Integrated twitter analysis to distinguish systems thinkers at various levels: a case study of COVID-19.

Systems Thinking (ST) has become essential for practitioners and experts when dealing with turbulent and complex environments. Twitter medium harbors social capital including systems thinkers, however there are limited studies available in the extant literature that investigate how experts' systems thinking skills, if possible at all, can be revealed within Twitter analysis. This study aims to reveal systems thinking levels of experts from their Twitter accounts represented as a network. Unraveling of latent Twitter network clusters ensues the centrality analysis of their follower networks inferred in terms of systems thinking dimensions. COVID-19 emerges as a relevant case study to investigate the relationship between COVID-19 experts' Twitter network and their systems thinking capabilities. A sample of 55 trusted expert Twitter accounts related to COVID-19 has been selected for the current study based on the lists from Forbes, Fortune, and Bustle. The Twitter network has been constructed based on the features extracted from their Twitter accounts. Community detection reveals three distinct groups of experts. In order to relate system thinking qualities to each group, systems thinking dimensions are matched with the follower network characteristics such as node-level metrics and centrality measures including degree, betweenness, closeness and Eigen centrality. Comparison of the 55 expert follower network characteristics elucidates three clusters with significant differences in centrality scores and node-level metrics. The clusters with a higher, medium, lower scores can be classified as Twitter accounts of Holistic thinkers, Middle thinkers, and Reductionist thinkers, respectfully. In conclusion, systems thinking capabilities are traced through unique network patterns in relation to the follower network characteristics associated with systems thinking dimensions.

Role of systems engineering attributes in enhancing supply chain resilience: Healthcare in context of COVID-19 pandemic.

In recent years, the area of supply chain resilience has received heightened attention as a plethora of new risks, ranging from climate change to cybersecurity and infectious diseases, have emerged as serious threats to operational performance. The COVID-19 pandemic, in particular, has exposed the fragility of global supply chains in many sectors. Given these concerns, supply chain networks, including those designed based on the principles of lean philosophies, are increasingly being re-examined as firms grapple with the challenge of strengthening the capacity to withstand, absorb, and rebound from unexpected shocks. Addressing the urgency of this imperative, this study presents a novel framework-based on theories and concepts in the systems engineering (SE) and supply chain resilience domains to enhance the resilience implementation capabilities that are lacking in many of today's firms. By applying a Grounded Theory methodology, this study develops and validates a conceptual model that identifies six core attributes fundamental to developing resilience capabilities in complex supply chains. The study concludes by providing examples of, and insights into, the role of these attributes in building supply chain resilience.

An analysis of the impact of policies and political affiliation on racial disparities in COVID-19 infections and deaths in the USA.

This research aimed to quantify the racial disparities of COVID-19 for primarily positive tests and deaths across the US and territories individually and collectively. The first research hypothesis investigated whether positive cases and death rates were higher for people of color (POC) than the White ethnic group. The second hypothesis examined whether there is a significant difference in confirmed positive cases and death rates between ethnic groups across the US and territories. The third hypothesis investigated if political party control and governmental policies affected the number of cases and death proportion rates across ethnic groups. The research findings suggest that POC positive cases and death rates were higher in some states. Black ethnic groups were dying at a high rate in the southeastern states, the District of Columbia, and in Maryland. Specifically, in the District of Columbia, the death rate is five times higher than the White ethnic group. For Latinx ethnic groups, the high cases and death rates have mostly occurred in western states, including Texas. The Latinx ethnic group accounted for half the total deaths in Texas and California. The Latinx ethnic group death rate is higher than the White ethnic group in four states: Texas, California, New Mexico, and the District of Columbia. The research findings also show that the rate of deaths and cases per ethnic group for policies and political factors were significant except for the mask mandate policy. Based on the analyzed data, mask mandates were not a factor in the cases or death rates of any ethnic group. Each state's policies for bars, curfews, public schools, and travel-along with legislative party control-had the most influences across ethnic groups. The research results for the death rates and number of cases due to these implemented policies varied between ethnic groups.

Secondary spinal cord changes and spinal deformity following traumatic spinal cord injury.

