Hawkeye: Change-targeted Testing for Android Apps based on Deep Reinforcement Learning

Android Apps are frequently updated to keep up with changing user, hardware, and business demands. Ensuring the correctness of App updates through extensive testing is crucial to avoid potential bugs reaching the end user. Existing Android testing tools generate GUI events focussing on improving the test coverage of the entire App rather than prioritising updates and its impacted elements. Recent research has proposed change-focused testing but relies on random exploration to exercise the updates and impacted GUI elements that is ineffective and slow for large complex Apps with a huge input exploration space. We propose directed testing of App updates with Hawkeye that is able to prioritise executing GUI actions associated with code changes based on deep reinforcement learning from historical exploration data. Our empirical evaluation compares Hawkeye with state-of-the-art model-based and reinforcement learning-based testing tools FastBot2 and ARES using 10 popular open-source and 1 commercial App. We find that Hawkeye is able to generate GUI event sequences targeting changed functions more reliably than FastBot2 and ARES for the open source Apps and the large commercial App. Hawkeye achieves comparable performance on smaller open source Apps with a more tractable exploration space. The industrial deployment of Hawkeye in the development pipeline also shows that Hawkeye is ideal to perform smoke testing for merge requests of a complicated commercial App

The Composition, Diversity and Predictive Metabolic Profiles of Bacteria Associated With the Gut Digesta of Five Sea Urchins in Luhuitou Fringing Reef (Northern South China Sea)

Sea urchins strongly affect reef ecology, and the bacteria associated with their gut digesta have not been well studied in coral reefs. In the current study, we analyze the bacterial composition of five sea urchin species collected from Luhuitou fringing reef, namely Stomopneustes variolaris, Diadema setosum, Echinothrix calamaris, Diadema savignyi, and Tripneustes gratilla, using high-throughput 16S rRNA gene-based pyrosequencing. Propionigenium, Prolixibacter, and Photobacterium were found to be the dominant bacterial genera in all five species. Interestingly, four sea urchin species, including S. variolaris, D. setosum, E. calamaris, and D. savignyi, displayed a higher mean total abundance of the three bacterial genera (69.72 ± 6.49%) than T. gratilla (43.37 ± 13.47%). Diversity analysis indicated that the gut digesta of sea urchin T. gratilla displayed a higher bacterial α-diversity compared with the other four species. PCoA showed that the four groups representing D. setosum, D. savignyi, E. calamaris, and S. variolaris were overlapping, but distant from the group representing T. gratilla. Predictive metagenomics performed by PICRUSt revealed that the abundances of genes involved in amino acid metabolism and metabolism of terpenoid and polyketide were higher in T. gratilla, while those involved in carbohydrate metabolism were higher in the other four sea urchin species. Therefore, our results indicated that the composition, diversity and predictive metabolic profiles of bacteria associated with the gut digesta of T. gratilla were significantly different from those of the other four sea urchin species in Luhuitou fringing reef

Discriminative analysis of schizophrenia patients using graph convolutional networks: A combined multimodal MRI and connectomics analysis

IntroductionRecent studies in human brain connectomics with multimodal magnetic resonance imaging (MRI) data have widely reported abnormalities in brain structure, function and connectivity associated with schizophrenia (SZ). However, most previous discriminative studies of SZ patients were based on MRI features of brain regions, ignoring the complex relationships within brain networks.MethodsWe applied a graph convolutional network (GCN) to discriminating SZ patients using the features of brain region and connectivity derived from a combined multimodal MRI and connectomics analysis. Structural magnetic resonance imaging (sMRI) and resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 140 SZ patients and 205 normal controls. Eighteen types of brain graphs were constructed for each subject using 3 types of node features, 3 types of edge features, and 2 brain atlases. We investigated the performance of 18 brain graphs and used the TopK pooling layers to highlight salient brain regions (nodes in the graph).ResultsThe GCN model, which used functional connectivity as edge features and multimodal features (sMRI + fMRI) of brain regions as node features, obtained the highest average accuracy of 95.8%, and outperformed other existing classification studies in SZ patients. In the explainability analysis, we reported that the top 10 salient brain regions, predominantly distributed in the prefrontal and occipital cortices, were mainly involved in the systems of emotion and visual processing.DiscussionOur findings demonstrated that GCN with a combined multimodal MRI and connectomics analysis can effectively improve the classification of SZ at an individual level, indicating a promising direction for the diagnosis of SZ patients. The code is available at https://github.com/CXY-scut/GCN-SZ.git

Metagenomic insights into production of zero valent sulfur from dissimilatory sulfate reduction in a methanogenic bioreactor

Dissimilatory sulfate reduction mediated by sulfate-reducing microorganisms (SRMs) has a pivotal role in the sulfur cycle, from which the generation of zero valent sulfur (ZVS) represents a novel pathway. Molecular details in the sulfite reduction to sulfide are still in debate. Also, the community composition and metabolic potential in sulfate-to-ZVS microbial communities remain to be elucidated. In this study, we employed genome-centric metagenomics approach to investigate the major players in a sulfate-to-ZVS bioreactor (ZVS-SR). Totally 51 metagenome assembled genomes (MAGs) were retrieved from the ZVS-SR microbiome, most belonging to phyla Proteobacteria, Actinobacteria, Bacteroides and Chloroflexi. Major players possibly responsible for ZVS generation included Desulfobacter, Desulfococcus, Desulfobacula and Desulfobacterales. A Desulfobacterales bacterium (SRB-bin23) was selected for subsequent detailed characterization of genome-encoded metabolic pathways and key functional genes involved in ZVS generation. This study expands our knowledge on the dissimilatory sulfate reduction in SRMs and may have important environmental implications

