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Based on drilling and logging data, as well as geological experiments, the geological characteristics and factors controlling high-yield and enrichment of hydrocarbons in ultra-deep clastic rocks in the Linhe Depression, Hetao Basin, are studied. The results are obtained in four aspects. First, the inland saline lacustrine high-quality source rocks developed in the Paleogene in the Linhe Depression have the characteristics of early maturity, early expulsion, high hydrocarbon yield, and continuous and efficient hydrocarbon generation, providing an important resource basis for the formation of ultra-high pressure and high-yield reservoirs. Second, the weak compaction, early charging, and weak cementation for pore-preserving, together with the ultra-high pressure for pore-preserving and fracture expansion to improve the permeability, leads to the development of high-quality reservoirs with medium porosity (greater than 15%) and medium permeability (up to 226×10−3 μm2) in the ultra-deep strata (deeper than 6 500 m), which represents a greatly expanded space for oil and gas exploration. Third, the Linhe Formation adjacent to the trough exhibits a low net-to-gross (NTG) and good reservoir-caprock assemblage, and it is overlaid by very thick high-quality mudstone caprock, which are conducive to the continuous and efficient hydrocarbon generation and pressurization and the formation of ultra-high pressure oil and gas reservoirs. Fourth, the most favorable targets for ultra-deep exploration are the zones adjacent to the hydrocarbon generating center of the Paleogene Linhe Formation and with good tectonic setting and structural traps, mainly including the Xinglong faulted structural zone and the Nalinhu faulted buried-hill zone. The significant breakthrough of ultra-deep oil and gas exploration in the Linhe Depression reveals the good potential of ultra-deep clastic rocks in this area, and provides valuable reference for oil and gas exploration of ultra-deep clastic rocks in other areas.

Abstract Tin dioxide is regarded as an alternative anode material rather than graphite due to its high theoretical specific capacity. Modification with carbon is a typical strategy to mitigate the volume expansion effect of SnO2 during the charge process. Strengthening the interface bonding is crucial for improving the electrochemical performance of SnO2/C composites. Here, SnO2-embedded reduced graphene oxide (rGO) composite with a low graphene content of approximately 5 wt.% was in situ synthesized via a cetyltrimethylammonium bromide (CTAB)-assisted hydrothermal method. The structural integrity of the SnO2/rGO composite is significantly improved by optimizing the Sn–O–C electronic structure with CTAB, resulting a reversible capacity of 598 mAh g−1 after 200 cycles at a current density of 1 A g−1. CTAB-assisted synthesis enhances the rate performance and cyclic stability of tin dioxide/graphene composites, and boosts their application as the anode materials for the next-generation lithium-ion batteries.

Based on new data from cores, drilling and logging, combined with extensive rock and mineral testing analysis, a systematic analysis is conducted on the characteristics, diagenesis types, genesis and controlling factors of deep to ultra-deep abnormally high porosity clastic rock reservoirs in the Oligocene Linhe Formation in the Hetao Basin. The reservoir space of the deep to ultra-deep clastic rock reservoirs in the Linhe Formation is mainly primary pores, and the coupling of three favorable diagenetic elements, namely the rock fabric with strong compaction resistance, weak thermal compaction diagenetic dynamic field, and diagenetic environment with weak fluid compaction-weak cementation, is conducive to the preservation of primary pores. The Linhe Formation clastic rocks have a superior preexisting material composition, with an average total content of 90% for quartz, feldspar, and rigid rock fragments, and strong resistance to compaction. The geothermal gradient in Linhe Depression in the range of (2.0–2.6) °C/100 m is low, and together with the burial history of long-term shallow burial and late rapid deep burial, it forms a weak thermal compaction diagenetic dynamic field environment. The diagenetic environment of the saline lake basin is characterized by weak fluid compaction. At the same time, the paleosalinity has zoning characteristics, and weak cementation in low salinity areas is conducive to the preservation of primary pores. The hydrodynamic conditions of sedimentation, salinity differentiation of ancient water in saline lake basins, and sand body thickness jointly control the distribution of high-quality reservoirs in the Linhe Formation.

