How rating agencies could support African governments in overcoming debt crises

An effective framework for restructuring global debt remains an urgent need for Africa, which could be supported by changing sovereign rating practices. By integrating the severity of financial losses in a default episode, rating agencies could better serve investors, while also incentivising overleveraged governments to seek debt relief. As interest rates rise, the world economy slows and food prices mount, procrastination around debt relief would result in avoidable humanitarian crises

Evolution and Evaluation of the Penalty Method for Alternative Graphs

Computing meaningful alternative routes in a road network is a complex problem -- already giving a clear definition of a best alternative seems to be impossible. Still, multiple methods describe how to compute reasonable alternative routes, each according to their own quality criteria. Among these methods, the penalty method has received much less attention than the via-node or plateaux based approaches. A mayor cause for the lack of interest might be the unavailability of an efficient implementation. In this paper, we take a closer look at the penalty method and extend upon its ideas. We provide the first viable implementation --suitable for interactive use-- using dynamic runtime adjustments to perform up to multiple orders of magnitude faster queries than previous implementations. Using our new implementation, we thoroughly evaluate the penalty method for its flaws and benefits

HOW CAN DIGITAL START-UPS SUCCESSFULLY RECRUIT IT PROFESSIONALS?

We investigate how digital start-ups can successfully recruit senior IT professionals. This is a challenge, which many young companies face due to their liabilities of newness and smallness but also due to market characteristics such as talent scarcity. We highlight success factors throughout the whole process of senior IT recruiting in a start-up context using an in-depth single case study. Our results suggest that the use of state-of-the-art technology and free choice of hardware are very important recruiting factors. Using multiple platforms to recruit first highly qualified candidates attracts further good talents. Not only typical recruiting platforms are important, but our results show that the use of expert online forums by already employed IT staff can send important signals, strengthen ties with potential candidates, and enable referrals. The recruiting process itself must be fast and interviews should communicate the appraisal of seniority, learning opportunities and management accessibility

Who can be nudged? Examining nudging effectiveness in the context of need for cognition and need for uniqueness

In the last decade, there has been a growing research focus on the subtle modifications of choice architecture that have strong effects on consumer behavior and are subsumed under the term nudging. There is still little research, however, on how different nudges influence individuals with different personality characteristics. An experimental online shopping scenario is used to test whether a customer\u27s Need for Cognition and Need for Uniqueness moderate the effectiveness of two of the most prominent nudges—defaults and social influence. Two experiments with samples stratified by age, gender, and education (total N = 1,561) reveal that defaults and social influence have the predicted impact on a customer\u27s decision. Across both studies, nudge effectiveness was partially impacted by Need for Cognition and not impacted at all by Need for Uniqueness. These findings imply that both types of nudges are strong and robust techniques to influence consumer decision‐making and are effective across different levels of consumer\u27s Need for Cognition or Need for Uniqueness

Towards Connecting Control to Perception: High-Performance Whole-Body Collision Avoidance Using Control-Compatible Obstacles

One of the most important aspects of autonomous systems is safety. This includes ensuring safe human-robot and safe robot-environment interaction when autonomously performing complex tasks or in collaborative scenarios. Although several methods have been introduced to tackle this, most are unsuitable for real-time applications and require carefully hand-crafted obstacle descriptions. In this work, we propose a method combining high-frequency and real-time self and environment collision avoidance of a robotic manipulator with low-frequency, multimodal, and high-resolution environmental perceptions accumulated in a digital twin system. Our method is based on geometric primitives, so-called primitive skeletons. These, in turn, are information-compressed and real-time compatible digital representations of the robot's body and environment, automatically generated from ultra-realistic virtual replicas of the real world provided by the digital twin. Our approach is a key enabler for closing the loop between environment perception and robot control by providing the millisecond real-time control stage with a current and accurate world description, empowering it to react to environmental changes. We evaluate our whole-body collision avoidance on a 9-DOFs robot system through five experiments, demonstrating the functionality and efficiency of our framework.Comment: Accepted for publication at 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2023

Three-Dimensional Digital Evaluation of the Fit of Endocrowns Fabricated from Different CAD/CAM Materials

