Social networks in COVID-19 America: Americans remotely together but politically apart

The COVID-19 pandemic has presented a social dilemma; "social distancing" was required to stop the spread of disease, but close social contacts were needed more than ever to collectively overcome the unprecedented challenges of the crisis. How did Americans mobilize their social ties in response to the pandemic? Drawing from a nation-wide daily online survey of 36,345 Americans from April 2020 through April 2021, we examine the characteristics of Americans' core networks within which people discuss "important matters." Comparing the COVID-19 networks to those previously collected in eight national core network surveys from 1985 to 2016, we observe remarkable stability in the size and relationship composition of core networks during COVID-19. In contrast to the robust nature of core networks, we discover a significant rise in racial homophily among kin ties, and political homophily among non-kin ties. Simultaneously, our study reveals a significant surge in the adoption of remote communication technology to connect with individuals who are geographically distant. We demonstrate that the changing mode of communication contributes to increases in racial and political homophily. These results suggest that the COVID-19 pandemic may bring people remotely together but only with the like-minded, deepening social divides in American society

A Comparison of Image Aligning and Correcting Software with an Unmanned Aerial System

In the past few decades, many kinds of UAS for image acquisition have been developed. But software for image aligning and correcting is mostly high-cost commercial. This problem caused the cost-problem in using UAS. Nowadays, a variety of software, not only commercial but also open-source, provides powerful image processing tool. There are a number of software to support image processing. In this study,five popular programs are tested for comparison. The goal of this study is to compare popular open-source software based on the ease use, overall accuracy and processing time for chunk of images from UAS

Too Much Is Too Bad: The Strategic Complementarity Effect of Unrelated News Media on Cryptocurrency Markets

2

Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers

<p>The COVID-19 pandemic, with millions of Americans compelled to stay home and work remotely, presented an opportunity to explore the dynamics of social relationships in a predominantly remote world. Using the 1972-2022 General Social Surveys, we found that the pandemic significantly disrupted the patterns of social gatherings with family, friends, and neighbors, but only momentarily. Drawing from the nationwide ego-network surveys of 41,033 Americans from 2020 to 2022, we found that the size and composition of core networks remained stable, though political homophily increased among non-kin relationships compared to previous surveys between 1985 and 2016. Critically, heightened remote communication during the initial phase of the pandemic was associated with increased interaction with the same partisans, though political homophily decreased during the later phase of the pandemic when in-person contacts increased. These results underscore the crucial role of social institutions and social gatherings in promoting spontaneous encounters with diverse political backgrounds.</p&gt

Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers

<p>The COVID-19 pandemic, with millions of Americans compelled to stay home and work remotely, presented an opportunity to explore the dynamics of social relationships in a predominantly remote world. Using the 1972-2022 General Social Surveys, we found that the pandemic significantly disrupted the patterns of social gatherings with family, friends, and neighbors, but only momentarily. Drawing from the nationwide ego-network surveys of 41,033 Americans from 2020 to 2022, we found that the size and composition of core networks remained stable, though political homophily increased among non-kin relationships compared to previous surveys between 1985 and 2016. Critically, heightened remote communication during the initial phase of the pandemic was associated with increased interaction with the same partisans, though political homophily decreased during the later phase of the pandemic when in-person contacts increased. These results underscore the crucial role of social institutions and social gatherings in promoting spontaneous encounters with diverse political backgrounds.</p&gt

