Contrastive Counterfactual Learning for Causality-aware Interpretable Recommender Systems

There has been a recent surge in the study of generating recommendations within the framework of causal inference, with the recommendation being treated as a treatment. This approach enhances our understanding of how recommendations influence user behaviour and allows for identification of the factors that contribute to this impact. Many researchers in the field of causal inference for recommender systems have focused on using propensity scores, which can reduce bias but may also introduce additional variance. Other studies have proposed the use of unbiased data from randomized controlled trials, though this approach requires certain assumptions that may be difficult to satisfy in practice. In this paper, we first explore the causality-aware interpretation of recommendations and show that the underlying exposure mechanism can bias the maximum likelihood estimation (MLE) of observational feedback. Given that confounders may be inaccessible for measurement, we propose using contrastive SSL to reduce exposure bias, specifically through the use of inverse propensity scores and the expansion of the positive sample set. Based on theoretical findings, we introduce a new contrastive counterfactual learning method (CCL) that integrates three novel positive sampling strategies based on estimated exposure probability or random counterfactual samples. Through extensive experiments on two real-world datasets, we demonstrate that our CCL outperforms the state-of-the-art methods.Comment: conferenc

Effect of zinc acetate concentration on optimization of photocatalytic activity of p-Co3O4/n-ZnO heterostructures

In this work, p-Co3O4/n-ZnO heterostructures were fabricated on Ni substrate by hydrothermal-decomposition method using cobaltous nitrate hexahydrate (Co(NO3)(2)center dot 6H(2)O) and zinc acetate dihydrate (Zn(CH3COO)(2)center dot 2H(2)O) as precursors with zinc acetate concentration varying from 5.0 to 55.0 mM. Structure and morphology of the developed samples were characterized by X-ray diffraction (XRD), Raman spectroscopy, and scanning electron microscopy (SEM). Effect of zinc acetate concentration on the photocatalytic activity of p-Co3O4/n-ZnO heterostructures was investigated by degradation of methyl orange (MO) under the UV light irradiation. The fabricated p-Co3O4/n-ZnO heterostructures exhibited higher photocatalytic activity than pure Co3O4 particles. In order to obtain the maximum photocatalytic activity, zinc acetate concentration was optimized. Specifically, at 35 mM of zinc acetate, the p-Co3O4/n-ZnO showed the highest photocatalytic activity with the degradation efficiency of MO reaching 89.38% after 72 h irradiation. The improvement of photocatalytic performance of p-Co3O4/n-ZnO heterostructures is due to the increased concentration of photo-generated holes on Co3O4 surface and the higher surface-to-volume ratio in the hierarchical structure formed by nano-lamellas

Newly added characters and data matrix for oviraptorids phylogeny

This character description was modified from Longrich et al. (Longrich, N. R., Currie, P. J. & Dong, Z. M. 2010 A new oviraptorid (Dinosauria: Theropoda) from the Upper Cretaceous of Bayan Mandahu, Inner Mongolia. Palaeontology, 53, 945–960). The matrix was expanded by adding four characters and two taxa (Banji long and Ganzhousaurus nankangensis; for a total of 185 characters and 19 taxa)

China state grid

Many of us regard electricity as a basic necessity, while few of us know or even wonder how this seemingly magical current arrives in our houses. Fewer still think about the people behind the scenes, those who work day in and day out to ensure our electric needs are met. The stories in this book are those of unsung heroes, whose personal sacrifices ensured the dawn of a strong and smart Chinese electric network. Their tireless thirst for innovation is shown through their dedication to the cause

Data from: A new oviraptorid (Dinosauria: Theropoda) from the Upper Cretaceous of southern China

This paper describes a new oviraptorid dinosaur taxon, Ganzhousaurus nankangensis gen. et sp. nov., based on a specimen collected from the Upper Cretaceous Nanxiong Formation of Nankang County, Ganzhou City, Jiangxi Province, southern China. This new taxon is distinguishable from other oviraptorids based on the following unique combination of primitive and derived features: relatively shallow dentary; absence of fossa or pneumatopore on lateral surface of dentary; weakly downturned anterior mandibular end; shallow depression immediately surrounding anterior margin of external mandibular fenestra; external mandibular fenestra subdivided by anterior process of surangular; dentary posteroventral process slight-ly twisted and positioned on mandibular ventrolateral surface; shallow longitudinal groove along medial surface of den-tary posteroventral process; angular anterior process wider transversely than deep dorsoventrally; sharp groove along ventrolateral surface of angular anterior process; ventral border of external mandibular fenestra formed mainly by angular; ventral flange along distal half of metatarsal II; and arctometatarsal condition absent. Phylogenetic analysis places Ganzhousaurus nankangensis gen. et sp. nov. in the clade Oviraptoridae, together with Oviraptor, Citipati, Rinchenia and the unnamed Zamyn Khondt oviraptorid

Improvement of Low-Frequency Radiated Emission in Electric Vehicle by Numerical Analysis

In this paper, a methodology for improving vehicle-level radiated electromagnetic interference (EMI) in electric vehicle (EV) is proposed. This methodology predicts vehicle-level radiated EMI by using the multiport network theory, based on analyzing the contribution from each electronic component to find out the main EMI source. To validate its effectiveness, the proposed methodology is applied in an actual EV for low-frequency radiated emissions. Simulation in a commercially available electromagnetics software and measurement in the EV are combined to predict the vehicle-level emissions, and then the electronic component with the greatest EMI that causes failure to meet the EMC standard is identified. After improving this component, the vehicle-level radiated emission is reduced to comply with the EMC standard, proving that the presented numerical method is effective. The proposed methodology can also be used in other EMC issues, regardless of the amount of interference sources and sensitive equipment