Testing by Dualization

Software engineering requires rigorous testing to guarantee the product's quality. Semantic testing of functional correctness is challenged by nondeterminism in behavior, which makes testers difficult to write and reason about. This thesis presents a language-based technique for testing interactive systems. I propose a theory for specifying and validating nondeterministic behaviors, with guaranteed soundness and correctness. I then apply the theory to testing practices, and show how to derive specifications into interactive tester programs. I also introduce a language design for producing test inputs that can effectively detect and reproduce invalid behaviors. I evaluate the methodology by specifying and testing real-world systems such as web servers and file synchronizers, demonstrating the derived testers' ability to find disagreements between the specification and the implementation

Testing By Dualization

Software engineering requires rigorous testing to guarantee the product\u27s quality. Semantic testing of functional correctness is challenged by nondeterminism in behavior, which makes testers difficult to write and reason about. This thesis presents a language-based technique for testing interactive systems. I propose a theory for specifying and validating nondeterministic behaviors, with guaranteed soundness and correctness. I then apply the theory to testing practices, and show how to derive specifications into interactive tester programs. I also introduce a language design for producing test inputs that can effectively detect and reproduce invalid behaviors. I evaluate the methodology by specifying and testing real-world systems such as web servers and file synchronizers, demonstrating the derived testers\u27 ability to find disagreements between the specification and the implementation

A deep learning model for network intrusion detection with imbalanced data

With an increase in the number and types of network attacks, traditional firewalls and data encryption methods can no longer meet the needs of current network security. As a result, intrusion detection systems have been proposed to deal with network threats. The current mainstream intrusion detection algorithms are aided with machine learning but have problems of low detection rates and the need for extensive feature engineering. To address the issue of low detection accuracy, this paper proposes a model for traffic anomaly detection named a deep learning model for network intrusion detection (DLNID), which combines an attention mechanism and the bidirectional long short-term memory (Bi-LSTM) network, first extracting sequence features of data traffic through a convolutional neural network (CNN) network, then reassigning the weights of each channel through the attention mechanism, and finally using Bi-LSTM to learn the network of sequence features. In intrusion detection public data sets, there are serious imbalance data generally. To address data imbalance issues, this paper employs the method of adaptive synthetic sampling (ADASYN) for sample expansion of minority class samples, to eventually form a relatively symmetric dataset, and uses a modified stacked autoencoder for data dimensionality reduction with the objective of enhancing information fusion. DLNID is an end-to-end model, so it does not need to undergo the process of manual feature extraction. After being tested on the public benchmark dataset on network intrusion detection NSL-KDD, experimental results show that the accuracy and F1 score of this model are better than those of other comparison methods, reaching 90.73% and 89.65%, respectively

The oyster genome reveals stress adaptation and complexity of shell formation

The Pacific oyster Crassostrea gigas belongs to one of the most species-rich but genomically poorly explored phyla, the Mollusca. Here we report the sequencing and assembly of the oyster genome using short reads and a fosmid-pooling strategy, along with transcriptomes of development and stress response and the proteome of the shell. The oyster genome is highly polymorphic and rich in repetitive sequences, with some transposable elements still actively shaping variation. Transcriptome studies reveal an extensive set of genes responding to environmental stress. The expansion of genes coding for heat shock protein 70 and inhibitors of apoptosis is probably central to the oyster's adaptation to sessile life in the highly stressful intertidal zone. Our analyses also show that shell formation in molluscs is more complex than currently understood and involves extensive participation of cells and their exosomes. The oyster genome sequence fills a void in our understanding of the Lophotrochozoa. © 2012 Macmillan Publishers Limited. All rights reserved

Testing by Dualization

Software engineering requires rigorous testing to guarantee the product\u27s quality. Semantic testing of functional correctness is challenged by nondeterminism in behavior, which makes testers difficult to write and reason about. This thesis presents a language-based technique for testing interactive systems. I propose a theory for specifying and validating nondeterministic behaviors, with guaranteed soundness and correctness. I then apply the theory to testing practices, and show how to derive specifications into interactive tester programs. I also introduce a language design for producing test inputs that can effectively detect and reproduce invalid behaviors. I evaluate the methodology by specifying and testing real-world systems such as web servers and file synchronizers, demonstrating the derived testers\u27 ability to find disagreements between the specification and the implementation

An Organizational Structure and Self-Adaptive Mechanism for Holonic Multi-Agent Systems

A holonic multi-agent system combines the concept of a holon with a multi-agent system; this combination has been proven to be an effective way to build a complex system. Great progress has been made in this area, but previous studies are fragmented and lack of a task-based perspective to model different systems in the real world. Therefore, this article proposes a formalistic model for HMAS from a task-based perspective. Not only the static organizational structure is designed, but also the dynamic running mechanism, including the self-adaptive mechanism and the task assignment mechanism based on the proposed holonic structure, are also discussed. Finally, a case study is provided to verify the self-adaptive mechanism. The experimental results show that our proposed DHMAS has the ability to adapt to the changing environment, and performs better in terms of the success rate and the response time when the system is heavily loaded

