Check Me If You Can: Detecting ChatGPT-Generated Academic Writing using CheckGPT

With ChatGPT under the spotlight, utilizing large language models (LLMs) for academic writing has drawn a significant amount of discussions and concerns in the community. While substantial research efforts have been stimulated for detecting LLM-Generated Content (LLM-content), most of the attempts are still in the early stage of exploration. In this paper, we present a holistic investigation of detecting LLM-generate academic writing, by providing a dataset, evidence, and algorithms, in order to inspire more community effort to address the concern of LLM academic misuse. We first present GPABenchmark, a benchmarking dataset of 600,000 samples of human-written, GPT-written, GPT-completed, and GPT-polished abstracts of research papers in CS, physics, and humanities and social sciences (HSS). We show that existing open-source and commercial GPT detectors provide unsatisfactory performance on GPABenchmark, especially for GPT-polished text. Moreover, through a user study of 150+ participants, we show that it is highly challenging for human users, including experienced faculty members and researchers, to identify GPT-generated abstracts. We then present CheckGPT, a novel LLM-content detector consisting of a general representation module and an attentive-BiLSTM classification module, which is accurate, transferable, and interpretable. Experimental results show that CheckGPT achieves an average classification accuracy of 98% to 99% for the task-specific discipline-specific detectors and the unified detectors. CheckGPT is also highly transferable that, without tuning, it achieves ~90% accuracy in new domains, such as news articles, while a model tuned with approximately 2,000 samples in the target domain achieves ~98% accuracy. Finally, we demonstrate the explainability insights obtained from CheckGPT to reveal the key behaviors of how LLM generates texts

Different responses of soil fungal and bacterial communities to nitrogen addition in a forest grassland ecotone

IntroductionContinuous nitrogen deposition increases the nitrogen content of terrestrial ecosystem and affects the geochemical cycle of soil nitrogen. Forest-grassland ecotone is the interface area of forest and grassland and is sensitive to global climate change. However, the structure composition and diversity of soil microbial communities and their relationship with soil environmental factors at increasing nitrogen deposition have not been sufficiently studied in forest-grassland ecotone.MethodsIn this study, experiments were carried out with four nitrogen addition treatments (0 kgN·hm−2·a−1, 10 kgN·hm−2·a−1, 20 kgN·hm−2·a−1 and 40 kgN·hm−2·a−1) to simulate nitrogen deposition in a forest-grassland ecotone in northwest Liaoning Province, China. High-throughput sequencing and qPCR technologies were used to analyze the composition, structure, and diversity characteristics of the soil microbial communities under different levels of nitrogen addition.Results and discussionThe results showed that soil pH decreased significantly at increasing nitrogen concentrations, and the total nitrogen and ammonium nitrogen contents first increased and then decreased, which were significantly higher in the N10 treatment than in other treatments (N:0.32 ~ 0.48 g/kg; NH4+-N: 11.54 ~ 13 mg/kg). With the increase in nitrogen concentration, the net nitrogen mineralization, nitrification, and ammoniation rates decreased. The addition of nitrogen had no significant effect on the diversity and structure of the fungal community, while the diversity of the bacterial community decreased significantly at increasing nitrogen concentrations. Ascomycetes and Actinomycetes were the dominant fungal and bacterial phyla, respectively. The relative abundance of Ascomycetes was negatively correlated with total nitrogen content, while that of Actinomycetes was positively correlated with soil pH. The fungal community diversity was significantly negatively correlated with nitrate nitrogen, while the diversity of the bacterial community was significantly positively correlated with soil pH. No significant differences in the abundance of functional genes related to soil nitrogen transformations under the different treatments were observed. Overall, the distribution pattern and driving factors were different in soil microbial communities in a forest-grassland ecotone in northwest Liaoning. Our study enriches research content related to factors that affect the forest-grassland ecotone

Experimental and kinetic study of the nitration of 2-ethylhexanol in capillary microreactors

