pwc-archive/papers-with-abstracts huggingface dataset:
Matching Theory and Evidence on Covid-19 using a Stochastic Network SIR Model
Authors: M. Hashem Pesaran, Cynthia Fan Yang
Date: 2021-09-01 00:00:00
Tasks: counterfactual

This paper develops an individual-based stochastic network SIR model for the empirical analysis of the Covid-19 pandemic. It derives moment conditions for the number of infected and active cases for single as well as multigroup epidemic models. These moment conditions are used to investigate the identification and estimation of the transmission rates. The paper then proposes a method that jointly estimates the transmission rate and the magnitude of under-reporting of infected cases. Empirical evidence on six European countries matches the simulated outcomes once the under-reporting of infected cases is addressed. It is estimated that the number of actual cases could be between 4 to 10 times higher than the reported numbers in October 2020 and declined to 2 to 3 times in April 2021. The calibrated models are used in the counterfactual analyses of the impact of social distancing and vaccination on the epidemic evolution, and the timing of early interventions in the UK and Germany.
The Potential of Sufficiency Measures to Achieve a Fully Renewable Energy System -- A case study for Germany
Authors: Elmar Zozmann, Mirjam Helena Eerma, Dylan Manning, Gro Lill Økland, Citlali Rodriguez del Angel, Paul E. Seifert, Johanna Winkler, Alfredo Zamora Blaumann, Seyedsaeed Hosseinioun, Leonard Göke, Mario Kendziorski, Christian von Hirschhausen
Date: 2021-09-01 00:00:00

The paper provides energy system-wide estimates of the effects sufficiency measures in different sectors can have on energy supply and system costs. In distinction to energy efficiency, we define sufficiency as behavioral changes to reduce useful energy without significantly reducing utility, for example by adjusting thermostats. By reducing demand, sufficiency measures are a potentially decisive but seldomly considered factor to support the transformation towards a decarbonized energy system. Therefore, this paper addresses the following question: What is the potential of sufficiency measures and what is their impacts on the supply side of a 100% renewable energy system? For this purpose, an extensive literature review is conducted to obtain estimates for the effects of different sufficiency measures on final energy demand in Germany. Afterwards, the impact of these measures on the supply side and system costs is quantified using a bottom-up planning model of a renewable energy system. Results indicate that final energy could be reduced by up to 20.5% and as a result cost reduction between 11.3% to 25.6% are conceivable. The greatest potential for sufficiency measures was identified in the heating sector.
Decentralized Payment Clearing using Blockchain and Optimal Bidding
Authors: Hamed Amini, Maxim Bichuch, Zachary Feinstein
Date: 2021-09-01 00:00:00

In this paper, we construct a decentralized clearing mechanism which endogenously and automatically provides a claims resolution procedure. This mechanism can be used to clear a network of obligations through blockchain. In particular, we investigate default contagion in a network of smart contracts cleared through blockchain. In so doing, we provide an algorithm which constructs the blockchain so as to guarantee the payments can be verified and the miners earn a fee. We, additionally, consider the special case in which the blocks have unbounded capacity to provide a simple equilibrium clearing condition for the terminal net worths; existence and uniqueness are proven for this system. Finally, we consider the optimal bidding strategies for each firm in the network so that all firms are utility maximizers with respect to their terminal wealths. We first look for a mixed Nash equilibrium bidding strategies, and then also consider Pareto optimal bidding strategies. The implications of these strategies, and more broadly blockchain, on systemic risk are considered.
Nota Sobre Algumas Interpretacoes da Teoria de Tributacao Otima
Authors: Jose Ricardo Bezerra Nogueira
Date: 2021-09-01 00:00:00

This note discusses some aspects of interpretations of the theory of optimal taxation presented in recent works on the Brazilian tax system.
Production Networks and War
Authors: Vasily Korovkin, Alexey Makarin
Date: 2020-11-30 00:00:00

