Knowledge Representing: Efficient, Sparse Representation of Prior Knowledge for Knowledge Distillation

Despite the recent works on knowledge distillation (KD) have achieved a further improvement through elaborately modeling the decision boundary as the posterior knowledge, their performance is still dependent on the hypothesis that the target network has a powerful capacity (representation ability). In this paper, we propose a knowledge representing (KR) framework mainly focusing on modeling the parameters distribution as prior knowledge. Firstly, we suggest a knowledge aggregation scheme in order to answer how to represent the prior knowledge from teacher network. Through aggregating the parameters distribution from teacher network into more abstract level, the scheme is able to alleviate the phenomenon of residual accumulation in the deeper layers. Secondly, as the critical issue of what the most important prior knowledge is for better distilling, we design a sparse recoding penalty for constraining the student network to learn with the penalized gradients. With the proposed penalty, the student network can effectively avoid the over-regularization during knowledge distilling and converge faster. The quantitative experiments exhibit that the proposed framework achieves the state-ofthe-arts performance, even though the target network does not have the expected capacity. Moreover, the framework is flexible enough for combining with other KD methods based on the posterior knowledge

Preparation of Polyfunctional Biaryl Derivatives by Cyclolanthanation of 2‐Bromobiaryls and Heterocyclic Analogues Using nBu2LaCl⋅4 LiCl

Various aryl‐ and heteroaryl‐substituted 2‐bromobiaryls are converted to cyclometalated lanthanum intermediates by reaction with nBu2LaCl⋅4 LiCl. These resulting lanthanum heterocycles are key intermediates for the facile preparation of functionalized 2,2′‐diiodobiaryls, silafluorenes, fluoren‐9‐ones, phenanthrenes, and their related heterocyclic analogues. X‐ray absorption fine structure (XAFS) spectroscopy was used to rationalize the proposed structures of the involved organolanthanum species

Bio-Inspired Eco-Friendly Superhydrophilic/Underwater Superoleophobic Cotton for Oil-Water Separation and Removal of Heavy Metals

Effective integrated methods for oil-water separation and water remediation have signifi-cance in both energy and environment fields. Materials with both superlyophobic and superlyophilic properties toward water and oil have aroused great attention due to their energy-saving and high-efficient advantages in oil-water separation. However, in order to fulfill the superlyophobicity, low surface tension fluorinated components are always being introduced. These constituents are environmentally harmful, which may lead to additional contamination during the separating process. Moreover, the heavy metal ions, which are water-soluble and highly toxic, are always contained in the oil-water mixtures created during industrial production. Therefore, material that is integrated by both capacities of oil-water separation and removal of heavy metal contamination would be of significance in both industrial applications and environmental sustainability. Herein, inspired by the composition and wettability of the shrimp shell, an eco-friendly chitosan-coated (CTS) cotton was developed. The treated cotton exhibits the superhydrophilic/underwater superoleophobic property and is capable of separating both immiscible oil-water mixtures and stabilized oil-in-water emulsions. More significantly, various harmful water-soluble heavy metal ions can also be effectively removed during the separation of emulsions. The developed CTS coated cotton demonstrates an attractive perspective toward oil-water separation and wastewater treatment in various applications

DataSheet1_Development and validation of a prognostic prediction model for iron metabolism-related genes in patients with pancreatic adenocarcinoma.ZIP

Background: Pancreatic adenocarcinoma (PAAD) is one of the most aggressive tumors of the digestive tract, with low surgical resection rate and insensitivity to radiotherapy and chemotherapy. Existing evidence suggests that regulation of ferroptosis can induce PAAD cell death, inhibit tumor growth, and may synergistically improve the sensitivity of other antitumor drugs. However, there is little of systematic research on iron metabolism-related genes in PAAD. In this study, a risk-score system of PAAD iron metabolism-related genes was designed and tested, and verified to be robust.Materials and Methods: The TCGA database was used to download 177 PAAD patients’ message RNA (mRNA) expression profiles and clinical characteristics. By identifying dysregulated iron metabolism-related genes between PAAD related tissues and adjacent normal tissues, univariate Cox proportional hazards regression and LASSO regression algorithm were used to establish prognostic risk-score system and construct nomogram to estimate the 1-, 2-, 3-year survival in PAAD patients. Finally, selected genes were validated by quantitative PCR (q-PCR).Results: A 9-gene related to iron metabolism risk-score system of PAAD was constructed and validated. The clinicopathological characteristics of age, histologic grade, pathologic stage, T stage, residual tumor, and primary therapy outcome were all worse in patients with a higher risk-score. Further, immunohistochemistry results of SLC2A1, MBOAT2, XDH, CTSE, MOCOS, and ATP6V0A4 confirmed that patients with higher expression are more malignant. Then, a nomogram with 9-gene risk score system as a separate clinical factor was utilized to foretell the 1-, 2-, 3-year overall survival rate of PAAD patients. Results of q-PCR showed that 8 of the 9 genes screened were significantly up-regulated in at least one PAAD cell line, and one gene was significantly down-regulated in three PAAD cell lines.Conclusion: To conclude, we generated a nine-gene system linked to iron metabolism as an independent indicator for predicting PAAD prognosis, therefore presenting a possible prognostic biomarker and potential treatment targets for PAAD.</p