Purpose A wide variety of CAD/CAM materials are available for single‐tooth restorations. CAD/CAM material characteristics are different and may influence CAM fabrication accuracy. There is no study investigating the influence of different CAD/CAM materials on the final fit of the restoration. The aim of this study was to evaluate the fit of endocrowns fabricated from different CAD/CAM materials using a new 3D evaluation method with an intraoral scanning system. The null hypothesis was that there are no significant differences for the fitting accuracy of different CAD/CAM materials. Materials and Methods Preparation for an endocrown was performed on a maxillary right first molar on a typodont, and restorations were fabricated with a chairside CAD/CAM system (CEREC Omnicam, MCXL). Three groups using three different CAD/CAM materials were established (each n = 10): zirconia‐reinforced lithium silicate ceramic (Celtra Duo; CD), leucite‐reinforced silicate ceramic (Empress CAD; EM), resin nanoceramic (Lava Ultimate; LU). A 3D digital measurement technique (OraCheck, Cyfex AG) using an intraoral scanner (CEREC Omnicam) was used to measure the difference in fit between the three materials for a master endocrown preparation. The preparation scan and the endocrown fit scan were matched with special difference analysis software OraCheck. Three areas were selected for fitting accuracy measurements: margin (MA), axial (AX), occlusal (OC). Statistical analysis was performed using 80% percentile, one‐way ANOVA, and post‐hoc Scheffé test. Significance level was set to p = 0.05. Results Results varied from best 88.9 ± 7.7 μm for marginal fit of resin nanoceramic restorations (LU_MA) to worst 182.3 ± 24.0 μm for occlusal fit of zirconia‐reinforced lithium silicate restorations (CD_OC). Statistically significant differences were found both within and among the test groups. Group CD performed statistically significantly different from group LU for marginal fit (MA) and axial fit (AX) (p 0.05). Deviation pattern for differences was visually analyzed with a color‐coded scheme for each restoration. Conclusions Statistically significant differences were found for different CAD/CAM materials if the CAM procedure was identical. Within the limitations of this study, the choice of CAD/CAM material may influence the fitting accuracy of CAD/CAM‐fabricated restorations

Revisiting Signaling Theory for Initial Coin Offerings

Blockchain applications such as Initial Coin Offerings (ICOs) have recently garnered significant attention as means of entrepreneurial financing. While receiving attention in the press, the majority of ICOs do not meet their financial goals. Lacking traditional ways to estimate value or gather information (e.g. a centralized valuation authority or a centralized platform of communication), ICOs have turned to using persuasion signals on social media to directly communicate the alleged value of their offerings to investors. In this study, we draw on signaling theory and lock-up situations, to examine the efficacy of the most commonly used persuasion signals of ICOs (social proof and authority). Technology induced lock-up periods in this context are defined as the inability to sell the purchased tokens for an unknown period of time and have not been in the focus of academic literature so far. To quantitatively test our hypotheses, we conducted a 2x2 factorial online experiment with 473 participants. Our experimental study suggests that persuasion signals were effective in the absence of a lock-up period. However, when the ICO includes a lock-up period, the persuasion signals do not work as expected from existing theory. The results even suggest that the perceived plausibility of an ICO is significantly reduced because of the combination of a lock-up period and persuasion signals

Incentive Mechanisms in Peer-to-Peer Networks — A Systematic Literature Review

Centralized networks inevitably exhibit single points of failure that malicious actors regularly target. Decentralized networks are more resilient if numerous participants contribute to the network’s functionality. Most decentralized networks employ incentive mechanisms to coordinate the participation and cooperation of peers and thereby ensure the functionality and security of the network. This article systematically reviews incentive mechanisms for decentralized networks and networked systems by covering 165 prior literature reviews and 178 primary research papers published between 1993 and October 2022. Of the considered sources, we analyze 11 literature reviews and 105 primary research papers in detail by categorizing and comparing the distinctive properties of the presented incentive mechanisms. The reviewed incentive mechanisms establish fairness and reward participation and cooperative behavior. We review work that substitutes central authority through independent and subjective mechanisms run in isolation at each participating peer and work that applies multiparty computation. We use monetary, reputation, and service rewards as categories to differentiate the implementations and evaluate each incentive mechanism’s data management, attack resistance, and contribution model. Further, we highlight research gaps and deficiencies in reproducibility and comparability. Finally, we summarize our assessments and provide recommendations to apply incentive mechanisms to decentralized networks that share computational resources

African Governments Need to Restructure Their Debt – And Rating Agencies Can Help

An effective global debt restructuring framework remains an urgent need, and a supportive element could consist of a change of sovereign rating practices. By integrating severity of financial losses in a default episode, rating agencies could better serve investors, while also incentivising overleveraged governments to seek debt relief. As interest rates rise, the world economy slows and food prices mount, procrastination around debt relief would result in avoidable humanitarian crises