Short-term drought response of N2O and CO2 emissions from mesic agricultural soils in the US Midwest

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Agriculture, Ecosystems & Environment 212 (2015): 127-133, doi:10.1016/j.agee.2015.07.005.Climate change is causing the intensification of both rainfall and droughts in temperate climatic zones, which will affect soil drying and rewetting cycles and associated processes such as soil greenhouse gas (GHG) fluxes. We investigated the effect of soil rewetting following a prolonged natural drought on soil emissions of nitrous oxide (N2O) and carbon dioxide (CO2) in an agricultural field recently converted from 22 years in the USDA Conservation Reserve Program (CRP). We compared responses to those in a similarly managed field with no CRP history and to a CRP reference field. We additionally compared soil GHG emissions measured by static flux chambers with off-site laboratory analysis versus in situ analysis using a portable quantum cascade laser and infrared gas analyzer. Under growing season drought conditions, average soil N2O fluxes ranged between 0.2 and 0.8 μg N m−2 min−1 and were higher in former CRP soils and unaffected by nitrogen (N) fertilization. After 18 days of drought, a 50 mm rewetting event increased N2O fluxes by 34 and 24 fold respectively in the former CRP and non-CRP soils. Average soil CO2 emissions during drought ranged from 1.1 to 3.1 mg C m−2 min−1 for the three systems. CO2 emissions increased ∼2 fold after the rewetting and were higher from soils with higher C contents. Observations are consistent with the hypothesis that during drought soil N2O emissions are controlled by available C and following rewetting additionally influenced by N availability, whereas soil CO2 emissions are independent of short-term N availability. Finally, soil GHG emissions estimated by off-site and in situ methods were statistically identical.Financial support for this work was provided by the DOE Office of Science (DE-FC02-07ER64494) and Office of Energy Efficiency and Renewable Energy (DE-AC05-76RL01830), the US National Science Foundation LTER program (DEB 1027253), and MSU AgBioResearch. J. Tang and M. Cui were supported additionally by NSF/DBI-959333, Brown University seed funding, and the Brown University–Marine Biological Laboratory graduate program in Biological and Environmental Sciences

Energy System Digitization in the Era of AI: A Three-Layered Approach towards Carbon Neutrality

The transition towards carbon-neutral electricity is one of the biggest game changers in addressing climate change since it addresses the dual challenges of removing carbon emissions from the two largest sectors of emitters: electricity and transportation. The transition to a carbon-neutral electric grid poses significant challenges to conventional paradigms of modern grid planning and operation. Much of the challenge arises from the scale of the decision making and the uncertainty associated with the energy supply and demand. Artificial Intelligence (AI) could potentially have a transformative impact on accelerating the speed and scale of carbon-neutral transition, as many decision making processes in the power grid can be cast as classic, though challenging, machine learning tasks. We point out that to amplify AI's impact on carbon-neutral transition of the electric energy systems, the AI algorithms originally developed for other applications should be tailored in three layers of technology, markets, and policy.Comment: To be published in Patterns (Cell Press

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation

Health risk prediction is one of the fundamental tasks under predictive modeling in the medical domain, which aims to forecast the potential health risks that patients may face in the future using their historical Electronic Health Records (EHR). Researchers have developed several risk prediction models to handle the unique challenges of EHR data, such as its sequential nature, high dimensionality, and inherent noise. These models have yielded impressive results. Nonetheless, a key issue undermining their effectiveness is data insufficiency. A variety of data generation and augmentation methods have been introduced to mitigate this issue by expanding the size of the training data set through the learning of underlying data distributions. However, the performance of these methods is often limited due to their task-unrelated design. To address these shortcomings, this paper introduces a novel, end-to-end diffusion-based risk prediction model, named MedDiffusion. It enhances risk prediction performance by creating synthetic patient data during training to enlarge sample space. Furthermore, MedDiffusion discerns hidden relationships between patient visits using a step-wise attention mechanism, enabling the model to automatically retain the most vital information for generating high-quality data. Experimental evaluation on four real-world medical datasets demonstrates that MedDiffusion outperforms 14 cutting-edge baselines in terms of PR-AUC, F1, and Cohen's Kappa. We also conduct ablation studies and benchmark our model against GAN-based alternatives to further validate the rationality and adaptability of our model design. Additionally, we analyze generated data to offer fresh insights into the model's interpretability

