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Dipeptidyl peptidases constitute a class of non-classical serine proteases that regulate an array of biological functions, making them pharmacologically attractive enzymes. With this work, we identified and characterized a dipeptidyl peptidase from Mycobacterium tuberculosis (MtDPP) displaying a strong preference for proline residues at the P1 substrate position and an unexpectedly high thermal stability. MtDPP was also characterized with alanine replacements of residues of its active site that yielded, for the most part, loss of catalysis. We show that MtDPP catalytic activity is inhibited by well-known human DPP4 inhibitors. Using MALDI-TOF mass spectrometry we also describe that in vitro, MtDPP mediates the truncation of the C-X-C motif chemokine ligand 10, indicating a plausible role in immune modulation for this mycobacterial enzyme.

Benefiting from maneuverability, flexibility, and low-cost deployment, aerial base stations (ABSs) have emerged as a promising solution to meet the coverage demand when terrestrial BSs are overloaded and unavailable. Nevertheless, the high mobility of ABSs and the complicated interference incurred by the addition of ABSs inevitably cause the spatial-temporal discontinuity in air-to-ground (A2G) coverage, which renders the network unable to provide users with on-demand coverage. On this account, this article discusses how to enhance the A2G coverage by exploiting the ever more enhanced computation capability of network edge nodes. In particular, we propose a coverage-oriented computing control architecture for adaptive coverage structure generation and resource orchestration based on the designed optimal deployment scheme for ABSs. This architecture can flexibly adjust the coverage structure and available resources to ensure the spatial continuity in A2G coverage. Furthermore, we design an efficient aerial-computing-based resource management scheme for ABSs to enable temporal continuity in A2G coverage by exploiting artificial intelligence approaches.

As the key running part of the railway freight transportation system, the wheel not only bears the load of the vehicle, but also ensures the running and steering of the car body on the rails. The frequent high-speed friction with the rail and brake is the main reason for early failure of wheelset tread. Therefore, real-time status monitoring and early fault diagnosis of wheel treads have become key technical issues that must be solved in the reform of the railway freight maintenance system. In this paper, an adaptive hybrid Simulated Annealing Cuckoo Search algorithm (SA-ACS) is proposed and applied to the Deep Belief Network (DBN). The SA-ACS-DBN algorithm is used to improve the training speed and convergence accuracy of the diagnosis model. Finally, it is found through the comparison experiment of wheel tread fault data that the data results prove the feasibility of the SA-ACS-DBN model in the application of wheelset fault diagnosis.

Dipeptidyl peptidases constitute a class of non-classical serine proteases that regulate an array of biological functions, making them pharmacologically attractive enzymes. With this work, we identified and characterized a dipeptidyl peptidase from Mycobacterium tuberculosis (MtDPP) displaying a strong preference for proline residues at the P1 substrate position and an unexpectedly high thermal stability. MtDPP was also characterized with alanine replacements of residues of its active site that yielded, for the most part, loss of catalysis. We show that MtDPP catalytic activity is inhibited by well-known human DPP4 inhibitors. Using MALDI-TOF mass spectrometry we also describe that in vitro, MtDPP mediates the truncation of the C-X-C motif chemokine ligand 10, indicating a plausible role in immune modulation for this mycobacterial enzyme.

A novel, waterborne polydimethylsiloxane (PDMS)-modified polyurethane-acrylic (Si-PUA)/pigment hybrid emulsion was synthesized by one-step miniemulsion polymerization for the pigment printing of polyester fabric. The phase structure, hydrophobicity, and thermal and mechanical properties of the formed films with different PDMS contents from the hybrid emulsion were investigated. The results indicated that the pigment particles were uniformly distributed in the homogeneous phase polymer substrate without phase separation occurring between the PDMS phase and polyurethane-acrylic. The hydrophobicity and toughness of the Si-PUA/pigment hybrid latex films gradually increased with the increase of PDMS content. Moreover, the obtained hybrid emulsion was used as a self-curable hybrid pigment that was applied to polyethylene terephthalate fabric for pigment printing. This showed that the Si-PUA/pigment hybrid latex particles yielded similarly good values in terms of color strength, and dry- and wet-rubbing fastness to the PDMS-free hybrid latex particles. Furthermore, use of the Si-PUA/pigment hybrid latex avoided certain problems related to printed fabric, such as poor air permeability and softness.

