IPO performance of portfolio ventures funded by impact investors versus venture capital investors

in Journal of International Financial Management and Accounting (2023)

With the global rise of impact investments to achieve societal goals, an increasing number of new ventures that aim to create societal impact now seek to go public. However, while many conceptual studies ... [more ▼]

With the global rise of impact investments to achieve societal goals, an increasing number of new ventures that aim to create societal impact now seek to go public. However, while many conceptual studies suggest that impact investors are less likely to pursue financially oriented exit plans in exchange for generating societal impact, there is little empirical evidence to back up this claim. Using a propensity score matching approach, we draw on data from Crunchbase and empirically compare the initial public offering (IPO) performance of a large sample of 3398 investments by impact investors with 3398 investments by matched venture capital (VC) investors. We find that impact investor investments are less likely to lead to an IPO than VC investments. Besides, our results indicate that syndication by impact investors increases the likelihood of an IPO. This suggests that companies funded by impact investors benefit more from syndication than their VC-funded counterparts. Our findings have practical implications for impact investors, portfolio ventures, and policymakers. [less ▲]

Optimizing vaccine distribution in developing countries under natural disaster risk

in Naval Research Logistics (2023)

For many developing countries, COVID-19 vaccination roll-out programs are not only slow but vaccination centers are also exposed to the risk of natural disaster, like flooding, which may slow down ... [more ▼]

For many developing countries, COVID-19 vaccination roll-out programs are not only slow but vaccination centers are also exposed to the risk of natural disaster, like flooding, which may slow down vaccination progress even further. Policy-makers in developing countries therefore seek to implement strategies that hedge against distribution risk in order for vaccination campaigns to run smoothly and without delays. We propose a stochastic-dynamic facility location model that allows policy-makers to choose vaccination facilities while accounting for possible facility failure. The model is a multi-stage stochastic variant of the classic facility location problem where disruption risk is modelled as a binary multivariate random process - a problem class that has not yet been studied in the extant literature. To solve the problem, we propose a novel approximate dynamic programming algorithm which trains the shadow price of opening a flood-prone facility on historical data, thereby alleviating the need to fit a stochastic model. We trained the model using rainfall data provided by the local government of several major cities in the Philippines which are exposed to multiple flooding events per year. Numerical results demonstrate that the solution approach yields approximately 30-40% lower cost than a baseline approach that does not consider the risk of flooding. Recommendations based on this model were implemented following a collaboration with two large cities in the Philippines which are exposed to multiple flooding events per year. [less ▲]

Enhanced energy management system for isolated microgrid with diesel generators, renewable generation, and energy storages

in Applied Energy (2023), 350(15 November 2023),

This paper presents an enhanced control and energy management strategy for the remote isolated power system. The presented control method includes the hybrid energy storage system control with a ... [more ▼]

This paper presents an enhanced control and energy management strategy for the remote isolated power system. The presented control method includes the hybrid energy storage system control with a supercapacitor voltage restoration loop. This method improves the transient response and extends the battery lifespan while maintaining the SC voltage at a defined range of operation. To maximize the usage of renewable energy and reduce the diesel generator’s frequent turn-on and off operation, the novel battery state of charge stop control is included in the energy management system. This improves the lifetime of diesel generators and reduces maintenance costs. In the proposed control method, a stabilizing control method is also introduced which helps in a seamless transition from grid-connected mode to islanded operating mode. The effectiveness of the proposed EMS and control method is validated by real-time simulation studies. [less ▲]

Towards a peer-to-peer residential short-term load forecasting with federated learning

in Proceedings of the 2023 IEEE Belgrade PowerTech (2023, August 09)

The inclusion of intermittent and renewable energy sources has increased the importance of demand forecasting in the power systems. Smart meters play a critical role in modern load forecasting due to the ... [more ▼]

The inclusion of intermittent and renewable energy sources has increased the importance of demand forecasting in the power systems. Smart meters play a critical role in modern load forecasting due to the high granularity of the measurement data. Federated Learning can enable accurate residential load forecasting in a distributed manner. In this regard, to compensate for the variability of households, clustering them in groups with similar patterns can lead to more accurate forecasts. Usually, clustering requires a central server that has access to the entire dataset, which collides with the decentralized nature of federated learning. In order to complement federated learning, this study proposes a decentralized Peer-to-Peer strategy that employs agent-based modeling. We evaluate it in comparison to a typical centralized k-means clustering. To create clusters, we compare Euclidian and Dynamic time warping distances. We employ these clusters to build short-term load forecasting models using federated learning. Our results reveal the possibility of using Peer-to-Peer clustering along with simple Euclidean distances and Federated Learning to obtain highly performant load forecasting models in a fully decentralized setting. [less ▲]