Protective Effect of Anthocyanin on Neurovascular Unit in Cerebral Ischemia/Reperfusion Injury in Rats

Treating cerebral ischemia continues to be a clinical challenge. Studies have shown that the neurovascular unit (NVU), as the central structural basis, plays a key role in cerebral ischemia. Here, we report that anthocyanin, a safe and natural antioxidant, could inhibit apoptosis and inflammation to protect NVU in rats impaired by middle cerebral artery occlusion/reperfusion (MCAO/R). Administration of anthocyanin significantly reduced infarct volume and neurological scores in MCAO/R rats. Anthocyanin could also markedly ameliorate cerebral edema and reduce the concentration of Evans blue (EB) by inhibiting MMP-9. Moreover, anthocyanin alleviated apoptotic injury resulting from MCAO/R through the regulation of Bcl-2 family proteins. The levels of inflammation-related molecules including tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and interleukin-6 (IL-6), which were over-expressed with MCAO/R, were decreased by anthocyanin. In addition, Nuclear factor-kappa B (NF-κB) and the NLRP3 inflammasome pathway might be involved in the anti-inflammatory effect of anthocyanin. In conclusion, anthocyanin could protect the NVU through multiple pathways, and play a protective role in cerebral ischemia/reperfusion injury

Vitamin B12 Levels in Methamphetamine Addicts

Objective: It has been established that reduced vitamin B12 serum levels are associated with cognitive decline and mental illness. The chronic use of methamphetamine (MA), which is a highly addictive drug, can induce cognitive impairment and psychopathological symptoms. There are few studies addressing the association of MA with vitamin B12 serum levels. This study examined whether the serum levels of B12 are associated with MA addiction.Methods: Serum vitamin B12, homocysteine (Hcy), glucose and triglyceride concentrations were measured in 123 MA addicts and 108 controls. In addition, data were collected on their age, marital status, level of education and Body Mass Index (BMI) for all participants. In the patient group, the data for each subject were collected using the Fagerstrom Test for Nicotine Dependence (FTND), the Alcohol Use Disorders Identification Test (AUDIT), and a drug use history, which included the age of onset, total duration of MA use, the number of relapses and addiction severity.Results: Our results showed that MA addicts had lower vitamin B12 levels (p < 0.05) than those of healthy controls, but Hcy levels were not significantly different between the two groups (p > 0.05). Serum B12 levels were negatively correlated with the number of relapses in the MA group. Furthermore, binary logistics regression analysis indicated that the B12 was an influencing factor contributing to addiction severity.Conclusion: The findings of this study suggest that some MA addicts might have vitamin B12 deficiency, and serum B12 levels may be involved in the prognosis of MA addiction

The Aesthetic Imagination of Chinese “Blockbuster” Movies under the Transformation of Digital Technology

This paper explores the aesthetic imagination of Chinese “blockbuster” films in the context of digital technological innovation, focusing on how virtual reality (VR) technology has reshaped the aesthetic experience of cinema and enhanced artistic expression and emotional interaction, thereby revealing the new position and value of Chinese cinema in the global cultural landscape. Using a combination of qualitative and quantitative approaches, this study deeply explores the multidimensional impact of this change through an in-depth analysis of the definition and characteristics of virtual reality technology and its application in cinema, combined with specific case studies of emotional expression in film. The study results show that VR technology significantly improves the immersion (21.01% growth rate) and interactivity (21.67% growth rate) of movies, and effectively enhances the audience’s emotional resonance and aesthetic awareness through the immersive experience. VR technology provides a new way of artistic expression for China’s “blockbuster” movies and brings a new way of creative expression for the Development of the film industry. VR technology not only provides a unique artistic expression for Chinese “blockbuster” movies, but also brings new possibilities for the Development of the movie industry, which helps to promote the critical position of Chinese movies in the global cultural map

Cesium Carbonate-Catalyzed Reduction of Amides with Hydrosilanes

Cesium carbonate has been found to be an effective catalyst for the reduction of tertiary carboxamides with the simple, commercially available PhSiH₃ under solvent-free conditions. The catalytic system can effectively reduce a range of amides under relatively mild conditions (from room temperature to 80 °C) to yield the corresponding amines in good to excellent yields (71–100%) and thus has the potential for practical applications