pwc-archive/papers-with-abstracts huggingface dataset:
Name order and the top elite: Long-term effects of a hidden cur-riculum
Authors: Eiji Yamamura
Date: 2023-12-21 00:00:00

In Japanese primary and secondary schools, an alphabetical name list is used in various situations. Generally, students are called on by the teacher during class and in the cer-emony if their family name is early on the list. Therefore, students whose surname ini-tials are earlier in the Japanese alphabet acquire more experience. Surname advantages are considered to have a long-term positive effect on life in adulthood. This study ex-amines the surname effect. The data set is constructed by gathering lists of representative figures from various fields. Based on the list, we calculate the proportion of surname groups according to Japanese alphabetical column lists. The major findings are as follows: (1) people whose surnames are in the A-column (the first column among 10 Japanese name col-umns) are 20% more likely to appear among the ruling elite but are less likely to ap-pear in entertainment and sports lists. (2) This tendency is rarely observed in the Uni-versity of Tokyo entrance examination pass rate. Consequently, the A-column sur-names are advantageous in helping students succeed as part of the elite after graduating from universities but not when gaining entry into universities. The surname helps form non-cognitive skills that help students become part of the ruling elite instead of specif-ic cognitive skills that help students enter elite universities. Keywords: Surname, Education, Name order, Hidden curriculum, Cognitive skill, Non-cognitive skill, Elite, Vice Minister, Academic, Prestigious university, Enter-tainment, Sports.
The Effect of Antitrust Enforcement on Venture Capital Investments
Authors: Wentian Zhang
Date: 2023-12-21 00:00:00

This paper studies the effect of antitrust enforcement on venture capital (VC) investments and VC-backed companies. To establish causality, I exploit the DOJ's decision to close several antitrust field offices in 2013, which reduced the antitrust enforcement in areas near the closed offices. I find that the reduction in antitrust enforcement causes a significant decrease in VC investments in startups located in the affected areas. Furthermore, these affected VC-backed startups exhibit a reduced likelihood of successful exits and diminished innovation performance. These negative results are mainly driven by startups in concentrated industries, where incumbents tend to engage in anticompetitive behaviors more frequently. To mitigate the adverse effect, startups should innovate more to differentiate their products. This paper sheds light on the importance of local antitrust enforcement in fostering competition and innovation.
Recognising natural capital on the balance sheet: options for water utilities
Authors: Marie-Chantale Pelletier, Claire Horner, Mathew Vickers, Aliya Gul, Eren Turak, Christine Turner
Date: 2023-12-21 00:00:00
Tasks: Asset Management, Management

Purpose: The aim of this study was to explore the feasibility of natural capital accounting for the purpose of strengthening sustainability claims by reporting entities. The study linked riparian land improvement to ecosystem services and tested options for incorporating natural capital into financial accounting practices, specifically on the balance sheet. Methodology: To test the approach, the study used a public asset manager (a water utility) with accountabilities to protect the environment including maintaining and enhancing riparian land assets. Research activities included stakeholder engagement, physical asset measurement, monetary valuation and financial recognition of natural capital income and assets. Natural capital income was estimated by modelling and valuing ecosystem services relating to stormwater filtration and carbon storage. Findings: This research described how a water utility could disclose changes in the natural capital assets they manage either through voluntary disclosures, in notes to the financial statements or as balance sheet items. We found that current accounting standards allowed the recognition of some types of environmental income and assets where ecosystem services were associated with cost savings. The proof-of-concept employed to estimate environmental income through ecosystem service modelling proved useful to strengthen sustainability claims or report financial returns on natural capital investment. Originality/value: This study applied financial accounting processes and principles to a realistic public asset management scenario with direct participation by the asset manager working together with academic researchers and a sub-national government environment management agency. Importantly it established that natural assets could be included in financial statements, proposing a new approach to measuring and reporting on natural capital.
Can Digital Aid Deliver During Humanitarian Crises?
Authors: Michael Callen, Miguel Fajardo-Steinhäuser, Michael G. Findley, Tarek Ghani
Date: 2023-12-20 00:00:00
Tasks: Humanitarian, Nutrition

