Experimental Investigation of Three-Dimensional Multi-Directional Piezoelectric Wind Energy Harvester.

The wind-induced vibration energy harvester is a type of ideal power source for wireless sensor nodes. To adapt to the uncertainty of wind direction in natural environments, this paper proposes a three-dimensional multi-directional piezoelectric wind energy harvester (WEH), whose bluff body is an external shell with the shape like a lampshade, supported by three internal piezoelectric composite beams. A harvester prototype was made using 3D printing technology, and its multi-directional energy harvesting characteristics were systematically tested in a wind tunnel.

A Multiple-Stimuli-Responsive Amphiphilic Copolymer for Antifouling and Antibacterial Functionality via a "Resistance-Kill-Release" Mechanism.

In recent years, polymers with stimuli-responsive properties have been increasingly reported on due to their diverse applications. However, most of the studies have only focused on the performance of polymers under specific scenarios. The laws of changes in the properties in response to various external stimuli have been less systematically and quantitatively studied.

Integrating satellite and unmanned aircraft system (UAS) imagery to model livestock population dynamics in the Longbao Wetland National Nature Reserve, China.

The collection of field-based animal data is laborious, risky and costly in some areas, such as various nature reserves. Although multiple studies have used satellite imagery, aerial imagery, and field data individually for some animal species surveys, several technical issues still need to be addressed before full standardization of remote sensing methods for modeling animal population dynamics over large areas. This study is the first to model the population dynamics of livestock in the Longbao Wetland National Nature Reserve, China by utilizing yak estimations from Worldview-2 satellite imagery (0.

Tree-based approach for exploring marine spatial patterns with raster datasets.

From multiple raster datasets to spatial association patterns, the data-mining technique is divided into three subtasks, i.e., raster dataset pretreatment, mining algorithm design, and spatial pattern exploration from the mining results.