pwc-archive/papers-with-abstracts huggingface dataset:
Cell lineage statistics with incomplete population trees
Authors: Arthur Genthon, Takashi Nozoe, Luca Peliti, David Lacoste
Date: 2023-05-09 00:00:00

Cell lineage statistics is a powerful tool for inferring cellular parameters, such as division rate, death rate or the population growth rate. Yet, in practice such an analysis suffers from a basic problem: how should we treat incomplete lineages that do not survive until the end of the experiment? Here, we develop a model-independent theoretical framework to address this issue. We show how to quantify fitness landscape, survivor bias and selection for arbitrary cell traits from cell lineage statistics in the presence of death, and we test this method using an experimental data set in which a cell population is exposed to a drug that kills a large fraction of the population. This analysis reveals that failing to properly account for dead lineages can lead to misleading fitness estimations. For simple trait dynamics, we prove and illustrate numerically that the fitness landscape and the survivor bias can in addition be used for the non-parametric estimation of the division and death rates, using only lineage histories. Our framework provides universal bounds on the population growth rate, and a fluctuation-response relation which quantifies the reduction of population growth rate due to the variability in death rate. Further, in the context of cell size control, we obtain generalizations of Powell's relation that link the distributions of generation times with the population growth rate, and show that the survivor bias can sometimes conceal the adder property, namely the constant increment of volume between birth and division.
Dynamical properties and mechanisms of metastability: a perspective in neuroscience
Authors: Kalel L. Rossi, Roberto C. Budzinski, Everton S. Medeiros, Bruno R. R. Boaretto, Lyle Muller, Ulrike Feudel
Date: 2023-05-09 00:00:00

Metastability, characterized by a variability of regimes in time, is a ubiquitous type of neural dynamics. It has been formulated in many different ways in the neuroscience literature, however, which may cause some confusion. In this Perspective, we discuss metastability from the point of view of dynamical systems theory. We extract from the literature a very simple but general definition through the concept of metastable regimes as long-lived but transient epochs of activity with unique dynamical properties. This definition serves as an umbrella term that encompasses formulations from other works, and readily connects to concepts from dynamical systems theory. This allows us to examine general dynamical properties of metastable regimes, propose in a didactic manner several dynamics-based mechanisms that generate them, and discuss a theoretical tool to characterize them quantitatively. This perspective leads to insights that help to address issues debated in the literature and also suggest pathways for future research.
Osmolyte-Induced Protein Stability Changes Explained by Graph Theory
Authors: Mattia Miotto, Nina Warner, Giancarlo Ruocco, Gian Gaetano Tartaglia, Oren A. Scherman, Edoardo Milanetti
Date: 2023-05-08 00:00:00

Enhanced stabilisation of protein structures via the presence of inert excipients is a key mechanism adopted both by physiological systems and in biotechnological applications. While the intrinsic stability of proteins is ultimately fixed by their amino acid composition and organisation, the interactions between excipients and proteins together with their concentrations introduce an additional layer of complexity and in turn, method of modulating protein stability. Here, we combined experimental measurements with molecular dynamics simulations and graph-theory based analyses to assess the stabilising/destabilising effects of different kinds of osmolytes on proteins during heat-mediated denaturation. We found that (i) proteins in solution with stability-enhancing osmolytes tend to have more compact interaction networks than those assumed in presence of destabilising excipients; (ii) a strong negative correlation (R = -0.85) characterises the relationship between the melting temperature Tm and the preferential interaction coefficient defined by the radial distribution functions of osmolytes and water around the protein and (iii) a positive correlation exists between osmolyte-osmolyte clustering and the extent of preferential exclusion from the local domain of the protein, suggesting that exclusion may be driven by enhanced steric hindrance of aggregated osmolytes.
Software-defined Optoacoustic Tomography
Authors: Roberto Insabella, Martin Gonzalez, Lucas Riobo, Klaus Hass, Francisco Veiras
Date: 2023-05-04 00:00:00

