MOSS: End-to-End Dialog System Framework with Modular Supervision

A major bottleneck in training end-to-end task-oriented dialog system is the lack of data. To utilize limited training data more efficiently, we propose Modular Supervision Network (MOSS), an encoder-decoder training framework that could incorporate supervision from various intermediate dialog system modules including natural language understanding, dialog state tracking, dialog policy learning, and natural language generation. With only 60% of the training data, MOSS-all (i.e., MOSS with supervision from all four dialog modules) outperforms state-of-the-art models on CamRest676. Moreover, introducing modular supervision has even bigger benefits when the dialog task has a more complex dialog state and action space. With only 40% of the training data, MOSS-all outperforms the state-of-the-art model on a complex laptop network troubleshooting dataset, LaptopNetwork, that we introduced. LaptopNetwork consists of conversations between real customers and customer service agents in Chinese. Moreover, MOSS framework can accommodate dialogs that have supervision from different dialog modules at both the framework level and model level. Therefore, MOSS is extremely flexible to update in a real-world deployment

Genetic relationship between hydrocarbon system evolution and Carlin-type gold mineralization: Insights from ReOs pyrobitumen and pyrite geochronology in the Nanpanjiang Basin, South China

The spatial association of hydrocarbons with metalliferous ore deposits is found worldwide and is particularly common to Carlin-type gold systems. Both liquid oil and pyrobitumen are found in Carlin-type gold deposits of North Nevada, USA and the Nanpanjiang Basin, South China. However, the temporal and genetic association of hydrocarbons and gold mineralization are still debated. To this end, using rhenium‑osmium (Resingle bondOs) geochronology of pyrobitumen and gold-bearing pyrite from the Laizishan and Banqi reservoirs and the Yata Carlin-type gold deposit in the Nanpanjiang Basin, we consider hydrocarbons played a critical role in the mineralization process. A Resingle bondOs age of 228 ± 16 Ma obtained for highly mature pyrobitumen suggests that liquid oil cracking occurred during the Late Triassic in the Laizishan and Banqi reservoirs. This age is in agreement with the modelled thermal history of the Nanpanjiang Basin. Additionally, a broadly identical gold-bearing pyrite Resingle bondOs age of 218 ± 25 Ma from Yata Carlin-type gold deposit which is in agreement with ages reported for other Carlin-type gold deposits in the Nanpanjiang Basin (e.g., in-situ SIMS Usingle bondPb rutile = 213.6 ± 5.4 Ma, Resingle bondOs arsenopyrite = 204 ± 19 Ma - 235 ± 33 Ma and Rbsingle bondSr illite = 212.8 ± 4.6 Ma) suggests the auriferous Carlin-type systems of the Nanpanjiang Basin also formed during the Late Triassic. Integrating our Resingle bondOs data, with recent liquid hydrocarbon experimental data and fluid inclusion data from both reservoirs and gold deposits within the Nanpanjiang Basin, a methane (CH4) dominated thermochemical sulfate reduction (TSR) process, which introduced hydrogen sulfide (H2S) into basinal fluid and ultimately led to the deposition of gold-bearing pyrite by sulfidation, is considered to be the genetic link between of pyrobitumen and gold-bearing pyrite mineralization of the Carlin-type systems of the Nanpanjiang Basin

FedVision: An Online Visual Object Detection Platform Powered by Federated Learning

Visual object detection is a computer vision-based artificial intelligence (AI) technique which has many practical applications (e.g., fire hazard monitoring). However, due to privacy concerns and the high cost of transmitting video data, it is highly challenging to build object detection models on centrally stored large training datasets following the current approach. Federated learning (FL) is a promising approach to resolve this challenge. Nevertheless, there currently lacks an easy to use tool to enable computer vision application developers who are not experts in federated learning to conveniently leverage this technology and apply it in their systems. In this paper, we report FedVision - a machine learning engineering platform to support the development of federated learning powered computer vision applications. The platform has been deployed through a collaboration between WeBank and Extreme Vision to help customers develop computer vision-based safety monitoring solutions in smart city applications. Over four months of usage, it has achieved significant efficiency improvement and cost reduction while removing the need to transmit sensitive data for three major corporate customers. To the best of our knowledge, this is the first real application of FL in computer vision-based tasks

Evaluation of microbe-driven soil organic matter quantity and quality by thermodynamic theory

