49 research outputs found

    SETI: Systematicity Evaluation of Textual Inference

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    We propose SETI (Systematicity Evaluation of Textual Inference), a novel and comprehensive benchmark designed for evaluating pre-trained language models (PLMs) for their systematicity capabilities in the domain of textual inference. Specifically, SETI offers three different NLI tasks and corresponding datasets to evaluate various types of systematicity in reasoning processes. In order to solve these tasks, models are required to perform compositional inference based on known primitive constituents. We conduct experiments of SETI on six widely used PLMs. Results show that various PLMs are able to solve unseen compositional inferences when having encountered the knowledge of how to combine primitives, with good performance. However, they are considerably limited when this knowledge is unknown to the model (40-100% points decrease). Furthermore, we find that PLMs can improve drastically once exposed to crucial compositional knowledge in minimalistic shots. These findings position SETI as the first benchmark for measuring the future progress of PLMs in achieving systematicity generalization in the textual inference.Comment: Accepted to Findings of ACL202

    Dynamic MOdularized Reasoning for Compositional Structured Explanation Generation

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    Despite the success of neural models in solving reasoning tasks, their compositional generalization capabilities remain unclear. In this work, we propose a new setting of the structured explanation generation task to facilitate compositional reasoning research. Previous works found that symbolic methods achieve superior compositionality by using pre-defined inference rules for iterative reasoning. But these approaches rely on brittle symbolic transfers and are restricted to well-defined tasks. Hence, we propose a dynamic modularized reasoning model, MORSE, to improve the compositional generalization of neural models. MORSE factorizes the inference process into a combination of modules, where each module represents a functional unit. Specifically, we adopt modularized self-attention to dynamically select and route inputs to dedicated heads, which specializes them to specific functions. We conduct experiments for increasing lengths and shapes of reasoning trees on two benchmarks to test MORSE's compositional generalization abilities, and find it outperforms competitive baselines. Model ablation and deeper analyses show the effectiveness of dynamic reasoning modules and their generalization abilities

    Long-term water use efficiency and non-structural carbohydrates of dominant tree species in response to nitrogen and water additions in a warm temperate forest

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    Nitrogen (N) deposition tends to accompany precipitation in temperate forests, and vegetation productivity is mostly controlled by water and N availability. Many studies showed that tree species response to precipitation or N deposition alone influences, while the N deposition and precipitation interactive effects on the traits of tree physiology, especially in non-structural carbohydrates (NSCs) and long-term water use efficiency (WUE), are still unclear. In this study, we measured carbon stable isotope (delta C-13), total soluble sugar and starch content, total phenols, and other physiological traits (e.g., leaf C:N:P stoichiometry, lignin, and cellulose content) of two dominant tree species (Quercus variabilis Blume and Liquidambar formosana Hance) under canopy-simulated N deposition and precipitation addition to analyze the changes of long-term WUE and NSC contents and to explain the response strategies of dominant trees to abiotic environmental changes. This study showed that N deposition decreased the root NSC concentrations of L. formosana and the leaf lignin content of Q. variabilis. The increased precipitation showed a negative effect on specific leaf area (SLA) and a positive effect on leaf WUE of Q. variabilis, while it increased the leaf C and N content and decreased the leaf cellulose content of L. formosana. The nitrogen-water interaction reduced the leaf lignin and total phenol content of Q. variabilis and decreased the leaf total phenol content of L. formosana, but it increased the leaf C and N content of L. formosana. Moreover, the response of L. formosana to the nitrogen-water interaction was greater than that of Q. variabilis, highlighting the differences between the two dominant tree species. The results showed that N deposition and precipitation obviously affected the tree growth strategies by affecting the NSC contents and long-term WUE. Canopy-simulated N deposition and precipitation provide a new insight into the effect of the nitrogen-water interaction on tree growth traits in a temperate forest ecosystem, enabling a better prediction of the response of dominant tree species to global change