In this work we present the first application of software-defined optoelectronics (SDO) for bidimensional optoacoustic tomography (OAT). The SDO concept refers to optoelectronic systems where the functionality associated with the conditioning and processing of optical and electrical signals are digitally implemented and controlled by software. This paradigm takes advantage of the flexibility of software-defined hardware platforms to develop adaptive instrumentation systems. We implement an OAT system based on a heterodyne interferometer in a Mach-Zehnder configuration and a commercial software-defined radio platform (SDR). Here the SDR serves as a function generator and oscilloscope at the same time providing perfect carrier synchronization between its transmitter and receiver in a coherent baseband modulator scheme. Therefore, the carrier synchronization enables us to have a much better phase recovery. We study the performance of the OAT SDO system by means of different bidimensional phantoms and the analysis of the reconstructed images.
Real-Time Blind Photonic Interference Cancellation for mmWave MIMO
Authors: Joshua C. Lederman, Weipeng Zhang, Thomas Ferreira de Lima, Eric C. Blow, Simon Bilodeau, Bhavin J. Shastri, Paul R. Prucnal
Date: 2023-05-06 00:00:00

Multiple-input multiple-output (MIMO) mmWave devices broadcast multiple spatially-separated data streams simultaneously in order to increase data transfer rates. Data transfer can, however, be compromised by interference. Conventional techniques for mitigating interference require additional space and power not generally available in handheld mobile devices. Here, we propose a photonic mmWave MIMO receiver architecture capable of interference cancellation with greatly reduced space and power needs. We demonstrate real-time photonic interference cancellation with an integrated FPGA-photonic system that executes a novel zero-calibration micro-ring resonator control algorithm. The system achieves sub-second cancellation weight determination latency with sub-Nyquist sampling. We evaluate the impact of canceller design parameters on performance, establishing that effective photonic cancellation is possible in handheld devices with less than 30 ms weight determination latency.
GPT in Game Theory Experiments
Authors: Fulin Guo
Date: 2023-05-09 00:00:00
Tasks: Fairness

This paper explores the use of Generative Pre-trained Transformers (GPT) in strategic game experiments, specifically the ultimatum game and the prisoner's dilemma. I designed prompts and architectures to enable GPT to understand the game rules and to generate both its choices and the reasoning behind decisions. The key findings show that GPT exhibits behaviours similar to human responses, such as making positive offers and rejecting unfair ones in the ultimatum game, along with conditional cooperation in the prisoner's dilemma. The study explores how prompting GPT with traits of fairness concern or selfishness influences its decisions. Notably, the "fair" GPT in the ultimatum game tends to make higher offers and reject offers more frequently compared to the "selfish" GPT. In the prisoner's dilemma, high cooperation rates are maintained only when both GPT players are "fair". The reasoning statements GPT produces during gameplay reveal the underlying logic of certain intriguing patterns observed in the games. Overall, this research shows the potential of GPT as a valuable tool in social science research, especially in experimental studies and social simulations.
Resource Dimensioning for Single-Cell Edge Video Analytics
Authors: Jaume Anguera Peris, Viktoria Fodor
Date: 2023-05-09 00:00:00

Edge intelligence is an emerging technology where the base stations located at the edge of the network are equipped with computing units that provide machine learning services to the end users. To provide high-quality services in a cost-efficient way, the wireless and computing resources need to be dimensioned carefully. In this paper, we address the problem of resource dimensioning in a single-cell system that supports edge video analytics under latency and accuracy constraints. We show that the resource-dimensioning problem can be transformed into a convex optimization problem, and we provide numerical results that give insights into the trade-offs between the wireless and computing resources for varying cell sizes and for varying intensity of incoming tasks. Overall, we observe that the wireless and computing resources exhibit opposite trends; the wireless resources favor from smaller cells, where high attenuation losses are avoided, and the computing resources favor from larger cells, where statistical multiplexing allows for computing more tasks. We also show that small cells with low loads have high per-request costs, even when the wireless resources are increased to compensate for the low multiplexing gain at the servers.
CSI-Inpainter: Enabling Visual Scene Recovery from CSI Time Sequences for Occlusion Removal
Authors: Cheng Chen, Shoki Ohta, Takayuki Nishio, Mehdi Bennis, Jihong Park, Mohamed Wahib
Date: 2023-05-09 00:00:00
Tasks: Image Inpainting, Image Restoration

