Prediction and analysis of components and functions of Ixeris chinensis based on network pharmacology and molecular docking.

Background: It is reported that the Ixeris chinensis has high medicinal value, but there are few reports about its potential molecular mechanism. We used a network pharmacology approach to predict the active ingredients, targets of action and possible interventions in diseases of Ixeris chinensis. Methods: We employed various databases and software to predict the active ingredients, target genes, protein interactions, signaling pathways, network diagrams, and molecular docking of Ixeris chinensis. Simultaneously, we searched multiple Chinese and English databases and conducted meta-analyses of five randomized controlled trials. Results: The analysis results revealed 12 effective components, including apigenin ß-sitosterol, baicalin, baicalein, and luteolin; and selected 40 key targets, including AKT1, TNF, EGFR, ESR1, SRC, among others. GO analysis generated 225 biological processes, 39 cellular components, and 65 molecular functions; KEGG analysis revealed 103 signaling pathways. Molecular docking results indicated that the main active components of Ixeris chinensis can bind well with key targets. Five randomized controlled trials were included. Meta-analysis showed that Ixeris extract can effectively reduce animal blood lipid levels. Conclusion: This study revealed the main active ingredients and key targets of Ixeris chinensis, analyzed the signaling pathways of potential targets, conducted disease prediction, and performed molecular docking prediction, providing a basis for research on the pathways of Ixeris treatment for related diseases and subsequent new drug development.

Uterine tumors resembling ovarian sex cord tumors: A retrospective analysis of 7 cases from a single institution.

To investigate the clinicopathological features, diagnosis, surgical treatment and prognosis of uterine tumors similar to ovarian sex cord tumors (UTROSCT). The clinical data, surgical approach, histopathological, and immunohistochemical features of 7 cases of UTROSCTs were retrospectively reviewed and followed up. All 4 patients were premenopausal women. The most common clinical presentation was menorrhagia (n = 4) followed by postmenopausal lower abdominal mass (n = 2) and postmenopausal bleeding (n = 1). Gynecological ultrasonography suggested uterine fibroids in 4 cases, adenomyosis with uterine fibroids in 2 cases, and an intrauterine mass in 1 case. Pelvic MRI was performed preoperatively in only 2 cases, and both indicated uterine fibroid degeneration, including 1 patient with suspected malignancy. Preoperative serum tumor markers were measured in 6 patients, and only 1 patient had elevated CA125 levels, up to 158 U/mL. Total hysterectomy with bilateral adnexectomy or salpingectomy was the most common treatment pattern (n = 6). The tumors were located within the myometrium (n = 4), submucosa (n = 1), and isthmus to external cervical os (n = 1), with a range of 2 to 12 (mean = 8) cm. Edema and degeneration were observed in 2 cases, and necrosis in 1 case. Postoperative follow-up ranged from 31 to 82 (mean = 43) months. Unfortunately, 1 patient died at 54 months of follow-up without undergoing hysterectomy. The remaining 6 cases showed no tumor recurrence or metastasis after surgery. Histological examination revealed a tumor composed of epithelioid tumor-like cells arranged in cords, trabeculae, and nests. All 7 tumors showed expression of 2 sex cord differentiation markers. Furthermore, all tumors expressed the smooth muscle marker, while epithelial marker CK (4/7). endometrial stromal marker CD10(0/7). The Ki-67 proliferation index was found to be <5% (5/7). The option of total hysterectomy may be considered for women who do not have any fertility requirements. However, for young women who desire to maintain their reproductive capacity, surgery to preserve the uterus may be an alternative, although it necessitates careful postoperative monitoring. In terms of follow-up monitoring, MRI is more suitable than ultrasound. The diagnosis of UTROSCT heavily relies on histopathological examination and immunohistochemical analysis.

Liver Fibrosis Amelioration by Macrophage-Biomimetic Polydopamine Nanoparticles via Synergistically Alleviating Inflammation and Scavenging ROS.

