Chinese cities show different trend toward carbon peak.

Understanding the disparities in carbon emission trend among cities is critical for achieving carbon peak goal. However, the status and trends of carbon peaking and reduction in various city types are still unclear. Therefore, this study classified 315 Chinese cities according to their economic and industrial structure by SOM-K-means, aiming to evaluate the trends and dynamic drivers of carbon peaking progress in different city types.

A piezoelectric-driven microneedle platform for skin disease therapy.

With over a million cases detected each year, skin disease is a global public health problem that diminishes the quality of life due to its difficulty to eradicate, propensity for recurrence, and potential for post-treatment scarring. Photodynamic therapy (PDT) is a treatment with minimal invasiveness or scarring and few side effects, making it well tolerated by patients. However, this treatment requires further research and development to improve its effective clinical use.

Acoustic hologram-induced virtual in vivo enhanced waveguide (AH-VIEW).

Optical imaging and phototherapy in deep tissues face notable challenges due to light scattering. We use encoded acoustic holograms to generate three-dimensional acoustic fields within the target medium, enabling instantaneous and robust modulation of the volumetric refractive index, thereby noninvasively controlling the trajectory of light. Through this approach, we achieved a remarkable 24.

Low-Frequency Ultrasound Sensitive Piezo1 Channels Regulate Keloid-Related Characteristics of Fibroblasts.

Keloids are benign fibroproliferative tumors that severely diminish the quality of life due to discomfort, dysfunction, and disfigurement. Recently, ultrasound technology as a noninvasive adjuvant therapy is developed to optimize treatment protocols. However, the biophysical mechanisms have not yet been fully elucidated.

Non-invasive evaluation of transdermal drug delivery using 3-D transient triplet differential (TTD) photoacoustic imaging.

Transdermal drug delivery (TDD) is less invasive and avoids first-pass metabolism, making it an attractive method for treating various diseases such as diabetes and hypertension. However, current methods for evaluating TDD systems lack in vivo descriptions of drug distribution in the skin. In this study, we demonstrate the capability of the Transient Triplet Differential (TTD) method, a non-invasive and background-free photoacoustic imaging technique, for accurately mapping drug distribution and evaluating different TDD systems.

Integrating machine learning with linguistic features: A universal method for extraction and normalization of temporal expressions in Chinese texts.

Background And Objective: With the rapid development of information dissemination technology, the amount of events information contained in massive texts now far exceeds the intuitive cognition of humans, and it is hard to understand the progress of events in order of time. Temporal information runs through the whole process of beginning, proceeding, and ending of events, and plays an important role in many natural language processing applications, such as information extraction, question answering, and text summary. Accurately extracting temporal information from Chinese texts and automatically mapping the temporal expressions in natural language to the time axis are crucial to understanding the development of events and dynamic changes in them.

Clustering by measuring local direction centrality for data with heterogeneous density and weak connectivity.

Clustering is a powerful machine learning method for discovering similar patterns according to the proximity of elements in feature space. It is widely used in computer science, bioscience, geoscience, and economics. Although the state-of-the-art partition-based and connectivity-based clustering methods have been developed, weak connectivity and heterogeneous density in data impede their effectiveness.

3D-Printed Integrated Ultrasonic Microneedle Array for Rapid Transdermal Drug Delivery.

Transdermal drug delivery (TDD) is an attractive alternative to oral and hypodermic injection drug administration, and is poised to increase its impact on medicine and pharmaceutical design. Microneedles (MNs) are a new minimally invasive TDD method widely used in medicine and cosmetology. MNs create a microscale channel from the stratum corneum to the dermis and enable drug delivery of hydrophilic and macromolecular into the skin.

Bipartite Network of Interest (BNOI): Extending Co-Word Network with Interest of Researchers Using Sensor Data and Corresponding Applications as an Example.

Traditional co-word networks do not discriminate keywords of researcher interest from general keywords. Co-word networks are therefore often too general to provide knowledge if interest to domain experts. Inspired by the recent work that uses an automatic method to identify the questions of interest to researchers like "problems" and "solutions", we try to answer a similar question "what sensors can be used for what kind of applications", which is great interest in sensor- related fields.

Green and facile fabrication of silver nanoparticles using Konjac Glucomannan by photocatalytic strategy.

Green fabrication of highly stable silver nanoparticles (AgNPs) is vital for its development. Herein, AgNPs with enhanced stability were prepared in an environmentally friendly manner using aqueous mixture of 0.8 mM silver nitrate and 10.

