We present an approach to household thermal regulation and energy saving from an all-season perspective by developing a mechanically flexible and energy-free coating that automatically adapts its ...thermal emittance to different ambient temperatures.
We demonstrate a new MEOM multifunctional platform activated by the structural phase transition of an embedded vanadium dioxide layer. Its diverse stimuli and > 50% optical modulation depth over a ...broad wavelength range promise versatile applications.
A Reprogrammable Photonic Meta-platform Dong, Kaichen; Hong, Sukjoon; Deng, Yang ...
2018 Conference on Lasers and Electro-Optics (CLEO)
Conference Proceeding
We present an all-solid, reprogrammable meta-platform, which can be rapidly (re)programmed into nearly arbitrary photonic devices by writing/erasing patterns on it. The writing is performed with a ...low-power laser, and the erasing utilizes global cooling.
Cet article présente et analyse un type de traités d'agriculture, les yueling ("préceptes mensuels"). Partant des ouvrages les plus anciens, l'auteur considère successivement l'ensemble de la ...littérature existant sur ce thème et en montre les prolongements contemporains.
This article presents and gives an analysis of a special kind of agricultural treatises : yueling ("monthly ordinances"). Beginning with the most ancient texts, the author considers the whole literature still existing on this theme and shows their modern equivalents.
Dong Kaichen. A preliminary discussion of Chinese agricultural treatises in the style of "monthly ordinances" yueling. In: Journal d'agriculture traditionnelle et de botanique appliquée, 28ᵉ année, bulletin n°3-4, Juillet-décembre 1981. pp. 231-251.
Cet article présente et analyse un type de traités d'agriculture, les yueling ("préceptes mensuels"). Partant des ouvrages les plus anciens, l'auteur considère successivement l'ensemble de la ...littérature existant sur ce thème et en montre les prolongements contemporains.
This article presents and gives an analysis of a special kind of agricultural treatises : yueling ("monthly ordinances"). Beginning with the most ancient texts, the author considers the whole literature still existing on this theme and shows their modern equivalents.
Abstract
The fabrication of integrated circuits (ICs) employing two-dimensional (2D) materials is a major goal of semiconductor industry for the next decade, as it may allow the extension of the ...Moore’s law, aids in in-memory computing and enables the fabrication of advanced devices beyond conventional complementary metal-oxide-semiconductor (CMOS) technology. However, most circuital demonstrations so far utilizing 2D materials employ methods such as mechanical exfoliation that are not up-scalable for wafer-level fabrication, and their application could achieve only simple functionalities such as logic gates. Here, we present the fabrication of a crossbar array of memristors using multilayer hexagonal boron nitride (h-BN) as dielectric, that exhibit analog bipolar resistive switching in >96% of devices, which is ideal for the implementation of multi-state memory element in most of the neural networks, edge computing and machine learning applications. Instead of only using this memristive crossbar array to solve a simple logical problem, here we go a step beyond and present the combination of this h-BN crossbar array with CMOS circuitry to implement extreme learning machine (ELM) algorithm. The CMOS circuit is used to design the encoder unit, and a h-BN crossbar array of 2D hexagonal boron nitride (h-BN) based memristors is used to implement the decoder functionality. The proposed hybrid architecture is demonstrated for complex audio, image, and other non-linear classification tasks on real-time datasets.
Malnutrition is persistent in 50%–75% of children with congenital heart disease (CHD) after surgery, and early prediction is crucial for nutritional intervention. The aim of this study was to develop ...and validate machine learning (ML) models to predict the malnutrition status of children with CHD. We used explainable ML methods to provide insight into the model's predictions and outcomes.
This prospective cohort study included consecutive children with CHD admitted to the hospital from December 2017 to May 2020. The cohort data were divided into the training and test data sets based on the follow-up time. The outcome of the study was CHD child malnutrition 1 year after surgery, the primary outcome was an underweight status, and the secondary outcomes were stunted and wasting status. We used five ML algorithms with multiple features to construct prediction models, and the performance of these ML models was measured by an area under the receiver operating characteristic curve (AUC) analysis. We also used the permutation importance and SHapley Additive exPlanations (SHAP) to determine the importance of the selected features and interpret the ML models.
We enrolled 536 children with CHD who underwent complete repair. The proportions of children with an underweight, stunted, or wasting status 1 year after surgery were 18.1% (97/536), 12.1% (65/536), and 17.5% (94/536), respectively. All patients contributed to the generation of 115 useable features, which allowed us to build models to predict malnutrition. Five prediction algorithms were used, and the XGBoost model achieved the greatest AUC in all outcomes. The results obtained from the permutation importance and SHAP analyses showed that the 1-month postoperative WAZ-score, discharge WAZ score and preoperative WAZ score were the top 3 important features in predicting an underweight status in the XGBoost algorithm. Regarding the stunted status, the top 3 important features were the 1-month postoperative HAZ score, discharge HAZ score, and aortic clamping time. Regarding the wasting status, the top 3 important features were the hospital length of stay, formula intake, and discharge WHZ-score. We also used a narrative case report as an example to describe the clinical manifestations and predicted the primary outcomes of two children.
We developed an ML model (XGBoost) that provides accurate early predictions of malnutrition 1-year postoperatively in children with CHD. Because the ML model is explainable, it may better enable clinicians to better understand the reasoning underlying the outcome. Our study could aid in determining individual treatment and nutritional follow-up strategies for children with CHD.
PDF