Can digital payments systems help reduce extreme hunger? Humanitarian needs are at their highest since 1945, aid budgets are falling behind, and hunger is concentrating in fragile states where repression and aid diversion present major obstacles. In such contexts, partnering with governments is often neither feasible nor desirable, making private digital platforms a potentially useful means of delivering assistance. We experimentally evaluated digital payments to extremely poor, female-headed households in Afghanistan, as part of a partnership between community, nonprofit, and private organizations. The payments led to substantial improvements in food security and mental well-being. Despite beneficiaries' limited tech literacy, 99.75\% used the payments, and stringent checks revealed no evidence of diversion. Before seeing our results, policymakers and experts are uncertain and skeptical about digital aid, consistent with the lack of prior evidence on digital payments for humanitarian response. Delivery costs are under 7 cents per dollar, which is 10 cents per dollar less than the World Food Programme's global figure for cash-based transfers. These savings can help reduce hunger without additional resources, demonstrating how hybrid partnerships utilizing digital platform technologies can help address grand challenges in difficult contexts.
Enabling Secure Wireless Communications via Movable Antennas
Authors: Zhenqiao Cheng, Nanxi Li, Jianchi Zhu, Xiaoming She, Chongjun Ouyang, Peng Chen
Date: 2023-12-21 00:00:00
Tasks: Position

A pioneering secure transmission scheme is proposed, which harnesses movable antennas (MAs) to optimize antenna positions for augmenting the physical layer security. Particularly, an MA-enabled secure wireless system is considered, where a multi-antenna transmitter communicates with a single-antenna receiver in the presence of an eavesdropper. The beamformer and antenna positions at the transmitter are jointly optimized under two criteria: power consumption minimization and secrecy rate maximization. For each scenario, a novel suboptimal algorithm was proposed to tackle the resulting nonconvex optimization problem, capitalizing on the approaches of alternating optimization and gradient descent. Numerical results demonstrate that the proposed MA systems significantly improve physical layer security compared to various benchmark schemes relying on conventional fixed-position antennas (FPAs).
Sequence Selection with Dispersion-Aware Metric for Long-Haul Transmission Systems
Authors: Jingtian Liu, Élie Awwad, Hartmut Hafermann, Yves Jaouën
Date: 2023-12-21 00:00:00

We introduce a novel sign-dependent metric: the energy dispersion index (EDI) of sequences that endured chromatic dispersion, denoted as D-EDI, which exhibits a more accurate opposite variations with the transmission performance compared to the standard EDI metric. Then, by applying D-EDI and EDI to the sequence selection (SS) process, %with enumerative sphere shaping (ESS) for $M$-QAM signaling, we present two signaling approaches denoted as D-SS and E-SS respectively. These approaches are designed to minimize rate loss and enhance transmission performance in nonlinear optical fiber transmission systems, catering to both short-distance and long-haul scenarios. With enumerative sphere shaping (ESS) as distribution matcher (DM), our simulation results reveal significant performance gains over ESS without sequence selection (SS), with improvements up to $0.4$~bits/4D-symbol. These improvements were observed over a $205$-km single-span standard single mode fiber link in WDM transmission, with five dual-polarization channels, each operating at a net rate of $400$~Gbit/s. Furthermore, we demonstrate that D-SS surpasses ESS without SS by $0.03$~bits/4D-symbol in achievable information rate over a $30\times80$~km link in a single-wavelength, with 8 discrete multi-band (DMB) transmission, and an $880$~Gbit/s net rate. Notably, our proposed D-SS scheme achieves similar performance to a sequence selection based on a full split-step Fourier method (SSFM) simulation and it consistently delivers throughput enhancements across various block lengths and selected sequence lengths.
Millimeter-wave Radio SLAM: End-to-End Processing Methods and Experimental Validation
Authors: Elizaveta Rastorgueva-Foi, Ossi Kaltiokallio, Yu Ge, Matias Turunen, Jukka Talvitie, Bo Tan, Musa Furkan Keskin, Henk Wymeersch, Mikko Valkama
Date: 2023-12-21 00:00:00
Tasks: parameter estimation, Simultaneous Localization and Mapping

