate that SF was the most effective method for the comprehensive analysis of the biomolecular composition although the sectioning success rate was relatively low. Moreover, SF-MeOH was found to be effective when SF is not sufficient in obtaining good morphology in sections, or when the effect of chemical bonding on the composition of biomolecules upon SF-MeOH can be neglected. Finally, SF-GP and PS-PA were found to be the most effective methods considering the overall morphological observation. However, they were less suitable for metabolic studies. We believe our results can provide guidance for further studies of Raman on symbiotic deep-sea biological samples. It is of great importance for the wide application of Raman technique.

Massive pulmonary embolism (MPE) is a high-risk medical emergency. Seizure as the clinical presentation of MPE is extremely rare, and to our knowledge, there have been no reports on successful percutaneous, catheter-based treatment of MPE presenting with new-onset seizures and cardiac arrest. In this report, we discuss the case of a 64-year-old woman who presented with an episode of seizure that lasted 5 h. Seizure occurred four times within 12 h after arrival at the hospital, and in the end, she sustained a cardiac arrest. The patient had no past history of seizure or cardiopulmonary disease. Bilateral MPE was detected by a computed tomography pulmonary angiogram, and she was successfully treated with percutaneous, catheter-directed anticoagulant therapy. Pulmonary embolism-related seizures are more difficult to diagnose and have higher mortality rates than seizures. MPE should be suspected in patients presenting with new-onset seizures and hemodynamic instability.

The mixed finite element (MFE) method is one of the most valid numerical approaches to solve hydrodynamic equations because it can be very suited to solving problems with complex computing domains. Regrettably, the MFE method for the hydrodynamic equations would include lots of unknowns. Especially, when it is applied to settling the practical engineering problems, it could contain hundreds of thousands and even tens of millions of unknowns. Thus, it would bring about many difficulties for actual applications, such as consuming a long CPU running time and accumulating many round-off errors, so as to be very difficult to obtain the desired numerical solutions. Therefore, we herein take the two-dimensional (2D) unsteady Navier–Stokes equation in hydrodynamics as an example. Using the proper orthogonal decomposition to lower the dimension of unknown Crank–Nicolson MFE (CNMFE) solution coefficient vectors for the 2D unsteady Navier–Stokes equation about vorticity–stream functions, we construct a reduced-dimension recursive CNMFE (RDRCNMFE) method with unchanged basis functions. In the circumstances, the RDRCNMFE method can keep the basis functions unchanged in an MFE subspace and has the same precision as the classical CNMFE method. We employ the matrix method to analyse the existence and stability along with errors to the RDRCNMFE solutions, leading to a very simple theory analysis. We use the numerical simulations for the backwards-facing step flow to verify the effectiveness of the RDRCNMFE method. The RDRCNMFE method with unchanged basis functions only reduces the dimension of the solution coefficient vectors of the CNMFE, which is completely different from previous order reduction methods which greatly affects the accuracy by reducing the dimension of the MFE subspace.

Herein, we mainly employ the fixed point theorem and Lax-Milgram theorem in functional analysis to prove the existence and uniqueness of generalized and mixed finite element (MFE) solutions for two-dimensional steady Boussinesq equation. Thus, we can fill in the gap of research for the steady Boussinesq equation since the existing studies for the equation are assumed the existence and uniqueness of generalized solution without providing proof.

