Plasmonic Nano-Rotamers with Programmable Polarization-Resolved Coloration

3D-shaped artificial Mg nano-rotamers with a programmable dihedral angle between two plasmonic arms, designed to exhibit both programmable linear and circular polarization properties, are presented. The nanoscale physical shadow growth technique offers precise control over the angular alignment in these nanostructures with 1° angular precision, thus controlling their symmetry from achiral C2v and C2h to chiral C2. As a result, they give rise to a wide range of polarization-resolved coloration, spanning from invisible to visible colors with 46% transmission contrast for linear polarization while exhibiting 0.08 g-factor in visible for circular polarization. These nano-rotamers hold great potential for various applications in adaptive photonic filters, memory, and anticounterfeiting devices, benefiting from their tunable plasmonic properties

Coverage analysis of heterogeneous cellular networks in urban areas

© 2016 IEEE. In this article, a network model incorporating both line-of-sight (LOS) and non-line-of-sight (NLOS) transmissions is proposed to investigate impacts of blockages in urban areas on heterogeneous network coverage performance. Results show that co-existence of NLOS and LOS transmissions has a significant impact on network performance. We find in urban areas, that deploying more BSs in different tiers is better than merely deploying all BSs in the same tier in terms of coverage probability

Performance, microbial community and fluorescent characteristic of microbial products in a solid-phase denitrification biofilm reactor for WWTP effluent treatment

© 2018 Microbial products, i.e. extracellular polymeric substance (EPS) and soluble microbial product (SMP), have a significant correlation with microbial activity of biologically based systems. In present study, the spectral characteristics of two kinds of microbial products were comprehensively evaluated in a solid-phase denitrification biofilm reactor for WWTP effluent treatment by using poly (butylene succinate) (PBS) as carbon source. After the achievement of PBS-biofilm, nitrate and total nitrogen removal efficiencies were high of 97.39 ± 1.24% and 96.38 ± 1.1%, respectively. The contents of protein and polysaccharide were changed different degrees in both LB-EPS and TB-EPS. Excitation-emission matrix (EEM) implied that protein-like substances played a significant role in the formation of PBS-biofilm. High-throughput sequencing result implied that the proportion of denitrifying bacteria, including Simplicispira, Dechloromonas, Diaphorobacter, Desulfovibrio, increased to 9.2%, 7.4%, 4.8% and 3.6% in PBS-biofilm system, respectively. According to EEM-PARAFAC, two components were identified from SMP samples, including protein-like substances for component 1 and humic-like and fulvic acid-like substances for component 2, respectively. Moreover, the fluorescent scores of two components expressed significant different trends to reaction time. Gas chromatography-mass spectrometer (GC-MS) implied that some new organic matters were produced in the effluent of SP-DBR due to biopolymer degradation and denitrification processes. The results could provide a new insight about the formation and stability of solid-phase denitrification PBS-biofilm via the point of microbial products

Prediction of the functional class of metal-binding proteins from sequence derived physicochemical properties by support vector machine approach

Metal-binding proteins play important roles in structural stability, signaling, regulation, transport, immune response, metabolism control, and metal homeostasis. Because of their functional and sequence diversity, it is desirable to explore additional methods for predicting metal-binding proteins irrespective of sequence similarity. This work explores support vector machines (SVM) as such a method. SVM prediction systems were developed by using 53,333 metal-binding and 147,347 non-metal-binding proteins, and evaluated by an independent set of 31,448 metal-binding and 79,051 non-metal-binding proteins. The computed prediction accuracy is 86.3%, 81.6%, 83.5%, 94.0%, 81.2%, 85.4%, 77.6%, 90.4%, 90.9%, 74.9% and 78.1% for calcium-binding, cobalt-binding, copper-binding, iron-binding, magnesium-binding, manganese-binding, nickel-binding, potassium-binding, sodium-binding, zinc-binding, and all metal-binding proteins respectively. The accuracy for the non-member proteins of each class is 88.2%, 99.9%, 98.1%, 91.4%, 87.9%, 94.5%, 99.2%, 99.9%, 99.9%, 98.0%, and 88.0% respectively. Comparable accuracies were obtained by using a different SVM kernel function. Our method predicts 67% of the 87 metal-binding proteins non-homologous to any protein in the Swissprot database and 85.3% of the 333 proteins of known metal-binding domains as metal-binding. These suggest the usefulness of SVM for facilitating the prediction of metal-binding proteins. Our software can be accessed at the SVMProt server