Introducing CSI-Inpainter, a pioneering approach for occlusion removal using Channel State Information (CSI) time sequences, this work propels the application of wireless signal processing into the realm of visual scene recovery. Departing from traditional occlusion removal, CSI-Inpainter leverages CSI data to construct and refine obscured visual elements in a scene, facilitating recovery independent of lighting conditions. Validated through comprehensive testing in both office and industrial environments, CSI-Inpainter demonstrates a robust capacity for discerning and reconstructing occluded segments, establishing a new frontier for obstacle removal. This first-of-its-kind framework offers a transformative perspective on how environmental visual information can be extracted from CSI, thereby broadening the scope for computer vision applications in everyday contexts.
Radar Altimeter Redesign for Multi-Stage Interference Risk Mitigation in 5G and Beyond
Authors: Jarret Rock, Ying Wang
Date: 2023-05-09 00:00:00
Tasks: Collision Avoidance

The radar altimeter is installed on most 14 CFR Pt 25 category aircraft, which are applicable to passenger travel and represent most airline traffic. The radar altimeter system is highly accurate and reports the height above the terrain. It plays a significant role in the take-off, approach, and landing phases of the applicable aircraft. In critical conditions, including reduced visibility, proximity to terrain, collision avoidance, and autoland procedures, the accuracy of radar altimeters is crucial to the safety of aircraft. This study aims to address the inappropriate behavior of the susceptible system that may cause essential safety concerns with unknown interoperability and operational impacts. We design and verify a strategic approach to mitigate the risks of potential airborne interference to a radar altimeter due to the coexistence of a 5G and future G signal, especially with the growing demand for the Space Air Ground Integrated Network (SAGIN). This study details a design change to a pre-existing radar altimeter system, and the process necessary to gain certification approval following this change is analyzed. We address the certification aspects from a TSO perspective resulting from changes made to a system post-certification. Artifacts, as defined in the FAA Project Specific Certification Plan template, including the Change Impact Analysis, Means of Compliance, and Test Plans, which are mandated by the certification authorities and requested by aircraft manufacturers and operators to ensure a level of compliance during the engineering cycle, have been adhered to.
3DInvNet: A Deep Learning-Based 3D Ground-Penetrating Radar Data Inversion
Authors: Qiqi Dai, Yee Hui Lee, Hai-Han Sun, Genevieve Ow, Mohamed Lokman Mohd Yusof, Abdulkadir C. Yucel
Date: 2023-05-09 00:00:00
Tasks: 3D Reconstruction, Decoder, Denoising, GPR

The reconstruction of the 3D permittivity map from ground-penetrating radar (GPR) data is of great importance for mapping subsurface environments and inspecting underground structural integrity. Traditional iterative 3D reconstruction algorithms suffer from strong non-linearity, ill-posedness, and high computational cost. To tackle these issues, a 3D deep learning scheme, called 3DInvNet, is proposed to reconstruct 3D permittivity maps from GPR C-scans. The proposed scheme leverages a prior 3D convolutional neural network with a feature attention mechanism to suppress the noise in the C-scans due to subsurface heterogeneous soil environments. Then a 3D U-shaped encoder-decoder network with multi-scale feature aggregation modules is designed to establish the optimal inverse mapping from the denoised C-scans to 3D permittivity maps. Furthermore, a three-step separate learning strategy is employed to pre-train and fine-tune the networks. The proposed scheme is applied to numerical simulation as well as real measurement data. The quantitative and qualitative results show the network capability, generalizability, and robustness in denoising GPR C-scans and reconstructing 3D permittivity maps of subsurface objects.
EMF Exposure Mitigation in RIS-Assisted Multi-Beam Communications
Authors: Herman L. dos Santos, Cristian J. Vaca-Rubio, Radosław Kotaba, Yi Song, Taufik Abrão, Petar Popovski
Date: 2023-05-09 00:00:00