Exploiting the time-varying feature of wireless channels, retransmission could enable reliable data transmission. However, the growing deployment of small cell base stations (BSs) would induce significant temporal interference correlation. In consequence, once the current transmission fails, the subsequent ones are likely to fail as well. In this light, we investigate the retransmission performance in dense networks with temporally correlated interference in terms of network spatial throughput (ST). Our results reveal that the impact of temporal interference correlation on the retransmission performance critically depends on the BS density. Specifically, temporal interference correlation would cause a greater network ST attenuation when the BS density is closer to the critical density, under which network ST is maximized. Moreover, the impact of temporal interference correlation is shown to be cumulative as the number of retransmission attempts increases. Furthermore, towards efficient retransmission, we adopt and optimize a P-Activation strategy (PAS). It is shown that the optimized PAS is able to effectively mitigate the overwhelming strength and temporal correlation of interference. As a result, the retransmission performance in improving network ST is significantly enhanced in dense networks, while the variation of network ST with BS density exhibits sigmoid trend instead of the previous near-bell shape.

Background and Aims High-throughput phenotyping is a limitation in plant genetics and breeding due to large-scale experiments in the field. Unmanned aerial vehicles (UAVs) can help to extract plant phenotypic traits rapidly and non-destructively with high efficiency. The general aim of this study is to estimate the dynamic plant height and leaf area index (LAI) by nadir and oblique photography with a UAV, and to compare the integrity of the established three-dimensional (3-D) canopy by these two methods. Methods Images were captured by a high-resolution digital RGB camera mounted on a UAV at five stages with nadir and oblique photography, and processed by Agisoft Metashape to generate point clouds, orthomosaic maps and digital surface models. Individual plots were segmented according to their positions in the experimental design layout. The plant height of each inbred line was calculated automatically by a reference ground method. The LAI was calculated by the 3-D voxel method. The reconstructed canopy was sliced into different layers to compare leaf area density obtained from oblique and nadir photography. Key Results Good agreements were found for plant height between nadir photography, oblique photography and manual measurement during the whole growing season. The estimated LAI by oblique photography correlated better with measured LAI (slope = 0.87, R2 = 0.67), compared with that of nadir photography (slope = 0.74, R2 = 0.56). The total number of point clouds obtained by oblique photography was about 2.7–3.1 times than those by nadir photography. Leaf area density calculated by nadir photography was much less than that obtained by oblique photography, especially near the plant base. Conclusions Plant height and LAI can be extracted automatically and efficiently by both photography methods. Oblique photography can provide intensive point clouds and relatively complete canopy information at low cost. The reconstructed 3-D profile of the plant canopy can be easily recognized by oblique photography.

Background and Aims Light interception is closely related to canopy architecture. Few studies based on multi-view photography have been conducted in a field environment, particularly studies that link 3-D plant architecture with a radiation model to quantify the dynamic canopy light interception. In this study, we combined realistic 3-D plant architecture with a radiation model to quantify and evaluate the effect of differences in planting patterns and row orientations on canopy light interception. Methods The 3-D architectures of maize and soybean plants were reconstructed for sole crops and intercrops based on multi-view images obtained at five growth dates in the field. We evaluated the accuracy of the calculated leaf length, maximum leaf width, plant height and leaf area according to the measured data. The light distribution within the 3-D plant canopy was calculated with a 3-D radiation model. Finally, we evaluated canopy light interception in different row orientations. Key Results There was good agreement between the measured and calculated phenotypic traits, with an R2 >0.97. The light distribution was more uniform for intercropped maize and more concentrated for sole maize. At the maize silking stage, 85 % of radiation was intercepted by approx. 55 % of the upper canopy region for maize and by approx. 33 % of the upper canopy region for soybean. There was no significant difference in daily light interception between the different row orientations for the entire intercropping and sole systems. However, for intercropped maize, near east–west orientations showed approx. 19 % higher daily light interception than near south–north orientations. For intercropped soybean, daily light interception showed the opposite trend. It was approx. 49 % higher for near south–north orientations than for near east–west orientations. Conclusions The accurate reconstruction of 3-D plants grown in the field based on multi-view images provides the possibility for high-throughput 3-D phenotyping in the field and allows a better understanding of the relationship between canopy architecture and the light environment.