PurposeTo establish and verify a predictive model involving multiparameter MRI and clinical manifestations for predicting synchronous lung metastases (SLM) in osteosarcoma.Materials and MethodsSeventy-eight consecutive patients with osteosarcoma (training dataset, n = 54; validation dataset, n = 24) were enrolled in our study. MRI features were extracted from the T1‐weighted image (T1WI), T2‐weighted image (T2WI), and contrast-enhanced T1-weighted image (CE-T1WI) of each patient. Least absolute shrinkage and selection operator (LASSO) regression and multifactor logistic regression were performed to select key features and build radiomics models in conjunction with logistic regression (LR) and support vector machine (SVM) classifiers. Eight individual models based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI+CE-T1WI, T2WI+CE-T1WI, T1WI+T2WI+CE-T1WI, and clinical features, as well as two combined models, were built. The area under the receiver operating characteristic curve (AUC), sensitivity and specificity were employed to assess the different models.ResultsTumor size was the most significant univariate clinical indicator (1). The AUC values of the LR predictive model based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI+CE-T1WI, T2WI+CE-T1WI, and T1WI+T2WI+CE-T1WI were 0.686, 0.85, 0.87, 0.879, 0.736, 0.85, and 0.914, respectively (2). The AUC values of the SVM predictive model based on T1WI, T2WI, CE-T1WI, T1WI+T2WI, T1WI +CE-T1WI, T2WI +CE-T1WI, and T1WI+T2WI+CE-T1WI were 0.629, 0.829, 0.771, 0.879, 0.643, 0.829, and 0.929, respectively (3). The AUC values of the clinical, combined 1 (clinical and LR-radiomics) and combined 2 (clinical and SVM-radiomics) predictive models were 0.779, 0.957, and 0.943, respectively.ConclusionThe combined model exhibited good performance in predicting osteosarcoma SLM and may be helpful in clinical decision-making.

Cold seep and hydrothermal vent system have unique function in mass circulation of the earth, and have been explored by in situ detection technologies in past decades. A brief review on the development and the newest applications of in situ laser spectroscopy for deep sea research is presented here. The laser Raman spectroscopy and laser induced breakdown spectroscopy, with the advantages exactly meeting the requirement of the in situ detection, are emphatically introduced in this paper. The prospect of the in situ laser spectroscopy for the possible application in the deep sea is also discussed in this paper, aiming to provide a reference for the future development of spectroscopy.

Abstract Background Although typical and atypical CT image findings of COVID-19 are reported in current studies, the CT image features of COVID-19 overlap with those of viral pneumonia and other respiratory diseases. Hence, it is difficult to make an exclusive diagnosis. Methods Thirty confirmed cases of COVID-19 and forty-three cases of other aetiology or clinically confirmed non-COVID-19 in a general hospital were included. The clinical data including age, sex, exposure history, laboratory parameters and aetiological diagnosis of all patients were collected. Seven positive signs (posterior part/lower lobe predilection, bilateral involvement, rounded GGO, subpleural bandlike GGO, crazy-paving pattern, peripheral distribution, and GGO +/− consolidation) from significant COVID-19 CT image features and four negative signs (only one lobe involvement, only central distribution, tree-in-bud sign, and bronchial wall thickening) from other non-COVID-19 pneumonia were used. The scoring analysis of CT features was compared between the two groups (COVID-19 and non-COVID-19). Results Older age, symptoms of diarrhoea, exposure history related to Wuhan, and a lower white blood cell and lymphocyte count were significantly suggestive of COVID-19 rather than non-COVID-19 (p 4, a sensitivity of 100% and a specificity of 23.26% for a score > 0, and a sensitivity of 86.67% and a specificity of 67.44% for a score > 2. Conclusions With a simple and practical scoring system based on CT imaging features, we can make a hierarchical diagnosis of COVID-19 and non-COVID-19 with different management suggestions.

Abstract We develop the Crank–Nicolson finite element (CNFE) method for the two-dimensional (2D) uniform transmission line equation, study the stability and existence as well as error estimates for the CNFE solutions of the 2D uniform transmission line equation by strict theoretical approaches. We verify the correctness of the obtained theoretical results by means of numerical tests.

Abstract In this article, we mainly develop a reduced order extrapolating model for the solution coefficient vectors of the classical collocation spectral (CCS) scheme to the two-dimensional (2D) telegraph equation by means of a proper orthogonal decomposition (POD). Therefore, we first present the CCS scheme, offer the existence, stability, and error estimates to the SC solutions, and rewrite the CCS scheme into a matrix-form. We then build a reduced order extrapolating collocation spectral (ROECS) model and analyze the existence and stability as well as errors of the ROECS solutions by some matrix tools. We finally verify the reliability and validity of the ROECS model by means of two sets of numerical simulations for the magnetic field produced by two parallel wires with the same voltage.

