pwc-archive/papers-with-abstracts huggingface dataset:
A hybrid green energy-based framework with a multi-objective optimization approach for optimal frost prevention in horticulture
Authors: Ercan Atam, Tamer F. Abdelmaguid, Muhammed Emre Keskin, Eric C. Kerrigan
Date: 2021-04-15 00:00:00

In this paper, first we propose a novel hybrid renewable energy-based solution for frost prevention in horticulture applications involving active heaters. Then, we develop a multi-objective robust optimization-based formulation to optimize the distribution of a given number of active heaters in a given large-scale orchard. The objectives are to optimally heat the orchard by the proposed frost prevention system and to minimize the total length of the energy distribution pipe network (which is directly related to the installation cost and the cost of energy losses during energy transfer). Next, the resulting optimization problem is approximated using a discretization scheme. A case study is provided to give an idea of the potential savings using the proposed optimization method compared to the result from a heuristic-based design, which showed a 24.13% reduction in the total pipe length and a 54.29% increase in frost prevention.
Gyrator-Capacitor Modeling of a Continuously Variable Series Reactor in Different Operating Modes
Authors: Mohammadali Hayerikhiyavi, Aleksandar Dimitrovski
Date: 2021-04-15 00:00:00

Continuously Variable Series Reactor (CVSR) can regulate its reactance on the ac side using the nonlinear ferromagnetic core, shared by an ac and a dc winding for applications like power flow control, oscillation damping, load balancing and others. In order to use a CVSR in the power grid, it is essential to know its operating characteristics. The Gyrator-Capacitor approach has been applied to model the magnetic circuit coupled with the electrical circuit. In the paper, we investigate the CVSR behavior in terms of induced voltages across the dc winding, flux densities (B) through the core legs, and power exchange between the ac controlled and the dc control circuit.
Synchronization of Identical Boundary-Actuated Semilinear Infinite-Dimensional Systems
Authors: Francesco Ferrante, Giacomo Casadei, Christophe Prieur
Date: 2021-04-14 00:00:00

This paper deals with synchronization of a class of infinite-dimensional systems. The considered network is described by a collection of semilinear Lipschitz boundary-actuated infinite-dimensional dynamics. For undirected connected graphs, sufficient conditions for asymptotic synchronization are established. We show that the proposed conditions when applied to systems of hyperbolic semilinear conservation laws can be recast into a set of matrix inequalities. For this class of systems, sufficient conditions in the form of linear matrix inequalities for the design of synchronizing policies are provided.
Addendum: Action potential propagation and block in a model of atrial tissue with myocyte-fibroblast coupling
Authors: Peter Mortensen, Hao Gao, Godfrey Smith, Radostin D. Simitev
Date: 2021-04-14 00:00:00

The analytical theory of our earlier study (Mortensen et al. (2021), Mathematical Medicine and Biology, 38(1), pp. 106-131) is extended to address the outstanding cases of fibroblast barrier distribution and myocyte strait distribution. In particular, closed-form approximations to the resting membrane potential and to the critical parameter values for propagation are derived for these two non-uniform fibroblast distributions and are in good agreement with numerical estimates.
Democracy and Growth in the 21st Century
Authors: Yusuke Narita
Date: 2021-04-15 00:00:00

We find that, in the 21st century, democracy has persistent negative impacts on growth in GDP and night-time light intensity. This finding emerges from five different instrumental variable strategies that account for potential invalidity in some of the instruments. Our analysis also suggests a key mechanism: In this century, many electoral democracies shift toward populism and protectionism. These political changes weaken trade and investment, collectively dampening economic growth. Democracies also experienced lower growth in subjective life satisfaction among citizens. However, democracy causes slower growth in CO2 emissions and energy use, suggesting a trade-off between economic growth and socio-environmental performance.
Lessons Learned from Photovoltaic Auctions in Germany
Authors: Taimyra Batz Liñeiro, Felix Müsgens
Date: 2021-04-15 00:00:00