The progression of liver fibrosis is determined by the interaction of damaged hepatocytes, active hepatic stellate cells, and macrophages, contributing to the development of oxidative stress and inflammatory environments within the liver. Unfortunately, the current pharmacological treatment for liver fibrosis is limited by its inability to regulate inflammation and oxidative stress concurrently. In this study, we developed a cell membrane biomaterial for the treatment of liver fibrosis, which we designated as PM. PM is a biomimetic nanomaterial constructed by encapsulating polydopamine (PDA) with a macrophage membrane (MM). It is hypothesized that PM nanoparticles (NPs) can successfully target the site of inflammation, simultaneously inhibit inflammation, and scavenge reactive oxygen species (ROS). In vitro experiments demonstrated that PM NPs exhibited strong antioxidant properties and the ability to neutralize pro-inflammatory cytokines (TNF-α, IL-6, and IL-1ß). Moreover, the capacity of PM NPs to safeguard cells from oxidative stress and their anti-inflammatory efficacy in an inflammatory model were validated in subsequent cellular experiments. Additionally, PM NPs exhibited a high biocompatibility. In a mouse model of hepatic fibrosis, PM NPs were observed to aggregate efficiently in the fibrotic liver, displaying excellent antioxidant and anti-inflammatory properties. Notably, PM NPs exhibited superior targeting, anti-inflammatory, and ROS scavenging abilities in inflamed tissues compared to MM, PDA, or erythrocyte membrane-encapsulated PDA. Under the synergistic effect of anti-inflammation and antioxidant, PM NPs produced significant therapeutic effects on liver fibrosis in mice. In conclusion, the synergistic alleviation of inflammation and ROS scavenging by this specially designed nanomaterial, PM NPs, provides valuable insights for the treatment of liver fibrosis and other inflammatory- or oxidative stress-related diseases.

Chromium Catalysts for Selective Ethylene Oligomerization Featuring Binuclear PNP Ligands.

A series of novel binuclear PNP ligands based on the cyclohexyldiamine scaffold were synthesized for this study. The experimental results showed that positioning the two PNP sites at the para-positions of the cyclohexyl framework led to a significant enhancement in the catalytic activity for selective tri/tetramerization of ethylene. The PNP/Cr(acac)3/MAO(methylaluminoxane) catalytic system exhibited relatively high catalytic activity (up to 3887.7 kg·g-1·h-1) in selective ethylene oligomerization with a total selectivity of 84.5% for 1-hexene and 1-octene at 40 °C and 50 bar. The relationship between the ligand structure and ethylene oligomerization performance was further explored using density functional theory calculations.

Design optimization of groundwater circulation well based on numerical simulation and machine learning.

The optimal design of groundwater circulation wells (GCWs) is challenging. The key to purifying groundwater using this technique is its proficiency and productivity. However, traditional numerical simulation methods are limited by long modeling times, random optimization schemes, and optimization results that are not comprehensive. To address these issues, this study introduced an innovative approach for the optimal design of a GCW using machine learning methods. The FloPy package was used to create and implement the MODFLOW and MODPATH models. Subsequently, the formulated models were employed to calculate the characteristic indicators of the effectiveness of the GCW operation, including the radius of influence (R) and the ratio of particle recovery (Pr). A detailed collection of 3000 datasets, including measures of operational efficiency and key elements in machine learning, was meticulously compiled into documents through model execution. The optimization models were trained and evaluated using multiple linear regression (MLR), artificial neural networks (ANN), and support vector machines (SVM). The models produced by the three approaches exhibited notable correlations between anticipated outcomes and datasets. For the optimal design of circulating well parameters, machine learning methods not only improve the optimization speed, but also expand the scope of parameter optimization. Consequently, these models were applied to optimize the configuration of the GCW at a site in Xi'an. The optimal scheme for R (Q = 293.17 m3/d, a = 6.09 m, L = 7.28 m) and optimal scheme for Pr (Q = 300 m3/d, a = 3.64 m, L = 1 m) were obtained. The combination of numerical simulations and machine learning is an effective tool for optimizing and predicting the GCW remediation effect.