Abstract In this study, a time semi-discretized Crank–Nicolson (CN) scheme of the two-dimensional (2D) unsteady conduction–convection problems for vorticity and stream functions is first built together with showing the existence and stability along with error estimates to the semi-discretized CN solutions. Afterwards, a fully discretized spectral element CN (SECN) model of the 2D unsteady conduction–convection problems as regards the vorticity and stream functions is set up together with showing the proof of the existence and stability along with error estimates of the SECN solution. Lastly, a set of numerical experiments are offered for checking the correctness of the theoretical conclusions.

Objective: To evaluate the mammographic features, clinicopathological characteristics, treatments, and prognosis of pure and mixed tubular carcinomas of the breast. Materials and methods: Twenty-five tubular carcinomas were pathologically confirmed at our hospital from January 2011 to May 2019. Twenty-one patients underwent preoperative mammography. A retrospective analysis of mammographic features, clinicopathological characteristics, treatment, and outcomes was performed. Results: Altogether, 95% of the pure tubular carcinomas (PTCs) and mixed tubular carcinomas (MTCs) showed the presence of a mass or structural distortions on mammography and the difference was not statistically significant ( P = .373). MTCs exhibited a larger tumor size than PTCs ( P = .033). Lymph node metastasis was more common ( P = .005) in MTCs. Patients in our study showed high estrogen receptor and progesterone receptor positivity rates, but low human epidermal growth factor receptor 2 positivity rate. The overall survival rate was 100% in both PTC and MTC groups and the 5-year disease-free survival rates were 100% and 75%, respectively with no significant difference between the groups ( P = .264). Conclusion: Tubular carcinoma of the breast is potentially malignant and has a favorable prognosis. Digital breast tomosynthesis may improve its detection. For patients with PTC, breast-conserving surgery and sentinel lymph node biopsy are recommended based on the low rate of lymph node metastasis and good prognosis. MTC has a relatively high rate of lymph node metastasis and a particular risk of metastasis. Axillary lymph node dissection should be performed for MTC even if the tumor is smaller than 2 cm.

Characterizing habitats and species distribution is important to understand the structure and function of cold seep ecosystems. This paper develops a deep learning model for the fast and accurate recognition and classification of substrates and the dominant associated species in cold seeps. Considering the dense distribution of the dominant associated species and small objects caused by overlap in cold seeps, the feature pyramid network (FPN) embed into the faster region-convolutional neural network (R-CNN) was used to detect large-scale changes and small missing objects without increasing the number of calculations. We applied three classifiers (Faster R-CNN + FPN for mussel beds, lobster clusters and biological mixing, CNN for shell debris and exposed authigenic carbonates, and VGG16 for reduced sediments and muddy bottom) to improve the recognition accuracy of substrates. The model’s results were manually verified using images obtained in the Formosa cold seep during a 2016 cruise. The recognition accuracy of the two dominant species, e.g., Gigantidas platifrons and Munidopsidae could be 70.85 and 56.16%, respectively. Seven subcategories of substrates were also classified with a mean accuracy of 74.87%. The developed model is a promising tool for the fast and accurate characterization of substrates and epifauna in cold seeps, which is crucial for large-scale quantitative analyses.

The unsaturated flow problem is of important applied background and its mixed finite element (MFE) method can be used to simultaneously calculate both water content and flux in soil, which is the most ideal calculation method. Nonetheless, it includes many unknowns. Thereby, herein we will employ the proper orthogonal decomposition (POD) to lower the dimension of unknown solution coefficient vectors in the MFE method for the unsaturated flow problem. Thus, we first examine the MFE method for the unsaturated flow problem and the existence and convergence of the classical MFE solutions. We then take advantage of the initial L MFE solution coefficient vectors to generate a set of POD basis vectors and utilize the most POD basis vectors to create the preserving precision MFE reduced-dimension (PPMFERD) format. Under the circumstances, the PPMFERD format has the same basis functions as the classical MFE format so that it can maintain the same accuracy as the classical MFE format, but it only includes a few unknowns, so it greatly lightens the calculating load, retards the accumulation of computing errors, saves CPU runtime, and improves the accuracy of the real-time calculation in the computational process. Next, we employ the analysis of matrices to demonstrate the existence and convergence of the PPMFERD solutions such that the theoretical analysis becomes very simple and elegant. Finally, we take advantage of some numerical simulations to check on the correctness of the PPMFERD method. It shows that the PPMFERD method is effective and feasible for simulating both water content and flux in unsaturated flow soil.