This paper proposes a method for reducing {third-party} exposure to electromagnetic fields (EMF) by exploiting the capability of a reconfigurable intelligent surfaces' (RIS) to manipulate the electromagnetic environment. We consider users capable of multi-beam communication, such that a user can use a set of different propagation paths enabled by the RIS. The optimization objective is to find propagation alternatives that allow to maintain the target quality of service while minimizing the level of EMF at surrounding non-intended users (NUEs). We provide an evolutionary heuristic solution based on Genetic Algorithm (GA) for power equalization and multi-beam selection of a codebook at the Base Station. Our results show valuable insights into how RIS-assisted multi-beam communications can mitigate EMF exposure with minimal degradation of the spectral efficiency.
Integrated Super-Resolution Sensing and Communication with 5G NR Waveform: Signal Processing with Uneven CPs and Experiments
Authors: Chaoyue Zhang, Zhiwen Zhou, Huizhi Wang, Yong Zeng
Date: 2023-05-09 00:00:00
Tasks: Integrated sensing and communication, ISAC, Super-Resolution

Integrated sensing and communication (ISAC) is a promising technology to simultaneously provide high-performance wireless communication and radar sensing services in future networks. In this paper, we propose the concept of \emph{integrated super-resolution sensing and communication} (ISSAC), which uses super-resolution algorithms in ISAC systems to achieve extreme sensing performance for those critical parameters, such as delay, Doppler, and angle of the sensing targets. Based on practical fifth generation (5G) New Radio (NR) waveforms, the signal processing techniques of ISSAC are investigated and prototyping experiments are performed to verify the achievable performance. To this end, we first study the effect of uneven cyclic prefix (CP) lengths of 5G NR orthogonal frequency division multiplexing (OFDM) waveforms on various sensing algorithms. Specifically, the performance of the standard Periodogram based radar processing method, together with the two classical super-resolution algorithms, namely, MUltiple SIgnal Classification (MUSIC) and Estimating Signal Parameter via Rotational Invariance Techniques (ESPRIT) are analyzed in terms of the delay and Doppler estimation. To resolve the uneven CP issue, a new structure of steering vector for MUSIC and a new selection of submatrices for ESPRIT are proposed. Furthermore, an ISSAC experiment platform is setup to validate the theoretical analysis, and the experimental results show that the performance degradation caused by unequal CP length is insignificant and high-resolution delay and Doppler estimation of the target can be achieved with 5G NR waveforms.
Synthesis of Length-Tunable DNA Carriers for Nanopore Sensing
Authors: Zachary Roelen, Vincent Tabard-Cossa
Date: 2023-05-08 00:00:00

Molecular carriers represent an increasingly common strategy in the field of nanopore sensing to use secondary molecules to selectively report on the presence of target analytes in solution, allowing for sensitive assays of otherwise hard-to-detect molecules such as small, weakly-charged proteins. However, existing carrier designs can often introduce drawbacks to nanopore experiments including higher levels of cost/complexity and carrier-pore interactions that lead to ambiguous signals and elevated clogging rates. In this work, we present a simple method of carrier production based on sticky-ended DNA molecules that emphasizes ease-of-synthesis and compatibility with nanopore sensing and analysis. In particular, our method incorporates the ability to flexibly control the length of the DNA carriers produced, enhancing the multiplexing potential of this carrier system through the separable nanopore signals they could generate for distinct targets. A proof-of-concept nanopore experiment is also presented, involving carriers produced by our method with multiple lengths and attached to DNA nanostructure targets, in order to validate the capabilities of the system. As the breadth of applications for nanopore sensors continues to expand, the availability of tools such as those presented here to help translate the outcomes of these applications into robust nanopore signals will be of major importance.
Prokaryotic genome editing based on the subtype I-B-Svi CRISPR-Cas system
Authors: Wang-Yu Tong, De-Xiang Yong, Xin Xu, Cai-Hua Qiu, Yan Zhang, Xing-Wang Yang, Ting-Ting Xia, Qing-Yang Liu, Su-Li Cao, Yan Sun, Xue Li
Date: 2023-05-08 00:00:00
Tasks: Diversity, Vocal Bursts Type Prediction