A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction.

Prediction of individual mobility is crucial in human mobility related applications. Whereas, existing research on individual mobility prediction mainly focuses on next location prediction and short-term dependencies between traveling locations. Long-term location sequence prediction is of great importance for long-time traffic planning and location advertising, and long-term dependencies exist as individual mobility regularity typically occurs daily and weekly.

Coupling cellular automata with area partitioning and spatiotemporal convolution for dynamic land use change simulation.

Urbanization processes have accelerated over recent decades, prompting efforts to model land use change (LUC) patterns for decision support and urban planning. Cellular automata (CA) are extensively employed given their simplicity, flexibility, and intuitiveness when simulating dynamic LUC. Previous research, however, has ignored the spatial heterogeneity among sub-regions, instead applying the same transition rules across entire regions; moreover, most existing methods extract neighborhood effects with only one data time slice, which is inconsistent with the nature of neighborhood interactions as a long-term process exhibiting obvious spatiotemporal dependency.

City-Wide Traffic Flow Forecasting Using a Deep Convolutional Neural Network.

City-wide traffic flow forecasting is a significant function of the Intelligent Transport System (ITS), which plays an important role in city traffic management and public travel safety. However, this remains a very challenging task that is affected by many complex factors, such as road network distribution and external factors (e.g.

Fabrication of highly stable silver nanoparticles using polysaccharide-protein complexes from abalone viscera and antibacterial activity evaluation.

Silver nanoparticles (AgNPs) are eco-friendly antibacterial agents, yet their use is limited by their facile aggregation and precipitation. Therefore, the development of highly stable AgNPs is desirable. Herein, a polysaccharide-protein complex (PSP) was successfully obtained from viscera of abalone through a combination of enzymatic hydrolysis, membrane filtration, and gel permeation chromatography.

DCT-Based Preprocessing Approach for ICA in Hyperspectral Data Analysis.

The huge quantity of information and the high spectral resolution of hyperspectral imagery present a challenge when performing traditional processing techniques such as classification. Dimensionality and noise reduction improves both efficiency and accuracy, while retaining essential information. Among the many dimensionality reduction methods, Independent Component Analysis (ICA) is one of the most popular techniques.

Effects of miR-29a and miR-101a Expression on Myocardial Interstitial Collagen Generation After Aerobic Exercise in Myocardial-infarcted Rats.

Background And Aims: Myocardial infarction (MI) is accompanied by increased collagen deposition, cell necrosis and angiogenesis in cardiac tissue, which results in reduced ventricular compliance. Both microRNA-29a (miR-29a) and microRNA-101a (miR-101a) target the mRNAs encoding collagens and other proteins involved in fibrosis.

Methods: We assessed the effects of intermittent aerobic exercise on the expression of cardiac miR-29a and miR-101a and following effects on the TGFβ, fos, Smad2/3, COL1A1 and COL3A1 in MI model of rats.

Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback.

Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving.

Effect of molecular characteristics of Konjac glucomannan on gelling and rheological properties of Tilapia myofibrillar protein.

Konjac glucomannan (KGM) is an important gelling agent in composite gels. This study aimed to investigate the effects of KGM molecular characteristics (molecular weight, size and conformation) on gelling properties of Tilapia myofibrillar protein (TMP). In this work, TMP composite gels were prepared under neutral pH with varying KGM (native KGM, 10kGy-KGM, 20kGy-KGM, and 100kGy-KGM) of different molecular characteristics.

ANXA2 enhances the progression of hepatocellular carcinoma via remodeling the cell motility associated structures.

Hepatocellular carcinoma (HCC) ranks as the fifth most common malignancy worldwide. The detailed mechanism of signal regulation for HCC progression is still not known, and the high motility of cancer cells is known as a core property for cancer progression maintenance. Annexin A2 (ANXA2), a calcium-dependent phospholipids binding protein is highly expressed in HCC.

Main Road Extraction from ZY-3 Grayscale Imagery Based on Directional Mathematical Morphology and VGI Prior Knowledge in Urban Areas.

Main road features extracted from remotely sensed imagery play an important role in many civilian and military applications, such as updating Geographic Information System (GIS) databases, urban structure analysis, spatial data matching and road navigation. Current methods for road feature extraction from high-resolution imagery are typically based on threshold value segmentation. It is difficult however, to completely separate road features from the background.

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences.