Weakly Supervised Video Salient Object Detection via Point Supervision

Video salient object detection models trained on pixel-wise dense annotation have achieved excellent performance, yet obtaining pixel-by-pixel annotated datasets is laborious. Several works attempt to use scribble annotations to mitigate this problem, but point supervision as a more labor-saving annotation method (even the most labor-saving method among manual annotation methods for dense prediction), has not been explored. In this paper, we propose a strong baseline model based on point supervision. To infer saliency maps with temporal information, we mine inter-frame complementary information from short-term and long-term perspectives, respectively. Specifically, we propose a hybrid token attention module, which mixes optical flow and image information from orthogonal directions, adaptively highlighting critical optical flow information (channel dimension) and critical token information (spatial dimension). To exploit long-term cues, we develop the Long-term Cross-Frame Attention module (LCFA), which assists the current frame in inferring salient objects based on multi-frame tokens. Furthermore, we label two point-supervised datasets, P-DAVIS and P-DAVSOD, by relabeling the DAVIS and the DAVSOD dataset. Experiments on the six benchmark datasets illustrate our method outperforms the previous state-of-the-art weakly supervised methods and even is comparable with some fully supervised approaches. Source code and datasets are available.Comment: accepted by ACM MM 202

Bulk Density Adjustment of Resin-Based Equivalent Material for Geomechanical Model Test

An equivalent material is of significance to the simulation of prototype rock in geomechanical model test. Researchers attempt to ensure that the bulk density of equivalent material is equal to that of prototype rock. In this work, barite sand was used to increase the bulk density of a resin-based equivalent material. The variation law of the bulk density was revealed in the simulation of a prototype rock of a different bulk density. Over 300 specimens were made for uniaxial compression test. Test results indicated that the substitution of quartz sand by barite sand had no apparent influence on the uniaxial compressive strength and elastic modulus of the specimens but can increase the bulk density, according to the proportional coarse aggregate content. An ideal linearity was found in the relationship between the barite sand substitution ratio and the bulk density. The relationship between the bulk density and the usage of coarse aggregate and barite sand was also presented. The test results provided an insight into the bulk density adjustment of resin-based equivalent materials

First-Principles Study of Bimetallic Pairs Embedded on Graphene Co-Doped with N and O for N₂ Electroreduction

The electrocatalytic nitrogen reduction reaction (NRR) is considered a viable alternative to the Haber–Bosch process for ammonia synthesis, and the design of highly active and selective catalysts is crucial for the industrialization of the NRR. Dual-atom catalysts (DACs) with dual active sites offer flexible active sites and synergistic effects between atoms, providing more possibilities for the tuning of catalytic performance. In this study, we designed 48 graphene-based DACs with N4O2 coordination (MM′@N4O2-G) using density functional theory. Through a series of screening strategies, we explored the reaction mechanisms of the NRR for eight catalysts in depth and revealed the “acceptance–donation” mechanism between the active sites and the N2 molecules through electronic structure analysis. The study found that the limiting potential of the catalysts exhibited a volcano-shaped relationship with the d-band center of the active sites, indicating that the synergistic effect between the bimetallic components can regulate the d-band center position of the active metal M, thereby controlling the reaction activity. Furthermore, we investigated the selectivity of the eight DACs and identified five potential NRR catalysts. Among them, MoCo@N4O2-G showed the best NRR performance, with a limiting potential of −0.20 V. This study provides theoretical insights for the design and development of efficient NRR electrocatalysts

Highly Sensitive Paper-Based Force Sensors with Natural Micro-Nanostructure Sensitive Element

