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Abstract The central Sichuan Basin, located in western China, holds great significance in terms of hydrocarbon production, especially in relation to complex carbonate reservoirs, notably the Qixia Formation of the Middle Permian epoch. However, the comprehensive evaluation of this geological formation presents considerable challenges due to complex lithology, limited availability of reservoir property data at various scales, inadequacies in data integration, and the absence of a reliable reservoir ranking system for development decision making. Previous studies primarily relying on conventional data at the reservoir level, such as well logs and geological information, have proven insufficient in accurately characterizing the reservoir. This is especially evident without precise lithological information and detailed knowledge of microscale properties, which are crucial for effective reservoir evaluation. To address these challenges, this study integrates advanced technologies like X-ray diffraction, micro-CT and scanning electron microscope (SEM) techniques in digital drill cutting analysis at the microscale. A novel scoring system has been developed using a prominent component analysis (PCA) approach and an expert scoring system, which incorporates existing conventional well log data and digital cutting analysis. This scoring system has been validated using actual production data, thus establishing a robust evaluation methodology for assessing the exploration potential and optimizing development strategies for carbonate gas reservoirs in the Qixia Formation. The innovative approach, which incorporates parameters at both micro- and macroscales, holds promising potential in facilitating future exploration and development efforts.

Parkinson’s disease (PD) is a ubiquitous brain cell degeneration disease and presents a significant therapeutic challenge. By injecting 6-hydroxydopamine (6-OHDA) into the left medial forebrain bundle, rats were made to exhibit PD-like symptoms and treated by intranasal administration of a low-dose (2 × 105) or high-dose (1 × 106) human neural stem cells (hNSCs). Apomorphine-induced rotation test, stepping test, and open field test were implemented to evaluate the motor behavior and high-performance liquid chromatography was carried out to detect dopamine (DA), 3,4-dihydroxyphenylacetic acid (DOPAC), serotonin, and 5-hydroxyindole-3-acetic acid in the striatum of rats. Animals injected with 6-OHDA showed significant motor function deficits and damaged dopaminergic system compared to the control group, which can be restored by hNSCs treatment. Treatment with hNSCs significantly increased the tyrosine hydroxylase-immunoreactive cell count in the substantia nigra of PD animals. Moreover, the levels of neurotransmitters exhibited a significant decline in the striatum tissue of animals injected with 6-OHDA when compared to that of the control group. However, transplantation of hNSCs significantly elevated the concentration of DA and DOPAC in the injured side of the striatum. Our study offered experimental evidence to support prospects of hNSCs for clinical application as a cell-based therapy for PD.

BackgroundThe systemic immune-inflammation index (SII) showed an extensive link between immunological dysfunction and the activation of systemic inflammation. Several studies have confirmed the application of SII to orthopedic diseases. However, the significance of SII in critically ill elderly individuals with hip fracture who require intensive care unit (ICU) admission is not yet known. This study centered on exploring the relationship between SII and clinical outcomes among critically ill elderly hip fracture individuals.MethodsThe study centered around elderly patients experiencing severe illness following hip fractures and requiring admission to the ICU. These patients from the MIMIC-IV database formed the basis of this study’s cohort. We stratified them into quartiles according to their SII levels. The results involved the mortality at 30 days and 1 year post-admission. Then we employ Cox proportional hazards regression analysis as well as restricted cubic splines to explore the association between the SII and clinical results in critically ill elderly patients with hip fracture.ResultsThe study encompassed 991 participants, among whom 63.98% identified as females. Notably, the mortality rates attributed to any cause within 30 days and 1 year after hospitalization stood at 19.68 and 33.40%, respectively. The multivariate Cox proportional hazards model disclosed a significant correlation between an elevated SII and all-cause mortality. Following adjustments for confounding variables, individuals with a high SII showed a notable correlation with 30-day mortality [adjusted hazard ratio (HR), 1.065; 95% confidence interval (CI), 1.044–1.087; p

Traditional machining is transforming to digital and intelligent machining, in which adaptive machining cyber-physical system (CPS) provides a useful approach to control the machining quality of large thin-walled parts. And the running of adaptive machining CPS is a complex multi-processes execution flow, which can be regarded as a continuous–discrete hybrid system. To realise adaptive controlling of machining quality and adaptive managing of process flow, a unified model for continuous–discrete hybrid adaptive machining CPS is constructed. Firstly, an architecture of adaptive machining CPS is proposed. Next, the cutting process in adaptive machining CPS is modelled as a continuous-variable system (CVS), while the process flow in adaptive machining CPS is modelled as a discrete-events system (DES). Then, the finite state machine is adopted to integrate the CVS and DES to form the unified model of adaptive machining CPS. Finally, an adaptive machining CPS is developed based on the unified model, and the machining results demonstrate that machining quality is efficiently controlled, as well as the process flow is orderly managed. The built unified model has four features, respectively universality, integrability, scalability, and reconfigurability, which can be reconstructed to form a new instancing model according to the different machining requirements. [ABSTRACT FROM AUTHOR]

