Plastic Inorganic Semiconductors for Flexible Electronics

Featured with bendability and deformability, smartness and lightness, flexible materials and devices have wide applications in electronics, optoelectronics, and energy utilization. The key for flexible electronics is the integration of flexibility and decent electrical performance of semiconductors. It has long been realized that high-performance inorganic semiconductors are brittle, and the thinning-down-induced flexibility does not change the intrinsic brittleness. This inconvenient fact severely restricts the fabrication and service of inorganic semiconductors in flexible and deformable electronics. By contrast, flexible and soft polymers can be readily deformed but behave poorly in terms of electrical properties. Recently, Ag2S was discovered as the room-temperature ductile inorganic semiconductor. The intrinsic flexibility and plasticity of Ag2S are attributed to multicentered chemical bonding and solid linkage among easy slip planes. Furthermore, the electrical and thermoelectric properties of Ag2S can be readily optimized by Se/Te alloying while the ductility is maintained, giving birth to a high-efficiency full inorganic flexible thermoelectric device. This chapter briefly reviews this big discovery, relevant backgrounds, and research advances and tries to demonstrate a clear structure-performance correlation between crystal structure/chemical bonding and mechanical/electrical properties

Vehicle Detection of Multi-source Remote Sensing Data Using Active Fine-tuning Network

Vehicle detection in remote sensing images has attracted increasing interest in recent years. However, its detection ability is limited due to lack of well-annotated samples, especially in densely crowded scenes. Furthermore, since a list of remotely sensed data sources is available, efficient exploitation of useful information from multi-source data for better vehicle detection is challenging. To solve the above issues, a multi-source active fine-tuning vehicle detection (Ms-AFt) framework is proposed, which integrates transfer learning, segmentation, and active classification into a unified framework for auto-labeling and detection. The proposed Ms-AFt employs a fine-tuning network to firstly generate a vehicle training set from an unlabeled dataset. To cope with the diversity of vehicle categories, a multi-source based segmentation branch is then designed to construct additional candidate object sets. The separation of high quality vehicles is realized by a designed attentive classifications network. Finally, all three branches are combined to achieve vehicle detection. Extensive experimental results conducted on two open ISPRS benchmark datasets, namely the Vaihingen village and Potsdam city datasets, demonstrate the superiority and effectiveness of the proposed Ms-AFt for vehicle detection. In addition, the generalization ability of Ms-AFt in dense remote sensing scenes is further verified on stereo aerial imagery of a large camping site

Evaluation of Groundwater Storage Variations Estimated from GRACE Data Assimilation and State-of-the-Art Land Surface Models in Australia and the North China Plain

The accurate knowledge of the groundwater storage variation (ΔGWS) is essential for reliable water resource assessment, particularly in arid and semi-arid environments (e.g., Australia, the North China Plain (NCP)) where water storage is significantly affected by human activities and spatiotemporal climate variations. The large-scale ΔGWS can be simulated from a land surface model (LSM), but the high model uncertainty is a major drawback that reduces the reliability of the estimates. The evaluation of the model estimate is then very important to assess its accuracy. To improve the model performance, the terrestrial water storage variation derived from the Gravity Recovery And Climate Experiment (GRACE) satellite mission is commonly assimilated into LSMs to enhance the accuracy of the ΔGWS estimate. This study assimilates GRACE data into the PCRaster Global Water Balance (PCR-GLOBWB) model. The GRACE data assimilation (DA) is developed based on the three-dimensional ensemble Kalman smoother (EnKS 3D), which considers the statistical correlation of all extents (spatial, temporal, vertical) in the DA process. The ΔGWS estimates from GRACE DA and four LSM simulations (PCR-GLOBWB, the Community Atmosphere Biosphere Land Exchange (CABLE), the Water Global Assessment and Prognosis Global Hydrology Model (WGHM), and World-Wide Water (W3)) are validated against the in situ groundwater data. The evaluation is conducted in terms of temporal correlation, seasonality, long-term trend, and detection of groundwater depletion. The GRACE DA estimate shows a significant improvement in all measures, notably the correlation coefficients (respect to the in situ data) are always higher than the values obtained from model simulations alone (e.g., ~0.15 greater in Australia, and ~0.1 greater in the NCP). GRACE DA also improves the estimation of groundwater depletion that the models cannot accurately capture due to the incorrect information of the groundwater demand (in, e.g., PCR-GLOBWB, WGHM) or the unavailability of a groundwater consumption routine (in, e.g., CABLE, W3). In addition, this study conducts the inter-comparison between four model simulations and reveals that PCR-GLOBWB and CABLE provide a more accurate ΔGWS estimate in Australia (subject to the calibrated parameter) while PCR-GLOBWB and WGHM are more accurate in the NCP (subject to the inclusion of anthropogenic factors). The analysis can be used to declare the status of the ΔGWS estimate, as well as itemize the possible improvements of the future model development.This work is funded by The University of Newcastle to support NASA’s GRACE and GRACE Follow-On projects as an international science team member to the missions