Auctions have become the primary instrument for promoting renewable energy around the world. However, the data published on such auctions are typically limited to aggregated information (e.g., total awarded capacity, average payments). These data constraints hinder the evaluation of realisation rates and other relevant auction dynamics. In this study, we present an algorithm to overcome these data limitations in German renewable energy auction programme by combining publicly available information from four different databases. We apply it to the German solar auction programme and evaluate auctions using quantitative methods. We calculate realisation rates and - using correlation and regression analysis - explore the impact of PV module prices, competition, and project and developer characteristics on project realisation and bid values. Our results confirm that the German auctions were effective. We also found that project realisation took, on average, 1.5 years (with 28% of projects finished late and incurring a financial penalty), nearly half of projects changed location before completion (again, incurring a financial penalty) and small and inexperienced developers could successfully participate in auctions.
The Struggle with Inequality
Authors: Shin-Ichiro Inaba
Date: 2021-04-15 00:00:00

This is an introductory textbook of the history of economics of inequality for undergraduates and genreral readers. It begins with Adam Smith's critique of Rousseau. The first and second chapters focus on Smith and Karl Marx, in the broad classical tradition of economics, where it is believed that there is an inseparable relationship between production and distribution, economic growth and inequality. Chapters 3 and 4 argue that despite the fact that the founders of the neoclassical school had shown an active interest in social issues, namely worker poverty, the issues of production and distribution became discussed separately among neoclassicals. Toward the end of the 20th century, however, there was a renewed awareness within economics of the problem of the relationship between production and distribution. The young Piketty's beginnings as an economist are set against this backdrop. Chapters 5 to 8 explain the circumstances of the restoration of classical concerns within the neoclassical framework. Then, in chapters 9 and 10, I discuss the fact that Thomas Piketty's seminal work is a new development in this "inequality renaissance," and try to gain a perspective on future trends in the debate. Mathematical appendix presents simple models of growth and distribution.
Exporters' reaction to positive foreign demand shocks
Authors: Asier Minondo
Date: 2021-04-15 00:00:00

I use the quasi-natural experiment of the 2018 African swine fever (ASF) outbreak in China to analyze swine exporters' reaction to a foreign market's positive demand shock. I use the universe of Spanish firms' export transactions to China and other countries, and compare the performance of swine and other exporters before and after the ASF. The ASF almost tripled Spanish swine exporters' sales to China. Swine exporters did not increase exported product portfolio or export revenue concentration in their best-performing products in China after the ASF. The increase in exports to China positively impacted export revenue and survival in third markets. This positive impact was especially intense for small swine exporters. Domestic sales also increased for swine exporters with liquidity constraints before the ASF.
Optimal Design of Limited Partnership Agreements
Authors: Mohammad Abbas Rezaei
Date: 2021-04-14 00:00:00

General partners (GP) are sometimes paid on a deal-by-deal basis and other times on a whole-portfolio basis. When is one method of payment better than the other? I show that when assets (projects or firms) are highly correlated or when GPs have low reputation, whole-portfolio contracting is superior to deal-by-deal contracting. In this case, by bundling payouts together, whole-portfolio contracting enhances incentives for GPs to exert effort. Therefore, it is better suited to alleviate the moral hazard problem which is stronger than the adverse selection problem in the case of high correlation of assets or low reputation of GPs. In contrast, for low correlation of assets or high reputation of GPs, information asymmetry concerns dominate and deal-by-deal contracts become optimal, as they can efficiently weed out bad projects one by one. These results shed light on recent empirical findings on the relationship between investors and venture capitalists.
Mission Statement Effect on Research and Innovation Performance
Authors: Julian D. Cortes, Diego Tellez, Jesus Godoy
Date: 2021-04-13 00:00:00