A Framework for Single-Panicle Litchi Flower Counting by Regression with Multitask Learning.

The number of flowers is essential for evaluating the growth status of litchi trees and enables researchers to estimate flowering rates and conduct various phenotypic studies, particularly focusing on the information of individual panicles. However, manual counting remains the primary method for quantifying flowers, and there has been insufficient emphasis on the advancement of reliable deep learning methods for estimation and their integration into research. Furthermore, the current density map-based methods are susceptible to background interference. To tackle the challenges of accurately quantifying small and dense male litchi flowers, a framework counting the flowers in panicles is proposed. Firstly, an existing effective algorithm YOLACT++ is utilized to segment individual panicles from images. Secondly, a novel algorithm FlowerNet based on density map regression is proposed to accurately count flowers in each panicle. By employing a multitask learning approach, FlowerNet effectively captures both foreground and background information, thereby overcoming interference from non-target areas during pixel-level regression tasks. It achieves a mean absolute error of 47.71 and a root mean squared error of 61.78 on the flower dataset constructed. Additionally, a regression equation is established using a dataset of inflorescences to examine the application of the algorithm for flower counting. It captures the relationship between the predicted number of flowers by FlowerNet and the manually counted number, resulting in a determination coefficient (R2) of 0.81. The proposed algorithm shows promise for automated estimation of litchi flowering quantity and can serve as a valuable reference for litchi orchard management during flowering period.

The application value of deep learning-based nomograms in benign-malignant discrimination of TI-RADS category 4 thyroid nodules.

Thyroid nodules are a common occurrence, and although most are non-cancerous, some can be malignant. The American College of Radiology has developed the Thyroid Imaging Reporting and Data System (TI-RADS) to standardize the interpretation and reporting of thyroid ultrasound results. Within TI-RADS, a category 4 designation signifies a thyroid nodule with an intermediate level of suspicion for malignancy. Accurate classification of these nodules is crucial for proper management, as it can potentially reduce unnecessary surgeries and improve patient outcomes. This study utilized deep learning techniques to effectively classify TI-RADS category 4 thyroid nodules as either benign or malignant. A total of 500 patients were included in the study and randomly divided into a training group (350 patients) and a test group (150 patients). The YOLOv3 model was constructed and evaluated using various metrics, achieving an 84% accuracy in the classification of TI-RADS category 4 thyroid nodules. Based on the predictions of the model, along with clinical and ultrasound data, a nomogram was developed. The performance of the nomogram was superior in both the training and testing groups. Furthermore, the calibration curve demonstrated good agreement between predicted probabilities and actual outcomes. Decision curve analysis further confirmed that the nomogram provided greater net benefits. Ultimately, the YOLOv3 model and nomogram successfully improved the accuracy of distinguishing between benign and malignant TI-RADS category 4 thyroid nodules, which is crucial for proper management and improved patient outcomes.

Research on the ditching resistance reduction of self-excited vibrations ditching device based on MBD-DEM coupling simulation.

In plant horticulture, furrow fertilizing is a common method to promote plant nutrient absorption and to effectively avoid fertilizer waste. Considering the high resistance caused by soil compaction in southern orchards, an energy-saving ditching device was proposed. A standard ditching blade with self-excited vibration device was designed, and operated in sandy clay with a tillage depth of 30cm. To conduct self-excited vibration ditching experiments, a simulation model of the interaction between soil and the ditching mechanism was established by coupling the ADAMS and EDEM software. To begin with, the ditching device model was first set up, taking into account its motion and morphological characteristics. Then, the MBD-DEM coupling method was employed to investigate the interaction mechanism and the effect of ditching between the soil particles and the ditching blade. Afterwards, the time-domain and frequency-domain characteristics of vibration signals during the ditching process were analyzed using the fast fourier transform (FFT) method, and the energy distribution characteristics were extracted using power spectral density (PSD). The experimental results revealed that the vibrations ditching device has reciprocating displacement in the Dx direction and torsional displacements in the θy and θz directions during operation, verifying the correctness of the coupling simulation and the effectiveness of vibrations ditching resistance reduction. Also, a load vibrations ditching bench test was conducted, and the results demonstrated that the self-excited vibrations ditching device, compared with common ditching device, achieved a reduction in ditching resistance of up to 12.3%. The reasonable parameters of spring stiffness, spring damping, and spring quality in self-excited vibrations ditching device can achieve a satisfied ditching performance with relatively low torque consumption at an appropriate speed.