Exogenous application of plant growth regulators increased the total flavonoid content in Taraxacum officinale Wigg

The effects of plant growth regulators (PGRs) were studied on growth, total flavonoid, gibberellins (GA) and salicylic acid (SA) contents of Taraxacum officinale (dandelion), a widely used medicinal plant in Korea. All the four PGRs used; gibberellic acid (GA3), kinetin (Kn), salicylic acid (SA) and ethephon (2- chloroethylphosphonic acid) were applied at the rates of 0.5 and 1.0 mM. GA3 markedly enhanced fresh shoot weight, while 0.5 mM of kinetin application significantly enhanced dry root mass as compared tocontrol. SA enhanced both shoot and root attributes, while ethephon decreased plant growth. Endogenous bioactive GA1 and GA4 content and SA content enhanced with the application of GA3, SA and kinetin, but declined with ethephon. The flavonoid content of dandelion significantly increased with SA treatment, but was not altered with the application of other PGRs. The current study demonstrated the favorable effect of GA3, kinetin and SA on growth, bioactive GAs, SA and flavonoid contents of dandelion. These investigations offered interesting information as PGRs were never tested for plant growth and development of dandelion. It also reports the presence of both early C-13 hydroxylation and non C-13 hydroxylation pathways of GA biosynthesis in dandelion for the first time

Immunogenicity of SCB-2019 Coronavirus Disease 2019 Vaccine Compared With 4 Approved Vaccines

A significant correlation has been shown between the binding antibody responses against original severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein and vaccine efficacy of 4 approved coronavirus disease 2019 vaccines. We therefore assessed the immune response against original SARS-CoV-2 elicited by the adjuvanted S-Trimer vaccine, SCB-2019 + CpG/alum, in the same assay and laboratory. Responses to SCB-2019 were comparable or superior for antibody to original and Alpha variant when compared with 4 approved vaccines. The comparison accurately predicted success of the recently reported efficacy trial of SCB-2019 vaccine. Immunogenicity comparisons to original strain and variants of concern should be considered as a basis for authorization of vaccines

Ocean temperature and salinity components of the Madden-Julian oscillation observed by Argo floats

New diagnostics of the Madden-Julian Oscillation (MJO) cycle in ocean temperature and, for the first time, salinity are presented. The MJO composites are based on 4 years of gridded Argo float data from 2003 to 2006, and extend from the surface to 1,400 m depth in the tropical Indian and Pacific Oceans. The MJO surface salinity anomalies are consistent with precipitation minus evaporation fluxes in the Indian Ocean, and with anomalous zonal advection in the Pacific. The Argo sea surface temperature and thermocline depth anomalies are consistent with previous studies using other data sets. The near-surface density changes due to salinity are comparable to, and partially offset, those due to temperature, emphasising the importance of including salinity as well as temperature changes in mixed-layer modelling of tropical intraseasonal processes. The MJO-forced equatorial Kelvin wave that propagates along the thermocline in the Pacific extends down into the deep ocean, to at least 1,400 m. Coherent, statistically significant, MJO temperature and salinity anomalies are also present in the deep Indian Ocean

Nitrogen removal via nitrite in a partial nitrification sequencing batch biofilm reactor treating high strength ammonia wastewater and its greenhouse gas emission