How do severe shocks such as war alter the economy? We study how a country's production network is affected by a devastating but localized conflict. Using unique transaction-level data on Ukrainian railway shipments around the start of the 2014 Russia-Ukraine crisis, we uncover several novel indirect effects of conflict on firms. First, we document substantial propagation effects on interfirm trade--trade declines even between partners outside the conflict areas if one of them had traded with those areas before the conflict events. The magnitude of such second-degree effect of conflict is one-fifth of the first-degree effect. Ignoring this propagation would lead to an underestimate of the total impact of conflict on trade by about 67\%. Second, war induces sudden changes in the production-network structure that influence firm performance. Specifically, we find that firms that exogenously became more central--after the conflict practically cut off certain regions from the rest of Ukraine--received a relative boost to their revenues. Finally, in a production-network model, we separately estimate the effects of the exogenous firm removal and the subsequent endogenous network adjustment on firm revenue distribution. For a median firm, network adjustment compensates for 80\% of the network destruction a year after the conflict onset.
Costly Multidimensional Screening
Authors: Frank Yang
Date: 2021-09-01 00:00:00

A screening instrument is costly if it is socially wasteful and productive otherwise. A principal screens an agent with multidimensional private information and quasilinear preferences that are additively separable across two components: a one-dimensional productive component and a multidimensional costly component. Can the principal improve upon simple one-dimensional mechanisms by also using the costly instruments? We show that if the agent has preferences between the two components that are positively correlated in a suitably defined sense, then simply screening the productive component is optimal. The result holds for general type and allocation spaces, and allows for nonlinear and interdependent valuations. We discuss applications to multiproduct pricing (including bundling, quality discrimination, and upgrade pricing), intertemporal price discrimination, and labor market screening.
Risk measures induced by efficient insurance contracts
Authors: Qiuqi Wang, Ruodu Wang, Ricardas Zitikis
Date: 2021-09-01 00:00:00
Tasks: Management

The Expected Shortfall (ES) is one of the most important regulatory risk measures in finance, insurance, and statistics, which has recently been characterized via sets of axioms from perspectives of portfolio risk management and statistics. Meanwhile, there is large literature on insurance design with ES as an objective or a constraint. A visible gap is to justify the special role of ES in insurance and actuarial science. To fill this gap, we study characterization of risk measures induced by efficient insurance contracts, i.e., those that are Pareto optimal for the insured and the insurer. One of our major results is that we characterize a mixture of the mean and ES as the risk measure of the insured and the insurer, when contracts with deductibles are efficient. Characterization results of other risk measures, including the mean and distortion risk measures, are also presented by linking them to different sets of contracts.
Photonic-enabled radio-frequency self-interference cancellation incorporated in an in-band full-duplex radio-over-fiber system
Authors: Taixia Shi, Yu Chen, Yang Chen
Date: 2021-09-01 00:00:00

A photonic approach for radio-frequency (RF) self-interference cancellation (SIC) incorporated in an in-band full-duplex radio-over-fiber system is proposed. A dual-polarization binary phase-shift keying modulator is used for dual-polarization multiplexing at the central office (CO). A local oscillator signal and an intermediate-frequency signal carrying the downlink data are single-sideband modulated on the two polarization directions of the modulator, respectively. The optical signal is then transmitted to the remote unit, where the optical signals in the two polarization directions are split into two parts. One part is detected to generate the up-converted downlink RF signal, and the other part is re-modulated by the uplink RF signal and the self-interference, which is then transmitted back to the CO for the signal down-conversion and SIC via the optical domain signal adjustment and balanced detection. The functions of SIC, frequency up-conversion, down-conversion, and fiber transmission with dispersion immunity are all incorporated in the system. An experiment is performed. Cancellation depths of more than 39 dB for the single-tone signal and more than 20 dB for the 20-MBaud 16 quadrature amplitude modulation signal are achieved in the back-to-back case. The performance of the system does not have a significant decline when a section of 4.1-km optical fiber is incorporated.
Multi Anchor Point Shrinkage for the Sample Covariance Matrix (Extended Version)
Authors: Hubeyb Gurdogan, Alec Kercheval
Date: 2021-09-01 00:00:00