Laser Welding of Titanium/Steel Bimetallic Sheets with In Situ Formation of Fex(CoCrNiMn)Tiy High-Entropy Alloys in Weld Metal.

Due to the notable disparities in the physical and chemical characteristics between titanium and steel, the direct fusion of titanium/steel bimetallic sheets results in a considerable formation of fragile intermetallic compounds, making it difficult to achieve excellent metallurgical welded joints. In this study, a multi-principal powder of CoCrNiMn was designed and utilized as a filler material in the welding of the TA1/Q345 bimetallic sheet. It was expected that the in situ formation of Fex(CoCrNiMn)Tiy high-entropy alloys would be achieved using the filler powders, combined with the Ti and Fe elements from the melting of the TA1 and Q345 so as to restrain the generation of Fe-Ti IMCs and obtain the promising welded joints of the TA1/Q345 bimetallic sheet. An interesting finding is that high-entropy alloys were successfully obtained in the weld metal. The Fe-Ti intermetallic compounds at the welding interface were significantly reduced. The tensile strength was ~293 MPa, accounting for 60% of the strength of the base metal. Dimples were observed at the fracture of the welded joint.

Bacterial and host factors involved in zoonotic Streptococcal meningitis.

Zoonotic streptococci cause several invasive diseases with high mortality rates, especially meningitis. Numerous studies elucidated the meningitis pathogenesis of zoonotic streptococci, some specific to certain bacterial species. In contrast, others are shared among different bacterial species, involving colonization and invasion of mucosal barriers, survival in the bloodstream, breaching the blood-brain and/or blood-cerebrospinal fluid barrier to access the central nervous system, and triggering inflammation of the meninges. This review focuses on the recent advancements in comprehending the molecular and cellular events of five major zoonotic streptococci responsible for causing meningitis in humans or animals, including Streptococcus agalactiae, Streptococcus equi subspecies zooepidemicus, Streptococcus suis, Streptococcus dysgalactiae, and Streptococcus iniae. The underlying mechanism was summarized into four themes, including 1) bacterial survival in blood, 2) brain microvascular endothelial cell adhesion and invasion, 3) penetration of the blood-brain barrier, and 4) activation of the immune system and inflammatory reaction within the brain. This review may contribute to developing therapeutics to prevent or mitigate injury of streptococcal meningitis and improve risk stratification.

Role of macrophage polarization in periodontitis promoting atherosclerosis.

Periodontitis is a chronic inflammatory destructive disease occurring in periodontal supporting tissues. Atherosclerosis(AS) is one of the most common cardiovascular diseases. Periodontitis can promote the development and progression of AS. Macrophage polarization is closely related to the development and progression of the above two diseases, respectively. The purpose of this animal study was to evaluate the effect of periodontitis on aortic lesions in atherosclerotic mice and the role of macrophage polarization in this process. 45 ApoE-/-male mice were randomly divided into three groups: control (NC), atherosclerosis (AS), and atherosclerosis with periodontitis (AS + PD). Micro CT, serological testing and pathological testing(hematoxylin-eosin staining, oil red O staining and Masson staining) were used for Evaluate the modeling situation. Immunohistochemistry(IHC) and immunofluorescence(IF) were performed to evaluate macrophage content and macrophage polarization in plaques. Cytokines associated with macrophage polarization were analyzed using quantitative real-time polymerase chain reaction(qRT-PCR) and enzyme-linked immunosorbent assay(Elisa). The expression of macrophages in plaques was sequentially elevated in the NC, AS, and AS + PD groups(P < 0.001). The expression of M1 and M1-related cytokines showed the same trend(P < 0.05). The expression of M2 and M2-related cytokines showed the opposite trend(P < 0.05). The rate of M1/M2 showed that AS + PD > AS > NC. Our preliminary data support that experimental periodontitis can increase the content of macrophage in aortic plaques to exacerbate AS. Meanwhile, experimental periodontitis can increase M1 macrophages, and decrease M2 macrophages, increasing M1/M2 in the plaque.

