Combining conditional and unconditional moment restrictions with missing responses

AbstractMany statistical models, e.g. regression models, can be viewed as conditional moment restrictions when distributional assumptions on the error term are not assumed. For such models, several estimators that achieve the semiparametric efficiency bound have been proposed. However, in many studies, auxiliary information is available as unconditional moment restrictions. Meanwhile, we also consider the presence of missing responses. We propose the combined empirical likelihood (CEL) estimator to incorporate such auxiliary information to improve the estimation efficiency of the conditional moment restriction models. We show that, when assuming responses are strongly ignorable missing at random, the CEL estimator achieves better efficiency than the previous estimators due to utilization of the auxiliary information. Based on the asymptotic property of the CEL estimator, we also develop Wilks’ type tests and corresponding confidence regions for the model parameter and the mean response. Since kernel smoothing is used, the CEL method may have difficulty for problems with high dimensional covariates. In such situations, we propose an instrumental variable-based empirical likelihood (IVEL) method to handle this problem. The merit of the CEL and IVEL are further illustrated through simulation studies

Combining conditional and unconditional moment restrictions with missing responses

Many statistical models, e.g. regression models, can be viewed as conditional moment restrictions when distributional assumptions on the error term are not assumed. For such models, several estimators that achieve the semiparametric efficiency bound have been proposed. However, in many studies, auxiliary information is available as unconditional moment restrictions. Meanwhile, we also consider the presence of missing responses. We propose the combined empirical likelihood (CEL) estimator to incorporate such auxiliary information to improve the estimation efficiency of the conditional moment restriction models. We show that, when assuming responses are strongly ignorable missing at random, the CEL estimator achieves better efficiency than the previous estimators due to utilization of the auxiliary information. Based on the asymptotic property of the CEL estimator, we also develop Wilks' type tests and corresponding confidence regions for the model parameter and the mean response. Since kernel smoothing is used, the CEL method may have difficulty for problems with high dimensional covariates. In such situations, we propose an instrumental variable-based empirical likelihood (IVEL) method to handle this problem. The merit of the CEL and IVEL are further illustrated through simulation studies.Conditional moment restrictions Combined empirical likelihood Missing response Unconditional moment restrictions Wilks' theorem

Plastic wastes-derived N-doped carbon nanotubes for efficient removal of sulfamethoxazole in high salinity wastewater via nonradical peroxymonosulfate activation

Peroxymonosulfate (PMS) catalytic activation is effective to eliminate organic pollutants from water, thus the development of low-cost and efficient catalysts is significant in applications. The resource conversion of plastic wastes (PWs) into carbon nanotubes (CNTs) is a promising candidate for PMS-based advanced oxidation processes (AOPs), and also a sustainable strategy to realize plastic management and reutilization. Herein, cost-effective PWs-derived N-doped CNTs (N-pCNTs) were synthesized, which displayed efficient activity for PMS activation through an electron transfer pathway (ETP) for sulfamethoxazole (SMX) degradation in high salinity water. The pyrrolic N induced the positively charged surface of N-pCNTs, favoring the electrostatic adsorption of PMS and subsequent generation of active PMS* . A galvanic oxidation process was developed to prove the electron-shuttle dominated ETP for SMX oxidation. Combined with theoretical calculations, the efficiency of ETP was determined by the potential difference between HOMO of SMX and LUMO of N-pCNTs. Such oxidation produced low-toxicity intermediates and resulted in selective degradation of specific sulfonamide antibiotics. This work reveals the feasibility of low-cost N-pCNTs catalysts from PWs serving as an appealing candidate for PMS-AOPs in water remediation, providing a new solution to alleviate environmental issues caused by PWs and also advances the understanding of ETP during PMS activation. [Abstract copyright: Copyright © 2023 Elsevier B.V. All rights reserved.

Efficient photocatalytic H2O2 production from oxygen and pure water over graphitic carbon nitride decorated by oxidative red phosphorus

Photocatalytic H2O2 production in pure water is prerequisite for diverse on-site applications, but challengeable to be realized owing to sluggish water oxidation and significant recombination of photogenerated charges. Herein, efficient photocatalytic H2O2 production in pure water was realized on graphitic carbon nitride (GCN) decorated by oxidative red phosphorus (ORP). The composite produces 250 μM of H2O2 within 120 min under visible light irradiation via synchronous water oxidation and oxygen reduction reactions, which is more than 25-fold enhancement of pristine GCN. It is revealed that red phosphorus (RP) can significantly promote charge separation but induce reductive decomposition of H2O2. Successfully, H2O2 decomposition over RP is dramatically suppressed by preventing the interaction between H2O2 and P atoms through oxidizing RP with the formation of P[sbnd]O bonds by an oxidation post-treatment. This strategy opens a new door for the rational design of highly active metal-free photocatalysts toward solar-to-H2O2 conversion in pure water