Secondary spinal cord changes can follow spinal cord injuries (SCIs). This retrospective study was to uncover the chronic secondary changes that affect the spinal cord following severe injuries and to evaluate the influence of residual spinal deformity in the development of posttraumatic spinal cord changes. Fifty-eight patients (39 male, 19 female) with complete traumatic SCI and recent Magnetic resonance imaging (MRI) follow-up were reviewed retrospectively. A minimum of 2 years duration between trauma and MRI study was required (mean 2.9 years [2.1-4.7]). Two groups of patients were formed: with spinal deformity (and or spinal canal compromise) and without spinal deformity (and or spinal canal compromise). MRI of the injured spine demonstrated four major types of spinal cord changes; these are spinal cord atrophy, myelomalacia, syrinx, and focal cyst formation. The correlation of these changes to the presence of spinal deformity and or spinal canal compromise was also studied. Twenty-three patients (40%) of the studied population had more than 30° kyphosis and or 50% compromise of the spinal canal. Chronic spinal cord changes occurred in 25 patients (43%), 17 of these changes occurred in patients with spinal deformity and the remaining 8 occurred in patients without spinal deformity or canal compromise (p ≤ .05). The prevalence of spinal cord atrophy and focal cysts was significantly higher in patients with residual deformity and or spinal canal compromise (p ≤ .05). The authors recommend proper spinal cord decompression and fixation for patients with complete SCI to reduce the chance of secondary SCI.

Leveraging a Bayesian network approach to model and analyze supplier vulnerability to severe weather risk: A case study of the U.S. pharmaceutical supply chain following Hurricane Maria.

The United States government has identified the health care sector as part of the critical infrastructure for homeland security to protect citizens against health risks arising from terrorism, natural disasters, and epidemics. Citizens also have expectations about the role that health care plays in enjoying a good quality of life, by providing response systems to handle emergencies and other illness situations adequately. Among the systems required to supportdesired performance levels is a robust and resilient pharmaceutical supply chain that is free of disruption. Shortages of drugs place undue pressure on healthcare providers to devise alternative approaches to administer patient care. With climate change expected to result in increasingly severe weather patterns in the future, it is critical that logistics engineers understand the impact that a catastrophic weather event could have on supply chain disruption to facilitate the design of supply systems that are robust and resilient. This study investigates the main causal and intermediate events that led to risk propagation in, and disruption of, the U.S. pharmaceutical supply chain following Hurricane Maria. A causality Bayesian model is developed to depict linkages between risk events and quantify the associated cumulative risk. The quantification is further examined through different advanced techniques such as predictive inference reasoning and sensitivity analysis. The general interpretation of these analyses suggests that port resilience is imperative to pharmaceutical supply chain performance in the case of Puerto Rico.

The Impact of Participants' Anthropometry on Muscle Activation Levels While Interacting with the Level of Expertise, Task Type, and Single Muscles.

In this research paper, we implemented a mixed factor design in order to investigate the effect of four anthropometries: height, weight, lower-arm dimensions, and upper-arm dimensions on the muscle activation level of participants when interacting with three types of moderators: experiment expertise, task type, and muscle type. The research paper focused on two levels of expertise (novice and expert), two tasks (deck-building and picket installation), and four arm muscles (Brachioradialis (BR), Extensor Carpi Ulnaris (ECU), Flexor Carpi Radialis (FCR), and Flexor Carpi Ulnaris (FCU)), which resulted in 16 (2 × 2 × 4) groups. For each of the 16 groups, the data were analyzed in order to investigate the relationship between the four anthropometries and the four muscle activation levels of the participants. Amos software (IBM, Armonk, NY, USA), along with multiple group structural equation modeling, was used to test a total of 16 direct relationships, as well as the moderation effects in the designed experiment. The results show that the participants' expertise can moderate the relationship between their height and muscle activation levels, the relationship between their weight and muscle activation levels, and the relationship between their lower arm dimensions and muscle activation levels. Moreover, the findings of this research paper demonstrate that the relationship between the lower arm dimensions and muscle activation levels, and the relationship between weight and muscle activation levels are moderated by the type of muscle used by the participants (i.e., BR, ECU, FCR, and FCU).

Structural, Elastic, Electronic and Optical Properties of SrTMO3 (TM = Rh, Zr) Compounds: Insights from FP-LAPW Study.

The structural, mechanical, electronic and optical properties of SrTMO3 (TM = Rh, Zr) compounds are investigated by using first principle calculations based on density functional theory (DFT). The exchange-correlation potential was treated with the generalized gradient approximation (GGA) for the structural properties. Moreover, the modified Becke-Johnson (mBJ) approximation was also employed for the electronic properties. The calculated lattice constants are in good agreement with the available experimental and theoretical results. The elastic constants and their derived moduli reveal that SrRhO3 is ductile and SrZrO3 is brittle in nature. The band structure and the density of states calculations with mBJ-GGA predict a metallic nature for SrRhO3 and an insulating behavior for SrZrO3. The optical properties reveal that both SrRhO3 and SrZrO3 are suitable as wave reflectance compounds in the whole spectrum for SrRhO3 and in the far ultraviolet region (FUV) for SrZrO3.