Practical Operation Strategies for Energy Storage System under Uncertainty

Recent advances in battery technologies have reduced the financial burden of using the energy storage system (ESS) for customers. Peak cut, one of the benefits of using ESS, can be achieved through proper charging/discharging scheduling of ESS. However, peak cut is sensitive to load-forecasting error, and even a small forecasting error may result in the failure of peak cut. In this paper, we propose a two-phase approach of day-ahead optimization and real-time control for minimizing the total cost that comes from time-of-use (TOU), peak load, and battery degradation. In day-ahead optimization, we propose to use an internalized pricing to manage peak load in addition to the cost from TOU. The proposed method can be implemented by using dynamic programming, which also has an advantage of accommodating the state-dependent battery degradation cost. Then in real-time control, we propose a concept of marginal power to alleviate the performance loss incurred from load-forecasting error and mimic the offline optimal battery scheduling by learning from load-forecasting error. By exploiting the marginal power, real-time ESS charging/discharging power gets close to the offline optimal battery scheduling. Case studies show that under load-forecasting uncertainty, the peak power using the proposed method is only 22.4% higher than the offline optimal peak power, while the day-ahead optimization has 76.8% higher peak power than the offline optimal power. In terms of profit, the proposed method achieves 77.0% of the offline optimal profit while the day-ahead method only earns 19.6% of the offline optimal profit, which shows the substantial improvement of the proposed method

Engineering Biology to Construct Microbial Chassis for the Production of Difficult-to-Express Proteins

A large proportion of the recombinant proteins manufactured today rely on microbe-based expression systems owing to their relatively simple and cost-effective production schemes. However, several issues in microbial protein expression, including formation of insoluble aggregates, low protein yield, and cell death are still highly recursive and tricky to optimize. These obstacles are usually rooted in the metabolic capacity of the expression host, limitation of cellular translational machineries, or genetic instability. To this end, several microbial strains having precisely designed genomes have been suggested as a way around the recurrent problems in recombinant protein expression. Already, a growing number of prokaryotic chassis strains have been genome-streamlined to attain superior cellular fitness, recombinant protein yield, and stability of the exogenous expression pathways. In this review, we outline challenges associated with heterologous protein expression, some examples of microbial chassis engineered for the production of recombinant proteins, and emerging tools to optimize the expression of heterologous proteins. In particular, we discuss the synthetic biology approaches to design and build and test genome-reduced microbial chassis that carry desirable characteristics for heterologous protein expression

Remote machine mode detection in cold forging using vibration signal

Detecting machine mode can allow smarter process monitoring systems and more accurate fault prediction without external information. A remote machine monitoring system was installed on a cold heading machine in the factory of an automotive fastener manufacturing company. The process monitoring system was non-intrusive and was designed to measure vibration. The end goal of the study was to predict tool wear, but part classification was required first, as the machine produced multiple parts which produced different vibration signals. The collected vibration data was processed using wavelet transform and passed through a convolutional neural network for part classification. This method achieved part classification accuracy as high as 86% when looking at data for a 1-month period. The results show that meaningful classification features are present in the data using the process monitoring system as designed.11Nscopu

Snowtography quantifies effects of forest cover on net water input to soil at sites with ephemeral or stable seasonal snowpack in Arizona, USA

Forested, snow-dominated watersheds provide a range of ecosystem services including water supply, carbon sequestration, habitat and recreation. While hydrologic partitioning has been well-studied in watersheds with stable seasonal snowpack, less is known about watersheds with ephemeral snowpack. Furthermore, drought-related disturbances and/or management practices are altering vegetation cover in many forests, with unknown and potentially different, consequences for stable seasonal versus ephemeral snowpacks. This study quantifies net water input (NWI) to soil for two sites with contrasting stable seasonal and ephemeral snowpacks, respectively, for three water years in Arizona, USA. Observations include a network of automated cameras and graduated snow stakes (snowtography) deployed across gradients of forest structure, airborne lidar maps of topography and forests and SNOTEL station records. Given the importance of mixed-phase precipitation in ephemeral snowpack watersheds, an algorithm is developed to distinguish among snowfall and rainfall that does/does not contribute to snowpack mass. Finally, existing canopy interception and snowpack models are used to estimate how NWI varies with canopy cover. At the ephemeral snowpack site, increasing canopy cover reduces NWI amount and advances its seasonal timing less strongly than at the stable seasonal snowpack site. Interestingly, canopy reduces NWI duration at the ephemeral site but prolongs it at the stable seasonal snowpack site. These effects are more important in a cool/wet and average year than a warm/dry year. Understanding differences between canopy impacts on amount, timing and duration of NWI for areas with ephemeral versus stable seasonal snowpack is increasingly important as the number of watersheds with ephemeral snowpack grows.U.S. Forest ServicePublic domain articleThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]