Portfolio managers faced with limited sample sizes must use factor models to estimate the covariance matrix of a high-dimensional returns vector. For the simplest one-factor market model, success rests on the quality of the estimated leading eigenvector "beta". When only the returns themselves are observed, the practitioner has available the "PCA" estimate equal to the leading eigenvector of the sample covariance matrix. This estimator performs poorly in various ways. To address this problem in the high-dimension, limited sample size asymptotic regime and in the context of estimating the minimum variance portfolio, Goldberg, Papanicolau, and Shkolnik developed a shrinkage method (the "GPS estimator") that improves the PCA estimator of beta by shrinking it toward a constant target unit vector. In this paper we continue their work to develop a more general framework of shrinkage targets that allows the practitioner to make use of further information to improve the estimator. Examples include sector separation of stock betas, and recent information from prior estimates. We prove some precise statements and illustrate the resulting improvements over the GPS estimator with some numerical experiments.
Coagulapathies after vaccination against SARS-CoV-2 may be derived from a combination effect of SARS-CoV-2 spike protein and adenovirus vector-triggered signaling pathways
Authors: Ralf Kircheis
Date: 2021-08-31 00:00:00

The novel coronavirus SARS-CoV-2 has resulted in a global pandemic with worldwide 6-digital infection rates and thousands death tolls daily. Enormeous effords are undertaken to achieve high coverage of immunization in order to reach herd immunity to stop spreading of SARS-CoV-2 infection. Several SARS-CoV-2 vaccines, based either on mRNA, viral vectors, or inactivated SARS-CoV-2 virus have been approved and are being applied worldwide. However, recently increased numbers of normally very rare types of thromboses associated with thrombocytopenia have been reported in particular in the context of the adenoviral vector vaccine ChAdOx1 nCoV-19 from Astra Zeneca. While statistical prevalence of these side effects seem to correlate with this particular vaccine type, i.e. adenonoviral vector based vaccines, the exact molecular mechanisms are still not clear. The present review summarizes current data and hypotheses for molecular and cellular mechanisms into one integrated hypothesis indicating that coagulopathies, including thromboses, thrombocytopenia and other related side effects are correlated to an interplay of the two components in the vaccine, i.e. the spike antigen and the adenoviral vector, with the innate and immune system which under certain circumstances can imitate the picture of a limited COVID-19 pathological picture.
Biological applications of ferroelectric materials
Authors: Alfonso Blázquez-Castro, Angel García-Cabañes, Mercedes Carrascosa
Date: 2021-09-01 00:00:00

The study and applications of ferroelectric materials in the biomedical and biotechnological fields is a novel and very promising scientific area that spans roughly one decade. However, some groups have already provided experimental proof of very interesting biological modulation when living systems are exposed to different ferroelectrics and excitation mechanisms. These materials should offer several advantages in the field of bioelectricity, such as no need of an external electric power source or circuits, scalable size of the electroactive regions, flexible and reconfigurable virtual electrodes, or fully proved biocompatibility. In this focused review we provide the underlying physics of ferroelectric activity and a recount of the research reports already published, along with some tentative biophysical mechanisms that can explain the observed results. More specifically, we focused on the biological actions of domain ferroelectrics, and ferroelectrics excited by the bulk photovoltaic effect or the pyroelectric effect. It is our goal to provide a comprehensive account of the published material so far, and to set the stage for a vigorous expansion of the field, with envisioned applications that span from cell biology and signaling to cell and tissue regeneration, antitumoral action, or cell bioengineering to name a few.
Is cell segregation like oil and water: asymptotic versus transitory regime
Authors: Florian Franke, Sebatian Aland, Hans-Joachim Böhme, Anja Voss-Böhme, Steffen Lange
Date: 2021-09-01 00:00:00

