Heat capacity and relaxation dynamics of glassy films: A lattice model study.

We study the calorimetric properties and structural relaxation of glassy films using a distinguishable particle lattice model (DPLM). We determine the glass transition temperature versus film thickness from the heat capacity during heating as well as from the local relaxation time. The results based on both approaches are in good agreement with the experimentally observed Keddie-Cory-Jones relation.

EEGGAN-Net: enhancing EEG signal classification through data augmentation.

Background: Emerging brain-computer interface (BCI) technology holds promising potential to enhance the quality of life for individuals with disabilities. Nevertheless, the constrained accuracy of electroencephalography (EEG) signal classification poses numerous hurdles in real-world applications.

Methods: In response to this predicament, we introduce a novel EEG signal classification model termed EEGGAN-Net, leveraging a data augmentation framework.

Relating fragile-to-strong transition to fragile glass via lattice model simulations.

Glass formers are, in general, classified as strong or fragile depending on whether their relaxation rates follow Arrhenius or super-Arrhenius temperature dependence. There are, however, notable exceptions, such as water, which exhibit a fragile-to-strong (FTS) transition and behave as fragile and strong, respectively, at high and low temperatures. In this work, the FTS transition is studied using a distinguishable-particle lattice model previously demonstrated to be capable of simulating both strong and fragile glasses [C.

Correction: Surface mobility gradient and emergent facilitation in glassy films.

Correction for 'Surface mobility gradient and emergent facilitation in glassy films' by Qiang Zhai , , 2024, https://doi.org/10.1039/D4SM00221K.

Surface mobility gradient and emergent facilitation in glassy films.

Confining glassy polymers into films can substantially modify their local and film-averaged properties. We present a lattice model of film geometry with void-mediated facilitation behaviors but free from any elasticity effect. We analyze the spatially varying viscosity to delineate the transport properties of glassy films.

MGL: Mutual Graph Learning for Camouflaged Object Detection.

Camouflaged object detection, which aims to detect/segment the object(s) that blend in with their surrounding, remains challenging for deep models due to the intrinsic similarities between foreground objects and background surroundings. Ideally, an effective model should be capable of finding valuable clues from the given scene and integrating them into a joint learning framework to co-enhance the representation. Inspired by this observation, we propose a novel Mutual Graph Learning (MGL) model by shifting the conventional perspective of mutual learning from regular grids to graph domain.

Rice nitrogen nutrition monitoring classification method based on the convolution neural network model: Direct detection of rice nitrogen nutritional status.

The nitrogen nutrition status affects the main factors of rice yield. In traditional rice nitrogen nutrition monitoring methods, most experts enter the farmland to observe leaf color and growth and apply an appropriate amount of nitrogen fertilizer according to the results. However, this method is labor- and time-consuming.

Taxonomic status of Rana nigromaculata mongolia and the validity of Pelophylax tenggerensis (Anura, Ranidae).

The Black-spotted Pond Frog, Pelophylax nigromaculatus, is widely distributed across mainland China, Korean Peninsula, and Japan. The taxonomic relationships among P. n.

Preparation and Characterisation of Polyurethane Acrylate-Based Titanium Dioxide Pigment for Blue Light-Curable Ink.

Herein, a polyurethane acrylate-based TiO (PU-TiO) was fabricated using a two-step method. First, a polyurethane prepolymer was prepared. Second, PU-TiO was prepared using amino-modified TiO (A-TiO).

Impact Measurement of COVID-19 Lockdown on China's Electricity-Carbon Nexus.

Lockdown measures to prevent the spread of coronavirus disease 2019 (COVID-19) resulted in the plummeting of China's overall electric-power demand and production. To date, power generation remains one of the largest carbon dioxide (CO) emitting sectors of China on account of its high carbon intensity. Within this context, our study seeks to measure the impacts of COVID-19 lockdown on the electricity-power related carbon footprints on both generation and consumption sides.

Life Cycle Impact Assessment of Garbage-Classification Based Municipal Solid Waste Management Systems: A Comparative Case Study in China.

Confronted with a series of problems caused by surging generation of municipal solid waste (MSW), the Chinese central and local governments have promulgated and implemented policies to deal with them, including promotions of the classification of MSW. However, to date, practical knowledge and understanding about benefits for garbage classification from its environmental performance perspective is still limited. The present study is purposed to comprehensively investigate the environmental effects of garbage classification on municipal solid waste management (MSWM) systems based on three proposed garbage classification scenarios in China, via a comparative life cycle impact assessment (LCIA).

Clinical and imaging characteristics of hematologic disease complicated by air leak syndrome: A STROBE-compliment observational study.

There are limited systematic studies on hematologic disease complicated by air leak syndrome (ALS). Physicians in radiology departments and hematology departments have a limited awareness of ALS.The aim of this study was to explore the similarities and differences in clinical data between the clinical group and imaging group in patients with hematologic disease complicated by ALS.

Life Cycle Assessment on Wave and Tidal Energy Systems: A Review of Current Methodological Practice.

Recent decades have witnessed wave and tidal energy technology receiving considerable attention because of their low carbon emissions during electricity production. However, indirect emissions from their entire life cycle should not be ignored. Therefore, life cycle assessment (LCA) has been widely applied as a useful approach to systematically evaluate the environmental performance of wave and tidal energy technologies.

A Novel Approach to Droplet's 3D Shape Recovery Based on Mask R-CNN and Improved Lambert⁻Phong Model.

Aiming at the demand for extracting the three-dimensional shapes of droplets in microelectronic packaging, life science, and some related fields, as well as the problems of complex calculation and slow running speed of conventional shape from shading (SFS) illumination reflection models, this paper proposes a Lambert⁻Phong hybrid model algorithm to recover the 3D shapes of micro-droplets based on the mask regions with convolutional neural network features (R-CNN) method to extract the highlight region of the droplet surface. This method fully integrates the advantages of the Lambertian model's fast running speed and the Phong model's high accuracy for reconstruction of the highlight region. First, the Mask R-CNN network is used to realize the segmentation of the highlight region of the droplet and obtain its coordinate information.

2,2'-Fluorine mono-carbonyl curcumin induce reactive oxygen species-Mediated apoptosis in Human lung cancer NCI-H460 cells.

In this paper, we synthesized three fluorine-substituted mono-carbonyl curcumin analogs and evaluated their cytotoxicity against several cancer cells by the MTT assay. The results exhibited that all the three compounds were more active than the leading curcumin. Especially, 2,2'-F mono-carbonyl curcumin, 1a, surfaced as an important lead compound displaying almost 4-fold cytotoxicity relative to curcumin.