    Simulation of CSSTs astrometric capability

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    The China Space Station Telescope (CSST) will enter a low Earth orbit around 2024 and operate for 10 years, with seven of those years devoted to surveying the area of the median-to-high Galactic latitude and median-to-high Ecliptic latitude of the sky. To maximize the scientific output of CSST, it is important to optimize the survey schedule. We aim to evaluate the astrometric capability of CSST for a given survey schedule and to provide independent suggestions for the optimization of the survey strategy. For this purpose, we first construct the astrometric model and then conduct simulated observations based on the given survey schedule. The astrometric solution is obtained by analyzing the simulated observation data. And then we evaluate the astrometric capability of CSST by analyzing the properties of the astrometric solution. We find that the accuracy of parallax and proper motion of CSST is better than 1 mas( yr1) for the sources of 18-22 mag in g band, and about 1-10 mas( yr1) for the sources of 22-26 mag in g band, respectively. The results from real survey could be worse since the assumptions are optimistic and simple. We find that optimizing the survey schedule can improve the astrometric accuracy of CSST. In the future, we will improve the astrometric capability of CSST by continuously iterating and optimizing the survey schedule.Comment: 17 pages, 10 figure

    Photometric Variability in the CSTAR Field: Results From the 2008 Data Set

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    The Chinese Small Telescope ARray (CSTAR) is the first telescope facility built at Dome A, Antarctica. During the 2008 observing season, the installation provided long-baseline and high-cadence photometric observations in the i-band for 18,145 targets within 20 deg2 CSTAR field around the South Celestial Pole for the purpose of monitoring the astronomical observing quality of Dome A and detecting various types of photometric variability. Using sensitive and robust detection methods, we discover 274 potential variables from this data set, 83 of which are new discoveries. We characterize most of them, providing the periods, amplitudes and classes of variability. The catalog of all these variables is presented along with the discussion of their statistical properties.Comment: 38 pages, 11 figures, 4 tables; Accepted for publication in ApJ

    Prevalence, associated factors and outcomes of pressure injuries in adult intensive care unit patients: the DecubICUs study

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    Funder: European Society of Intensive Care Medicine; doi: http://dx.doi.org/10.13039/501100013347Funder: Flemish Society for Critical Care NursesAbstract: Purpose: Intensive care unit (ICU) patients are particularly susceptible to developing pressure injuries. Epidemiologic data is however unavailable. We aimed to provide an international picture of the extent of pressure injuries and factors associated with ICU-acquired pressure injuries in adult ICU patients. Methods: International 1-day point-prevalence study; follow-up for outcome assessment until hospital discharge (maximum 12 weeks). Factors associated with ICU-acquired pressure injury and hospital mortality were assessed by generalised linear mixed-effects regression analysis. Results: Data from 13,254 patients in 1117 ICUs (90 countries) revealed 6747 pressure injuries; 3997 (59.2%) were ICU-acquired. Overall prevalence was 26.6% (95% confidence interval [CI] 25.9–27.3). ICU-acquired prevalence was 16.2% (95% CI 15.6–16.8). Sacrum (37%) and heels (19.5%) were most affected. Factors independently associated with ICU-acquired pressure injuries were older age, male sex, being underweight, emergency surgery, higher Simplified Acute Physiology Score II, Braden score 3 days, comorbidities (chronic obstructive pulmonary disease, immunodeficiency), organ support (renal replacement, mechanical ventilation on ICU admission), and being in a low or lower-middle income-economy. Gradually increasing associations with mortality were identified for increasing severity of pressure injury: stage I (odds ratio [OR] 1.5; 95% CI 1.2–1.8), stage II (OR 1.6; 95% CI 1.4–1.9), and stage III or worse (OR 2.8; 95% CI 2.3–3.3). Conclusion: Pressure injuries are common in adult ICU patients. ICU-acquired pressure injuries are associated with mainly intrinsic factors and mortality. Optimal care standards, increased awareness, appropriate resource allocation, and further research into optimal prevention are pivotal to tackle this important patient safety threat
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