We herein mainly employ a proper orthogonal decomposition (POD) to study the reduced dimension of unknown solution coefficient vectors in the Crank–Nicolson finite element (FE) (CNFE) method for the symmetric tempered fractional diffusion equation so that we can build the reduced-dimension recursive CNFE (RDRCNFE) method. In this case, the RDRCNFE method keeps the same basic functions and accuracy as the CNFE method. Especially, we adopt the matrix analysis to discuss the stability and convergence of RDRCNFE solutions, resulting in the very laconic theoretical analysis. We also use some numerical simulations to confirm the correctness of theoretical results.

In this study, we mainly employ a proper orthogonal decomposition (POD) to lower the dimension for the unknown Crank–Nicolson finite element (FE) (CNFE) solution coefficient vectors of the viscoelastic wave (VW) equation so as to build a reduced-dimension recursive CNFE (RDRCNFE) algorithm, adopt matrix analysis to analyze the stability together with errors to the RDRCNFE solutions, and utilize some numerical experimentations to verify the effectiveness of the RDRCNFE algorithm.

Abstract In this paper, we mainly use a proper orthogonal decomposition (POD) to reduce the order of the coefficient vectors of the solutions for the classical collocation spectral (CS) method of two-dimensional (2D) Sobolev equations. We first establish a reduced-order extrapolating collocation spectral (ROECS) method for 2D Sobolev equations so that the ROECS method includes the same basis functions as the classic CS method and the superiority of the classic CS method. Then we use the matrix means to discuss the existence, stability, and convergence of the ROECS solutions so that the procedure of theoretical analysis becomes very concise. Lastly, we present two set of numerical examples to validate the effectiveness of theoretical conclusions and to illuminate that the ROECS method is far superior to the classic CS method, which shows that the ROECS method is quite valid to solve Sobolev equations. Therefore, both theory and method of this paper are completely different from the existing reduced-order methods.

Abstract In this paper, by means of a proper orthogonal decomposition (POD) we mainly reduce the order of the classical Crank–Nicolson finite difference (CCNFD) model for the fractional-order parabolic-type sine-Gordon equations (FOPTSGEs). Toward this end, we will first review the CCNFD model for FOPTSGEs and the theoretical results (such as existence, stabilization, and convergence) of the CCNFD solutions. Then we establish an optimized Crank–Nicolson finite difference extrapolating (OCNFDE) model, including very few unknowns but holding the fully second-order accuracy for FOPTSGEs via POD. Next, by a matrix analysis we will discuss the existence, stabilization, and convergence of the OCNFDE solutions. Finally, we will use a numerical example to validate the validity of theoretical conclusions. Moreover, we show that the OCNFDE model is very valid for settling FOPTSGEs.

By means of a proper orthogonal decomposition (POD) to cut down the dimensionality of unknown finite element (FE) solution coefficient vectors in the Crank–Nicolson (CN) mixed FE (CNMFE) method for two-dimensional (2D) unsteady Stokes equations in regard to vorticity stream functions, a reduced dimension recursive-CNMFE (RDR-CNMFE) method is constructed. In this case, the RDR-CNMFE method has the same FE basis functions and accuracy as the CNMFE method. The existence, stability, and errors of RDR-CNMFE solutions are analyzed by matrix analyzing, resulting in very simple theory analysis. Some numerical tries are used to check on the validity of the RDR-CNMFE method. The RDR-CNMFE method has second-order time accuracy and few unknowns so as to be able to shorten CPU runtime and retard the error cumulation in simulation calculating process, and improve real-time calculating accuracy.