Segregation of different cell types is a crucial process for the pattern formation in tissues, in particular during embryogenesis. Since the involved cell interactions are complex and difficult to measure individually in experiments, mathematical modelling plays an increasingly important role to unravel the mechanisms governing segregation. The analysis of these theoretical models focuses mainly on the asymptotic behavior at large times, in a steady regime and for large numbers of cells. Most famously, cell-segregation models based on the minimization of the total surface energy, a mechanism also driving the demixing of immiscible fluids, are known to exhibit asymptotically a particular algebraic scaling behavior. However, it is not clear, whether the asymptotic regime of the numerical models is relevant at the spatio-temporal scales of actual biological processes and in-vitro experiments. By developing a mapping between cell-based models and experimental settings, we are able to directly compare previous experimental data to numerical simulations of cell segregation quantitatively. We demonstrate that the experiments are reproduced by the transitory regime of the models rather than the asymptotic one. Our work puts a new perspective on previous model-driven conclusions on cell segregation mechanisms.
Fluorescent redox-dependent labeling of lipid droplets in cultured cells by reduced phenazine methosulfate
Authors: Juan C. Stockert, María C. Carou, Adriana G. Casas, María C. García Vior, Sergio D. Ezquerra Riega, María M. Blanco, Jesús Espada, Alfonso Blázquez-Castro, Richard W. Horobin, Daniel M. Lombardo
Date: 2021-09-01 00:00:00

Natural and synthetic phenazines are widely used in biomedical sciences. In dehydrogenase histochemistry, phenazine methosulfate (PMS) is applied as a redox reagent for coupling reduced coenzymes to the reduction of tetrazolium salts into colored formazans. PMS is also currently used for cytotoxicity and viability assays of cell cultures using sulfonated tetrazoliums. Under UV (340 nm) excitation, aqueous solutions of the cationic PMS show green fluorescence ({\lambda}em: 526 nm), whereas the reduced hydrophobic derivative (methyl-phenazine, MPH) shows blue fluorescence ({\lambda}em: 465 nm). Under UV (365 nm) excitation, cultured cells (LM2, IGROV-1, BGC-1, and 3T3-L1 adipocytes) treated with PMS (5 ug/mL, 30 min) showed cytoplasmic granules with bright blue fluorescence, which correspond to lipid droplets labeled by the lipophilic methyl-phenazine. After formaldehyde fixation blue-fluorescing droplets could be stained with oil red O. Interestingly, PMS-treated 3T3-L1 adipocytes observed under UV excitation 24 h after labeling showed large lipid droplets with a weak green emission within a diffuse pale blue-fluorescing cytoplasm, whereas a strong green emission was observed in small lipid droplets. This fluorescence change from blue to green indicates that reoxidation of methyl-phenazine to PMS can occur. Regarding cell uptake and labeling mechanisms, QSAR models predict that the hydrophilic PMS is not significantly membrane-permeant, so most PMS reduction is expected to be extracellular and associated with a plasma membrane NAD(P)H reductase. Once formed, the lipophilic and blue-fluorescing methyl-phenazine enters live cells and mainly accumulates in lipid droplets. Overall, the results reported here indicate that PMS is an excellent fluorescent probe to investigate labeling and redox dynamics of lipid droplets in cultured cells.
Inferring gene regulation dynamics from static snapshots of gene expression variability
Authors: Euan Joly-Smith, Zitong Jerry Wang, Andreas Hilfinger
Date: 2021-09-01 00:00:00

Inferring functional relationships within complex networks from static snapshots of a subset of variables is a ubiquitous problem in science. For example, a key challenge of systems biology is to translate cellular heterogeneity data obtained from single-cell sequencing or flow-cytometry experiments into regulatory dynamics. We show how static population snapshots of co-variability can be exploited to rigorously infer properties of gene expression dynamics when gene expression reporters probe their upstream dynamics on separate time-scales. This can be experimentally exploited in dual-reporter experiments with fluorescent proteins of unequal maturation times, thus turning an experimental bug into an analysis feature. We derive correlation conditions that detect the presence of closed-loop feedback regulation in gene regulatory networks. Furthermore, we show how genes with cell-cycle dependent transcription rates can be identified from the variability of co-regulated fluorescent proteins. Similar correlation constraints might prove useful in other areas of science in which static correlation snapshots are used to infer causal connections between dynamically interacting components.
Resting state fMRI-based temporal coherence mapping
Authors: Ze Wang
Date: 2021-09-01 00:00:00