© 2017 Elsevier Ltd In present study, the feasibility of partial nitrification (PN) process achievement and its greenhouse gas emission were evaluated in a sequencing batch biofilm reactor (SBBR). After 90 days’ operation, the average effluent NH4+-N removal efficiency and nitrite accumulation rate of PN-SBBR were high of 98.2% and 87.6%, respectively. Both polysaccharide and protein contents were reduced in loosely bound extracellular polymeric substances (LB-EPS) and tightly bound EPS (TB-EPS) during the achievement of PN-biofilm. Excitation-emission matrix spectra implied that aromatic protein-like, tryptophan protein-like and humic acid-like substances were the main compositions of both kinds of EPS in seed sludge and PN-biofilm. According to typical cycle, the emission rate of CO2had a much higher value than that of N2O, and their total amounts per cycle were 67.7 and 16.5 mg, respectively. Free ammonia (FA) played a significant role on the inhibition activity of nitrite-oxidizing bacteria and the occurrence of nitrite accumulation

Selenium nanoparticles as candidates for antibacterial substitutes and supplements against multidrug-resistant bacteria

In recent years, multidrug-resistant (MDR) bacteria have increased rapidly, representing a major threat to human health. This problem has created an urgent need to identify alternatives for the treatment of MDR bacteria. The aim of this study was to identify the antibacterial activity of selenium nanoparticles (SeNPs) and selenium nanowires (SeNWs) against MDR bacteria and assess the potential synergistic effects when combined with a conventional antibiotic (linezolid). SeNPs and SeNWs were characterized by transmission electron microscopy (TEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), zeta potential, and UV-visible analysis. The antibacterial effects of SeNPs and SeNWs were confirmed by the macro-dilution minimum inhibi-tory concentration (MIC) test. SeNPs showed MIC values against methicillin-sensitive S. aureus (MSSA), methicillin-resistant S. aureus (MRSA), vancomycin-resistant S. aureus (VRSA), and vanco-mycin-resistant enterococci (VRE) at concentrations of 20, 80, 320, and >320 μg/mL, respectively. On the other hand, SeNWs showed a MIC value of >320 μg/mL against all tested bacteria. Therefore, MSSA, MRSA, and VRSA were selected for the bacteria to be tested, and SeNPs were selected as the antimicrobial agent for the following experiments. In the time-kill assay, SeNPs at a concentration of 4X MIC (80 and 320 μg/mL) showed bactericidal effects against MSSA and MRSA, respectively. At a concentration of 2X MIC (40 and 160 μg/mL), SeNPs showed bacteriostatic effects against MSSA and bactericidal effects against MRSA, respectively. In the synergy test, SeNPs showed a synergistic effect with linezolid (LZD) through protein degradation against MSSA and MRSA. In conclusion, these results suggest that SeNPs can be candidates for antibacterial substitutes and supplements against MDR bacteria for topical use, such as dressings. However, for use in clinical situations, additional experiments such as toxicity and synergistic mechanism tests of SeNPs are needed

Cutting tool tracking and recognition based on infrared and visual imaging systems using principal component analysis (PCA) and discrete wavelet transform (DWT) combined with neural networks

The implementation of computerised condition monitoring systems for the detection cutting tools’ correct installation and fault diagnosis is of a high importance in modern manufacturing industries. The primary function of a condition monitoring system is to check the existence of the tool before starting any machining process and ensure its health during operation. The aim of this study is to assess the detection of the existence of the tool in the spindle and its health (i.e. normal or broken) using infrared and vision systems as a non-contact methodology. The application of Principal Component Analysis (PCA) and Discrete Wavelet Transform (DWT) combined with neural networks are investigated using both types of data in order to establish an effective and reliable novel software program for tool tracking and health recognition. Infrared and visual cameras are used to locate and track the cutting tool during the machining process using a suitable analysis and image processing algorithms. The capabilities of PCA and Discrete Wavelet Transform (DWT) combined with neural networks are investigated in recognising the tool’s condition by comparing the characteristics of the tool to those of known conditions in the training set. The experimental results have shown high performance when using the infrared data in comparison to visual images for the selected image and signal processing algorithms