In this article, we address the timely topic of cellular bistatic simultaneous localization and mapping (SLAM) with specific focus on end-to-end processing solutions, from raw I/Q samples, via channel parameter estimation to user equipment (UE) and landmark location information in millimeter-wave (mmWave) networks, with minimal prior knowledge. Firstly, we propose a new multipath channel parameter estimation solution that operates directly with beam reference signal received power (BRSRP) measurements, alleviating the need to know the true antenna beam-patterns or the underlying beamforming weights. Additionally, the method has built-in robustness against unavoidable antenna sidelobes. Secondly, we propose new snapshot SLAM algorithms that have increased robustness and identifiability compared to prior art, in practical built environments with complex clutter and multi-bounce propagation scenarios, and do not rely on any a priori motion model. The performance of the proposed methods is assessed at the 60 GHz mmWave band, via both realistic ray-tracing evaluations as well as true experimental measurements, in an indoor environment. A wide set of offered results demonstrate the improved performance, compared to the relevant prior art, in terms of the channel parameter estimation as well as the end-to-end SLAM performance. Finally, the article provides the measured 60 GHz data openly available for the research community, facilitating results reproducibility as well as further algorithm development.
Angle of Arrival and Centimeter Distance Estimation on a Smart UWB Sensor Node
Authors: Tobias Margiani, Silvano Cortesi, Milena Keller, Christian Vogt, Tommaso Polonelli, Michele Magno
Date: 2023-12-21 00:00:00
Tasks: Indoor Localization

Accurate and low-power indoor localization is becoming more and more of a necessity to empower novel consumer and industrial applications. In this field, the most promising technology is based on UWB modulation; however, current UWB positioning systems do not reach centimeter accuracy in general deployments due to multipath and nonisotropic antennas, still necessitating several fixed anchors to estimate an object's position in space. This article presents an in-depth study and assessment of angle of arrival (AoA) UWB measurements using a compact, low-power solution integrating a novel commercial module with phase difference of arrival (PDoA) estimation as integrated feature. Results demonstrate the possibility of reaching centimeter distance precision and ang 2.4 average angular accuracy in many operative conditions, e.g., in a ang 90 range around the center. Moreover, integrating the channel impulse response, the phase differential of arrival, and the point-to-point distance, an error correction model is discussed to compensate for reflections, multipaths, and front-back ambiguity.
A low-cost PPG sensor-based empirical study on healthy aging based on changes in PPG morphology
Authors: Muhammad Saran Khalid, Ikramah Shahid Quraishi, Hadia Sajjad, Hira Yaseen, Ahsan Mehmood, Muhammad Mahboob Ur Rahman, Qammer H. Abbasi
Date: 2023-12-20 00:00:00
Tasks: Binary Classification, Data Augmentation, Photoplethysmography (PPG)

We present the findings of an experimental study whereby we correlate the changes in the morphology of the photoplethysmography (PPG) signal to healthy aging. Under this pretext, we estimate the biological age of a person as well as the age group he/she belongs to, using the PPG data that we collect via a non-invasive low-cost MAX30102 PPG sensor. Specifically, we collect raw infrared PPG data from the finger-tip of 179 apparently healthy subjects, aged 3-65 years. In addition, we record the following metadata of each subject: age, gender, height, weight, family history of cardiac disease, smoking history, vitals (heart rate and SpO2). We pre-process the raw PPG data to remove noise, artifacts, and baseline wander. We then construct 60 features based upon the first four PPG derivatives, the so-called VPG, APG, JPG, and SPG signals, and the demographic features. We then do correlation-based feature-ranking (which retains 26 most important features), followed by Gaussian noise-based data augmentation (which results in 15-fold increase in the size of our dataset). Finally, we feed the feature set to three machine learning classifiers (logistic regression, decision tree, random forest), and two shallow neural networks: a feedforward neural network (FFNN) and a convolutional neural network (CNN). For the age group classification, the shallow FFNN performs the best with 98% accuracy for binary classification (3-15 years vs. 15+ years), and 97% accuracy for three-class classification (3-12 years, 13-30 years, 30+ years). For biological age prediction, the shallow FFNN again performs the best with a mean absolute error (MAE) of 1.64.
Docking-based generative approaches in the search for new drug candidates
Authors: Tomasz Danel, Jan Łęski, Sabina Podlewska, Igor T. Podolak
Date: 2023-11-22 00:00:00
Tasks: Drug Design, Molecular Docking