Long-range temporal coherence (LRTC) is quite common to dynamic systems and is fundamental to the system function. LRTC in the brain has been shown to be important to cognition. Assessing LRTC may provide critical information for understanding the potential underpinnings of brain organization, function, and cognition. To facilitate this overarching goal, we provide a method, which is named temporal coherence mapping (TCM), to explicitly quantify LRTC using resting state fMRI. TCM is based on correlation analysis of the transit states of the phase space reconstructed by temporal embedding. A few TCM properties were collected to measure LRTC, including the averaged correlation, anti-correlation, the ratio of correlation and anticorrelation, the mean coherent and incoherent duration, and the ratio between the coherent and incoherent time. TCM was first evaluated with simulations and then with the large Human Connectome Project data. Evaluation results showed that TCM metrics can successfully differentiate signals with different temporal coherence regardless of the parameters used to reconstruct the phase space. In human brain, TCM metrics except the ratio of the coherent/incoherent time showed high test-retest reproducibility; TCM metrics are related to age, sex, and total cognitive scores. In summary, TCM provides a first-of-its-kind tool to assess LRTC and the imbalance between coherence and incoherence; TCM properties are physiologically and cognitively meaningful.
COVID-19 severity determinants inferred through ecological and epidemiological modeling
Authors: Sofija Markovic, Andjela Rodic, Igor Salom, Ognjen Milicevic, Magdalena Djordjevic, Marko Djordjevic
Date: 2021-08-31 00:00:00

Determinants of COVID-19 clinical severity are commonly assessed by transverse or longitudinal studies of the fatality counts. However, the fatality counts depend both on disease clinical severity and transmissibility, as more infected also lead to more deaths. Moreover, fatality counts (and related measures such as Case Fatality Rate) are dynamic quantities, as they appear with a delay to infections, while different geographic regions generally belong to different points on the epidemics curve. Instead, we use epidemiological modeling to propose a disease severity measure, which accounts for the underlying disease dynamics. The measure corresponds to the ratio of population averaged mortality and recovery rates (m/r). It is independent of the disease transmission dynamics (i.e., the basic reproduction number) and has a direct mechanistic interpretation. We use this measure to assess demographic, medical, meteorological and environmental factors associated with the disease severity. For this, we employ an ecological regression study design and analyze different US states during the first disease outbreak. Principal Component Analysis, followed by univariate and multivariate analyses based on machine learning techniques, is used for selecting important predictors. Without using prior knowledge from clinical studies, we recover significant predictors known to influence disease severity, in particular age, chronic diseases, and racial factors. Additionally, we identify long-term pollution exposure and population density as not widely recognized (though for the pollution previously hypothesized) predictors of the disease severity. Overall, the proposed measure is useful for inferring severity determinants of COVID-19 and other infectious diseases, and the obtained results may aid a better understanding of COVID-19 risks.
Optical Tweezers: Phototoxicity and Thermal Stress in Cells and Biomolecules
Authors: Alfonso Blázquez-Castro
Date: 2021-09-01 00:00:00

For several decades optical tweezers have proven to be an invaluable tool in the study and analysis of a myriad biological responses and applications. However, as every tool, it can have undesirable or damaging effects upon the very sample it is helping to study. In this review the main negative effects of optical tweezers upon biostructures and living systems will be presented. Three are the main areas on which the review will focus: linear optical excitation within the tweezers, non-linear photonic effects, and thermal load upon the sampled volume. Additional information is provided on negative mechanical effects of optical traps on biological structures. Strategies to avoid or, in the least, minimize these negative effects will be introduced. Finally, all these effects, undesirable for the most, can have positive applications under the right conditions. Some hints in this direction will also be discussed.