Driving mechanism of different nutrient conditions on microbial mediated nitrate reduction in magnetite-present river infiltration zone.

Significant research is focused on the ability of riparian zones to reduce groundwater nitrate contamination. Owing to the extremely high redox activity of nitrate, naturally existing electron donors, such as organic matter and iron minerals, are crucial in facilitating nitrate reduction in the riparian zone. Here, we examined the coexistence of magnetite, an iron mineral, and nitrate, a frequently observed coexisting system in sediments, to investigate nitrate reduction features at various C/N ratios and evaluate the response of microbial communities to these settings. Additionally, we aimed to use this information as a foundation for examining the effect of nutritional conditions on the nitrate reduction process in magnetite-present environments. These results emphasise the significance of organic matter in enabling dissimilatory nitrate reduction to ammonium (DNRA) and enhancing the connection between nitrate reduction and iron in sedimentary environments. In the later phases of nitrate reduction, nitrogen fixation was the prevailing process in low-carbon environments, whereas high-carbon environments tended to facilitate the breakdown of organic nitrogen. High-throughput sequencing analysis revealed a robust association between C/N ratios and alterations in microbial community composition, providing insights into notable modifications in essential functioning microorganisms. The nitrogen-fixing bacterium Ralstonia is more abundant in ecosystems with scarce organic matter. In contrast, in settings rich in organic matter, microorganisms, such as Acinetobacter and Clostridia, which may produce ammonia, play crucial roles. Moreover, the population of iron bacteria grows in such an environment. Hence, this study proposes that C/N ratios can influence Fe(II)/Fe(III) conversions and simultaneously affect the process of nitrate reduction by shaping the composition of specific microbial communities.

Anti-Inflammatory Effect of Columbianadin against D-Galactose-Induced Liver Injury In Vivo via the JAK2/STAT3 and JAK2/p38/NF-κB Pathways.

Angelicae pubescentis radix (APR) has been traditionally used for thousands of years in China to treat rheumatoid arthritis (RA), an autoimmune disorder. As the main active coumarin of APR, columbianadin (CBN) exhibits a significant anti-inflammatory effect in vitro. However, the anti-inflammatory activity and underlying mechanism of CBN in vivo remain unclear. This work aimed to elucidate the anti-inflammatory activity of CBN in vivo and its related signaling pathways in a D-Gal-induced liver injury mouse model. Analysis of biochemical indices (ALT and AST) and pro-inflammatory cytokines (IL-1ß and IL-6) in serum indicated that CBN significantly ameliorated D-Gal-induced liver injury. CBN treatment also significantly increased the activities of antioxidant enzymes (SOD, CAT, GPx), and decreased the levels of pro-inflammatory cytokines (TNF-α, IL-1ß and IL-6) in liver tissue. Liver histology revealed that CBN treatment reduced hepatic inflammation. Western blot analysis indicated that CBN down-regulates the expression of phosphorylated JAK2, STAT3, MAPK, and NF-κB in the related signaling pathways. These findings support the traditional use of APR as a remedy for the immune system, and indicate that the JAK2/STAT3 and JAK2/p38/NF-κB signaling pathways may be important mechanisms for the anti-inflammatory activity of CBN in vivo.

DR30318, a novel tri-specific T cell engager for Claudin 18.2 positive cancers immunotherapy.