Abstract Intravenous remdesivir (RDV) is US Food and Drug Administration–approved for hospitalized and nonhospitalized individuals with coronavirus disease 2019. RDV undergoes intracellular metabolic activation to form the active triphosphate, GS‐443902, and other metabolites. Alternative administration routes, including localized pulmonary delivery, can lower systemic exposure and maximize exposure at the site of action. This study evaluated the pharmacokinetics (PK) and safety of inhaled RDV in healthy adults. This phase Ia, randomized, placebo‐controlled study evaluated inhaled RDV in healthy participants randomized 4:1 to receive RDV or placebo as single doses (4 cohorts) or multiple once‐daily doses (3 cohorts). Doses in cohorts 1–6 were administered as an aerosolized solution for inhalation through a sealed facemask; doses in cohort 7 were administered as an aerosolized solution for inhalation through a mouthpiece. Safety was assessed throughout the study. Seventy‐two participants were enrolled (inhaled RDV, n = 58 and placebo, n = 14). Following single RDV doses, RDV, GS‐704277, and GS‐441524 plasma PK parameters indicated dose‐proportional increases in area under the concentration‐time curve (AUC) extrapolated to infinite time, AUC from time zero to last quantifiable concentration, and maximum observed concentration. Analyte plasma concentrations after multiple RDV doses were consistent with those for single‐dose RDV. Analyte plasma exposures were lower when RDV was administered with a mouthpiece versus a sealed facemask. The most common adverse events included nausea, dizziness, and cough. Single‐ and multiple‐dose inhaled RDV exhibited linear and dose‐proportional plasma PK. Administration of RDV via inhalation was generally safe and well‐tolerated.

Based on paleogeomorphology, drilling and seismic data, this paper systematically studies the structural and sedimentary evolution, source rock characteristics, reservoir characteristics and formation mechanism, hydrocarbon accumulation model and enrichment law in the Linhe Depression of the Hetao Basin, NW China. The Hetao Basin mainly experienced three stages of evolution, namely, weak extensional fault depression, strong extensional fault depression and strike-slip transformation, giving rise to four positive structural belts (Jilantai, Shabu, Nalinhu and Xinglong), which are favorable areas for oil and gas accumulation. The two main saline lacustrine source rocks, Lower Cretaceous Guyang Formation and Oligocene Linhe Formation, are characterized by high sulfur content, rich algae, early maturity, early expulsion, and wide oil generation window. The large structural transition belt in the intermountain area around the Hetao Basin controls the formation of large-scale braided river delta deposits, which are characterized by high quartz content (50%–76%), long-term shallow burial and weak compaction, low cement content, and good reservoir properties in delta front sandbody. The burial depth of the effective Paleogene reservoirs is predicted to reach 8000 m. Three hydrocarbon accumulation models, nose-uplift near sag, buried hill surrounding sag, fault nose near source rock, are constructed. The law of hydrocarbon accumulation in the Linhe Depression is finally clarified as follows: near-source around the depression is the foundation, high-quality thick reservoir is the premise, good tectonic setting and trap conditions are the key.

