Identifying Temporal Trends in Treated Sagebrush Communities Using Remotely Sensed Imagery

The sagebrush shrub steppe ecosystem is of great concern to researchers, conservationists, and the general public because of the documented declines associated with it. Monitoring in the past has generally been point-based and lacking in long-term data. To overcome these deficiencies, an automated method of monitoring was developed using GIS and remote sensing. Geospatial layers of vegetation, soils, fire history, roads, streams, and springs were acquired and processed to characterize selected monitoring locations. A temporal set of Landsat satellite imagery for the past 30 years was normalized to reduce the effects of sun angle, haze, and sensor change. After normalization, a Tasseled Cap Transformation was adapted with local coefficients to provide a landscape metric which was sensitive to actual ground conditions and meaningful at management level. The Tasseled Cap outputs of brightness and greenness are a relative measure of bare ground and plant productivity, respectively. When measured over time, brightness and greenness provided diagnostic trends and condition of treated big sagebrush communities

Agency Delays: How a Principal-Agent Approach Can Inform Judicial and Executive Branch Review of Agency Foot-Dragging

Article published in the Geo. Washington Law Review

Regularized Neural Detection for One-Bit Massive MIMO Communication Systems

Detection for one-bit massive MIMO systems presents several challenges especially for higher order constellations. Recent advances in both model-based analysis and deep learning frameworks have resulted in several robust one-bit detector designs. Our work builds on the current state-of-the-art gradient descent (GD)-based detector. We introduce two novel contributions in our detector design: (i) We augment each GD iteration with a deep learning-aided regularization step, and (ii) We introduce a novel constellation-based loss function for our regularized DNN detector. This one-bit detection strategy is applied to two different DNN architectures based on algorithm unrolling, namely, a deep unfolded neural network and a deep recurrent neural network. Being trained on multiple randomly sampled channel matrices, these networks are developed as general one-bit detectors. The numerical results show that the combination of the DNN-augmented regularized GD and constellation-based loss function improve the quality of our one-bit detector, especially for higher order M-QAM constellations.Comment: Initially submitted to IEEE TMLCN in October 202

Inside the Agency Class Action

Article published in the Yale Law Journal

Real-Time Operating System/360

RTOS has a cost savings advantage for real-time applications, such as those with random inputs requiring a flexible data routing facility, display systems simplified by a device independent interface language, and complex applications needing added storage protection and data queuing

Microstructure-guided numerical simulations to predict the thermal performance of a hierarchical cement-based composite material

This paper presents a microstructure-guided numerical homogenization technique to predict the effective thermal conductivity of a hierarchical cement-based material containing phase change material (PCM)-impregnated lightweight aggregates (LWA). Porous inclusions such as LWAs embedded in a cementitious matrix are filled with multiple fluid phases including PCM to obtain desirable thermal properties for building and infrastructure applications. Simulations are carried out on realistic three-dimensional microstructures generated using pore structure information. An inverse analysis procedure is used to extract the intrinsic thermal properties of those microstructural components for which data is not available. The homogenized heat flux is predicted for an imposed temperature gradient from which the effective composite thermal conductivity is computed. The simulated effective composite thermal conductivities are found to correlate very well with experimental measurements for a family of LWA-PCM composites considered in the paper. Comparisons with commonly used analytical homogenization models show that the microstructure-guided simulation approach provides superior results for composites exhibiting large property contrast between phases. By linking the microstructure and thermal properties of hierarchical materials, an efficient framework is available for optimizing the material design to improve thermal efficiency of a wide variety of heterogeneous materials

Addressing the evidence gap in the economic and social benefits of civil registration and vital statistics systems: a systematic review

Objectives: Considering the aspiration embedded in the Sustainable Development Goals to Leave No One Behind by 2030, civil registration and vital statistics systems have an essential role in providing reliable, up-to-date information to monitor the progress. Thus, the aim of this systematic review is to compile empirical evidence on the benefits of a functioning civil registration and vital statistics system. Methods: Selected databases were systematically searched until 2019. Key experts were also contacted for relevant literature. The review process was managed with the software EPPI-Reviewer and followed standard methods for systematic reviews. Results: A total of 18 studies were included. The findings revealed that having birth, death, and/or marriage registration, and vital statistics were associated with access to rights and protection, positive impact on economic and health outcomes, and increased access to education. Conclusion: The present review supports the idea that systemic approaches strengthen civil registration and vital statistics systems due to the cumulative effects of vital events' registration. Ensuring appropriate systems for civil registration will have an impact not only on the individuals but also on the generations to come

Expression Pattern of the Alpha-Kafirin Promoter Coupled with a Signal Peptide from Sorghum bicolor L. Moench

Regulatory sequences with endosperm specificity are essential for foreign gene expression in the desired tissue for both grain quality improvement and molecular pharming. In this study, promoters of seed storage α-kafirin genes coupled with signal sequence (ss) were isolated from Sorghum bicolor L. Moench genomic DNA by PCR. The α-kafirin promoter (α-kaf) contains endosperm specificity-determining motifs, prolamin-box, the O2-box 1, CATC, and TATA boxes required for α-kafirin gene expression in sorghum seeds. The constructs pMB-Ubi-gfp and pMB-kaf-gfp were microprojectile bombarded into various sorghum and sweet corn explants. GFP expression was detected on all explants using the Ubi promoter but only in seeds for the α-kaf promoter. This shows that the α-kaf promoter isolated was functional and demonstrated seed-specific GFP expression. The constructs pMB-Ubi-ss-gfp and pMB-kaf-ss-gfp were also bombarded into the same explants. Detection of GFP expression showed that the signal peptide (SP)::GFP fusion can assemble and fold properly, preserving the fluorescent properties of GFP