Type I CRISPR-Cas systems are the most common among six types of CRISPR-Cas systems, however, non-self-targeting genome editing based on a single Cas3 of type I CRISPR-Cas systems has not been reported. Here, we present the subtype I-B-Svi CRISPR-Cas system (with three confirmed CRISPRs and a cas gene cluster) and genome editing based on this system found in Streptomyces virginiae IBL14. Importantly, like the animal-derived bacterial protein SpCas9 (1368 amino-acids), the single, compact, non-animal-derived bacterial protein SviCas3 (771 amino-acids) can also direct template-based microbial genome editing through the target cell's own homology-directed repair system, which breaks the view that the genome editing based on type I CRISPR-Cas systems requires a full Cascade. Notably, no off-target changes or indel-formation were detected in the analysis of potential off-target sites. This discovery broadens our understanding of the diversity of type I CRISPR-Cas systems and will facilitate new developments in genome editing tools.
A Chip-Firing Game for Biocrust Reverse Succession
Authors: Shloka V. Janapaty
Date: 2023-05-09 00:00:00

Experimental work suggests that biological soil crusts, dominant primary producers in drylands and tundra, are particularly vulnerable to disturbances that cause reverse ecological succession. To model successional transitions in biocrust communities, we propose a resource-firing game that captures succession dynamics without specifying detailed function forms. The model is evaluated in idealized terrestrial ecosystems, where disturbances are modeled as a reduction in available resources that triggers inter-species competition. The resource-firing game is executed on a finite graph with nodes representing species in the community and a sink node that becomes active when every species is depleted of resources. First, we discuss the theoretical basis of the resource-firing game, evaluate it in the light of existing literature, and consider the characteristics of a biocrust community that has evolved to equilibrium. We then examine the dependence of resource-firing and game stability on species richness, showing that high species richness increases the probability of very short and long avalanches, but not those of intermediate length. Indeed, this result suggests that the response of the community to disturbance is both directional and episodic, proceeding towards reverse succession in bursts of variable length. Finally, we incorporate the spatial structure of the biocrust community into a Cayley Tree and derive a formula for the probability that a disturbance, modeled as a random attack, initiates a large species-death event.
Network pharmacology on the mechanism of Yi Qi Tong Qiao Pill inhibiting allergic rhinitis
Authors: Boyang Wang, DingFan Zhang, Tingyu Zhang, Chayanis Sutcharitchan, Jianlin Hua, Dongfang Hua, Bo Zhang, Shao Li
Date: 2023-05-06 00:00:00

Objective: The purpose of this study is to reveal the mechanism of action of Yi Qi Tong Qiao Pill (YQTQP) in the treatment of allergic rhinitis (AR), as well as establish a paradigm for the researches on traditional Chinese medicine (TCM) from systematic perspective. Methods: Based on the data collected from TCM-related and disease-related databases, target profiles of compounds in YQTQP were calculated through network-based algorithms and holistic targets of TQTQP was constructed. Network target analysis was performed to explore the potential mechanisms of YQTQP in the treatment of AR and the mechanisms were classified into different modules according to their biological functions. Besides, animal and clinical experiments were conducted to validate our findings inferred from Network target analysis. Results: Network target analysis showed that YQTQP targeted 12 main pathways or biological processes related to AR, represented by those related to IL-4, IFN-{\gamma}, TNF-{\alpha} and IL-13. These results could be classified into 3 biological modules, including regulation of immune and inflammation, epithelial barrier disorder and cell adhesion. Finally, a series of experiments composed of animal and clinical experiments, proved our findings and confirmed that YQTQP could improve related symptoms of AR, like permeability of nasal mucosa epithelium. Conclusion: A combination of Network target analysis and the experimental validation indicated that YQTQP was effective in the treatment of AR and might provide a new insight on revealing the mechanism of TCM against diseases.
Proofs that the Gerber Statistic is Positive Semidefinite
Authors: S. Gerber, H. Markowitz, P. Ernst, Y. Miao, B. Javid, P. Sargen
Date: 2023-05-09 00:00:00

In this brief note, we prove that both forms of the Gerber statistic introduced in Gerber et al. (2022) are positive semi-definite.