Abstract Introduction In the PINETREE study, early remdesivir treatment reduced risk of coronavirus disease 2019 (COVID-19)-related hospitalizations or all-cause death versus placebo by 87% by day 28 in high-risk, non-hospitalized patients. Here we report results of assessment of heterogeneity of treatment effect (HTE) of early outpatient remdesivir, focusing on time from symptom onset and number of baseline risk factors (RFs). Methods PINETREE was a double-blind, placebo-controlled trial of non-hospitalized patients with COVID-19 who were randomized within 7 days of symptom onset and had ≥ 1 RF for disease progression (age ≥ 60 years, obesity [body mass index ≥ 30], or certain coexisting medical conditions). Patients received remdesivir intravenously (200 mg on day 1 and 100 mg on days 2 and 3) or placebo. Results In this subgroup analysis, HTE of remdesivir by time from symptom onset at treatment initiation and number of baseline RFs was not detected. Treatment with remdesivir reduced COVID-19-related hospitalizations independent of stratification by time from symptom onset to randomization. Of patients enrolled ≤ 5 days from symptom onset, 1/201 (0.5%) receiving remdesivir and 9/194 (4.6%) receiving placebo were hospitalized (hazard ratio [HR] 0.10; 95% confidence interval [CI] 0.01–0.82). Of those enrolled at > 5 days from symptom onset, 1/78 (1.3%) receiving remdesivir and 6/89 (6.7%) receiving placebo were hospitalized (HR 0.19; 95% CI 0.02–1.61). Remdesivir was also effective in reducing COVID-19-related hospitalizations when stratified by number of baseline RFs for severe disease. Of patients with ≤ 2 RFs, 0/159 (0.0%) receiving remdesivir and 4/164 (2.4%) receiving placebo were hospitalized; of those with ≥ 3 RFs, 2/120 (1.7%) receiving remdesivir and 11/119 (9.2%) receiving placebo were hospitalized (HR 0.16; 95% CI 0.04–0.73). Conclusions In the outpatient setting, benefit of remdesivir initiated within 7 days of symptoms appeared to be consistent across patients with RFs. Therefore, it may be reasonable to broadly treat patients with remdesivir regardless of comorbidities. Trial Registration ClinicalTrials.gov number NCT04501952.

The effectiveness of a wind turbine elastic support in reducing vibrations significantly impacts the unit’s lifespan. During the structural design process, it is necessary to consider the influence of structural design parameters on multiple performance indicators. While neural networks can fit the relationships between design parameters on multiple performance indicators, traditional modeling methods often isolate multiple tasks, hindering the learning on correlations between tasks and reducing efficiency. Moreover, acquiring training data through physical experiments is expensive and yields limited data, insufficient for effective model training. To address these challenges, this research introduces a data generation method using a digital twin model, simulating physical conditions to generate data at a lower cost. Building on this, a Multi-gate Mixture-of-Experts multi-task prediction model with Long Short-Term Memory (MMoE-LSTM) module is developed. LSTM enhances the model’s ability to extract nonlinear features from data, improving learning. Additionally, a dynamic weighting strategy, based on coefficient of variation weighting and ridge regression, is employed to automate loss weight adjustments and address imbalances in multi-task learning. The proposed model, validated on datasets created using the digital twin model, achieved over 95% predictive accuracy for multiple tasks, demonstrating that this method is effective.

With the widespread application of computer technology in engineering education, Online Judge (OJ) systems have become an important platform for programming teaching. OJ systems provide a platform for learners to practice programming skills, submit solutions, and receive feedback. They offer a conducive environment for learners to engage in hands-on coding exercises and enhance their programming abilities. This article explores the use of OJ systems as a software tool for enhancing programming education in engineering. It investigates how the difficulty and order of programming problems affect the users' behavior, performance, and cognitive load in OJ environments. The research data were sourced from Project_CodeNet. Using statistical methods, such as Spearman correlation analysis and differential analysis, the study reveals the factors that influence the users' submission situations, answer order, and learning outcomes. The findings provide useful implications for OJ system developers, teachers, and learners in designing, implementing, and using OJ systems for programming education in engineering. The study suggests that problem difficulty and order should be considered and adjusted according to the users' abilities and progress, to provide appropriate challenges and support, balance the cognitive load, and improve the programming skills of the users.

Abstract Psoralea corylifolia L. (PCL), referred to as “Bu-gu-zhi” in Chinese, has great medicinal values since ancient times. PCL is the dried ripe fruit of Psoralea corylifolia L., which has been widely used in traditional Chinese medicine (TCM) for the treatment of kidney-yang deficiency, enuresis and urinary frequency, chills and pain of the waist and knees, dawn diarrhea and vitiligo. In this paper, a systematic of the botany, traditional uses, phytochemistry, pharmacology, toxicology, quality control and pharmacokinetics of PCL was presented, along with future research directions. According to the results, PCL contains approximately 163 chemical components, including coumarins, flavonoids, monoterpene phenols, benzofurans, glycosides, lipids, fatty acids, and volatile oils. PCL and its active ingredients have a variety of pharmacological activities, such as anti-inflammatory, antibacterial, antiviral, antioxidant, antitumor, antiosteoporosis, cardioprotective, neuroprotective, and immunomodulatory. Further study of quality control standards and potential mechanisms of PCL is also needed. In addition, more toxicological studies will also contribute to the progress of clinical trials.