BACKGROUND: Claudin 18.2 (CLDN18.2) is a highly anticipated target for solid tumor therapy, especially in advanced gastric carcinoma and pancreatic carcinoma. The T cell engager targeting CLDN18.2 represents a compelling strategy for enhancing anti-cancer efficacy. METHODS: Based on the in-house screened anti-CLDN18.2 VHH, we have developed a novel tri-specific T cell engager targeting CLDN18.2 for gastric and pancreatic cancer immunotherapy. This tri-specific antibody was designed with binding to CLDN18.2, human serum albumin (HSA) and CD3 on T cells. RESULTS: The DR30318 demonstrated binding affinity to CLDN18.2, HSA and CD3, and exhibited T cell-dependent cellular cytotoxicity (TDCC) activity in vitro. Pharmacokinetic analysis revealed a half-life of 22.2-28.6 h in rodents and 41.8 h in cynomolgus monkeys, respectively. The administration of DR30318 resulted in a slight increase in the levels of IL-6 and C-reactive protein (CRP) in cynomolgus monkeys. Furthermore, after incubation with human PBMCs and CLDN18.2 expressing cells, DR30318 induced TDCC activity and the production of interleukin-6 (IL-6) and interferon-gamma (IFN-γ). Notably, DR30318 demonstrated significant tumor suppression effects on gastric cancer xenograft models NUGC4/hCLDN18.2 and pancreatic cancer xenograft model BxPC3/hCLDN18.2 without affecting the body weight of mice.

ORF48 is required for optimal lytic replication of Kaposi's Sarcoma-Associated Herpesvirus.

Kaposi's sarcoma-associated herpesvirus (KSHV) establishes persistent infection in the host by encoding a vast network of proteins that aid immune evasion. One of these targeted innate immunity pathways is the cGAS-STING pathway, which inhibits the reactivation of KSHV from latency. Previously, we identified multiple cGAS/STING inhibitors encoded by KSHV, suggesting that the counteractions of this pathway by viral proteins are critical for maintaining a successful KSHV life cycle. However, the detailed mechanisms of how these viral proteins block innate immunity and facilitate KSHV lytic replication remain largely unknown. In this study, we report that ORF48, a previously identified negative regulator of the cGAS/STING pathway, is required for optimal KSHV lytic replication. We used both siRNA and deletion-based systems to evaluate the importance of intact ORF48 in the KSHV lytic cycle. In both systems, loss of ORF48 resulted in defects in lytic gene transcription, lytic protein expression, viral genome replication and infectious virion production. ORF48 genome deletion caused more robust and global repression of the KSHV transcriptome, possibly due to the disruption of RTA promoter activity. Mechanistically, overexpressed ORF48 was found to interact with endogenous STING in HEK293 cells. Compared with the control cell line, HUVEC cells stably expressing ORF48 exhibited repressed STING-dependent innate immune signaling upon ISD or diABZI treatment. However, the loss of ORF48 in our iSLK-based lytic system failed to induce IFNß production, suggesting a redundant role of ORF48 on STING signaling during the KSHV lytic phase. Thus, ORF48 is required for optimal KSHV lytic replication through additional mechanisms that need to be further explored.

CD97 inhibits osteoclast differentiation via Rap1a/ERK pathway under compression.

Acceleration of tooth movement during orthodontic treatment is challenging, with osteoclast-mediated bone resorption on the compressive side being the rate-limiting step. Recent studies have demonstrated that mechanoreceptors on the surface of monocytes/macrophages, especially adhesion G protein-coupled receptors (aGPCRs), play important roles in force sensing. However, its role in the regulation of osteoclast differentiation remains unclear. Herein, through single-cell analysis, we revealed that CD97, a novel mechanosensitive aGPCR, was expressed in macrophages. Compression upregulated CD97 expression and inhibited osteoclast differentiation; while knockdown of CD97 partially rescued osteoclast differentiation. It suggests that CD97 may be an important mechanosensitive receptor during osteoclast differentiation. RNA sequencing analysis showed that the Rap1a/ERK signalling pathway mediates the effects of CD97 on osteoclast differentiation under compression. Consistently, we clarified that administration of the Rap1a inhibitor GGTI298 increased osteoclast activity, thereby accelerating tooth movement. In conclusion, our results indicate that CD97 suppresses osteoclast differentiation through the Rap1a/ERK signalling pathway under orthodontic compressive force.