Abstract In this article, we first develop a semi-discretized Crank–Nicolson format about time for the two-dimensional non-stationary Stokes equations about vorticity–stream functions and analyze the existence, uniqueness, stability, and convergence of the semi-discretized Crank–Nicolson solutions. Then we establish a fully discretized Crank–Nicolson finite spectral element format based on the quadrilateral elements for the two-dimensional non-stationary Stokes equations about vorticity–stream functions and analyze the existence, uniqueness, stability, and convergence of the Crank–Nicolson finite spectral element solutions. In the end, we use three numerical examples to confirm the validity of our theoretical conclusions.

Abstract In this paper, we mainly focus to study the Crank–Nicolson collocation spectral method for two-dimensional (2D) telegraph equations. For this purpose, we first establish a Crank–Nicolson collocation spectral model based on the Chebyshev polynomials for the 2D telegraph equations. We then discuss the existence, uniqueness, stability, and convergence of the Crank–Nicolson collocation spectral numerical solutions. Finally, we use two sets of numerical examples to verify the validity of theoretical analysis. This implies that the Crank–Nicolson collocation spectral model is very effective for solving the 2D telegraph equations.

Abstract In this paper, we focus on the study of the Crank–Nicolson finite difference (CNFD) scheme for the Riesz space fractional-order parabolic-type sine-Gordon equation (RSFOPTSGE). For this purpose, we first establish the CNFD scheme for RSFOPTSGE. Then, we discuss the existence, uniqueness, stability, and convergence of the CNFD solutions. Finally, we supply a numerical experiment to validate the correctness of theoretical results. This indicates that the CNFD scheme is very effective for solving RSFOPTSGE.

Abstract This article mainly studies a collocation spectral method for two-dimensional (2D) Sobolev equations. To this end, a collocation spectral model based on the Chebyshev polynomials for the 2D Sobolev equations is first established. And then, the existence, uniqueness, stability, and convergence of the collocation spectral numerical solutions are discussed. Finally, some numerical experiments are provided to verify the corrections of theoretical results. This implies that the collocation spectral model is very effective for solving the 2D Sobolev equations.

Abstract In this article, we devote ourselves to establishing a natural boundary element (NBE) method for the Sobolev equation in the 2D unbounded domain. To this end, we first constitute the time semi-discretized super-convergence format for the Sobolev equation by means of the Newmark method. Then, using the principle of natural boundary reduction, we establish a fully discretized NBE format based on the natural integral equation and the Poisson integral formula of this problem and analyze the errors between the exact solution and the fully discretized NBE solutions. Finally, we use some numerical experiments to verify that the NBE method is effective and feasible for solving the Sobolev equation in the 2D unbounded domain.

Abstract In this study, we first present a classical finite element (FE) method for a two-dimensional (2D) viscoelastic wave equation and analyze the existence, stability, and convergence of the FE solutions. Then we establish an optimized FE extrapolating (OFEE) method based on a proper orthogonal decomposition (POD) method for the 2D viscoelastic wave equation and analyze the existence, stability, and convergence of the OFEE solutions and furnish the implement procedure of the OFEE method. Finally, we furnish a numerical example to verify that the numerical computing results correspond with the theoretical ones. This signifies that the OFEE method is feasible and efficient for solving the 2D viscoelastic wave equation.

Abstract In this article, we devote ourselves to building a stabilized finite volume element (SFVE) method with a non-dimensional real together with two Gaussian quadratures of the nonlinear incompressible viscoelastic flow equation in a two-dimensional (2D) domain, analyzing the existence, stability, and error estimates of the SFVE solutions and verifying the validity of the preceding theoretical conclusions by numerical simulations.

Abstract In this paper, we devote ourselves to establishing the unconditionally stable and absolutely convergent optimized finite difference Crank-Nicolson iterative (OFDCNI) scheme containing very few degrees of freedom but holding sufficiently high accuracy for the two-dimensional (2D) Sobolev equation by means of the proper orthogonal decomposition (POD) technique, analyzing the stability and convergence of the OFDCNI solutions and using the numerical simulations to verify the feasibility and effectiveness of the OFDCNI scheme.