Expansion of Agriculture in Northern Cold-Climate Regions: A Cross-Sectoral Perspective on Opportunities and Challenges

Agriculture in the boreal and Arctic regions is perceived as marginal, low intensity and inadequate to satisfy the needs of local communities, but another perspective is that northern agriculture has untapped potential to increase the local supply of food and even contribute to the global food system. Policies across northern jurisdictions target the expansion and intensification of agriculture, contextualized for the diverse social settings and market foci in the north. However, the rapid pace of climate change means that traditional methods of adapting cropping systems and developing infrastructure and regulations for this region cannot keep up with climate change impacts. Moreover, the anticipated conversion of northern cold-climate natural lands to agriculture risks a loss of up to 76% of the carbon stored in vegetation and soils, leading to further environmental impacts. The sustainable development of northern agriculture requires local solutions supported by locally relevant policies. There is an obvious need for the rapid development of a transdisciplinary, cross-jurisdictional, long-term knowledge development, and dissemination program to best serve food needs and an agricultural economy in the boreal and Arctic regions while minimizing the risks to global climate, northern ecosystems and communities

Arctic Energy Technology Development Laboratory

The Arctic Energy Technology Development Laboratory was created by the University of Alaska Fairbanks in response to a congressionally mandated funding opportunity through the U.S. Department of Energy (DOE), specifically to encourage research partnerships between the university, the Alaskan energy industry, and the DOE. The enabling legislation permitted research in a broad variety of topics particularly of interest to Alaska, including providing more efficient and economical electrical power generation in rural villages, as well as research in coal, oil, and gas. The contract was managed as a cooperative research agreement, with active project monitoring and management from the DOE. In the eight years of this partnership, approximately 30 projects were funded and completed. These projects, which were selected using an industry panel of Alaskan energy industry engineers and managers, cover a wide range of topics, such as diesel engine efficiency, fuel cells, coal combustion, methane gas hydrates, heavy oil recovery, and water issues associated with ice road construction in the oil fields of the North Slope. Each project was managed as a separate DOE contract, and the final technical report for each completed project is included with this final report. The intent of this process was to address the energy research needs of Alaska and to develop research capability at the university. As such, the intent from the beginning of this process was to encourage development of partnerships and skills that would permit a transition to direct competitive funding opportunities managed from funding sources. This project has succeeded at both the individual project level and at the institutional development level, as many of the researchers at the university are currently submitting proposals to funding agencies, with some success

Influence of Spatial Scales on the Performance of Saturated Subsurface Flow and Transport Models

Numerical modeling of saturated subsurface flow and transport has been widely used in the past using different numerical schemes such as finite difference and finite element methods. Such modeling often involves discretization of the problem in spatial and temporal scales. The choice of the spatial and temporal scales for a modeling scenario is often not straightforward. For example, a basin-scale saturated flow and transport analysis demands larger spatial and temporal scales than a meso-scale study, which in turn has larger scales compared to a pore-scale study. The choice of spatial-scale is often dictated by the computational capabilities of the modeler as well as the availability of fine-scale data. In this study, we analyze the impact of different spatial scales and scaling procedures on saturated subsurface flow and transport simulations

Multiple Regressive Pattern Recognition Technique: An Adapted Approach for Improved Georesource Estimation

Multiple Regressive Pattern Recognition Technique (MRPRT) is an adapted approach for improved geologic resource estimation. We developed and tested this approach for the Platinum (Pt) bearing region near Goodnews Bay, Alaska, which presents an example of a complex depositional environment. We applied geospatial and pattern recognition methods to assess the spatial distribution of offshore Pt in the Goodnews Bay area from point data collected by various agencies. We used the coefficient of correlation (r) and the Nash-Sutcliffe efficiency (E) to quantitatively assess the degree of accuracy of the estimated Pt distribution. We split the study area, based on trend analysis, into two regions: inside the Bay and outside the Bay. We could not obtain appreciable estimates from the geospatial and pattern recognition methods. Using MRPRT, we were able to improve r from 0.57 to 0.93 and the E from 28.31 to 92.91 inside the Bay. We achieved improvement in r from 0.55 to 0.61 and E from 28.46 to 34.52 outside the Bay. The reasons for a non-significant improvement outside the Bay have been discussed. The results indicate that the proposed MRPRT has wide application potential in georesource estimation where input data is often scarce. © 2011 International Association for Mathematical Geology

FDA approved L-type channel blocker Nifedipine reduces cell death in hypoxic A549 cells through modulation of mitochondrial calcium and superoxide generation

As hypoxia is a major driver for the pathophysiology of COVID-19, it is crucial to characterize the hypoxic response at the cellular and molecular levels. In order to augment drug repurposing with the identification of appropriate molecular targets, investigations on therapeutics preventing hypoxic cell damage is required. In this work, we propose a hypoxia model based on alveolar lung epithelial cells line using chemical inducer, CoCl2 that can be used for testing calcium channel blockers (CCBs). Since recent studies suggested that CCBs may reduce the infectivity of SARS-Cov-2, we specifically select FDA approved calcium channel blocker, nifedipine for the study. First, we examined hypoxia-induced cell morphology and found a significant increase in cytosolic calcium levels, mitochondrial calcium overload as well as ROS production in hypoxic A549 cells. Secondly, we demonstrate the protective behaviour of nifedipine for cells that are already subjected to hypoxia through measurement of cell viability as well as 4D imaging of cellular morphology and nuclear condensation. Thirdly, we show that the protective effect of nifedipine is achieved through the reduction of cytosolic calcium, mitochondrial calcium, and ROS generation. Overall, we outline a framework for quantitative analysis of mitochondrial calcium and ROS using 3D imaging in laser scanning confocal microscopy and the open-source image analysis platform ImageJ. The proposed pipeline was used to visualize mitochondrial calcium and ROS level in individual cells that provide an understanding of molecular targets. Our findings suggest that the therapeutic value of nifedipine may potentially be evaluated in the context of COVID-19 therapeutic trials. © 202