Despite the great popularity of virtual screening of existing compound libraries, the search for new potential drug candidates also takes advantage of generative protocols, where new compound suggestions are enumerated using various algorithms. To increase the activity potency of generative approaches, they have recently been coupled with molecular docking, a leading methodology of structure-based drug design. In this review, we summarize progress since docking-based generative models emerged. We propose a new taxonomy for these methods and discuss their importance for the field of computer-aided drug design. In addition, we discuss the most promising directions for further development of generative protocols coupled with docking.
Brain as a complex system, harnessing systems neuroscience tools & notions for an empirical approach
Authors: Shervin Safavi
Date: 2023-12-20 00:00:00

Finding general principles underlying brain function has been appealing to scientists. Indeed, in some branches of science like physics and chemistry (and to some degree biology) a general theory often can capture the essence of a wide range of phenomena. Whether we can find such principles in neuroscience, and [assuming they do exist] what those principles are, are important questions. Abstracting the brain as a complex system is one of the perspectives that may help us answer this question. While it is commonly accepted that the brain is a (or even the) prominent example of a complex system, the far reaching implications of this are still arguably overlooked in our approaches to neuroscientific questions. One of the reasons for the lack of attention could be the apparent difference in foci of investigations in these two fields -- neuroscience and complex systems. This thesis is an effort toward providing a bridge between systems neuroscience and complex systems by harnessing systems neuroscience tools & notions for building empirical approaches toward the brain as a complex system. Perhaps, in the spirit of searching for principles, we should abstract and approach the brain as a complex adaptive system as the more complete perspective (rather than just a complex system). In the end, the brain, even the most "complex system", need to survive in the environment. Indeed, in the field of complex adaptive systems, the intention is understanding very similar questions in nature. As an outlook, we also touch on some research directions pertaining to the adaptivity of the brain as well.
Antifragility as a complex system's response to perturbations, volatility, and time
Authors: Cristian Axenie, Oliver López-Corona, Michail A. Makridis, Meisam Akbarzadeh, Matteo Saveriano, Alexandru Stancu, Jeffrey West
Date: 2023-12-21 00:00:00

Antifragility characterizes the benefit of a dynamical system derived from the variability in environmental perturbations. Antifragility carries a precise definition that quantifies a system's output response to input variability. Systems may respond poorly to perturbations (fragile) or benefit from perturbations (antifragile). In this manuscript, we review a range of applications of antifragility theory in technical systems (e.g., traffic control, robotics) and natural systems (e.g., cancer therapy, antibiotics). While there is a broad overlap in methods used to quantify and apply antifragility across disciplines, there is a need for precisely defining the scales at which antifragility operates. Thus, we provide a brief general introduction to the properties of antifragility in applied systems and review relevant literature for both natural and technical systems' antifragility. We frame this review within three scales common to technical systems: intrinsic (input-output nonlinearity), inherited (extrinsic environmental signals), and interventional (feedback control), with associated counterparts in biological systems: ecological (homogeneous systems), evolutionary (heterogeneous systems), and interventional (control). We use the common noun in designing systems that exhibit antifragile behavior across scales and guide the reader along the spectrum of fragility-adaptiveness-resilience-robustness-antifragility, the principles behind it, and its practical implications.
Computational detection of antigen specific B cell receptors following immunization
Authors: Maria Francesca Abbate, Thomas Dupic, Emmanuelle Vigne, Melody A. Shahsavarian, Aleksandra M. Walczak, Thierry Mora
Date: 2023-12-20 00:00:00
Tasks: Diversity