Crop traits such as aboveground biomass (AGB), total leaf area (TLA), leaf chlorophyll content (LCC), and thousand kernel weight (TWK) are important indices in maize breeding. How to extract multiple crop traits at the same time is helpful to improve the efficiency of breeding. Compared with digital and multispectral images, the advantages of high spatial and spectral resolution of hyperspectral images derived from unmanned aerial vehicle (UAV) are expected to accurately estimate the similar traits among breeding materials. This study is aimed at exploring the feasibility of estimating AGB, TLA, SPAD value, and TWK using UAV hyperspectral images and at determining the optimal models for facilitating the process of selecting advanced varieties. The successive projection algorithm (SPA) and competitive adaptive reweighted sampling (CARS) were used to screen sensitive bands for the maize traits. Partial least squares (PLS) and random forest (RF) algorithms were used to estimate the maize traits. The results can be summarized as follows: The sensitive bands for various traits were mainly concentrated in the near-red and red-edge regions. The sensitive bands screened by CARS were more abundant than those screened by SPA. For AGB, TLA, and SPAD value, the optimal combination was the CARS-PLS method. Regarding the TWK, the optimal combination was the CARS-RF method. Compared with the model built by RF, the model built by PLS was more stable. This study provides guiding significance and practical value for main trait estimation of maize inbred lines by UAV hyperspectral images at the plot level.

By using organic pigment-based ink-jet inks, the digital ink-jet printing of textiles is one kind of environmentally friendly technology for cleaner dyeing. Due to the shortcomings of easy agglomeration and poor water dispersion stability of organic nanoparticles, however, the encapsulation and dispersion of organic pigment nanoparticles are also hot and difficult research problems. In this work, we report the reversible addition-fragmentation chain transfer (RAFT) polymerization technology was used to synthesize random copolymer of 2-(dimethylamino) ethyl methacrylate (DMAEMA), poly(ethylene glycol) methyl ether methacrylate (PEGA), and methyl methacrylate (MMA) or butyl acrylate (BA) with a trithiocarbonate reactive end-group. These cationic macromolecular RAFT agents (macro-RAFT) with a pH of 5 were subsequently adsorbed at the surface of size-monodisperse colloidal Pigment Red 170 particles. The absorbed macro-RAFT agents were considered to be the living points to mediate the RAFT polymerization of monomers (MMA and BA) by starved feed emulsion polymerization. TEM results shown that the resulting hybrid latexes synthesized in presence of the tri-copolymer macro-RAFT agents resulted in the formation of individually encapsulated pigment particles. In addition, the dynamic light scattering (DLS), zeta potential and stability tests found that the macro-RAFT agent participated in the growing latex stabilization which is the key to obtaining the stable and uniform core-shell hybrid latex. More importantly, the preparation of film-forming copolymer/pigment hybrid latex in this study shown that the high potential of the P(DMAEMA-co-PEGA-co-MMA or BA) macro-RAFT agent for the development of polymer-pigment hybrid latexes which has good application properties.

In recent years, the application of laser cladded composite coatings remains a challenge due to the uneven distribution of residual stress and the formation of cracks resulting from high cooling rates and thermal gradient. Hence, we report on the elimination of cracks and softening in-situ composite coatings by doping 4.0 wt% of Rhenium(Re). The variation in transient temperature field, cladding geometry, microstructure, phase composition and tribological properties were also investigated with different laser energy input. Results indicated that B4C and Stellite-6 can significantly improve the microhardness of the TC4 substrate owing to the in-situ formation of hard phases (metallic carbides and borides), whereas accompanied with numerous cracks. More notably, the addition of Re can effectively inhibit the occurrence of cracks and soften the composite coatings, meanwhile excellent surface morphologies and wear resistance were obtained. The as-prepared composite coatings exhibit the highest microhardness with the value of 608.2HV0.2 and the minimum wear rate for 0.938 ∗ 10−7 mm2/N.

Interference serves as the most dominant factor that quantitatively and qualitatively impacts the performance of ultra-dense networks (UDN). Especially, since interference of different time slots basically comes from the same set of interfering base stations (BSs), the temporal interference correlation becomes more significant with the growing deployment of network infrastructures. In this light, we develop an analytical framework to investigate the impact of temporal interference correlation on UDN in terms of network spatial throughput (ST) in this work. In contrast to the available research, which indicates that the interference correlation is independent of BS density, we show that a growing BS density would exacerbate the influence of interference correlation on the performance of UDN. In particular, when the BS density is closer to the critical density, under which network ST could be maximized, the ST attenuation caused by temporally correlated interference is more significant. Moreover, the effect of temporal interference correlation on network ST is additive over time slots. For instance, a greater number of transmissions of hybrid automatic repeat request (HARQ) would result in a more significant effect of temporally correlated interference on network ST.