The nitration process of 2-ethylhexanol (2-EH) with mixed acid was studied in different capillary microreactors. The conversion of 2-EH and selectivity to 2-ethylhexyl nitrate (EHN) were investigated by varying reaction temperature, molar ratio of nitrate to 2-EH, residence time and water content in mixed acid. Under optimized conditions, the conversion of 2-EH and selectivity to EHN could be up to 99% in less than 10 seconds, indicating great potential of microreactors in process intensification. Moreover, with an assumption of homogeneous reaction, a kinetic model based on first order kinetics for nitric acid and 2-EH was proposed to determine both the apparent and intrinsic reaction kinetics. By taking into account the activity of solutes that depend on the acidity (M-c), the intrinsic kinetic was obtained, which is independent of the sulfuric acid concentration. The reaction model can well predict the conversion of 2-EH

Distribution, Enrichment and Modes of Occurrence of Arsenic in Chinese Coals

Arsenic is one of the toxic trace elements in coals, which is harmful to both the ecological environment and human health. Based on published literature and the data obtained by our research group, a total of 5314 As concentrations of Chinese coals were analyzed. The arithmetic mean of arsenic content in Chinese coals is 6.97 mg/kg. Choosing the percentage of provincial coal resources in national coal resources as the weighting factor, the weighted average of arsenic content in Chinese coals is 5.33 mg/kg. The content of arsenic in Chinese coals increases from the north to the south. High arsenic content in coal primarily occurs in southwestern Yunnan and certain coalfields in the Guizhou Province. Additionally, arsenic is enriched in the coals from some regions, i.e., the western Yunnan, Guangxi, Tibet, southwestern Liaoning, Jilin, and Henan. The arsenic content in coals of different coal-forming periods shows an overall regularity: Paleogene and Neogene > Late Triassic > Late Permian > Late Jurassic and Early Cretaceous > Early and Middle Jurassic > Late Carboniferous and Early Permian. The modes of occurrence of arsenic in coals include sulfide-association, organic-association, arsenate-association, silicate-association, and soluble- and exchangeable-association. Generally, arsenic in Chinese coals exists predominantly in arsenic-bearing pyrite. Meanwhile, the organic arsenic content is relatively high in coal samples with a lower (<5.5 mg/kg) arsenic content and a low or medium ash yield (<30%)

Intensified CO2 absorption in a microchannel reactor under elevated pressures

This paper presents a study on the hydrodynamics and mass transfer performance of absorption of CO2 into deionized water and DEA solutions in a microreactor under elevated pressures up to 4.0 MPa. It is demonstrated that increasing gas density (system pressure) leads to increased pressure drop. Considering such effect, a modified Lockhart-Martinelli model is developed, showing good prediction over the two-phase pressure drop. For the mass transfer performance, parametric studies by varying system pressure, temperature of feeding fluids, molar ratio of DEA/CO2 and CO2-loaded DEA solutions are presented. Two empirical correlations based on the power consumption are developed for the prediction of mass transfer coefficients in physical and chemical absorptions, respectively. The results suggest significant intensification is achieved in the microreactor. Besides, dramatic increase of CO2 loading in the rich absorbents is also obtained, which is very attractive for solvent regeneration. The findings in this paper can serve as guidance in the design of processes with high-pressure operations, such as natural gas purification or biogas recovery.(C) 2017 Elsevier B.V. All rights reserved

Hybrid Compact Polarimetric SAR Calibration Considering the Amplitude and Phase Coefficients Inconsistency

Calibration using corner reflectors is an effective way to estimate the distortion parameters of hybrid compact polarimetric (HCP) synthetic aperture radar (SAR) systems. However, the existing literature lacks a discussion on the inconsistency of the amplitude and phase coefficients between measured scattering vectors of different corner reflectors. In response to this problem, this paper first proves that this inconsistency will seriously deteriorate the estimation accuracy of polarimetric distortion parameters. Based on the optimization algorithm, two calibration schemes for simultaneously estimating the traditional distortion parameters and the amplitude/phase coefficients are proposed while ignoring crosstalk (ICT) and considering crosstalk (CCT). In the process of distortion parameter estimation, the idea of “optimizing while compensating” is adopted to eliminate the problem of uneven echo intensity. Simulation results show that both schemes can eliminate the influence of the inconsistency of amplitude and phase coefficients, and estimate distortion parameters accurately. When the received crosstalk level is lower than −30 dB, the ICT scheme can accurately estimate polarimetric distortion parameters. The CCT scheme has a wider application range of crosstalk and can work well when the crosstalk level is lower than −20 dB, but it also has a higher requirement for the signal-to-clutter ratio (SCR). When SCR is greater than 35 dB, the CCT scheme yields higher estimation accuracy than the ICT scheme. In addition, the effectiveness of the calibration schemes is verified based on the L-band measured data acquired by the Aerospace Information Research Institute, Chinese Academy of Sciences