Viewpoint: Talent Retention Strategies for Highly Skilled Migrants

Article for general public (2023)

Translanguaging in frühkindlichen Bildungseinrichtungen in Luxemburg – mehrsprachiges Handeln von Kindern und Pädagoginnen

in Meier, Jörg; İnci, Dirim; Blaschitz, Verena (Eds.) Handbuch Mehrsprachigkeit (2023)

CogPonder: Towards a Computational Framework of General Cognitive Control

Poster (2023, August)

Current computational models of cognitive control exhibit notable limitations. In machine learning, artificial agents are now capable of performing complex tasks but often ignore critical constraints such ... [more ▼]

Current computational models of cognitive control exhibit notable limitations. In machine learning, artificial agents are now capable of performing complex tasks but often ignore critical constraints such as resource limitations and how long it takes for the agent to make decisions and act. Conversely, cognitive control models in psychology are limited in their ability to tackle complex tasks (e.g., play video games) or generalize across a battery of simple cognitive tests. Here we introduce CogPonder, a flexible, differentiable, cognitive control framework that is inspired by the Test-Operate-Test-Exit (TOTE) architecture in psychology and the PonderNet framework in machine learning. CogPonder functionally decouples the act of control from the controlled processes by introducing a controller that acts as a wrapper around any end-to-end deep learning model and decides when to terminate processing and output a response, thus producing both a response and response time. Our experiments show that CogPonder effectively learns from data to generate behavior that closely resembles human responses and response times in two classic cognitive tasks. This work demonstrates the value of this new computational framework and offers promising new research prospects for both psychological and computer sciences. [less ▲]

The Copernican Revolution of Luxembourg Nationality: From an Insular to an Expansive Citizenship Regime

in Robert Schuman Centre Open Access Working Papers (2023)

The EU’s Recovery and Resilience Facility: An Exceptional Borrowing Instrument?

in Journal of European Integration (2023), Early View

The Recovery and Resilience Facility (RRF) authorises the European Commission to borrow up to €672.5 billion to aid member states’ economic recovery from COVID-19. Some scholars see such funding as ... [more ▼]

The Recovery and Resilience Facility (RRF) authorises the European Commission to borrow up to €672.5 billion to aid member states’ economic recovery from COVID-19. Some scholars see such funding as unprecedented. Others see a tight link with earlier borrowing instruments. By comparing the EU’s pandemic facility to eleven such instruments created between 1952 and 2021, this article shows that the RRF is familiar in some respects but novel in others. Viewed through a historical institutionalist lens, the RRF shows signs of layering, but limited evidence of displacement or path dependence. Over the last seven decades, member states have added to earlier instruments, we show through process tracing, but they have rarely been locked into institutional choices. The RRF’s strict time limit is consistent with this finding. The RRF will not become permanent, our analysis suggests, but borrowing is now part of the EU’s toolkit. [less ▲]

Reconfigurable Intelligent Surfaces Enhanced NOMA D2D Communications Underlaying UAV Networks

E-print/Working paper (2023)

Device-to-device (D2D) communications offers high spectral efficiency, low energy consumption and transmission latency. However, one of the main limitations of D2D communications is co-channel ... [more ▼]

Device-to-device (D2D) communications offers high spectral efficiency, low energy consumption and transmission latency. However, one of the main limitations of D2D communications is co-channel interference from underlaying wireless system. Reconfigurable intelligent surfaces (RIS) is a promising technology because it can manipulate the electromagnetic waves in their environment to overcome interference and enhance wireless communications. This paper considers RIS enhanced D2D communications underlaying unmanned aerial vehicle (UAV) networks with non-orthogonal multiple access (NOMA). The objective is to maximize the sum rate of NOMA D2D communications by optimizing the power budget of D2D transmitter, NOMA power allocation coefficients of D2D receivers and passive beamforming of RIS while guaranteeing the quality of services of UAV user. Due to non-convexity, the optimization problem is intractable and challenging to handle. Therefore, it is solved in two parts using alternating optimization. Simulation results unviel the performance of the proposed RIS enhanced D2D communications scheme. Results demonstrate that the proposed scheme ach [less ▲]