Explores the role of dipole–dipole interactions in preventing solvent co-intercalation into graphite anodes, aiming to broaden the scope of electrolyte design. The study involves multiple authors and is published in Energy & Environmental Science in 2023.

The article discusses the use of photothermal ferrotherapy to induce immunogenic cell death in triple-negative breast cancer cells using iron-based ternary chalcogenide nanoparticles. This approach leverages the unique properties of these nanoparticles to target and destroy cancer cells, potentially offering a new avenue for cancer treatment.

A descriptive study at the East Carolina University School of Dental Medicine analyzed 534,983 procedures from 26,710 patients to describe dental service utilization patterns in North Carolina. The study found that payment method significantly influenced service type, with Medicaid beneficiaries more likely to receive restorative procedures, removable prosthetics, or oral surgery, but less preventive procedures than expected. Privately insured or self-paying individuals used a greater variety of services, including specialized procedures like endodontics and implants.

The study examines the covariation of risk-averse and escape behavior in the common lizard Zootoca vivipara, considering factors such as sex, state (gravid vs. postpartum; infested vs. noninfested), and life stages (adult vs. neonate). It finds that behavioral syndromes, specifically the 'risk-averse and escape' behavioral syndrome, differ between sexes and are mediated by individual states. The study reveals that gravid females exhibit this syndrome, which disappears postpartum and when lizards are infested by parasites. The research underscores the importance of considering individual states in the expression of behavioral syndromes and suggests that parasites may impact the covariation between risk-averse and escape behaviors.

The study addresses the ecological pressures in the Chengdu–Chongqing Economic Circle (CCEC) due to rapid economic development. It employs land use/cover data and environmental threat factors to construct Ecological Security Patterns (ESPs) using the InVEST model and Circuit Theory. The research identifies key ecological nodes, corridors, and sources, and suggests targeted measures for ecological protection and green development. The findings provide guidance for managing urban expansion and anthropogenic activities to enhance the ecological security level of the CCEC.

The article presents a detailed study on a microfluidic flowmeter based on a liquid crystal-filled nested capillary. It includes experimental observations, theoretical analysis, and simulations to demonstrate the device's performance. The study covers the influence of liquid crystal refractive index on the transmission spectrum, heat transfer simulations, and the impact of airflow rates on the wavelength shift of whispering gallery mode resonances. The results show that the proposed sensor has high sensitivity and stability, making it suitable for various applications, including monitoring injection pumps.

CroplandCDNet is a novel network designed for detecting cropland changes using multitemporal remote sensing images. It combines an adaptive receptive field and multiscale feature transmission fusion to enhance detection accuracy. The network effectively extracts multiscale features and uses an SK attention module to emphasize relevant changes while suppressing irrelevant information. Experiments using the CLCD and Jilin-1 datasets demonstrate that CroplandCDNet outperforms six advanced change detection methods, achieving the highest F1 and overall accuracy scores. The study highlights the network's robustness and potential for improving cropland change detection, with future plans to integrate SAR data and optimize for large-scale applications.

This study evaluates various pre-treatments and solvents for extracting anthocyanins from purple sweetpotato, focusing on color, yields, antioxidant capabilities, and brown index. Optimal results were obtained with steaming unpeeled whole sweetpotato and using 1% citric acid-ddH2O as the solvent. The color stability of purified anthocyanin solutions was assessed under different pH levels at 25 °C and 65 °C. The solutions showed a color spectrum from magenta to yellow across the pH range, with magenta hues at lower pH demonstrating higher color stability. Elevated temperatures significantly accelerated anthocyanin degradation. The study provides guidance for the extraction, preservation, and application of purple sweetpotato anthocyanins in the food industry.

The study addresses the development of a novel gas sensor using a nanoporous polymer modified with hexafluoroisopropanol (HFIP) for detecting dimethyl methylphosphonate (DMMP), a nerve agent simulator. The sensor, based on a surface acoustic wave (SAW) device, demonstrates high sensitivity, fast response, and good selectivity, detecting DMMP at 0.8 ppm with response/recovery times of 29.8/43.8 seconds and a detection limit of 0.11 ppm. The effects of temperature and humidity on sensor performance were analyzed, showing a linear relationship with the baseline signal. The study provides a new strategy for developing effective nerve agent sensors.

The study introduces a multiview data clustering algorithm called MFSC, which integrates similarity graph learning and unsupervised feature selection to improve clustering accuracy. The algorithm incorporates local manifold regularization and is evaluated using benchmark datasets, demonstrating superior performance compared to traditional methods. The research highlights the importance of capturing multiview manifold structures and addresses challenges such as high dimensionality and data redundancy. Future work aims to integrate deep learning techniques to enhance feature extraction capabilities for multiview data.