Differences in Nitrogen and Phosphorus Removal under Different Temperatures in <i>Oenanthe javanica</i> Cultivars

Plant selection plays a critical role in phytoremediation. However, previous research has focused on comparing different plant species but has ignored different cultivars. Here, a laboratory experiment was performed to analyze the nitrogen (N) and phosphorus (P) removal performance of different cultivars of Oenanthe javanica, which are widely employed for phytoremediation in China. Seven cultivars were planted on simulated livestock wastewater with high N and P content prepared with compounds for 22 days in two artificial climate chambers with different temperatures. N and P contents were monitored to estimate the nutrient removal performance of the cultivars. ‘Suzhou Yuanye’ had the highest N removal ability at room temperature (45.33 ± 1.92%) and under cold stress (39.63 ± 2.15%) in 22 days, and it could also remove P effectively (99.32 ± 0.33% at room temperature and 77.50 ± 0.08% under cold stress). ‘Yixing Yuanye’ performed the best in P removal (97.90 ± 2.89% at room temperature and 99.57 ± 0.61% under cold stress). ‘Liyang Baiqin’ performed well in N removal only at room temperature (44.30 ± 1.03%). ‘Suqian Jianye’ had low removal efficiencies for both N and P. From the biomass and N content, we could conclude that the high N removal efficiency of ‘Suzhou Yuanye’ is due to high N assimilation of the plant. However, ‘Yixing Yuanye’ did not show higher P assimilation ability than other cultivars. Taken together, the selection of cultivars is important for phytoremediation projects using O. javanica, and ‘Suzhou Yuanye’ is much more suitable for phytoremediation than other cultivars

Bioactivity-Guided Fractionation of Physical Fatigue-Attenuating Components from Rubus parvifolius L.

Alleviation of fatigue has been emerging as a serious issue that requires urgent attention. Health professionals and sports physiologists have been looking for active natural products and synthetic compounds to overcome fatigue in humans. This study was designed to define the anti-fatigue property of Rubus parvifolius L. (RPL) by characterization of active constituents using a mouse forced swimming test model. Four RPL fractions with different polarities containing anti-fatigue activity were sequentially isolated from the n-butanol RPL extract, followed by elution of 50% ethanol-water fraction from D101 macroporous resin chromatography to obtain nigaichigoside F1, suavissimoside R1 and coreanoside F1. Active constituents of the 50% ethanol-water eluate of RPL were total saponins. The fractions were examined based on the effect on weight-loaded swimming capacity of mice. Serum levels of urea nitrogen (SUN), triglyceride fatty acids (TG), lactate dehydrogenase (LDH), lactic acid (LA), ammonia and hepatic glycogen (HG) were also examined for potential mechanisms underlying the anti-fatigue effect of RPL extracts. During the experiment, two inflammatory markers, interleukin-6 (IL-6) and tumor necrosis factor (TNF-α) in serum, were measured. We found that total saponins from RPL possess potent capabilities to alleviate mouse fatigue induced by forced swimming and that nigaichigoside F1 was responsible for the pharmacological effect. The underlying mechanisms include delays of SUN and LA accumulation, a decrease in TG level by increasing fat consumption, increases in HG and LDH so that lactic acid accumulation and ammonia in the muscle were reduced, and suppression of increased immune activation and inflammatory cytokine production. Our findings will be helpful for functional identification of novel anti-fatigue components from natural medicinal herbs