The mission statement (MS) is the most used organizational strategic planning tool worldwide. The relationship between an MS and an organizations financial performance has been shown to be significantly positive, albeit small. However, an MSs relationship to the macroeconomic environment and to organizational innovation has not been investigated. We implemented a Structural Equation Modeling using the SCImago Institutional Ranking (SIR) as a global baseline sample and assessment of organizational research and innovation (RandI), an automated MS content analysis, and the Economic Complexity Index (ECI) as a comprehensive macroeconomic environment measure. We found that the median performance of organizations that do not report an MS is significantly higher than that of reporting organizations, and that a path-dependence driven by the State's long-term view and investment is a better explanatory variable for organizational RandI performance than the MS construct or the intermediate-term macroeconomic environment.
Mission Statements in Universities: Readability and performance
Authors: Julian D. Cortes, Liliana Rivera, Katerina Bohle Carbonell
Date: 2021-04-13 00:00:00
Tasks: Management

The mission statement(s) (MS) is one of the most-used tools for planning and management. Universities worldwide have implemented MS in their knowledge planning and management processes since the 1980s. Research studies have extensively explored the content and readability of MS and its effect on performance in firms, but their effect on public or nonprofit institutions such as universities has not been scrutinized with the same intensity. This study used Gunning's Fog Index score to determine the readability of a sample of worldwide universities' MS and two rankings, i.e., Quacquarelli Symonds World University Ranking and SCImago Institutions Rankings, to determine their effect on performance. No significant readability differences were identified in regions, size, focus, research type, age band, or status. Logistic regression (cumulative link model) results showed that variables, such as universities' age, focus, and size, have more-significant explanatory power on performance than MS readability.
Multi-compartment diffusion MRI, T2 relaxometry and myelin water imaging as neuroimaging descriptors for anomalous tissue detection
Authors: Elda Fischi-Gomez, Jonathan Rafael-Patino, Marco Pizzolato, Gian Franco Piredda, Tom Hilbert, Tobias Kober, Erick J. Canales-Rodriguez, Jean-Philippe Thiran
Date: 2021-04-15 00:00:00
Tasks: Diffusion  MRI, Prognosis, Specificity

Multiple sclerosis (MS) is an inflammatory and neurodegenerative disease characterized by diffuse and focal areas of tissue loss. Conventional MRI techniques such as T1-weighted and T2-weighted scans are generally used in the diagnosis and prognosis of the disease. Yet, these methods are limited by the lack of specificity between lesions, their perilesional area and non-lesional tissue. Alternative MRI techniques exhibit a higher level of sensitivity to focal and diffuse MS pathology than conventional MRI acquisitions. However, they still suffer from limited specificity when considered alone. In this work, we have combined tissue microstructure information derived from multicompartment diffusion MRI and T2 relaxometry models to explore the voxel-based prediction power of a machine learning model in a cohort of MS patients and healthy controls. Our results show that the combination of multi-modal features, together with a boosting enhanced decision-tree based classifier, which combines a set of weak classifiers to form a strong classifier via a voting mechanism, is able to utilise the complementary information for the classification of abnormal tissue.
Electromagnetic Models for Passive Detection and Localization of Multiple Bodies
Authors: Vittorio Rampa, Gian Guido Gentili, Stefano Savazzi, Michele D'Amico
Date: 2021-04-15 00:00:00

The paper proposes a multi-body electromagnetic (EM) model for the quantitative evaluation of the influence of multiple human bodies in the surroundings of a radio link. Modeling of human-induced fading is the key element for the development of real-time Device-Free (or passive) Localization (DFL) and body occupancy tracking systems based on the processing of the Received Signal Strength (RSS) data recorded by radio-frequency devices. The proposed physical-statistical model, is able to relate the RSS measurements to the position, size, orientation, and random movements of people located in the link area. This novel EM model is thus instrumental for crowd sensing, occupancy estimation and people counting applications for indoor and outdoor scenarios. The paper presents the complete framework for the generic N-body scenario where the proposed EM model is based on the knife-edge approach that is generalized here for multiple targets. The EM-equivalent size of each target is then optimized to reproduce the body-induced alterations of the free space radio propagation. The predicted results are then compared against the full EM simulations obtained with a commercially available simulator. Finally, experiments are carried out to confirm the validity the proposed model using IEEE 802.15.4-compliant industrial radio devices.
Quantitative processing of broadband data as implemented in a scientific splitbeam echosounder
Authors: Lars Nonboe Andersen, Dezhang Chu, Harald Heimvoll, Rolf Korneliussen, Gavin J. Macaulay, Egil Ona
Date: 2021-04-15 00:00:00