Pan et al. determine the impact of the antiviral remdesivir (RDV) on biomarkers associated with clinical outcomes, within a randomized, double-blind, placebo-controlled phase 3 study (PINETREE). They demonstrate that RDV-treated patients have an accelerated reduction in soluble angiopoietin-2, D-dimer and neutrophil-to-lymphocyte ratios.

Abstract Background The present study aimed to explore the boundary of acquisition time and propose an optimized acquisition time range for total-body positron emission tomography (PET)/computed tomography (CT) oncological imaging using half-dose (1.85 MBq/kg) 18F-fluorodeoxyglucose activity based on diagnostic needs. Methods In this retrospective study based on a total-body PET system (uEXPLORER), an exploration cohort (October 2019–December 2019) of 46 oncology patients was first studied. The acquisition time for all patients was 15 min, and the acquired images were reconstructed and further split into 15-, 8-, 5-, 3-, 2-, and 1-min duration groups (abbreviated as G15, G8, G5, G3, G2, and G1). The image quality and lesion detectability of reconstructed PET images with different acquisition times were evaluated subjectively (5-point scale, lesion detection rate) and objectively (standardized uptake values, tumor-to-background ratio). In the same way, the initial optimized acquisition times were further validated in a cohort of 147 oncology patients (December 2019–June 2021) by using the Gs images (the images obtained using the 15- and 10-min acquisition times) as controls. Results In the exploration cohort, the subjective scores for G1, G2, G3, G5, and G8 images were 2.0 ± 0.2, 2.9 ± 0.3, 3.0 ± 0.0, 3.9 ± 0.2, and 4.2 ± 0.4, respectively. Two cases in G1 were rated as 1 point. No significant difference in scores was observed between G5 and G8 (p > 0.99). In general, groups with a longer acquisition time showed lower background uptake and lesion conspicuity. Compared with G15, lesion detection rate significantly reduced to 85.3% in G1 (p 0.99). The detection rates (204 lesions) significantly reduced to 94.1–90.2% in G3 and G2 (all p

The stress relief processes, such as thermal stress relief (TSR) and vibratory stress relief (VSR), are generally applied to decrease and control the residual stress in the manufacturing process. Thermal-vibratory stress relief (TVSR) is a novel stress relief method developed in recent years, which has significant advantages over traditional methods. The stress relief mechanism of TVSR and stress evolution under the coupling effect of heat and vibration still need further investigation. In this study, TSR, VSR and TVSR with different process parameters are compared to study their stress relief effect on Ti6Al4V, and corresponding FEM simulations are performed to calculate the stress evolution. The residual stress is measured using X-ray diffraction method. EBSD and TEM characterizations are carried out to investigate the influences on the phase, crystal grain and dislocation. Results show that both TVSR and TSR can eliminate over 90% of residual stress of Ti6Al4V, but the efficiency of TVSR is 4.2 times as that of TSR. The stress relief rate of TVSR is 45.04% higher than that of VSR with the same dynamic stress. Finally, the quantitative relationship between TVSR parameters and residual stress is established, and the stress relief mechanism and effective parameter region of TVSR are analyzed.

