Hydrogel‐Enabled Transfer‐Printing of Conducting Polymer Films for Soft Organic Bioelectronics

The use of conducting polymers such as poly(3,4‐ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) for the development of soft organic bioelectronic devices, such as organic electrochemical transistors (OECTs), is rapidly increasing. However, directly manipulating conducting polymer thin films on soft substrates remains challenging, which hinders the development of conformable organic bioelectronic devices. A facile transfer‐printing of conducting polymer thin films from conventional rigid substrates to flexible substrates offers an alternative solution. In this work, it is reported that PEDOT:PSS thin films on glass substrates, once mixed with surfactants, can be delaminated with hydrogels and thereafter be transferred to soft substrates without any further treatments. The proposed method allows easy, fast, and reliable transferring of patterned PEDOT:PSS thin films from glass substrates onto various soft substrates, facilitating their application in soft organic bioelectronics. By taking advantage of this method, skin‐attachable tattoo‐OECTs are demonstrated, relevant for conformable, imperceptible, and wearable organic biosensing.The use of hydrogels enables transfer‐printing of poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate thin films from glass substrates onto various soft substrates. Taking advantage of this technique, skin‐attachable organic electrochemical transistors (OECTs) are fabricated on commercially available tattoo paper. Wearable tattoo‐OECTs are further demonstrated with the integration of a wireless readout system.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/1/adfm201906016.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/2/adfm201906016_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154307/3/adfm201906016-sup-0001-SuppMat.pd

Interactive effects of elevated CO2 concentration and irrigation on photosynthetic parameters and yield of maize in Northeast China.

Maize is one of the major cultivated crops of China, having a central role in ensuring the food security of the country. There has been a significant increase in studies of maize under interactive effects of elevated CO2 concentration ([CO2]) and other factors, yet the interactive effects of elevated [CO2] and increasing precipitation on maize has remained unclear. In this study, a manipulative experiment in Jinzhou, Liaoning province, Northeast China was performed so as to obtain reliable results concerning the later effects. The Open Top Chambers (OTCs) experiment was designed to control contrasting [CO2] i.e., 390, 450 and 550 µmol·mol(-1), and the experiment with 15% increasing precipitation levels was also set based on the average monthly precipitation of 5-9 month from 1981 to 2010 and controlled by irrigation. Thus, six treatments, i.e. C550W+15%, C550W0, C450W+15%, C450W0, C390W+15% and C390W0 were included in this study. The results showed that the irrigation under elevated [CO2] levels increased the leaf net photosynthetic rate (Pn) and intercellular CO2 concentration (Ci) of maize. Similarly, the stomatal conductance (Gs) and transpiration rate (Tr) decreased with elevated [CO2], but irrigation have a positive effect on increased of them at each [CO2] level, resulting in the water use efficiency (WUE) higher in natural precipitation treatment than irrigation treatment at elevated [CO2] levels. Irradiance-response parameters, e.g., maximum net photosynthetic rate (Pnmax) and light saturation points (LSP) were increased under elevated [CO2] and irrigation, and dark respiration (Rd) was increased as well. The growth characteristics, e.g., plant height, leaf area and aboveground biomass were enhanced, resulting in an improved of yield and ear characteristics except axle diameter. The study concluded by reporting that, future elevated [CO2] may favor to maize when coupled with increasing amount of precipitation in Northeast China

Structure-Preserved and Weakly Redundant Band Selection for Hyperspectral Imagery

In recent years, sparse self-representation has achieved remarkable success in hyperspectral band selection. However, the traditional sparse self-representation-based band selection methods tend to neglect the spatial distribution differences and spectral redundancy between heterogeneous regions. Consequently, the uniform band subset obtained cannot accurately express the key features of various region-specific objects. In this context, this article proposes the structure-preserved and weakly redundant (SPWR) band selection method for hyperspectral imagery (HSI). Initially, to preserve the spatial structure of HSI, heterogeneous regions are generated by superpixel segmentation. This process simulates the actual distribution of ground objects and captures the spectral feature differences from heterogeneous regions, thus adapting the sparse self-representation to diverse land cover types. Subsequently, given that the different objects between heterogeneous regions have different sensitive bands, a series of region-specific multimetric hypergraphs are constructed to more accurately express the multivariate adjacencies between bands for each region. Significantly, a new spectral similarity measure that integrates both the spectral distance and physical distance is elaborately utilized to group bands into various hypergraphs. Finally, a consensus matrix is designed to fuse multiple coefficient matrices carrying the local spatial-spectral information of HSI, thereby selecting the subset of bands for a unified characterization of HSI and achieving the complementarity of multiple regions. Extensive comparison experiments on four real-world datasets demonstrate that the proposed method SPWR can efficiently select representative bands and outperforms other comparison methods

Fully convolutional multi‐scale dense networks for monocular depth estimation

Monocular depth estimation is of vital importance in understanding the 3D geometry of a scene. However, inferring the underlying depth is ill‐posed and inherently ambiguous. In this study, two improvements to existing approaches are proposed. One is about a clean improved network architecture, for which the authors extend Densely Connected Convolutional Network (DenseNet) to work as end‐to‐end fully convolutional multi‐scale dense networks. The dense upsampling blocks are integrated to improve the output resolution and selected skip connection is incorporated to connect the downsampling and the upsampling paths efficiently. The other is about edge‐preserving loss functions, encompassing the reverse Huber loss, depth gradient loss and feature edge loss, which is particularly suited for estimation of fine details and clear boundaries of objects. Experiments on the NYU‐Depth‐v2 dataset and KITTI dataset show that the proposed model is competitive to the state‐of‐the‐art methods, achieving 0.506 and 4.977 performance in terms of root mean squared error respectively

Synthesis of 4,8-dimethoxy-1-naphthol via an acetyl migration

<p>Based on acetyl migration, an efficient synthesis of 4,8-dimethoxy-1-naphthol <b>(1)</b> has been achieved with high overall yield. Compared with the reported method, there were several advantages. First, the reaction conditions were mild. Second, the workup of each step was much simpler. Third, juglone as the starting material in the synthesis was readily available. The solvent and reaction temperature greatly influenced the migration process.</p

Change on ear characteristics of maize under effects of elevated [CO₂] and irrigation.

<p>The data are means ± SD (n = 3).</p><p>Different lower cases letters (a,b,c,d,e) indicated significant difference (<i>P</i><0.05).</p