Microbial communities, coupled with substrate quality and availability, regulate the stock (formation versus mineralization) of soil organic matter (SOM) in terrestrial ecosystems. However, our understanding of how soil microbes interact with contrasting substrates influencing SOM quantity and quality is still very superfi-cial. Here, we used thermodynamic theory principles and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) to evaluate the linkages between dissolved organic matter (DOM [organic substrates in soil that are readily available]), thermodynamic quality, and microbial communities. We investigated soils from subtropical paddy ecosystems across a 1,000-km gradient and comprising contrasting levels of SOM content and nutrient availability. Our region-scale study suggested that soils with a larger abundance of readily accessible resources (i.e., lower Gibbs free energy) supported higher levels of microbial diversity and higher SOM content. We further advocated a novel phylotype-level microbial classification based on their associations with OM quantities and qualities and identified two contrasting clusters of bacterial taxa: phylotypes that are highly positively correlated with thermodynami-cally favorable DOM and larger SOM content versus those which are associated with less-favorable DOM and lower SOM content. Both groups are expected to play criti-cal roles in regulating SOM contents in the soil. By identifying the associations between microbial phylotypes of different life strategies and OM qualities and quan-tities, our study indicates that thermodynamic theory can act as a proxy for the relationship between OM and soil microbial communities and should be considered in models of soil organic matter preservation. IMPORTANCE Microbial communities are known to be important drivers of organic matter (OM) accumulation in terrestrial ecosystems. However, despite the importance of these soil microbes and processes, the mechanisms behind these microbial-SOM associations remain poorly understood. Here, we used the principles of thermodynamic theory and novel Fourier transform ion cyclotron resonance mass spectrome-try techniques to investigate the links between microbial communities and dissolved OM (DOM) thermodynamic quality in soils across a 1,000-km gradient and comprising contrasting nutrient and C contents. Our region-scale study provided evidence that soils with a larger amount of readily accessible resources (i.e., lower Gibbs free energy) supported higher levels of microbial diversity and larger SOM con-tent. Moreover, we created a novel phylotype-level microbial classification based on the associations between microbial taxa and DOM quantities and qualities. We found two contrasting clusters of bacterial taxa based on their level of association with thermodynamically favorable DOM and SOM content. Our study advan-ces our knowledge on the important links between microbial communities and SOM. Moreover, by identifying the associations between microbial phylotypes of different life strategies and OM qualities and quantities, our study indicates that thermodynamic theory can act as a proxy for the relationship between OM and soil microbial communities. Together, our findings support that the association between microbial species taxa and substrate thermodynamic quality constituted an important complement explanation for soil organic matter preservation

Computation Bits Maximization for IRS-Aided Mobile-Edge Computing Networks With Phase Errors and Transceiver Hardware Impairments

Intelligent reflecting surface (IRS) is a hopeful technique to improve the computation offloading efficiency for mobile-edge computing (MEC) networks. However, the phase errors (PEs) of IRS and transceiver hardware impairments (THIs) will greatly degrade the performance of IRS-assisted MEC networks. To overcome this bottleneck, this paper first investigates the computation bits maximization problem for IRS-assisted MEC networks with PEs, where multiple Internet of Things (IoT) devices can offload their computation tasks to access points with the aid of IRS. By exploiting the block coordinate descent method, we design a multi-block optimization algorithm to tackle the non-convex problem. In particular, the optimal IRS phase shift, time allocation, transmit power and local computing frequencies of IoT devices are derived in closed-form expressions. Moreover, we further study the joint impact of PEs and THIs on the total computation bits of considered systems, where same methods in the scenario with PEs are used to obtain the optimal IRS phase shift and local computing frequencies of IoT devices, while an approximation algorithm and the variable substitution method are used to acquire the optimal transmit power and time allocation strategy. Finally, numerical results validate that our proposed methods can significantly outperform benchmark methods in terms of total computation bits

Beyond the snapshot: identification of the timeless, enduring indicator microbiome informing soil fertility and crop production in alkaline soils

Background Microorganisms are known to be important drivers of biogeochemical cycling in soil and hence could act as a proxy informing on soil conditions in ecosystems. Identifying microbiomes indicative for soil fertility and crop production is important for the development of the next generation of sustainable agriculture. Earlier researches based on one-time sampling have revealed various indicator microbiomes for distinct agroecosystems and agricultural practices as well as their importance in supporting sustainable productivity. However, these microbiomes were based on a mere snapshot of a dynamic microbial community which is subject to significant changes over time. Currently true indicator microbiomes based on long-term, multi-annual monitoring are not available. Results Here, using samples from a continuous 20-year field study encompassing seven fertilization strategies, we identified the indicator microbiomes ecophysiologically informing on soil fertility and crop production in the main agricultural production base in China. Among a total of 29,184 phylotypes in 588 samples, we retrieved a streamlined consortium including 2% of phylotypes that were ubiquitously present in alkaline soils while contributing up to half of the whole community; many of them were associated with carbon and nutrient cycling. Furthermore, these phylotypes formed two opposite microbiomes. One indicator microbiome dominated by Bacillus asahii, characterized by specific functional traits related to organic matter decomposition, was mainly observed in organic farming and closely associated with higher soil fertility and crop production. The counter microbiome, characterized by known nitrifiers (e.g., Nitrosospira multiformis) as well as plant pathogens (e.g., Bacillus anthracis) was observed in nutrient-deficit chemical fertilizations. Both microbiomes are expected to be valuable indictors in informing crop yield and soil fertility, regulated by agricultural management. Conclusions Our findings based on this more than 2-decade long field study demonstrate the exciting potential of employing microorganisms and maximizing their functions in future agroecosystems. Our results report a “most-wanted” or “most-unwanted” list of microbial phylotypes that are ready candidates to guide the development of sustainable agriculture in alkaline soils

