Control of spatiotemporal localization of infrared pulses in gas-filled capillaries using weak ultraviolet pulses

Manipulation of intense pulse propagation in gas-filled capillaries is desirable for various high-field applications. The conventional approach is to adjust the parameters of the driving laser pulse and working gas but it offers limited capability of control. Here we demonstrate through numerical simulations a novel scheme to control the intense infrared pulse propagation. A weak ultraviolet pulse is launched into the capillary with a negative delay with respect to the main infrared pulse. As the main pulse self-compresses, the control pulse becomes temporally overlapped with the main pulse due to dispersion and is red-shifted due to cross phase modulation. The frequency shift of the two pulse mitigates pulse walk-off and allows an efficient coupling, substantially extending the propagation length with an ionizing intensity. This interesting phenomenon not only adds to the rich spatiotemporal dynamics of intense pulse propagation but also has practical importance for applications such as high-order harmonic generation

GAN Ensemble for Anomaly Detection

When formulated as an unsupervised learning problem, anomaly detection often requires a model to learn the distribution of normal data. Previous works apply Generative Adversarial Networks (GANs) to anomaly detection tasks and show good performances from these models. Motivated by the observation that GAN ensembles often outperform single GANs in generation tasks, we propose to construct GAN ensembles for anomaly detection. In the proposed method, a group of generators and a group of discriminators are trained together, so every generator gets feedback from multiple discriminators, and vice versa. Compared to a single GAN, a GAN ensemble can better model the distribution of normal data and thus better detect anomalies. Our theoretical analysis of GANs and GAN ensembles explains the role of a GAN discriminator in anomaly detection. In the empirical study, we evaluate ensembles constructed from four types of base models, and the results show that these ensembles clearly outperform single models in a series of tasks of anomaly detection.Comment: 8 pages, 6 figures. To appear in Proceedings 35th AAAI Conference on Artificial Intelligence (AAAI 21

Estimating global cropland production from 1961 to 2010

Global cropland net primary production (NPP) has tripled over the last 50 years, contributing 17–45 % to the increase in global atmospheric CO2 seasonal amplitude. Although many regional-scale comparisons have been made between statistical data and modeling results, long-term national comparisons across global croplands are scarce due to the lack of detailed spatiotemporal management data. Here, we conducted a simulation study of global cropland NPP from 1961 to 2010 using a process-based model called Vegetation–Global Atmosphere–Soil (VEGAS) and compared the results with Food and Agriculture Organization of the United Nations (FAO) statistical data on both continental and country scales. According to the FAO data, the global cropland NPP was 1.3, 1.8, 2.2, 2.6, 3.0, and 3.6 PgC yr−1 in the 1960s, 1970s, 1980s, 1990s, 2000s, and 2010s, respectively. The VEGAS model captured these major trends on global and continental scales. The NPP increased most notably in the US Midwest, western Europe, and the North China Plain and increased modestly in Africa and Oceania. However, significant biases remained in some regions such as Africa and Oceania, especially in temporal evolution. This finding is not surprising as VEGAS is the first global carbon cycle model with full parameterization representing the Green Revolution. To improve model performance for different major regions, we modified the default values of management intensity associated with the agricultural Green Revolution differences across various regions to better match the FAO statistical data at the continental level and for selected countries. Across all the selected countries, the updated results reduced the RMSE from 19.0 to 10.5 TgC yr−1 (∼  45 % decrease). The results suggest that these regional differences in model parameterization are due to differences in socioeconomic development. To better explain the past changes and predict the future trends, it is important to calibrate key parameters on regional scales and develop data sets for land management history

International relations in international business research:A review and research agenda

The increasing dynamism of the international business (IB) environment has drawn greater scholarly attention to the implications of international politics for MNEs’ cross-border activities. However, a systematic overview of International Relations (IR) research which has been applied in IB studies is absent. To analyse this void, we propose a conceptual framework of the broader international context to delineate the research boundaries of the emerging IR in IB research domain and offer a critically synthesized review of the studies that have drawn on IRscholarship to explain MNEs’ behaviour. We conduct bibliometric and content analyses to understand the state of knowledge of IR in IB research and examine the main approaches to study the impact of IR factors on MNEs’ location choices, entry strategies, legitimacy and post-entry performance. By illuminating knowledge frontier issues, we derive important directions for deepening the integration of IR scholarship to advance IB research

International relations in international business research:A review and research agenda

The increasing dynamism of the international business (IB) environment has drawn greater scholarly attention to the implications of international politics for MNEs’ cross-border activities. However, a systematic overview of International Relations (IR) research which has been applied in IB studies is absent. To analyse this void, we propose a conceptual framework of the broader international context to delineate the research boundaries of the emerging IR in IB research domain and offer a critically synthesized review of the studies that have drawn on IRscholarship to explain MNEs’ behaviour. We conduct bibliometric and content analyses to understand the state of knowledge of IR in IB research and examine the main approaches to study the impact of IR factors on MNEs’ location choices, entry strategies, legitimacy and post-entry performance. By illuminating knowledge frontier issues, we derive important directions for deepening the integration of IR scholarship to advance IB research

mHealth in China and the United States: How Mobile Technology is Transforming Healthcare in the World's Two Largest Economies

In this paper, we explore ways mobile technology can help with these difficulties. Specifically, we look at avenues through which mobile devices boost productivity, aid communications, and help providers improve affordability, access, and treatment. Using data drawn from China and the United States as well as global trends, we look at recent developments andemerging opportunities in mobile health, or mHealth. We argue that mobile technology assists patients, health providers, and policymakers in several different respects. It helps patients by giving them tools to monitor their health conditions and communicate those results to physicians. It enables health providers to connect with colleagues and offers alternative sources of information for patients. It is also an important tool to inform policymakers on health delivery and medical outcomes