pwc-archive/papers-with-abstracts huggingface dataset:
Air-Ground Integrated Sensing and Communications: Opportunities and Challenges
Authors: Zesong Fei, Xinyi Wang, Nan Wu, Jingxuan Huang, J. Andrew Zhang
Date: 2023-02-13 00:00:00
Tasks: ISAC

The air-ground integrated sensing and communications (AG-ISAC) network, which consists of unmanned aerial vehicles (UAVs) and ground terrestrial networks, offers unique capabilities and demands special design techniques. In this article, we provide a review on AG-ISAC, by introducing UAVs as ``relay'' nodes for both communications and sensing to resolve the power and computation constraints on UAVs. We first introduce an AG-ISAC framework, including the system architecture and protocol. Four potential use cases are then discussed, with the analysis on the characteristics and merits of AG-ISAC networks. The research on several critical techniques for AG-ISAC is then discussed. Finally, we present our vision of the challenges and future research directions for AG-ISAC, to facilitate the advancement of the technology.
Implementation and Performance Analysis of a Low Resolution OFDM System Prototype With Low Cost Hardware
Authors: Eder O. de Souza, João T. Dias, Demerson N. Gonçalves
Date: 2023-02-11 00:00:00

The present work focus on the implementation and analyze of performance of a low-resolution OFDM system prototype with low-cost hardware. A software defined radio (SDR) system was chosen in this implementation due to its various advantages over a traditional radio system. Among the options of SDR devices available, the use of universal software radio peripherals (USRP) was avoided due to its high cost, despite its popularity in this field of research. Alternatively, a combination of two low-cost SDRs, "Hackrf One" and "RTL- SDR Blog V3" with the GNU Radio, a popular, free and open source radio software, were used. Thus, it was possible to emulate the behavior of a low resolution ADC in the receiver, characterize its performance and estimate its energy savings. This allowed us to determine the feasibility of building a component with the analog-to-digital conversion function with few bits of resolution. We conclude that the performance of an ADC with at least 5 bits of resolution is pretty reasonable and that this reduction in the number of bits, in comparison to 8-bit ADC, represents a fairly expressive energy saving.
Design Concept of a Low-Terahertz Imaging Radar
Authors: Amin Aminaei
Date: 2023-02-11 00:00:00

Terahertz (THz) imaging proved to be an efficient and powerful nondestructive examination (NDE) method for inspection of materials and detection of defects. Here, we present the development of a Low-Terahertz Imaging Radar(L-TIR) which is specifically designed for the evaluation of Fibre-Reinforced Polymer (FRP) composites. L-TIR will be a compact active radar with a laser pulse transmitter and a receiver which operates at the lower THz band (1 THz-2 THz). L-TIR will probe the structure and sub-layers of the FRP composites which makes it a suitable and fast tool to detect the cracks, breaks and deamination at sub-mm resolution. Keywords: THz Imaging Radar, NDE Method, FRP Composites
Data-Driven Web-Based Patching Management Tool Using Multi-Sensor Pavement Structure Measurements
Authors: Sneha Jha, Yaguang Zhang, Bongsuk Park, Seonghwan Cho, James V. Krogmeier, Tandra Bagchi, John E. Haddock
Date: 2023-02-10 00:00:00
Tasks: Management

Automating pavement maintenance suggestions is challenging,especially for actionable recommendations such as patching location,depth and priority.It is common practice among State agencies to manually inspect road segments of interest and decide maintenance requirements based on the pavement condition index (PCI).However,standalone PCI only evaluates the pavement surface condition and coupled with the variability in human perception of pavement distress,limits the accuracy and quality of current pavement maintenance practices.Here,a need for multi-sensor data integrated with standardized pavement distress condition ratings is required.This study explores the possibility of estimating the appropriate pavement patching strategy (i.e.,patching location,depth,and quantity) by integrating pavement structural and surface condition assessment with pavement specific ratings of distress.Especially,it combines pavement structural condition assessment parameter;falling weight deflectometer deflections along with surface condition assessment parameters;international roughness index,and cracking density for a better representation of overall pavement distress condition.Then,a pavement specific threshold-based patching suggestion algorithm is implemented to evaluate the pavement overall distress condition into a priority-based patching suggestion.The novelty in the use of pavement specific thresholds is placed on its data-driven ability to determine threshold values from current road condition measurements using a reliability concept validated by the theoretical pavement condition rating,pavement structural number.A web-based patching manager tool (PMT) was implemented to automate the patching suggestion procedure and visualize the results.Validated with road surface images obtained from three-dimensional laser sensors,PMT could successfully capture localized distresses in existing pavements.
3D Molecular Generation via Virtual Dynamics
Authors: Shuqi Lu, Lin Yao, Xi Chen, Hang Zheng, Di He, Guolin Ke
Date: 2023-02-12 00:00:00
Tasks: Drug Design, Drug Discovery