The use of quantitative broadband echosounders for biological studies and surveys offers considerable advantages over narrowband echosounders. These include improved spectral-based target identification and significantly increased ability to resolve individual targets. Biological studies and surveys typically require accurate measures of backscatter strength and we present here a systematic and comprehensive explanation of how to derive quantitative estimates of target strength and volume backscattering, as a function of frequency from broadband echosounder signals.
Meteorologically Introduced Impacts on Aerial Channels and UAV Communications
Authors: Mengan Song, Yiming Huo, Tao Lu, Xiaodai Dong, Zhonghua Liang
Date: 2021-04-14 00:00:00

As 5G wireless systems and networks are now being globally commercialized and deployed, more diversified application scenarios are emerging, quickly reshaping our societies and paving the road to the beyond 5G (6G) era when terahertz (THz) and unmanned aerial vehicle (UAV) communications may play critical roles. In this paper, aerial channel models under multiple meteorological conditions such as rain, fog and snow, have been investigated at frequencies of interest (from 2 GHz to 900 GHz) for UAV communications. Furthermore, the link budget and the received signal-to-noise ratio (SNR) performance under the existing air-to-ground (A2G) channel models are studied with antenna(s) system considered. The relationship between the 3D coverage radius and UAV altitude under the influence of multiple weather (MW) conditions is simulated. Numerical results show that medium rain has the most effects on the UAV's coverage for UAV communications at millimeter wave (mmWave) bands, while snow has the largest impacts at near THz bands. In addition, when the frequency increases, the corresponding increase in the number of antennas can effectively compensate for the propagation loss introduced by weather factors, while its form factor and weight can be kept to maintain the UAV's payload.
Simulations Approaching Data: Cortical Slow Waves in Inferred Models of the Whole Hemisphere of Mouse
Authors: Cristiano Capone, Chiara De Luca, Giulia De Bonis, Robin Gutzen, Irene Bernava, Elena Pastorelli, Francesco Simula, Cosimo Lupo, Leonardo Tonielli, Anna Letizia Allegra Mascaro, Francesco Resta, Francesco Pavone, Micheal Denker, Pier Stanislao Paolucci
Date: 2021-04-15 00:00:00

Thanks to novel, powerful brain activity recording techniques, we can create data-driven models from thousands of recording channels and large portions of the cortex, which can improve our understanding of brain-states neuromodulation and the related richness of traveling waves dynamics. We investigate the inference of data-driven models and the comparison among experiments and simulations, through the characterization of the spatio-temporal features of cortical waves in experimental recordings and simulations. Inference is built in two steps: the inner loop that optimizes by likelihood maximization a mean-field model, and the outer loop that optimizes a periodic neuro-modulation by relying on direct comparison of observables apt for the characterization of cortical slow waves. The model is capable to reproduce most of the features of the non-stationary and non-linear dynamics displayed by the high-resolution recording of the in-vivo mouse brain obtained by wide-field calcium imaging techniques. The proposed approach is of interest for both experimental and computational neuroscientists.
A High-fidelity, Machine-learning Enhanced Queueing Network Simulation Model for Hospital Ultrasound Operations
Authors: Yihan Pan, Zhenghang Xu, Jin Guang, Jingjing Sun, Chengwenjian Wang, Xuanming Zhang, Xinyun Chen, J. G. Dai, Yichuan Ding, Pengyi Shi, Hongxin Pan, Kai Yang, Song Wu
Date: 2021-04-12 00:00:00
Tasks: BIG-bench Machine Learning

