Flexible Sensors Based on Conductive Polymer Composites.

Elastic polymer-based conductive composites (EPCCs) are of great potential in the field of flexible sensors due to the advantages of designable functionality and thermal and chemical stability. As one of the popular choices for sensor electrodes and sensitive materials, considerable progress in EPCCs used in sensors has been made in recent years. In this review, we introduce the types and the conductive mechanisms of EPCCs. Furthermore, the recent advances in the application of EPCCs to sensors are also summarized. This review will provide guidance for the design and optimization of EPCCs and offer more possibilities for the development and application of flexible sensors.

Identification, characterization and application of M16AT, a new organic solvent-tolerant (R)-enantio-selective type IV amine transaminase from Mycobacterium sp. ACS1612.

Biocatalysis has emerged as a powerful alternative to traditional chemical methods, especially for asymmetric synthesis. As biocatalysts usually exhibit excellent chemical, regio- and enantioselectivity, they facilitate and simplify many chemical processes for the production of a broad range of products. Here, a new biocatalyst called, R-selective amine transaminases (R-ATAs), was obtained from Mycobacterium sp. ACS1612 (M16AT) using in-silico prediction combined with a genome and protein database. A two-step simple purification process could yield a high concentration of pure enzyme, suggesting that industrial application would be inexpensive. Additionally, the newly identified and characterized R-ATAs displayed a broad substrate spectrum and strong tolerance to organic solvents. Moreover, the synthetic applicability of M16AT has been demonstrated by the asymmetric synthesis of (R)-fendiline from of (R)-1-phenylethan-1-amine.

Composition analysis of Compound Shenhua Tablet, a seven-herb Chinese medicine for IgA nephropathy: evaluation of analyte-capacity of the assays.

Compound Shenhua Tablet, a medicine comprising seven herbs, is employed in treating IgA nephropathy. This study aimed to meticulously analyze its chemical composition. Based on a list of candidate compounds, identified through extensive literature review pertinent to the tablet's herbal components, the composition analysis entailed the systematic identification, characterization, and quantification of the constituents. The analyte-capacity of LC/ESI-MS-based and GC/EI-MS-based assays was evaluated. The identified and characterized constituents were quantified to determine their content levels and were ranked based on the constituents' daily doses. A total of 283 constituents, classified into 12 distinct categories, were identified and characterized in the Compound Shenhua Tablet. These constituents exhibited content levels of 1-10 982 µg·g-1, with daily doses of 0.01-395 µmol·d-1. The predominant constituents, with daily doses of ≥ 10 µmol·d-1, include nine organic acids (citric acid, quinic acid, chlorogenic acid, cryptochlorogenic acid, gallic acid, neochlorogenic acid, isochlorogenic acid C, isochlorogenic acid B, and linoleic acid), five iridoids (specnuezhenide, nuezhenoside G13, nuezhenidic acid, secoxyloganin, and secologanoside), two monoterpene glycosides (paeoniflorin and albiflorin), a sesquiterpenoid (curzerenone), a triterpenoid (oleanolic acid), and a phenylethanoid (salidroside). Additionally, there were 83, 126, and 55 constituents detected in the medicine with daily doses of 1-10, 0.1-1, and 0.01-0.1 µmol·d-1, respectively. The combination of the LC/ESI-MS-based and GC/EI-MS-based assays demonstrated a complementary relationship in their analyte-capacity for detecting the constituents present in the medicine. This comprehensive composition analysis establishes a solid foundation for further pharmacological research on Compound Shenhua Tablet and facilitates the quality evaluation of this complex herbal medicine.

Model Predictive Control of a Semi-Active Vehicle-Mounted Vibration Isolation Platform.

When conventional delivery vehicles are driven over complex terrain, large vibrations can seriously affect vehicle-loaded equipment and cargo. Semi-active vehicle-mounted vibration isolation control based on road preview can improve the stability of loaded cargo and instruments by enabling them to have lower vertical acceleration. A combined dynamic model including a vehicle and platform is developed first. In order to obtain a non-linear relationship between damping force and input current, a continuous damping control damper model is developed, and the corresponding external characteristic tests are carried out. Because some conventional control algorithms cannot handle complex constraints and preview information, a model predictive control algorithm based on forward road preview and input constraints is designed. Finally, simulations and real tests of the whole vehicle vibration environment are carried out. The results show that the proposed model predictive control based on road preview can effectively improve vibration isolation performance of the vehicle-mounted platform.