Daidzin decreases blood glucose and lipid in streptozotocin-induced diabetic mice

Purpose: To investigate the ameliorative effect of daidzin (DZ) on diabetes in streptozotocin (STZ)- induced diabetic Institute of Cancer Research (ICR) mice, with a view to determining its usefulness in the treatment of diabetes.Methods: The effect of DZ (100, 200 and 400 mg/kg) on blood glucose was investigated in both normal and STZ-induced diabetic mice with glibenclamide (3 mg/kg) and metformin (400 mg/kg) as positive control, respectively. Serum or hepatic levels of lipid, proinflammatory factors, malondialdehyde (MDA) and superoxide dismutase (SOD) were measured. Glucosidase activity assay and glucose uptake by C2C12 myotubes were performed in vitro and the expression of glucose transporter 4 (GLUT4) in C2C12 cells was determined by western blot.Results: DZ (200 and 400 mg/kg) did not decrease fasting blood glucose in normal mice but inhibited starch-induced postprandial glycemia. Oral administration of 400 mg/kg of DZ for 14 days significantly decreased mouse blood glucose (p < 0.01), as well as serum total cholesterol (TC, p < 0.01), triglycerides (TG, p < 0.01), low-density lipoprotein cholesterol (LDL-c, p < 0.01) levels in STZ-induced hyperglycemic mice and improved oral glucose tolerance. The serum and hepatic activity of SOD was enhanced (p < 0.01 and p < 0.001, respectively) while MDA level decreased (p < 0.001). Blood concentrations of interleukin-6 (IL-6, p < 0.001), tumor necrosis factor α (TNF-α, p < 0.01), monocyte chemotactic protein 1 (MCP-1, p < 0.01) were also significantly reduced. In vitro glucosidase activity results showed that DZ inhibited α-glucosidase with IC50 values of 82, 98 and 389 μg/mL for α- glucosidase from S. cerevisiae, Rhizopus sp. and rat intestines, respectively. It also stimulated glucose uptake and GLUT4 membrane translocation in C2C12 myotubes at 20 μM (p < 0.05).Conclusion: Oral administration of DZ is effective in alleviating diabetic hyperglycemia, dyslipidemia and inflammation. Inhibition of α-glucosidase and stimulation of glucose consumption by muscles may account for its inhibitory effect on blood glucose.Keywords: Daidzin, Diabetes, Inflammation, Superoxide dismutase (SOD), Malondialdehyde (MDA), Glucosidase, C2C12 myotubes, Glucose transporte

Comparative genomics study of polyhydroxyalkanoates (PHA) and ectoine relevant genes from Halomonas sp. TD01 revealed extensive horizontal gene transfer events and co-evolutionary relationships

BACKGROUND: Halophilic bacteria have shown their significance in industrial production of polyhydroxyalkanoates (PHA) and are gaining more attention for genetic engineering modification. Yet, little information on the genomics and PHA related genes from halophilic bacteria have been disclosed so far. RESULTS: The draft genome of moderately halophilic bacterium, Halomonas sp. TD01, a strain of great potential for industrial production of short-chain-length polyhydroxyalkanoates (PHA), was analyzed through computational methods to reveal the osmoregulation mechanism and the evolutionary relationship of the enzymes relevant to PHA and ectoine syntheses. Genes involved in the metabolism of PHA and osmolytes were annotated and studied in silico. Although PHA synthase, depolymerase, regulator/repressor and phasin were all involved in PHA metabolic pathways, they demonstrated different horizontal gene transfer (HGT) events between the genomes of different strains. In contrast, co-occurrence of ectoine genes in the same genome was more frequently observed, and ectoine genes were more likely under coincidental horizontal gene transfer than PHA related genes. In addition, the adjacent organization of the homologues of PHA synthase phaC1 and PHA granule binding protein phaP was conserved in the strain TD01, which was also observed in some halophiles and non-halophiles exclusively from γ-proteobacteria. In contrast to haloarchaea, the proteome of Halomonas sp. TD01 did not show obvious inclination towards acidity relative to non-halophilic Escherichia coli MG1655, which signified that Halomonas sp. TD01 preferred the accumulation of organic osmolytes to ions in order to balance the intracellular osmotic pressure with the environment. CONCLUSIONS: The accessibility of genome information would facilitate research on the genetic engineering of halophilic bacteria including Halomonas sp. TD01

