Identification of seed coat sculptures using deep learning

Seed coat sculptures, including anticlinal and periclinal walls, are of great taxonomic importance. In this study, we identified seed coat patterns of Allium seeds using five deep learning methods namely, CNN, AlexNet, GoogleNet, ResNet50, and VGG16 for the first time. Selected images of seed coat patterns from over 100 Allium species reported in previously published literature and data from our samples were classified into seven types of anticlinal (irregular curved, irregular curved to nearly straight, straight, S, U, UO, and omega) and five types of periclinal walls (granule, small verruca, large verruca, marginal verruca, and verrucate verruca). The results revealed that GoogleNet and VGG16 achieved the highest classification accuracy of 90.4% for the anticlinal wall, and VGG16 achieved the highest classification accuracy of 98.1% for the periclinal wall. Moreover, more than three, four, and five methods were combined, and their performance was investigated. Combining more than three methods was the most advantageous. The models achieved a suitable anticlinal wall classification using GoogleNet and periclinal wall classification using VGG16. In conclusion, using the machine-based method, we studied the seed coat of species of Allium on our own samples to see if the results of the machine-based method match with the human-based classification

Enabling Role-Based Orchestration for Cloud Applications

With the rapidly growing popularity of cloud services, the cloud computing faces critical challenges to orchestrate the deployment and operation of cloud applications on heterogenous cloud platforms. Cloud applications are built on a platform model that abstracts away underlying platform-specific details, so that their orchestration can benefit from the abstract view and flexibility of the underlying platform configuration. However, considerable efforts are still required to properly manage complicated cloud applications. This paper proposes a model-driven approach to cloud application orchestration which promotes the concerns of distinct roles for cloud system provisioning and operation. By establishing a set of capabilities as modeling constructs, our approach allows TOSCA-based application topology itself and its orchestration needs to be specified in a way to provide a more targeted support for different needs and concerns of application developers and operators. With novel orchestration features like application topology description, platform capability modeling, and role-awareness for cloud application orchestration, it can significantly reduce the complexity of application orchestration in diverse cloud environments. To show the feasibility and effectiveness of our proposal for cloud application orchestration, we present a proof-of-concept orchestration system implementation and evaluate its deployment and orchestration results in a Kubernetes cluster

Computational screening of potential non-immunoglobulin scaffolds using overlapped conserved residues (OCR)-based fingerprints

Cystatins and lipocalins have attracted considerable interest for their potential applications in non-immunoglobulin protein scaffold engineering. In the present study, their potential homologs were screened computationally from non-redundant protein sequence database based on the overlapped conserved residues (OCR)-fingerprints, which can detect the protein family with low sequence identity, such as cystatins and lipocalins. Two types of OCR-fingerprints for each family were designed and showed very high detection efficiency (>90%). The protein sequence database was scanned by the fingerprints, which yielded the hypothetical sequences for cystatins and lipocalins. The hypothetical sequences were validated further based on their sequence motifs and structural models, which allowed an identification of the potential homologs of cystatins and lipocalins

Electronically Double-Layered Metal Boride Hollow Nanoprism as an Excellent and Robust Water Oxidation Electrocatalysts

Metal-metalloid compounds have been paid much attention as new high-performance water oxidation catalysts due to their exceptional durability for water oxidation in alkaline media originating from the multi-dimensional covalent bonding of the metalloid with the surrounding metal atoms. However, compared to the excellent stability, a relatively low catalytic activity of metal-metalloids often limits their practical application as high-performance water oxidation catalysts. Here, for the first time, disclosed is a novel self-templating strategy combined with atomic layer deposition (ALD) to design the electrochemically active and stable quaternary metal boride (vanadium-doped cobalt nickel boride, VCNB), hollow nanoprism by inducing electronic double layers on the surface. The incorporation of V in a double-layered structure can substantially increase the number of surface active sites with unsaturated electronic structure. Furthermore, the induced electronic double layers of V can effectively protect the dissolution of the surface active sites. In addition, density functional theory (DFT) calculations reveal that the impressive water oxidation properties of VCNB originate from the synergetic physicochemical effects of the different metal elements, Co and B as active sites, Ni as a surface electronic structure modifier, and V as a charge carrier transporter and supplier

Room-Temperature Cell Disruption and Astaxanthin Recovery from <i>Haematococcus lacustris</i> Cysts Using Ultrathin α-Quartz Nanoplates and Ionic Liquids

Ionic liquids (ILs) are new green solvents, which are widely used in lignocellulosic and microalgal biorefineries. However, high-temperature operating conditions limit their application in the extraction of heat-labile algal products, such as bioactive astaxanthin. In this study, we report the technical feasibility of room-temperature astaxanthin extraction from Haematococcus lacustris cysts with a thick and complex cell wall structure, by combining ultrathin α-quartz nanoplates (NPLs) with ethyl-3-methylimidazolium ([Emim])-based ILs. When four different [Emim]-based ILs with thiocyanate (SCN), diethylphosphate (DEP), HSO4, and Cl anions were applied to 90-day-old H. lacustris cysts at room temperature (~28 °C), the astaxanthin extraction efficiency was as low as 9.6–14.2%. Under sonication, α-quartz NPLs disrupted the cyst cell wall for a short duration (5 min). The astaxanthin extraction efficacies of a subsequent IL treatment improved significantly to 49.8% for [Emim] SCN, 60.0% for [Emim] DEP, 80.7% for [Emim] HSO4, and 74.3% for [Emim] Cl ions, which were 4.4, 6.1, 8.4, and 5.2 times higher than the extraction efficacy of only ILs, respectively. This finding suggests that α-quartz NPLs can serve as powerful cell-wall-disrupting agents for the room-temperature IL-mediated extraction of astaxanthin from robust algal cyst cells

Optimized End Functionality of Silane-Terminated Liquid Butadiene Rubber for Silica-Filled Rubber Compounds

As the world is shifting from internal combustion engine vehicles to electric vehicles in response to environmental pollution, the tire industry has been conducting research on tire performance to meet the requirements of electric vehicles. In this experiment, functionalized liquid butadiene rubber (F-LqBR) with triethoxysilyl groups at both ends was introduced into a silica-filled rubber compound as a substitute for treated distillate aromatic extract (TDAE) oil, and comparative evaluation was conducted according to the number of triethoxysilyl groups. The results showed that F-LqBRs improved silica dispersion in the rubber matrix through the formation of chemical bonds between silanol groups and the base rubber, and reduced rolling resistance by limiting chain end mobility and improving filler–rubber interaction. However, when the number of triethoxysilyl groups in F-LqBR was increased from two to four, self-condensation increased, the reactivity of the silanol groups decreased, and the improvement of properties was reduced. As a result, the optimized end functionality of triethoxysilyl groups for F-LqBR in silica-filled rubber compound was two. The 2-Azo-LqBR with the optimized functionality showed an improvement of 10% in rolling resistance, 16% in snow traction, and 17% in abrasion resistance when 10 phr of TDAE oil was substituted