Flexible paper-based force sensors have garnered significant attention for their important potential applications in healthcare wearables, portable electronics, etc. However, most studies have only used paper as the flexible substrate for sensors, not fully exploiting the potential of paper’s micro-nanostructure for sensing. This article proposes a novel approach where paper serves both as the sensitive element and the flexible substrate of force sensors. Under external mechanical forces, the micro-nanostructure of the conductive-treated paper will change, leading to significant changes in the related electrical output and thus enabling sensing. To demonstrate the feasibility and universality of this new method, the article takes paper-based capacitive pressure sensors and paper-based resistive strain sensors as examples, detailing their fabrication processes, constructing sensing principle models based on the micro-nanostructure of paper materials, and testing their main sensing performance. For the capacitive paper-based pressure sensor, it achieves a high sensitivity of 1.623 kPa−1, a fast response time of 240 ms, and a minimum pressure resolution of 4.1 Pa. As for the resistive paper-based strain sensor, it achieves a high sensitivity of 72 and a fast response time of 300 ms. The proposed new method offers advantages such as high sensitivity, simplicity in the fabrication process, environmental friendliness, and cost-effectiveness, providing new insights into the research of flexible force sensors

Analysis of Optimal Loading Angle in Dynamic Flattened Brazilian Disc Splitting Test for Concrete

The mechanism of crack expansion in conventional Brazilian discs is clearly obtained with the help of numerical simulations, and the direction of crack expansion is related to the loading speed. Then the relationship between the stress field and the platform angle was given quantitatively based on the theoretical analysis. To obtain the accurate tensile strength of self-compacting concrete under the premise of numerical simulation and theoretical analysis, flattened Brazilian disc (BD) splitting tests with six loading angles were carried out by using the split Hopkinson pressure bar (SHPB) loading system. The crack initiation mode and fracture propagation mode of specimens under different loading angles and loading rates were analyzed through digital image correlation (DIC) and strain gauges. When the loading angle lies between 28° and 30°, the specimens easily meet the requirement of central cracking under high loading rates. The experimental results were well explained with theoretical analysis from a view of dimensionless Griffith’s equivalent stress. The dynamic tensile strength measured from the non-central crack mode in flattened BD splitting tests underestimates the inherent dynamic tensile strength

Androgen Metabolism and Response in Prostate Cancer Anti-Androgen Therapy Resistance

All aspects of prostate cancer evolution are closely related to androgen levels and the status of the androgen receptor (AR). Almost all treatments target androgen metabolism pathways and AR, from castration-sensitive prostate cancer (CSPC) to castration-resistant prostate cancer (CRPC). Alterations in androgen metabolism and its response are one of the main reasons for prostate cancer drug resistance. In this review, we will introduce androgen metabolism, including how the androgen was synthesized, consumed, and responded to in healthy people and prostate cancer patients, and discuss how these alterations in androgen metabolism contribute to the resistance to anti-androgen therapy

Patients with high nuclear grade pT1-ccRCC are more suitable for radical nephrectomy than partial nephrectomy: a multicenter retrospective study using propensity score

Abstract Background Partial nephrectomy (PN) is usually recommended for T1 stage clear cell renal cell carcinoma (ccRCC) regardless of the nuclear grades. However, the question remains unresolved as to whether PN is non-inferior to RN in patients with T1-ccRCC at higher risk of recurrence. In fact, we found that patients with high nuclear grades treated with PN had poorer prognosis compared with those treated with radical nephrectomy (RN). Therefore, this study was designed to evaluate the associations of PN and RN in the four nuclear grade subsets with oncologic outcomes. Methods A retrospective study was conducted in three Chinese urological centers that included 1,714 patients who underwent PN or RN for sporadic, unilateral, pT1, N0, and M0 ccRCC without positive surgical margins and neoadjuvant therapy between 2010 and 2019. Associations of nephrectomy type with local ipsilateral recurrence, distant metastases, and all-cause mortality (ACM) were evaluated using the Kaplan–Meier method and multivariable Cox proportional hazards regression models after overlap weighting (OW). Results A total of 1675 patients entered the OW cohort. After OW, in comparison to PN, RN associated with a reduced risk of local ipsilateral recurrence in the G2 subset (HR = 0.148, 95% CI 0.046–0.474; p < 0.05), G3 subset (HR = 0.097, 95% CI 0.021–0.455; p < 0.05), and G4 subset (HR = 0.091, 95% CI 0.011–0.736; p < 0.05), and resulting in increased five-year local recurrence-free survival rates of 7.0%, 17.9%, and 36.2%, respectively. An association between RN and a reduced risk of distant metastases in the G4 subset (HR = 0.071, 95% CI 0.016–0.325; p < 0.05), with the five-year distant metastases-free survival rate increasing by 33.1% was also observed. No significant difference in ACM between PN and RN was identified. Conclusions Our findings substantiate that opting for RN, as opposed to PN, is more advantageous for local recurrence-free survival and distant metastases-free survival in patients with high nuclear grade (especially G4) pT1-ccRCC. We recommend placing a heightened emphasis on enhancing preoperative nuclear grade assessment, as it can significantly influence the choice of surgical plan. Trial registration This study was registered at Chinese Clinical Trial Registry (ID: ChiCTR2200063333)

