A facile and efficient single-step approach for the fabrication of vancomycin functionalized polymer-based monolith as chiral stationary phase for nano-liquid chromatography

A facile single-step preparation strategy for fabricating vancomycin functionalized organic polymer based monolith within 100 mu m fused-silica capillary was developed. The synthetic chiral functional monomer, i.e 2-isocyanatoethyl methacrylate (ICNEML) derivative of vancomycin, was co-polymerized with the cross-linker ethylene dimethacrylate (EDMA) in the presence of methanol and dimethyl sulfoxide as the selected porogens. The co-polymerization conditions were systematically optimized in order to obtain satisfactory column performance. Adequate permeability, stability and column morphology were observed for the optimized poly(ICNEML-vancomycin-co-EDMA) monolith. A series of chiral drugs were evaluated on the monolith in either several other beta-blockers. The proposed single-step approach not only resulted in a vancomycin functionalized organer polar organic-phase or reversed-phase modes. After the optimization of separation conditions, baseline or partial enantioseparation were obtained for series of drugs including thalidomide, colchicine, carteolol, salbutamol, clenbuterol andic polymer-based monolith with acceptable performance, but also significantly simplified the preparation procedure by reducing time and labor

Global prevalence of Cryptosporidium spp. in pigs: a systematic review and meta-analysis

Cryptosporidium spp. are significant opportunistic pathogens causing diarrhoea in humans and animals. Pigs are one of the most important potential hosts for Cryptosporidium. We evaluated the prevalence of Cryptosporidium in pigs globally using published information and a random-effects model. In total, 131 datasets from 36 countries were included in the final quantitative analysis. The global prevalence of Cryptosporidium in pigs was 16.3% (8560/64 809; 95% confidence interval [CI] 15.0–17.6%). The highest prevalence of Cryptosporidium in pigs was 40.8% (478/1271) in Africa. Post-weaned pigs had a significantly higher prevalence (25.8%; 2739/11 824) than pre-weaned, fattening and adult pigs. The prevalence of Cryptosporidium was higher in pigs with no diarrhoea (12.2%; 371/3501) than in pigs that had diarrhoea (8.0%; 348/4874). Seven Cryptosporidium species (Cryptosporidium scrofarum, Cryptosporidium suis, Cryptosporidium parvum, Cryptosporidium muris, Cryptosporidium tyzzeri, Cryptosporidium andersoni and Cryptosporidium struthioni) were detected in pigs globally. The proportion of C. scrofarum was 34.3% (1491/4351); the proportion of C. suis was 31.8% (1385/4351) and the proportion of C. parvum was 2.3% (98/4351). The influence of different geographic factors (latitude, longitude, mean yearly temperature, mean yearly relative humidity and mean yearly precipitation) on the infection rate of Cryptosporidium in pigs was also analysed. The results indicate that C. suis is the dominant species in pre-weaned pigs, while C. scrofarum is the dominant species in fattening and adult pigs. The findings highlight the role of pigs as possible potential hosts of zoonotic cryptosporidiosis and the need for additional studies on the prevalence, transmission and control of Cryptosporidium in pigs

Atomically Thin Al2 O3 Films for Tunnel Junctions

Metal-insulator-metal tunnel junctions are common throughout the microelectronics industry. The industry standard AlOx tunnel barrier, formed through oxygen diffusion into an Al wetting layer, is plagued by internal defects and pinholes which prevent the realization of atomically thin barriers demanded for enhanced quantum coherence. In this work, we employ in situ scanning tunneling spectroscopy along with molecular-dynamics simulations to understand and control the growth of atomically thin Al2O3 tunnel barriers using atomic-layer deposition. We find that a carefully tuned initial H2O pulse hydroxylated the Al surface and enabled the creation of an atomically thin Al2O3 tunnel barrier with a high-quality M-I interface and a significantly enhanced barrier height compared to thermal AlOx. These properties, corroborated by fabricated Josephson junctions, show that atomic-layer deposition Al2O3 is a dense, leak-free tunnel barrier with a low defect density which can be a key component for the next generation of metal-insulator-metal tunnel junctions

Atomically Thin Al2O3 Films for Tunnel Junctions

Metal-insulator-metal tunnel junctions are common throughout the microelectronics industry. The industry standard AlOx tunnel barrier, formed through oxygen diffusion into an Al wetting layer, is plagued by internal defects and pinholes which prevent the realization of atomically thin barriers demanded for enhanced quantum coherence. In this work, we employ in situ scanning tunneling spectroscopy along with molecular-dynamics simulations to understand and control the growth of atomically thin Al2O3 tunnel barriers using atomic-layer deposition. We find that a carefully tuned initial H2O pulse hydroxylated the Al surface and enabled the creation of an atomically thin Al2O3 tunnel barrier with a high-quality M−I interface and a significantly enhanced barrier height compared to thermal AlOx. These properties, corroborated by fabricated Josephson junctions, show that atomic-layer deposition Al2O3 is a dense, leak-free tunnel barrier with a low defect density which can be a key component for the next generation of metal-insulator-metal tunnel junctions

PSIC-Net: Pixel-Wise Segmentation and Image-Wise Classification Network for Surface Defects

Recent years have witnessed the widespread research of the surface defect detection technology based on machine vision, which has spawned various effective detection methods. In particular, the rise of deep learning has allowed the surface defect detection technology to develop further. However, these methods based on deep learning still have some drawbacks. For example, the size of the sample data is not large enough to support deep learning; the location and recognition of surface defects are not accurate enough; the real-time performance of segmentation and classification is not satisfactory. In the context, this paper proposes an end-to-end convolutional neural network model: the pixel-wise segmentation and image-wise classification network (PSIC-Net). With the innovative design of a three-stage network structure, improved loss function and a two-step training mode, PSIC-Net can accurately and quickly segment and classify surface defects with a small dataset of training data. This model was evaluated with three public datasets, and compared with the most advanced defect detection methods. All the performance metrics prove the effectiveness and advancement of PSIC-Net

Review of Electrothermal Micromirrors

Electrothermal micromirrors have become an important type of micromirrors due to their large angular scanning range and large linear motion. Typically, electrothermal micromirrors do not have a torsional bar, so they can easily generate linear motion. In this paper, electrothermal micromirrors based on different thermal actuators are reviewed, and also the mechanisms of those actuators are analyzed, including U-shape, chevron, thermo-pneumatic, thermo-capillary and thermal bimorph-based actuation. Special attention is given to bimorph based-electrothermal micromirrors due to their versatility in tip-tilt-piston motion. The exemplified applications of each type of electrothermal micromirrors are also presented. Moreover, electrothermal micromirrors integrated with electromagnetic or electrostatic actuators are introduced