Abstract Purpose The purpose of this study was to investigate the image quality and diagnostic performance of different reconstructions over a wide range of patient body mass indices (BMIs) obtained by total-body PET/CT with ultra-low 18F-FDG activity (0.37 MBq/kg). Methods A total of 63 patients who underwent total-body PET/CT with ultra-low activity (0.37 MBq/kg) 18F-FDG were enrolled. Patients were grouped by their BMIs. Images were reconstructed with the following two algorithms: the ordered subset expectation maximization (OSEM) algorithm (2, 3 iterations), both with time of flight (TOF) and point spread function (PSF) corrections (hereinafter referred as OSEM2, OSEM3) and HYPER Iterative algorithm (β-values of 0.3, 0.4, 0.5, 0.6) embedded TOF and PSF technologies (hereinafter referred as HYPER0.3, HYPER0.4, HYPER0.5 and HYPER0.6, respectively). Subjective image quality was assessed by two experienced nuclear medicine physicians according to the Likert quintile, including overall image quality, image noise and lesion conspicuity. The standard deviation (SD) and signal-to-noise ratio (SNR) of the liver, and maximum standard uptake value (SUVmax), peak standard uptake value (SUVpeak), tumour background ratio (T/N) and the largest diameter of lesions were quantitatively analysed by a third reader who did not participate in the subjective image assessment. Results Increased noise was associated with increased BMI in all reconstruction groups. Significant differences occurred in the liver SNR among BMI categories of OSEM reconstructions (P 0.05). With the increase in BMI, overall image quality and image noise scores decreased significantly in all reconstructions, but there was no statistically significant difference of lesion conspicuity. The overall image quality score of the obese group was not qualified (score = 2.7) in OSEM3, while the others were qualified. The lesion conspicuity scores were significantly higher in HYPER Iterative reconstructions and lower in OSEM2 than in OSEM3 (all P

Abstract Iron is vital for many physiological functions, including energy production, and dysregulated iron homeostasis underlies a number of pathologies. Ferroptosis is a recently recognized form of regulated cell death that is characterized by iron dependency and lipid peroxidation, and this process has been reported to be involved in multiple diseases. The mechanisms underlying ferroptosis are complex, and involve both well-described pathways (including the iron-induced Fenton reaction, impaired antioxidant capacity, and mitochondrial dysfunction) and novel interactions linked to cellular energy production. In this review, we examine the contribution of iron to diverse metabolic activities and their relationship to ferroptosis. There is an emphasis on the role of iron in driving energy production and its link to ferroptosis under both physiological and pathological conditions. In conclusion, excess reactive oxygen species production driven by disordered iron metabolism, which induces Fenton reaction and/or impairs mitochondrial function and energy metabolism, is a key inducer of ferroptosis.

The visible-infrared pedestrian re- identification (VI Re-ID) task aims to match cross-modality pedestrian images with the same labels. Most current methods focus on mitigating the modality discrepancy by adopting a two-stream network and identity supervision. Based on current methods, we propose a novel feature fusion and center aggregation learning network ( $F^{2}$ CALNet) for cross-modality pedestrian re- identification. $F^{2}$ CALNet focuses on learning modality-irrelevant features by simultaneously reducing inter-modality discrepancies and increasing the inter-identity variations in a single framework. Specifically, we first adopt a two-stream backbone network to extract modality-independent and modality-shared information. Then, we embed modality mitigation modules in a two-stream network to learn feature maps that are stripped of the modality information. Finally, we devise a feature fusion and center aggregation learning module, which first merges two different granularity features to learn distinguishing features, then, we organize two kinds of center-based loss functions to reduce the intra-identity inter- and intra-modality differences and increase inter-identity variations by simultaneously pulling the features of the same identity close to their centers and pushing far away the centers of different identities. Extensive experiments on two public cross-modality datasets (SYSU-MM01 and RegDB) show that $F^{2}$ CALNet is superior to the state-of-the-art approaches. Furthermore, on the SYSU-MM01 datasets, our model outperforms the baseline by 5.52% and 4.25% for the accuracy of rank1 and mAP, respectively.

Li7La3Zr2O12 (LLZO) garnets are one of the most promising solid electrolytes for next generation all-solid-state Li metal batteries due to their high ionic conductivities, chemical stabilities to metallic lithium and wide electrochemical window. Single and co-doped LLZO with Ga, Al, Nb were prepared by solid state reaction and sintered under oxygen atmosphere. Lithium ion conduction properties were investigated through electrochemical impedance spectroscopy in the temperature range of −25 °C–45 °C. Among the doped compositions, Ga doped single phase cubic LLZO shows the highest ionic conductivity of 1.49 × 10−3 S/cm at room temperature and activation energy of 0.27eV, which is one of the best results reported in literature so far in terms of doped garnet structured LLZO. All single or co-doped LLZO samples exhibit low electronic conduction which are 4–5 orders of magnitude lower than their corresponding ionic conductivities. Ga-doped garnet LLZO of high ionic conductivity and negligible electronic conduction makes it a superior solid electrolyte for all-solid-state Li metal batteries.

