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961.
962.
The estimation of average treatment effect (ATE) as a causal parameter is carried out in two steps, where in the first step, the treatment and outcome are modeled to incorporate the potential confounders, and in the second step, the predictions are inserted into the ATE estimators such as the augmented inverse probability weighting (AIPW) estimator. Due to the concerns regarding the non-linear or unknown relationships between confounders and the treatment and outcome, there has been interest in applying non-parametric methods such as machine learning (ML) algorithms instead. Some of the literature proposes to use two separate neural networks (NNs) where there is no regularization on the network’s parameters except the stochastic gradient descent (SGD) in the NN’s optimization. Our simulations indicate that the AIPW estimator suffers extensively if no regularization is utilized. We propose the normalization of AIPW (referred to as nAIPW) which can be helpful in some scenarios. nAIPW, provably, has the same properties as AIPW, that is, the double-robustness and orthogonality properties. Further, if the first-step algorithms converge fast enough, under regulatory conditions, nAIPW will be asymptotically normal. We also compare the performance of AIPW and nAIPW in terms of the bias and variance when small to moderate regularization is imposed on the NNs. 相似文献
963.
The calculation of the Augmented Inverse Probability Weighting (AIPW) estimator of the Average Treatment Effect (ATE) is carried out in two steps, where in the first step, the treatment and outcome are modeled, and in the second step, the predictions are inserted into the AIPW estimator. The model misspecification in the first step has led researchers to utilize Machine Learning algorithms instead of parametric algorithms. However, the existence of strong confounders and/or Instrumental Variables (IVs) can lead the complex ML algorithms to provide perfect predictions for the treatment model which can violate the positivity assumption and elevate the variance of AIPW estimators. Thus the complexity of ML algorithms must be controlled to avoid perfect predictions for the treatment model while still learning the relationship between the confounders and the treatment and outcome. We use two NN architectures with an -regularization on specific NN parameters and investigate how their certain hyperparameters should be tuned in the presence of confounders and IVs to achieve a low bias-variance tradeoff for ATE estimators such as AIPW estimator. Through simulation results, we will provide recommendations as to how NNs can be employed for ATE estimation. 相似文献
964.
965.
In this paper,we study an extragradient algorithm for approximating solutions of quasi-equilibrium problems in Banach spaces.We prove strong convergence of the sequence generated by the extragradient method to a solution of the quasi-equilibrium problem. 相似文献
966.
In this research, a novel organic–inorganic hybrid salt, namely, N1,N1,N2,N2‐tetramethyl‐N1,N2‐bis(sulfo)ethane‐1,2‐diaminium tetrachloroferrate ([TMBSED][FeCl4]2) was prepared and characterized by Fourier‐transform infrared spectroscopy (FT‐IR), energy‐dispersive X‐ray spectroscopy (EDX), elemental mapping, field emission scanning electron microscopy (FE‐SEM), X‐ray diffraction (XRD), thermal gravimetric (TG), differential thermal gravimetric (DTG), and vibrating‐sample magnetometry (VSM) analyses. Catalytic activity of the hybrid salt was tested for the synthesis of N,N′‐alkylidene bisamides through the reaction of benzamide (2 eq.) and aromatic aldehydes (1 eq.) under solvent‐free conditions in which the products were obtained in high yields and short reaction times. The catalyst was superior to many of the reported catalysts in terms of two or more of these factors: the reaction medium and temperature, yield, time, and turnover frequency (TOF). [TMBSED][FeCl4]2 is a Brønsted–Lewis acidic catalyst; there are two SO3H groups (as Brønsted acidic sites) and two tetrachloroferrate anions (as Lewis acidic sites) in its structure. Highly effectiveness of the catalyst for the synthesis of N,N′‐alkylidene bisamides can be attributed to synergy of the Brønsted and Lewis acids and also possessing two sites of each acid. 相似文献
967.
Ulrich Markel Pia Lanvers Dr. Daniel F. Sauer Malte Wittwer Dr. Gaurao V. Dhoke Dr. Mehdi D. Davari Dr. Johannes Schiffels Prof. Dr. Ulrich Schwaneberg 《Chemistry (Weinheim an der Bergstrasse, Germany)》2021,27(3):954-958
Enzymatic oxidative decarboxylation is an up-and-coming reaction yet lacking efficient screening methods for the directed evolution of decarboxylases. Here, we describe a simple photoclick assay for the detection of decarboxylation products and its application in a proof-of-principle directed evolution study on the decarboxylase OleT. The assay was compatible with two frequently used OleT operation modes (directly using hydrogen peroxide as the enzyme's co-substrate or using a reductase partner) and the screening of saturation mutagenesis libraries identified two enzyme variants shifting the enzyme's substrate preference from long chain fatty acids toward styrene derivatives. Overall, this photoclick assay holds promise to speed-up the directed evolution of OleT and other decarboxylases. 相似文献
968.
Journal of Solid State Electrochemistry - In this work, based on the Lambert W-function and a single-diode five-parameter model, the electrical characteristics of the macro-porous silicon-based... 相似文献
969.
Mohabat Taghizadeh Mahmoud Ebrahimi Ebrahim Fooladi Mehdi Yoosefian 《Journal of separation science》2022,45(8):1434-1444
A sensitive and straightforward liquid–liquid–liquid microextraction method was developed to preconcentrate and cleanup antidepressants, including mirtazapine, venlafaxine, escitalopram, fluoxetine, and fluvoxamine, from biological samples before analyzing with high-performance liquid chromatography. The essential novelty of this study is using magnetic ionic liquids as the extraction phase in the lumen of hollow fiber and preparing a liquid magnetic stir bar. In this method, polypropylene hollow fiber was utilized as the permeable membrane for the analyte extraction. Six magnetic ionic liquids consisting of the transition metal and rare earth compounds were synthesized and then hollow fiber lumen was injected as acceptor phase to extract the antidepressants. Besides, 3-pentanol as a water-immiscible solvent was impregnated in the hollow fiber wall pores. The effective factors in the method were optimized with the central composition design. The resultant calibration curves were linear over the concentration range of 0.8–400.0 ng mL−1 (R2 ≥ 0.996). The method displayed the proper detection limit (0.11–0.24 ng mL−1), the reasonable limit of quantification (≤0.79 ng mL−1), wide linear ranges, high preconcentration factors (≥294.3), and suitable relative standard deviation (2.31–5.47%) for measuring antidepressant medications. Analysis of human milk and urine samples showed acceptable recoveries of 96.5–103.8% with excellent relative standard deviations lower than 5.95%. 相似文献
970.