Multi-Feature Extension via Semi-Autoencoder for Personalized Recommendation

Over the past few years, personalized recommendation systems aim to address the problem of information overload to help users achieve useful information and make quick decisions. Recently, due to the benefits of effective representation learning and no labeled data requirements, autoencoder-based models have commonly been used in recommendation systems. Nonetheless, auxiliary information that can effectively enlarge the feature space is always scarce. Moreover, most existing methods ignore the hidden relations between extended features, which significantly affects the recommendation accuracy. To handle these problems, we propose a Multi-Feature extension method via a Semi-AutoEncoder for personalized recommendation (MFSAE). First, we extract auxiliary information from DBpedia as feature extensions of items. Second, we leverage the LSI model to learn hidden relations on top of item features and embed them into low-dimensional feature vectors. Finally, the resulting feature vectors, combined with the original rating matrix and side information, are fed into a semi-autoencoder for recommendation prediction. We ran comprehensive experiments on the MovieLens datasets. The results demonstrate the effectiveness of MFSAE compared to state-of-the-art methods

Fungicidal Activity of AP10W, a Short Peptide Derived from AP-2 Complex Subunit mu-A, In Vitro and In Vivo

With the increase in the incidence of fungal infections, and the restrictions of existing antifungal drugs, the development of novel antifungal agents is urgent. Here we prove that AP10W, a short peptide derived from AP-2 complex subunit mu-A, displays conspicuous antifungal activities against the main fungal pathogens of human infections Candida albicans and Aspergillus fumigatus. We also show that AP10W suppresses the fungal biofilm formation, and reduces the pre-established fungal biofilms. AP10W appears to exert its fungicidal activity through a mode of combined actions, including interaction with the fungal cell walls via laminarin, mannan and chitin, enhancement of cell wall permeabilization, induction of membrane depolarization, and increase in intracellular ROS generation. Importantly, we demonstrate that AP10W exhibits little toxicity towards mammalian fibroblasts, and effectively promotes the healing of wounded skins infected by C. albicans. These together indicate that AP10W is a new member of fungicidal agents. It also suggests that AP10W has a considerable potential for future development as a novel antifungal drug

Stability mechanisms of soft rock mining roadways through roof cutting and pressure relief: an exploratory model experiment

IntroductionSoft rock mining roadways are severely deformed and damaged during coal mining. Blindly increasing the support strength not only has little effect but also wastes material resources.MethodsMaintaining the original support parameters, model experiments were conducted to investigate the mechanism of pressure relief protection of the front soft rock mining roadway by cutting the roof behind the longwall face. The roof-cutting height was 2.5 times the coal thickness, the angle was 10°, and the advance distance is 0. ResultsThe study found that the abutment stress borne by the roof of the original roadway was transferred to the coal seams to be mined. The average stress of the coal seams increased by 10%, while the average stress of the surrounding rock in the front roadway decreased by 12.57%. The roof cutting weakened the influence of the overlying strata in the gob on the rear roadway. The stability of the rear roadway also weakened the traction effect on the front roadway. The vertical convergence of the front roadway decreased by 27.3%, and the deformation of the coal pillars decreased by 15.7%.DiscussionThe roof cutting reduced the stress of the front roadway to the peak failure stress, fundamentally weakening the main factor that induced the deformation of the front roadway. Numerical simulations were performed to research the deformation and stress distribution properties of the surrounding rock after roof cutting, and the model experimental results were validated. Finally, engineering recommendations are presented, which are expected to provide a reference for controlling the roadway stability of soft rock masses

Retrofitting Sea Cucumber Nursery Tanks to Recirculating Aquaculture Systems for Highly Intensive Litopenaeus vannamei Aquaculture

Designing good recirculating aquaculture systems (RASs) is challenging in shrimp aquaculture. In this study, two sets of RASs were constructed using sea cucumber nursery tanks for rearing Litopenaeus vannamei. Recirculating aquaculture was supported by key technologies such as sewage collection and aeration systems adapted to the rectangular tanks and technologies for the removal of sewage, shrimp shells, and dead individuals. Six-hundred and eighty-five thousand juveniles were selected for rearing in the newly constructed RASs, where the average stocking density was 1013 shrimp/m3. During the recirculating aquaculture period of 53 days, the water temperature of the tanks was 24–31 °C, the salinity was 25–32‰, the pH was 6.4–8.2, the DO was ≥ 4.9 mg/L, the concentration of total ammonia nitrogen (TAN) was maintained between 0.17 and 4.9 mg/L, the concentration of nitrite nitrogen (NO2-N) was between 0.12 and 4.7 mg/L, and the total number of Vibrio bacteria remained between 330 and 9700 cfu/mL. At the end of the experiment, the final average weight of individual shrimp was 13.43 g, and the average yield reached 12.92 kg/m3. The great improvement in growth performance marks a breakthrough in RAS technology of shrimp, and it supports the use of an innovative methodology for the retrofitting and utilization of idle sea cucumber nursery tanks