Patronizing and condescending language (PCL) is a form of speech directed at vulnerable groups. As an essential branch of toxic language, this type of language exacerbates conflicts and confrontations among Internet c...
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Despite significant research on online harm, polarization, public deliberation, and justice, CSCW still lacks a comprehensive understanding of the experiences of religious minorities, particularly in relation to fear,...
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The concept of solar cell is changing the world in obtaining a clean energy that is an environment user friendly source of energy. Solar arrays process and convert the irradiance which is representing the quantity of ...
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Skin Cancer, particularly melanoma, poses a significant threat to human health with low chances of recovery and survival. Early detection plays a crucial role in improving survival rates, with potential rates reaching...
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Zn(CF_(3)SO_(3))_(2)as an electrolyte has been widely used to improve the electrochemical performance for ZIBs due to that the bulky CF_(3)SO_(3)-can reduce the solvation effect of Zn^(2+)and promote the ionic ***,we ...
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Zn(CF_(3)SO_(3))_(2)as an electrolyte has been widely used to improve the electrochemical performance for ZIBs due to that the bulky CF_(3)SO_(3)-can reduce the solvation effect of Zn^(2+)and promote the ionic ***,we found that Zn(CF_(3)SO_(3))_(2)electrolyte can induce different electrochemical mechanisms from ZnSO_(4)*** to the ZnSO^(4)electrolyte,the HNaV_(6)O_(16)·4H2_(O)electrode with Zn(CF_(3)SO_(3))_(2)electrolyte exhibits a high capacity of 444 mAh·g^(-1)at 500 mA·g^(-1)with a capacity retention of 92.3%after 80 ***,at a high rate of 5 Ag-1,the HNaV_(6)O_(16)·4H_(2)O electrode delivers an initial discharge capacity of 328 mAh·g^(-1)with a capacity retention of 93.7%after 1000 *** from the mechanism with ZnSO4 electrolyte,the excellent cycle stability of HNaV_(6)O_(16)·4H_(2)Oelectrode can be attributed to the in-situ phase transformation to ZnxV_(2)O_(5)·nH_(2)O based on the co-intercalation of Zn^(2+)/H^(+).
Adversarial attacks on neural networks are unplanned and skillfully produced inputs that are intended to influence the network’s output or predictions in a negative way. Adversarial attacks represent a serious threat...
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Bananas are a major food crop that feeds billions of people and provides an income to countless others. Nevertheless, they are prone to a range of diseases, which can lead to substantial loss in yield and quality as w...
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This article describes a new way to study how to classify the severity of Cucurbit leaf diseases using a federated learning framework and Convolutional Neural Networks (CNN). Clients ct-1 through ct-4 represent four d...
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The precise prediction of molecular properties is essential for advancements in drug development,particularly in virtual screening and compound *** recent introduction of numerous deep learningbased methods has shown ...
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The precise prediction of molecular properties is essential for advancements in drug development,particularly in virtual screening and compound *** recent introduction of numerous deep learningbased methods has shown remarkable potential in enhancing Molecular Property Prediction(MPP),especially improving accuracy and insights into molecular ***,two critical questions arise:does the integration of domain knowledge augment the accuracy of molecular property prediction and does employing multi-modal data fusion yield more precise results than unique data source methods?To explore these matters,we comprehensively review and quantitatively analyze recent deep learning methods based on various *** discover that integrating molecular information significantly improves Molecular Property Prediction(MPP)for both regression and classification ***,regression improvements,measured by reductions in Root Mean Square Error(RMSE),are up to 4.0%,while classification enhancements,measured by the area under the receiver operating characteristic curve(ROC-AUC),are up to 1.7%.Additionally,we discover that,as measured by ROC-AUC,augmenting 2D graphs with 3D information improves performance for classification tasks by up to 13.2%and enriching 2D graphs with 1D SMILES boosts multi-modal learning performance for regression tasks by up to 9.1%.The two consolidated insights offer crucial guidance for future advancements in drug discovery.
Reliable and accurate short-term forecasting of residential load plays an important role in DSM. However, the high uncertainty inherent in single-user loads makes them difficult to forecast accurately. Various traditi...
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