Selective Hydrogenation of Aromatic Ketone over Pt@Y Zeolite through Restricted Adsorption Conformation of Reactants by Zeolitic Micropores

With thermodynamically favorable prevailing flat-lying adsorption of aromatic ketone molecules on Pt/Y catalyst via pi-electron interaction, the 100 % selective hydrogenation toward aromatic alcohols is hardly achieved because of competitive hydrogenation on benzene rings. Here we developed a general method to prepare encapsulated Pt nanoparticles into Y Zeolite (Pt@Y), which provided a novel method to retard hydrogenation of benzene rings via thermodynamically unfavorable end-on adsorption conformation for almost 100 % selectivity from aromatic ketones to aromatic alcohols even at conversion close to 100 %

Image9_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.png

Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p

Image2_Identification of molecular subtypes and diagnostic model in clear cell renal cell carcinoma based on collagen-related genes may predict the response of immunotherapy.tif

Background: Collagen represents a prominent constituent of the tumor’s extracellular matrix (ECM). Nonetheless, its correlation with the molecular subtype attributes of clear cell renal cell carcinoma (ccRCC) remains elusive. Our objective is to delineate collagen-associated molecular subtypes and further construct diagnostic model, offering insights conducive to the precise selection of ccRCC patients for immunotherapeutic interventions.Methods: We performed unsupervised non-negative matrix factorization (NMF) analysis on TCGA-KIRC samples, utilizing a set of 33 collagen-related differentially expressed genes (33CRDs) for clustering. Our analysis encompassed evaluations of subtype-associated differences in pathways, immune profiles, and somatic mutations. Through weighted gene co-expression network analysis (WGCNA) and four machine learning algorithms, two core genes were found and a diagnostic model was constructed. This was subsequently validated in a clinical immunotherapy cohort. Single cell sequencing analysis and experiments demonstrated the role of core genes in ccRCC. Finally, we also analyzed the roles of MMP9 and SCGN in pan-cancer.Results: We described two novel collagen related molecular subtypes in ccRCC, designated subtype 1 and subtype 2. Compared with subtype 1, subtype 2 showed more infiltration of immune components, but had a higher TIDE (tumor immunedysfunctionandexclusion) score and increased levels of immune checkpoint molecules. Furthermore, reduced prognosis for subtype 2 was a consistent finding in both high and low mutation load subgroups. MMP9 and SCGN were identified as key genes for distinguishing subtype 1 and subtype 2. The diagnostic model based on them could better distinguish the subtype of patients, and the differentiated patients had different progression free survival (PFS) in the clinical immunotherapy cohort. MMP9 was predominantly expressed in macrophages and has been extensively documented in the literature. Meanwhile, SCGN, which was overexpressed in tumor cells, underwent experimental validation, emphasizing its role in ccRCC. In various cancers, MMP9 and SCGN were associated with immune-related molecules and immune cells.Conclusion: Our study identifies two collagen-related molecular subtypes of ccRCC and constructs a diagnostic model to help select appropriate patients for immunotherapy.</p