As an important part of the industrialization process, fully automated instrument monitoring and identification are experiencing an increasingly wide range of applications in industrial production, autonomous driving, and medical experimentation. However, digital instruments usually have multi-digit features, meaning that the numeric information on the screen is usually a multi-digit number greater than 10. Therefore, the accuracy of recognition with traditional algorithms such as threshold segmentation and template matching is low, and thus instrument monitoring still relies heavily on human labor at present. However, manual monitoring is costly and not suitable for risky experimental environments such as those involving radiation and contamination. The development of deep neural networks has opened up new possibilities for fully automated instrument monitoring; however, neural networks generally require large training datasets, costly data collection, and annotation. To solve the above problems, this paper proposes a new instrument monitoring method based on few-shot learning (FLIMM). FLIMM improves the average accuracy (ACC) of the model to 99% with only 16 original images via effective data augmentation method. Meanwhile, due to the controllability of simulated image generation, FLIMM can automatically generate annotation information for simulated numbers, which greatly reduces the cost of data collection and annotation.

The efficient and cost-effective residual stress control method is of great significance for the application of additive manufacturing (AM) technology. In this work, thermal-vibration stress relief (TVSR) with different temperatures and dynamic stresses was performed on Ti6Al4V samples prepared by selective laser melting (SLM), the stress relief effects of TVSR and its influence on phase and microstructure were investigated and compared with thermal stress relief (TSR) and vibration stress relief (VSR), and the stress relief mechanisms of these methods are discussed. It was found that the residual stress relief rate can reach 86.76% after TVSR treatment at a temperature of 380 °C and a dynamic stress of 400 MPa, which increased by 63.63% compared with VSR under the same dynamic stress. The efficiency is increased by 76% compared with TSR at 580 °C and the residual stress relief rate is almost the same. After TVSR, VSR and TSR treatments, the grain morphology, size and phase content of samples were basically unchanged, and low-angle grain boundaries (LAGBs) were increased after TVSR and VSR treatments and decreased after TSR treatment. The results confirm that the TVSR method has the ability to control the residual stress of selective laser melted Ti6Al4V with low time and cost consumption, and are helpful for engineering applications of TVSR.

Different alcoholic beverages and drinking patterns might exert divergent impacts on alcoholic liver disease (ALD) progression. Whether the abundant non-alcoholic components (NAC) in fermented wine could alleviate ethanol (EtOH)-induced adverse influences on the liver remains unknown. Hence, the chronic ALD mouse model was established to compare the effects of Huangjiu (a typical fermented wine) and EtOH feeding on the liver, intestinal barrier, gut microbiota, and intestinal short-chain fatty acids (SCFAs) content. Although Huangjiu intake led to slight hepatic steatosis, it mitigated oxidative stress, inflammation, and intestinal damage relative to EtOH intake. In comparison with EtOH feeding, Huangjiu significantly improved the intestinal barrier integrity and reduced hepatic lipopolysaccharide levels by up-regulating the expression of intestinal tight junction proteins (ZO-1 and occludin) and antimicrobial activity peptides (Reg3β and Reg3γ). The administration of Huangjiu NAC partially restored alcohol-induced gut microbiota dysbiosis via recovering the abundance of Lactobacillus, Faecalibaculum, and Akkermansia. Moreover, mice receiving Huangjiu showed higher SCFAs levels (such as acetic acid and butyric acid) than those receiving EtOH. Huangjiu consumption resulted in lower hepatotoxicity than pure EtOH, at the same alcohol dose. The NAC in Huangjiu might attenuate the progression of ALD by regulating intestinal barrier function and microbiota-meditated gut ecology.