Towards Rewriting Semantics of Software Architecture Specification

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A recombinant Fasciola gigantica 14-3-3 epsilon protein (rFg14-3-3e) modulates various functions of goat peripheral blood mononuclear cells

Background The molecular structure of Fasciola gigantica 14-3-3 protein has been characterized. However, the involvement of this protein in parasite pathogenesis remains elusive and its effect on the functions of innate immune cells is unknown. We report on the cloning and expression of a recombinant F. gigantica 14-3-3 epsilon protein (rFg14-3-3e), and testing its effects on specific functions of goat peripheral blood mononuclear cells (PBMCs). Methods rFg14-3-3e protein was expressed in Pichia pastoris. Western blot and immunofluorescence assay (IFA) were used to examine the reactivity of rFg14-3-3e protein to anti-F. gigantica and anti-rFg14-3-3e antibodies, respectively. Various assays were used to investigate the stimulatory effects of the purified rFg14-3-3e protein on specific functions of goat PBMCs, including cytokine secretion, proliferation, migration, nitric oxide (NO) production, phagocytosis, and apoptotic capabilities. Potential protein interactors of rFg14-3-3e were identified by querying the databases Intact, String, BioPlex and BioGrid. A Total Energy analysis of each of the identified interaction was performed. Gene Ontology (GO) enrichment analysis was conducted using Funcassociate 3.0. Results Sequence analysis revealed that rFg14-3-3e protein had 100% identity to 14-3-3 protein from Fasciola hepatica. Western blot analysis showed that rFg14-3-3e protein is recognized by sera from goats experimentally infected with F. gigantica and immunofluorescence staining using rat anti-rFg14-3-3e antibodies demonstrated the specific binding of rFg14-3-3e protein to the surface of goat PBMCs. rFg14-3-3e protein stimulated goat PBMCs to produce interleukin-10 (IL-10) and transforming growth factor beta (TGF-β), corresponding with low levels of IL-4 and interferon gamma (IFN-γ). Also, this recombinant protein promoted the release of NO and cell apoptosis, and inhibited the proliferation and migration of goat PBMCs and suppressed monocyte phagocytosis. Homology modelling revealed 65% identity between rFg14-3-3e and human 14-3-3 protein YWHAE. GO enrichment analysis of the interacting proteins identified terms related to apoptosis, protein binding, locomotion, hippo signalling and leukocyte and lymphocyte differentiation, supporting the experimental findings. Conclusions Our data suggest that rFg14-3-3e protein can influence various cellular and immunological functions of goat PBMCs in vitro and may be involved in mediating F. gigantica pathogenesis. Because of its involvement in F. gigantica recognition by innate immune cells, rFg14-3-3e protein may have applications for development of diagnostics and therapeutic interventions

An integrated framework for ensuring the quality of software design

Software development is an extremely complex process, during which human errors are introduced and result in faulty software systems. It is highly desirable and important that these errors can be prevented and detected as early as possible. Software architecture design is a high-level system description, which embodies many system features and properties that are eventually implemented in the final operational system. Therefore, methods for modeling and analyzing software architecture descriptions can help prevent and reveal human errors and thus improve software quality. Furthermore, if an analyzed software architecture description can be used to derive a partial software implementation, especially when the derivation can be automated, significant benefits can be gained with regard to both the system quality and productivity. This dissertation proposes a framework for an integrated analysis on both of the design and implementation. To ensure the desirable properties of the architecture model, we apply formal verification by using the model checking technique. To ensure the desirable properties of the implementation, we develop a methodology and the associated tool to translate an architecture specification into an implementation written in the combination of Arch-Java/Java/AspectJ programming languages. The translation is semi-automatic so that many manual programming errors can be prevented. Furthermore, the translation inserting monitoring code into the implementation such that runtime verification can be performed, this provides additional assurance for the quality of the implementation. Moreover, validations for the translations from architecture model to program are provided. Finally, several case studies are experimented and presented

Progress of Single-Crystal Nickel-Cobalt-Manganese Cathode Research

The booming electric vehicle industry continues to place higher requirements on power batteries related to economic-cost, power density and safety. The positive electrode materials play an important role in the energy storage performance of the battery. The nickel-rich NCM (LiNixCoyMnzO2 with x + y + z = 1) materials have received increasing attention due to their high energy density, which can satisfy the demand of commercial-grade power batteries. Prominently, single-crystal nickel-rich electrodes with s unique micron-scale single-crystal structure possess excellent electrochemical and mechanical performance, even when tested at high rates, high cut-off voltages and high temperatures. In this review, we outline in brief the characteristics, problems faced and countermeasures of nickel-rich NCM materials. Then the distinguishing features and main synthesis methods of single-crystal nickel-rich NCM materials are summarized. Some existing issues and modification methods are also discussed in detail, especially the optimization strategies under harsh conditions. Finally, an outlook on the future development of single-crystal nickel-rich materials is provided. This work is expected to provide some reference for research on single-crystal nickel-rich ternary materials with high energy density, high safety levels, long-life, and their contribution to sustainable development

A Novel Hybrid LMD–ETS–TCN Approach for Predicting Landslide Displacement Based on GPS Time Series Analysis

Landslide disasters cause serious property losses and casualties every year. Landslide displacement prediction is fundamental for mitigating landslide disasters. Several approaches have been used to predict landslide displacement, yet a more accurate and reliable displacement prediction still has a poor understanding of landslide early warning systems for landslide mitigation, due to limited data and mutational displacements. To boost the robustness and accuracy of landslide displacement prediction, this paper assembled a new hybrid model containing the local mean decomposition (LMD), innovations state space models for exponential smoothing (ETS), and the temporal convolutional network (TCN). The proposed model, which is based on over 10 years of long-term time series monitoring GPS data, was tested on the selected case—stepwise Baijiabao landslide in the Three Gorges Reservoir area of China (TGRA) was tested by the proposed model. The results presented that the LMD–ETS–TCN model has the best performance in comparison with other benchmark models. Compared with autoregressive integrated moving average (ARIMA), support vector regression (SVR), and long short-term memory neural network (LSTM), the accuracy was noticeably improved by an average of 40.9%, 46.2%, and 22.1%, respectively. The robustness and effectiveness of the presented approach are attested, and it has discernible improvements for landslide displacement prediction

Rhizosphere microorganisms can influence the timing of plant flowering

Background:Plant phenology has crucial biological, physical, and chemical effects on the biosphere. Phenological drivers have largely been studied, but the role of plant microbiota, particularly rhizosphere microbiota, has not been considered. - Results: We discovered that rhizosphere microbial communities could modulate the timing of flowering of Arabidopsis thaliana. Rhizosphere microorganisms that increased and prolonged N bioavailability by nitrification delayed flowering by converting tryptophan to the phytohormone indole acetic acid (IAA), thus downregulating genes that trigger flowering, and stimulating further plant growth. The addition of IAA to hydroponic cultures confirmed this metabolic network. - Conclusions: We document a novel metabolic network in which soil microbiota influenced plant flowering time, thus shedding light on the key role of soil microbiota on plant functioning. This opens up multiple opportunities for application, from helping to mitigate some of the effects of climate change and environmental stress on plants (e.g. abnormal temperature variation, drought, salinity) to manipulating plant characteristics using microbial inocula to increase crop potential