B cell receptors (BCRs) play a crucial role in recognizing and fighting foreign antigens. High-throughput sequencing enables in-depth sampling of the BCRs repertoire after immunization. However, only a minor fraction of BCRs actively participate in any given infection. To what extent can we accurately identify antigen-specific sequences directly from BCRs repertoires? We present a computational method grounded on sequence similarity, aimed at identifying statistically significant responsive BCRs. This method leverages well-known characteristics of affinity maturation and expected diversity. We validate its effectiveness using longitudinally sampled human immune repertoire data following influenza vaccination and Sars-CoV-2 infections. We show that different lineages converge to the same responding CDR3, demonstrating convergent selection within an individual. The outcomes of this method hold promise for application in vaccine development, personalized medicine, and antibody-derived therapeutics.
The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models
Authors: Maria Dzul, Charles B. Yackulic, William L. Kendall
Date: 2023-12-20 00:00:00

Survival is a key life history parameter that can inform management decisions and life history research. Because true survival is often confounded with permanent and temporary emigration from the study area, many studies must estimate apparent survival (i.e., probability of surviving and remaining inside the study area), which can be much lower than true survival for highly mobile species. One method for estimating true survival is the Barker joint live-recapture/live-resight (JLRLR) model, which combines capture data from a study area (hereafter the capture site) with resighting data from a broader geographic area. This model assumes that live resights occur throughout the entire area where animals can disperse to and this assumption is often not met in practice. Here we use simulation to evaluate survival bias from a JLRLR model under study design scenarios that differ in the site selection for resights: global, random, fixed including the capture site, and fixed excluding the capture site. Simulation results indicate that fixed designs that included the capture site showed negative survival bias, whereas fixed designs that excluded the capture site exhibited positive survival bias. The magnitude of the bias was dependent on movement and survival, where scenarios with high survival and frequent movement had minimal bias. In effort to help minimize bias, we developed a multistate version of the JLRLR and demonstrated reductions in survival bias compared to the single-state version for most designs. Our results suggest minimizing bias can be accomplished by: 1) using a random resight design when feasible and global sampling is not possible, 2) using the multistate JLRLR model when appropriate, 3) including the capture site in the resight sampling frame when possible, and 4) reporting survival as apparent survival if fixed sites are used for resight with the single state JLRLR model.
Empowering health in aging: Innovation in undernutrition detection and prevention through comprehensive monitoring
Authors: Abderrahim Derouiche, Ghazi Bouaziz, Damien Brulin, Eric Campo, Antoine Piau
Date: 2023-12-21 00:00:00
Tasks: Nutrition

Addressing the health challenges faced by the aging population, particularly undernutrition, is of paramount importance, given the significant representation of older individuals in society. Undernutrition arises from a disbalance between nutritional intake and energy expenditure, making its diagnosis crucial. Advances in technology allowed a better precision and efficiency of biomarker measurements, making it easier to detect undernutrition in the elderly. This article introduces an innovative system developed as part of the CART initiative at Toulouse University Hospital in France. This system takes a comprehensive approach to monitor health and well-being, collecting data that can provide insights, shape health outcomes, and even predict them. A key focus of this system is on identifying nutrition-related behaviors. By integrating quantitative and clinical assessments, which include biannual nutritional evaluations, as well as physical and physiological measurements like mobility and weight, this approach improves the diagnosis and prevention of undernutrition risks. It offers a more holistic perspective aligned with physiological standards. An example is given with the data collection of an elderly person followed at home for 3 months. We believe that this advance could make a significant contribution to the overall improvement of health and well-being, particularly in the elderly population.