We collaborate with a large teaching hospital in Shenzhen, China and build a high-fidelity simulation model for its ultrasound center to predict key performance metrics, including the distributions of queue length, waiting time and sojourn time, with high accuracy. The key challenge to build an accurate simulation model is to understanding the complicated patient routing at the ultrasound center. To address the issue, we propose a novel two-level routing component to the queueing network model. We apply machine learning tools to calibrate the key components of the queueing model from data with enhanced accuracy.
On principal component analysis of the convex combination of two data matrices and its application to acoustic metamaterial filters
Authors: Giorgio Gnecco, Andrea Bacigalupo
Date: 2021-04-04 00:00:00

In this short paper, a matrix perturbation bound on the eigenvalues found by principal component analysis is investigated, for the case in which the data matrix on which principal component analysis is performed is a convex combination of two data matrices. The application of the theoretical analysis to multi-objective optimization problems (e.g., those arising in the design of acoustic metamaterial filters) is briefly discussed, together with possible extensions.
Decoding of the Walking States and Step Rates from Cortical Electrocorticogram Signals
Authors: Po T. Wang, Colin M. McCrimmon, Susan J. Shaw, Hui Gong, Luis A. Chui, Payam Heydari, Charles Y. Liu, An H. Do, Zoran Nenadic
Date: 2021-04-14 00:00:00
Tasks: Decoder, EEG, Electroencephalogram (EEG)

Brain-computer interfaces (BCIs) have shown promising results in restoring motor function to individuals with spinal cord injury. These systems have traditionally focused on the restoration of upper extremity function; however, the lower extremities have received relatively little attention. Early feasibility studies used noninvasive electroencephalogram (EEG)-based BCIs to restore walking function to people with paraplegia. However, the limited spatiotemporal resolution of EEG signals restricted the application of these BCIs to elementary gait tasks, such as the initiation and termination of walking. To restore more complex gait functions, BCIs must accurately decode additional degrees of freedom from brain signals. In this study, we used subdurally recorded electrocorticogram (ECoG) signals from able-bodied subjects to design a decoder capable of predicting the walking state and step rate information. We recorded ECoG signals from the motor cortices of two individuals as they walked on a treadmill at different speeds. Our offline analysis demonstrated that the state information could be decoded from >16 minutes of ECoG data with an unprecedented accuracy of 99.8%. Additionally, using a Bayesian filter approach, we achieved an average correlation coefficient between the decoded and true step rates of 0.934. When combined, these decoders may yield decoding accuracies sufficient to safely operate present-day walking prostheses.
Combining the Projective Consciousness Model and Virtual Humans to assess ToM capacity in Virtual Reality: a proof-of-concept
Authors: David Rudrauf, Grégoire Sergeant-Perthuis, Yvain Tisserand, Teerawat Monnor, Olivier Belli
Date: 2021-04-02 00:00:00

Relating explicit psychological mechanisms and observable behaviours is a central aim of psychological and behavioural science. We implemented the principles of the Projective Consciousness Model into artificial agents embodied as virtual humans, as a proof-of-concept for a methodological framework aimed at simulating behaviours and assessing underlying psychological parameters, in the context of experiments in virtual reality. We focus on simulating the role of Theory of Mind (ToM) in the choice of strategic behaviours of approach and avoidance to optimise the satisfaction of agents' preferences. We designed an experiment in a virtual environment that could be used with real humans, allowing us to classify behaviours as a function of order of ToM, up to the second order. We show that our agents demonstrate expected behaviours with consistent parameters of ToM in this experiment. We also show that the agents can be used to estimate correctly each other order of ToM. A similar approach could be used with real humans in virtual reality experiments not only to enable human participants to interact with parametric, virtual humans as stimuli, but also as a mean of inference to derive model-based psychological assessments of the participants.