The Role of Economic Freedom in Interpreting Corruption Perception

The main purpose of the study is to examine the nexus between corruption and economic freedom to determine the most influencing factors to be focused on to reduce corruption. With this aim, two different machine learning algorithms are performed to find out the single effect, two-way, and three-way interaction effects of factors affecting corruption. As a result of the analysis, tax burden, government integrity, and government spending are the main indicators to be focused on to improve corruption steadily. Besides, critical thresholds of the tax burden, government integrity, and government spending are 83.3, 50.9, and 40.6, respectively. Since there are a limited number of studies to predict corruption by machine learning algorithms in the extant literature, this research provides highly detailed information to policy-makers where they can focus on reducing corruption perception.

Network percolation reveals adaptive bridges of the mobility network response to COVID-19

Human mobility is crucial to understand the transmission pattern of COVID-19 on spatially embedded geographic networks. This pattern seems unpredictable, and the propagation appears unstoppable, resulting in over 350,000 death tolls in the U.S. by the end of 2020. Here, we create the spatiotemporal inter-county mobility network using 10 TB (Terabytes) trajectory data of 30 million smart devices in the U.S. in the first six months of 2020. We investigate the bond percolation process by removing the weakly connected edges. As we increase the threshold, the mobility network nodes become less interconnected and thus experience surprisingly abrupt phase transitions. Despite the complex behaviors of the mobility network, we devised a novel approach to identify a small, manageable set of recurrent critical bridges, connecting the giant component and the second-largest component. These adaptive links, located across the United States, played a key role as valves connecting components in divisions and regions during the pandemic. Beyond, our numerical results unveil that network characteristics determine the critical thresholds and the bridge locations. The findings provide new insights into managing and controlling the connectivity of mobility networks during unprecedented disruptions. The work can also potentially offer practical future infectious diseases both globally and locally.

Strengthening External Emergency Assistance for Managing Extreme Events, Systemic, and Transboundary Risks in Asia

External emergency assistance (EEA) provided in the aftermath of a disaster has costs and benefits to the donor and recipient countries. Donors benefit from quick recovery feedback effects from the trade and cultural links, and recipient countries have additional resources to manage the emergency. However, EEA costs could outweigh the benefits. Costs include dependency, low development of risk reduction capacity, and staff burdened with managing the assistance as opposed to managing the recovery. Current efforts to reduce dependency on EEA are not sufficient; they are based on limited past experiences with extreme events and are not based on the understanding of future risks. In this article, we present the concept of a climate fragility risk index showing factors that affect a country’s predisposition to be fragile to climate change threats and we suggest that countries with a high climate fragility risk index tend to depend on EEA. Further, the article presents the concept of critical thresholds for extreme events as a metric to identify possible dependency on EEA. In addition, based on expert and policy consultations organized in the Philippines and Pakistan, we identify measures that can enhance the effectiveness of EEA including targeted EEA provision, better integration of lessons learned from the relief stage into the rest of the DRR operations, proper documentation of past assistance experiences and consideration of these lessons for the improvement of EEA in the future, as well as developing tools such as critical threshold concepts that can better guide the donor and recipient countries on more effective delivery of EEA.

Morphological control of receptor-mediated endocytosis

Receptor-mediated endocytosis is the primary process for nanoparticle uptake in cells and one of the main entry mechanisms for viral infection. The cell membrane adheres to the particle (nanoparticle or virus) and then wraps it to form a vesicle delivered to the cytosol. Previous findings identified a minimum radius for a spherical particle below which endocytosis cannot occur. This is due to the insufficient driving force, from receptor-ligand affinity, to overcome the energy barrier created by membrane bending. In this paper, we extend this result to the case of clathrin-mediated endocytosis, which is the most common pathway for virus entry. Moreover, we investigate the effect of ligand inhibitors on the particle surface, motivated by viral an- tibodies, peptides or phage capsids nanoparticles. We determine the necessary conditions for endocytosis by considering the additional energy barrier due to the membrane bending to wrap such inhibiting protrusions. We find that the density and size of inhibitors determine the size range of internalized particles, and endo- cytosis is completely blocked above critical thresholds. The assembly of a clathrin coat with a spontaneous curvature increases the energy barrier and sets a maximum particle size (in agreement with experimental observations on smooth particles). Our investigation suggests that morphological considerations can inform the optimal design of neutralizing viral antibodies and new strategies for targeted nanomedicine.

Tristable Properties in Electrostatically Actuated Initially Curved Coupled Micro Beams

A limit point behaviour analysis of a metastructure, composed of two double clamped, initially curved beams, coupled via a rigid truss at their respective centres, is carried out when subjected to a distributed electrostatic load. The analysis is based on a reduced order (RO) model resulting from Galerkin’s decomposition, with symmetric buckling modes taken as the base functions, for either beam. All solutions employed the implicit arc-length “Riks” method to accommodate for winding equilibrium paths, while validation of the said results were carried out against finite differences (FD) direct solutions. In addition, local stability analysis via the energy method, conducted on the primary beam was instrumental in clarifying the role of the various extremum points by characterising which branches are stable, and which are not. The combined analysis has shown that the driving beam, which directly encounters the load, is able to possess bistable as well as tristable properties, provided that the metastructure meets certain geometrical parameters. Several variations of tristability are disclosed in the study. The analysis indicates that a model with at least three degrees of freedom (DOF) is needed to predict such configurations, as well as the various critical thresholds, with reasonable errors of around one percent when compared against FD. In so doing, the model can be used to provide static characterisation of the structure.

Deciphering meteorological influencing factors for Alpine rockfalls: a case study in Aosta Valley

This study exploited the historical rockfall inventory and the meteorological stations database of Mont Cervin and Mont Emilius Mountain Communities (Aosta Valley, northern Italy) to decipher relationships between climate processes, typical of mountain environments and rockfall phenomena. The period from 1990 to 2018 was selected as reference to perform the analysis. Climate processes were translated into four climate indices, namely short-term rainfall (STR), effective water inputs (EWI, including both rainfall and snow melting), wet and dry episodes (WD) and freeze-thaw cycles (FT). The comparison between climate indices values at each rockfall occurrence and the statistical distributions describing the whole indices dataset allowed to define not ordinary climatic conditions for each index and their influence on rockfall occurrence. Most of the events analysed (>95% out of 136) occurred in correspondence of the defined not ordinary climatic conditions for one or for a combination of the indices. The relationships between rockfalls and climate showed a seasonality. In spring, most of the events resulted to be connected to FT (70%) while in autumn to EWI (49%). The relative seasonal importance of WD reached its maximum in summer with 23% of the events related to this index alone. Based on these results, different strategies to define empirical critical thresholds for each climate index were explored, in order to make them valid for the whole study area. A preliminary exploratory analysis of the influence of high temperatures and temperature gradients was carried out for some summertime rockfalls, not correlated to the other investigated indices. The presented approach is exportable in neighbouring regions, given the availability of a dated rockfall dataset, and could be adapted to include different processes.