Insights From Supply Chain Disruptions in the COVID-19 Era

The COVID-19 pandemic has created a devastating impact on supply chains. Especially, transportation disruptions, the slowdown in manufacturing, supply-demand imbalances, operational inefficiency in last-mile, and deficiencies in dealing with the crisis can be seen as main headings. This chapter aims to reveal the problems and learn lessons in these areas where significant risks are faced. During the COVID era, the need for resilient supply chains that are not affected by instantaneous changes has come to the fore. Accordingly, the second aim of the chapter is to offer solutions toward the short, medium, and long terms of the first-mile, production, and last-mile processes as enhancing the responsiveness of supply chains by the elements of supply chain resilience. This study is prepared as a review article in an exploratory approach through the supply chain literature and current practical examples. As a result of the study, digital-intensive business models, collaborative network design, and sustainability are highlighted as the main concepts to reach more resilient networks.

Aberrant modularity and lower resiliency of structural covariance network in first-episode antipsychotic-naive psychoses

Objective: Structural brain alterations are consistently observed in schizophrenia. However, divergent findings suggest that often-observed regions exist within a network of susceptible regions. We conducted structural covariance analysis of multiple morphometric features of 358 regions from 79 first-episode anti-psychotic-naive psychosis patients (FEAP) and 68 healthy controls to investigate network differences. Methods: Using graph theoretic methods, we investigated structural covariance network of Freesurfer-derived cortical gray matter volumes, thickness, curvature, and surface area using the Brain Connectivity Toolbox within MATLAB, compared network modularity using the Community Detection Toolbox within MATLAB, and examined the resilience of the network using simulated attacks. Results: FEAP showed decreased heterogeneity of cortical volumes compared to controls which was driven by decreased heterogeneity of cortical thickness but not surface area. Reduced morphological heterogeneity was associated with less differentiated community structure in FEAP compared to controls. FEAP patients, in general, showed less resilient networks that were more vulnerable to attacks on fewer nodes compared to healthy subjects. Conclusions: Our findings of decreased heterogeneity may be associated with FEAP-related pathology since the impact of illness chronicity and treatment are minimized. Contribution of cortical thickness but not surface area covariance network suggests that neurodevelopmental processes affecting the thickness rather than the surface area may be pathophysiologically more significant.

Substrate and cell fusion influence on slime mold network dynamics

The acellular slime mold Physarum polycephalum provides an excellent model to study network formation, as its network is remodelled constantly in response to mass gain/loss and environmental conditions. How slime molds networks are built and fuse to allow for efficient exploration and adaptation to environmental conditions is still not fully understood. Here, we characterize the network organization of slime molds exploring homogeneous neutral, nutritive and adverse environments. We developed a fully automated image analysis method to extract the network topology and followed the slime molds before and after fusion. Our results show that: (1) slime molds build sparse networks with thin veins in a neutral environment and more compact networks with thicker veins in a nutritive or adverse environment; (2) slime molds construct long, efficient and resilient networks in neutral and adverse environments, whereas in nutritive environments, they build shorter and more centralized networks; and (3) slime molds fuse rapidly and establish multiple connections with their clone-mates in a neutral environment, whereas they display a late fusion with fewer connections in an adverse environment. Our study demonstrates that slime mold networks evolve continuously via pruning and reinforcement, adapting to different environmental conditions.