A Miniature Fiber Optic Refractive Index Sensor Built in a MEMS-Based Microchannel

A small, highly sensitive, and electromagnetic interference (EMI)-immune refractive index (RI) sensor based on the Fabry-Perot (FP) interferometer is presented. The sensor’s FP cavity was fabricated by aligning two metal-deposited, single-mode optical fiber endfaces inside a microchannel on a silicon chip. The mirrors on the fiber endfaces were made of thermal-deposited metal films, which provided the high finesse necessary to produce a highly sensitive sensor. Microelectromechanical systems (MEMS) fabrication techniques, specifically photolithography and deep dry etching, were used to precisely control the profile and depth of the microchannel on the silicon chip with an accuracy of 2 μm. The RI change within the FP cavity was determined by demodulating the transmission spectrum phase shift. The sensitivity and finesse of the transmission spectrum were controlled by adjusting the cavity length and the thickness of the deposited metal. Our experimental results showed that the sensor’s sensitivity was 665.90 nm/RIU (RI Unit), and the limit of detection was 6 × 10−6 RIU. Using MEMS fabrication techniques to fabricate these sensors could make high yield mass production a real possibility. Multiple sensors could be integrated on a single small silicon chip to simultaneously measure RI, temperature, and biomolecule targets

Polysulfide Catalytic Materials for Fast-Kinetic Metal–Sulfur Batteries: Principles and Active Centers

Benefiting from the merits of low cost, ultrahigh-energy densities, and environmentally friendliness, metal–sulfur batteries (M–S batteries) have drawn massive attention recently. However, their practical utilization is impeded by the shuttle effect and slow redox process of polysulfide. To solve these problems, enormous creative approaches have been employed to engineer new electrocatalytic materials to relieve the shuttle effect and promote the catalytic kinetics of polysulfides. In this review, recent advances on designing principles and active centers for polysulfide catalytic materials are systematically summarized. At first, the currently reported chemistries and mechanisms for the catalytic conversion of polysulfides are presented in detail. Subsequently, the rational design of polysulfide catalytic materials from catalytic polymers and frameworks to active sites loaded carbons for polysulfide catalysis to accelerate the reaction kinetics is comprehensively discussed. Current breakthroughs are highlighted and directions to guide future primary challenges, perspectives, and innovations are identified. Computational methods serve an ever-increasing part in pushing forward the active center design. In summary, a cutting-edge understanding to engineer different polysulfide catalysts is provided, and both experimental and theoretical guidance for optimizing future M–S batteries and many related battery systems are offered

Development and characterization of a core set of SSR markers for fingerprinting analysis of Chinese maize varieties

A core set of 60 SSRs was selected and modified using 231 Chinese and USA maize (Zea mays L.) inbred lines from more than 2000 SSRs for DNA fingerprinting analysis. All 60 SSR markers met the following criteria: (1) amplification of a single locus; (2) distinct amplification products; (3) adequate intervals between adjacent alleles; (4) suitable PCR fragment size; (5) reasonable discrimination power (DP); and (6) even distribution across the maize genome. Furthermore, the 60 SSR primers were re-designed to adjust the PCR product size. Together with the application of four different fluorescent dyes, a high-throughput 10-plex capillary electrophoresis platform was explored. The 60 core SSR markers were further divided into three groups (20 SSRs per group) according to peak morphology and DP value. Groups I, II and III were used in DNA fingerprinting analysis as a basic core, an expanded core and a candidate core set respectively. The allele number per locus varied from three to 22 with an average of 8.95; the average number of alleles per group I, II and III was a respective 7.35, 7.8 and 11.4. The DP values ranged from 0.366 to 0.913, with an average of 0.718 among all loci; the average group DP values were 0.697, 0.718 and 0.737 for groups I, II and III respectively; and the cumulative values of discrimination power (CDP) approached 1 for all groups. Cluster analysis results using 60 selected loci divided the Chinese inbred lines into six groups, including Luda Red Cob, P, Improved Reid, Tang-si-ping-tou, Waxy and Lancaster. The USA inbred lines were segregated into four groups, including SSS, Lancaster, Iodent and Oh43/Oh07Mid mixed