Endobronchial Ultrasound-guided Transbronchial Needle Aspiration in the Diagnosis of Intrathoracic Metastasis from Extrapulmonary Malignancy

Background and objective Endobronchial ultrasound guided transbronchial needle aspiration (EBUS-TBNA) has been widely applied in diagnosing mediastinal and hilar adenopathy. This study is further to evaluate value and safety of EBUS-TBNA in diagnosing intrathoracic metastasis from extrapulmonary malignancy. Methods Prospectively analysis of 41 patients suspected intrathoracic metastasis from previous diagnosed/concurrent extrapulmonary malignancies in Shanghai Chest Hospital, with radiologic findings showing mediastinal/hilar lymph node enlargement or intrapulmonary lesion requiring EBUS-TBNA examination for pathological diagnosis. Results 41 candidate patients enrolled, and 67 mediastinal/hilar lymph nodes and 5 intrapulmonary lesions were aspirated. 14 intrathoracic metastasis, 10 primary lung cancer, 9 reactive lymphadenitis, 4 sarcoid-like reactions, and 1 tuberculosis was diagnosed by EBUS-TBNA. Sensitivity and accuracy of EBUS-TBNA in diagnosing intrathoracic metastasis was 87.50% and 95.12%, respectively. Immunohistochemistry (IHC) was performed in 18 malignant tumors to obtain definite type or origin, twelve intrathoracic metastasis and 6 primary lung cancer were further confirmed. Conclusion EBUS-TBNA is a safe, effective method for the diagnosis of intrathoracic metastasis from extrapulmonary malignancy. IHC can provide additional evidence for distinguishing extrapulmonary malignancy from primary lung cancer

The Trade-Offs and Synergies of Ecosystem Services in Jiulianshan National Nature Reserve in Jiangxi Province, China

Ecosystem services are directly related to human well-being. Previous studies showed that management policies and human activities alter the trade-offs and synergies of ecosystem services. Taking effective measures to manage the trade-offs and synergies of ecosystem services is essential to sustain ecological security and achieve a “win-win” situation between society and ecosystems. This study investigated the spatiotemporal changes of water yield, soil conservation, and carbon sequestration in the Jiulianshan National Nature Reserve from 2000 to 2020 based on the InVEST model. We distinguished spatial patterns of trade-offs and synergies between ecosystem services using the correlation relationship analysis. Then we analyzed the response of ecosystem services relationships among different vegetation types and elevation bands. The results showed that water yield and carbon sequestration presented an overall upward trend, while soil conservation remained a marginal degradation. Rising ecosystem services were mainly in the central, western, and southeastern regions, and declining areas were mainly distributed in the midwestern and northeastern fringes. Synergies spatially dominated the interactions among water yield, soil conservation, and carbon sequestration, and the trade-offs were primarily concentrated in the northern, southern, and southwestern fringes. Among the different vegetation types, synergies dominated ecosystem services in broad-leaved forests, coniferous forests, mixed forests, and Moso bamboo forests and in grass. The trade-offs were gradually reduced with elevation. This study highlighted that trade-off of ecosystem services should be incorporated into ecological management policies, strengthening the effectiveness of nature reserves in protecting and improving China’s ecosystem services

Day-night cycle as a key environmental factor affecting coral-Symbiodiniaceae symbiosis

Interpreting the coral-Symbiodiniaceae symbiosis in light of the day-night cycle may provide missing links in understanding the function of endosymbiosis. In this study, we found the photo-physiology, Symbiodinaiceae cell density and gene transcription of two coral holobionts (Acropora pruinosa-Cladocopium sp. and Pocillopora damicornis-Durusdinium sp.) have clear day-night oscillations. These two coral holobionts showed lower maximum quantum yield of photosystem II but higher Symbiodiniaceae cell density at day-time, as compared to at night-time. At day-time, the genes related to circadian rhythm and symbiosis in both hosts were up-regulated, while those related to immunity were down-regulated. Simultaneously, both symbionts had lower abundances of genes involved in the light reaction, Calvin cycle and glycolysis, but higher abundances of genes involved in the NH4+ assimilation. These results indicated the high density of Symbiodiniaceae at day-time might be attributed to up-regulating of genes involved in symbiosis and nitrogen metabolism but down-regulating of genes involved in immunity. Moreover, the A. pruinosa-Cladocopium sp. holobiont had larger day-night oscillations than P. damicornis-Durusdinium sp. holobiont, in terms of photo-physiology, Symbiodinaiceae cell density and gene transcription, revealing species-specific day-night oscillation. This study provides valuable insights into the cooperation strategies of coral holobionts to adapt to the day-night environmental changes