A radiomics-based brain network in T1 images: construction, attributes, and applications.

T1 image is a widely collected imaging sequence in various neuroimaging datasets, but it is rarely used to construct an individual-level brain network. In this study, a novel individualized radiomics-based structural similarity network was proposed from T1 images. In detail, it used voxel-based morphometry to obtain the preprocessed gray matter images, and radiomic features were then extracted on each region of interest in Brainnetome atlas, and an individualized radiomics-based structural similarity network was finally built using the correlational values of radiomic features between any pair of regions of interest. After that, the network characteristics of individualized radiomics-based structural similarity network were assessed, including graph theory attributes, test-retest reliability, and individual identification ability (fingerprinting). At last, two representative applications for individualized radiomics-based structural similarity network, namely mild cognitive impairment subtype discrimination and fluid intelligence prediction, were exemplified and compared with some other networks on large open-source datasets. The results revealed that the individualized radiomics-based structural similarity network displays remarkable network characteristics and exhibits advantageous performances in mild cognitive impairment subtype discrimination and fluid intelligence prediction. In summary, the individualized radiomics-based structural similarity network provides a distinctive, reliable, and informative individualized structural brain network, which can be combined with other networks such as resting-state functional connectivity for various phenotypic and clinical applications.

A planar tracking strategy based on multiple-interpretable improved PPO algorithm with few-shot technique.

Facing to a planar tracking problem, a multiple-interpretable improved Proximal Policy Optimization (PPO) algorithm with few-shot technique is proposed, namely F-GBQ-PPO. Compared with the normal PPO, the main improvements of F-GBQ-PPO are to increase the interpretability, and reduce the consumption for real interaction samples. Considering to increase incomprehensibility of a tracking policy, three levels of interpretabilities has been studied, including the perceptual, logical and mathematical interpretabilities. Detailly speaking, it is realized through introducing a guided policy based on Apollonius circle, a hybrid exploration policy based on biological motions, and the update of external parameters based on quantum genetic algorithm. Besides, to deal with the potential lack of real interaction samples in real applications, a few-shot technique is contained in the algorithm, which mainly generate fake samples through a multi-dimension Gaussian process. By mixing fake samples with real ones in a certain proportion, the demand for real samples can be reduced.

Structural analysis of global mineral governance system from the perspective of country.

The uneven spatial distribution of mineral resources necessitates the construction of mature global mineral governance system to ensure rational allocation of mineral resources. To this end, it is essential to analyze the structure of the global mineral governance system to provide a theoretical basis for the construction. The governance actor is the crucial element in driving the governance process, and country serves as the most central actor. Therefore, clarifying the roles and statuses of different countries in the governance system will be helpful to analyze the structure of the governance system. In the context of advancing globalization, a complex cooperative relationship has been presented between countries based on international organizations. Thus, we establish a national cooperation network based on the principle of the co-existence of countries in international organizations, to quantify these relationships between countries and identify the role and status of different countries, as well as the country communities in the cooperation network, by combining the characteristics of the countries in the network with the actual performance in the organizations. The research findings are as follow: (1) The UK, Germany, France, Sweden, and Canada play pivotal roles in promoting international cooperation as well as leading governance in the governance system. (2) Emerging economies are more actively engaged in these organizations and can promote international cooperation, but lack the capacity to assume leadership roles in governance. (3) The U.S. and China have a stronger ability to lead than to cooperate in the governance system. (4) Most African and South American countries, as well as some European nations, are marginalized in the governance system. (5) Countries with the same needs and similar economic and political conditions belong to the same community: The European countries and the U.S., consumer with a high level of economic and political development but low mineral resource endowment are in the first community. Canada, Australia, and certain African and South American countries, producers with high mineral resource endowments are in the second community. Most African and South American countries with lower levels of economic and political development are in the third group.