Optimizing product selectivity and conversion efficiency are primary goals in catalysis. However, efficiency and selectivity are often mutually antagonistic, so that high selectivity is accompanied by low efficiency and vice versa. Also, just increasing the temperature is very unlikely to change the reaction pathway. Here, by constructing hierarchical plasmonic nanoreactors, we show that nanoconfined thermal fields and energetic electrons, a combination of attributes that coexist almost uniquely in plasmonic nanostructures, can overcome the antagonism by regulating selectivity and promoting conversion rate concurrently. For propylene partial oxidation, they drive chemical reactions by not only regulating parallel reaction pathways to selectively produce acrolein but also reducing consecutive process to inhibit the overoxidation to CO2, resulting in valuable products different from thermal catalysis. This suggests a strategy to rationally use plasmonic nanostructures to optimize chemical processes, thereby achieving high yield with high selectivity at lower temperature under visible light illumination.

Malaria is one of the major global health threats. Microscopic examination has been designated as the “gold standard” for malaria detection by the World Health Organization. However, it heavily relies on the experience of doctors, resulting in long diagnosis time, low efficiency, and a high risk of missed or misdiagnosed cases. To alleviate the pressure on healthcare workers and achieve automated malaria detection, numerous target detection models have been applied to the blood smear examination for malaria cells. This paper introduces the multi-level attention split network (MAS-Net) that improves the overall detection performance by addressing the issues of information loss for small targets and mismatch between the detection receptive field and target size. Therefore, we propose the split contextual attention structure (SPCot), which fully utilizes contextual information and avoids excessive channel compression operations, reducing information loss and improving the overall detection performance of malaria cells. In the shallow detection layer, we introduce the multi-scale receptive field detection head (MRFH), which better matches targets of different scales and provides a better detection receptive field, thus enhancing the performance of malaria cell detection. On the NLM—Malaria Dataset provided by the National Institutes of Health, the improved model achieves an average accuracy of 75.9% in the public dataset of Plasmodium vivax (malaria)-infected human blood smear. Considering the practical application of the model, we introduce the Performance-aware Approximation of Global Channel Pruning (PAGCP) to compress the model size while sacrificing a small amount of accuracy. Compared to other state-of-the-art (SOTA) methods, the proposed MAS-Net achieves competitive results.

Cancer continues to threaten people's lives and health, and the number of deaths from cancer is very high each year. Traditional treatments such as chemotherapy and surgery are poorly selective and have many side effects. While traditional cancer treatments kill tumor cells, they also damage normal cells and cause a series of toxic side effects. Targeted therapy can compensate for the shortcomings of conventional therapies based on nanomaterials. This paper introduces novel nanomaterials commonly used in tumor-targeted drug delivery as well as imaging therapy, demonstrates the types of active and passive drug delivery systems, and gives examples of research and applications in the past three years. The characteristics of nanomaterials for tumor-targeted therapy and their recent research progress in tumor therapy are summarized. This paper provides theoretical and practical support for nanomaterial-based targeted drug delivery systems and imaging therapy for tumors and provides a reference for the development of nanomaterials for controlled targeted therapy for tumors.

Abstract Formation damage is a common phenomenon and is impaired to the reservoir by reducing the productivity. Formation damage is usually caused by solids plugging, clay swelling, saturation changes, etc., and fracturing fluids with a series of chemical additives are pumped into the well for production enhancement. It is difficult to optimize the fracture fluids and well shut-in time due to lack of fundamental understandings. Currently, little research has been done to investigate the mechanisms of formation damage at the pore scale. In this study, a combination of digital rock technology and core sample laboratory soaking experiments is used to evaluate the formation damages for different fracture fluids in tight sandstone reservoir. Three core samples from a full-diameter core are soaked in three different fracture fluids (surfactant, polymer, and gel) for eight different durations (from 2 h to 15d) to simulate well shut-in process. The samples in various soak times are scanned by X-ray micro-computer tomography (Micro-CT) to obtain the 3D images of the true geometry. The images are then compared to optimize the fracture fluids and quantify the damage degree after various well shut-in times. Then, displacement processes are simulated using lattice Boltzmann method (LBM) to evaluate the residual oil saturations and optimize the well shut-in time. The study suggests that the well shut-in process can cause irreversible damage to tight sandstone reservoir even for optimized fracture fluid. In the initial shut-in stages, clays swelling dominates pore structure alteration and reduces the porosity. Calcite will dissolute after which lead to slight porosity increase. In the flowback process after well shut-in, the simulated residual oil saturation will decrease initially and then increase after, which is complied with the porosity variation. The digital rock technology combined with the soaking experiments will provide alternative method for the evaluation of formation damage and the optimization of well shut-in time in tight sandstone reservoir, which can guide the selection of the fracture fluids and onsite fracturing operation.