Important ecophysiological roles of non-dominant Actinobacteria in plant residue decomposition, especially in less fertile soils

Background Microbial-driven decomposition of plant residues is integral to carbon sequestration in terrestrial ecosystems. Actinobacteria, one of the most widely distributed bacterial phyla in soils, are known for their ability to degrade plant residues in vitro. However, their in situ importance and specific activity across contrasting ecological environments are not known. Here, we conducted three field experiments with buried straw in combination with microcosm experiments with 13C-straw in paddy soils under different soil fertility levels to reveal the ecophysiological roles of Actinobacteria in plant residue decomposition. Results While accounting for only 4.6% of the total bacterial abundance, the Actinobacteria encoded 16% of total abundance of carbohydrate-active enzymes (CAZymes). The taxonomic and functional compositions of the Actinobacteria were, surprisingly, relatively stable during straw decomposition. Slopes of linear regression models between straw chemical composition and Actinobacterial traits were flatter than those for other taxonomic groups at both local and regional scales due to holding genes encoding for full set of CAZymes, nitrogenases, and antibiotic synthetases. Ecological co-occurrence network and 13C-based metagenomic analyses both indicated that their importance for straw degradation increased in less fertile soils, as both links between Actinobacteria and other community members and relative abundances of their functional genes increased with decreasing soil fertility. Conclusions This study provided DNA-based evidence that non-dominant Actinobacteria plays a key ecophysiological role in plant residue decomposition as their members possess high proportions of CAZymes and as a group maintain a relatively stable presence during plant residue decomposition both in terms of taxonomic composition and functional roles. Their importance for decomposition was more pronounced in less fertile soils where their possession functional genes and interspecies interactions stood out more. Our work provides new ecophysiological angles for the understanding of the importance of Actinobacteria in global carbon cycling

Hypidone Hydrochloride (YL-0919) Produces a Fast-Onset Reversal of the Behavioral and Synaptic Deficits Caused by Chronic Stress Exposure

Our previous study showed that hypidone hydrochloride (YL-0919), a partial serotonin 1A (5-HT1A) receptor agonist and 5-HT reuptake inhibitor, exerts a significant antidepressant effect in various animal models. The aim of the present study was to further investigate the underlying mechanisms and whether it could act as a fast-onset antidepressant. In the current study, depressive-like behavior was induced in rats by a chronic unpredictable stress (CUS) model and assessed with the Sucrose Preference Test (SPT). Treatment with YL-0919 (2.5 mg/kg, i.g.), but not with fluoxetine (Flx; 10 mg/kg, i.g.), caused a fast improvement in the SPT scores. In CUS-exposed rats, YL-0919 treatment for 5 days decreased the immobility time in a forced swimming test (FST), and a 10-day treatment decreased the latency to feed in a Novelty-Suppressed Feeding Test (NSFT). In addition to the behavioral tests, the effects of YL-0919 on synaptic protein expression were also evaluated. Western blotting showed that YL-0919 significantly enhanced the expression levels of synaptic proteins such as synapsin I, postsynaptic density protein 95 (PSD95), phosphorylated mammalian targeting of rapamycin (pmTOR) and brain-derived neurotrophic factor (BDNF) in the hippocampus. To determine how the mTOR signaling is involved in the fast-onset antidepressant-like effects of YL-0919, the mTOR-specific inhibitor rapamycin was administered intracerebroventricularly (i.c.v.) together with the YL-0919 treatment. The observed changes in behavioral tests and protein expression could be reversed by rapamycin treatment. This suggests that the fast-onset antidepressant effects of YL-0919 were partially caused by changes in synaptogenesis mediated by activation of mTOR pathways. Our data suggest that YL-0919 may be a powerful/effective antidepressant with fast-onset