Structure-based drug design, i.e., finding molecules with high affinities to the target protein pocket, is one of the most critical tasks in drug discovery. Traditional solutions, like virtual screening, require exhaustively searching on a large molecular database, which are inefficient and cannot return novel molecules beyond the database. The pocket-based 3D molecular generation model, i.e., directly generating a molecule with a 3D structure and binding position in the pocket, is a new promising way to address this issue. Herein, we propose VD-Gen, a novel pocket-based 3D molecular generation pipeline. VD-Gen consists of several carefully designed stages to generate fine-grained 3D molecules with binding positions in the pocket cavity end-to-end. Rather than directly generating or sampling atoms with 3D positions in the pocket like in early attempts, in VD-Gen, we first randomly initialize many virtual particles in the pocket; then iteratively move these virtual particles, making the distribution of virtual particles approximate the distribution of molecular atoms. After virtual particles are stabilized in 3D space, we extract a 3D molecule from them. Finally, we further refine atoms in the extracted molecule by iterative movement again, to get a high-quality 3D molecule, and predict a confidence score for it. Extensive experiment results on pocket-based molecular generation demonstrate that VD-Gen can generate novel 3D molecules to fill the target pocket cavity with high binding affinities, significantly outperforming previous baselines.
Physics of collective cell migration
Authors: Ivana Pajic-Lijakovic, Milan Milivojevic
Date: 2023-02-11 00:00:00

Movement of cell clusters along extracellular matrices (ECM) during tissue development, wound healing, and early stage of cancer invasion involve various inter-connected migration modes such as: (1) cell movement within clusters, (2) cluster extension (wetting) and compression (de-wetting), and (3) directional cluster movement. It has become increasingly evident that dilational and volumetric viscoelasticity of cell clusters and their surrounding substrate significantly influence these migration modes through physical parameters such as: cell and matrix surface tensions, interfacial tension between cells and substrate, gradients of surface and interfacial tensions, as well as, the accumulation of cell and matrix residual stresses. Inhomogeneous distribution of cell surface tension along migrating cell cluster can appear as a consequence of different strength of cell-cell adhesion contacts and cell contractility between leader and follower cells. While the directional cell migration caused by the matrix stiffness gradient (i.e. durotaxis) has been widely elaborated, the structural changes of matrix surface caused by cell tractions which lead to the generation of the matrix surface tension gradient has not been considered yet. The main goal of this theoretical consideration is to clarify the roles of various physical parameters in collective cell migration based on the formulating biophysical model. This complex phenomenon is discussed on the model systems such as the movement of cell clusters on the collagen I gel matrix by simultaneously reviewing various experimental data with and without cells.
Temporal stability of intracranial EEG abnormality maps for localising epileptogenic tissue
Authors: Yujiang Wang, Gabrielle M Schroeder, Jonathan J Horsley, Mariella Panagiotopoulou, Fahmida A Chowdhury, Beate Diehl, John S Duncan, Andrew W McEvoy, Anna Miserocchi, Jane de Tisi, Peter N Taylor
Date: 2023-02-11 00:00:00
Tasks: EEG, Electroencephalogram (EEG)

Objective: Identifying abnormalities in interictal intracranial EEG, by comparing patient data to a normative map, has shown promise for the localisation of epileptogenic tissue and prediction of outcome. The approach typically uses short interictal segments of around one minute. However, the temporal stability of findings has not been established. Methods: Here, we generated a normative map of iEEG in non-pathological brain tissue from 249 patients. We computed regional band power abnormalities in a separate cohort of 39 patients for the duration of their monitoring period (0.92-8.62 days of iEEG data, mean 4.58 days per patient, over 4,800 hours recording). To assess the localising value of band power abnormality, we computed DRS - a measure of how different the surgically resected and spared tissue were in terms of band power abnormalities - over time. Results: In each patient, band power abnormality was relatively consistent over time. The median DRS of the entire recording period separated seizure free (ILAE = 1) and not seizure free (ILAE > 1) patients well (AUC = 0.69). This effect was similar interictally (AUC = 0.69) and peri-ictally (AUC = 0.71). Significance: Our results suggest that band power abnormality DRS, as a predictor of outcomes from epilepsy surgery, is a relatively robust metric over time. These findings add further support for abnormality mapping of neurophysiology data during presurgical evaluation.
The dual-path hypothesis for the emergence of anosognosia in Alzheimer's disease
Authors: Katia Andrade, Thomas Guiyesse, Takfarinas Medani, Etienne Koechlin, Dimitrios Pantazis, Bruno Dubois
Date: 2023-02-11 00:00:00

Although neurocognitive models have been proposed to explain anosognosia in Alzheimer's disease (AD), the neural cascade responsible for its origin in the human brain remains unknown. Here, we build on a mechanistic dual-path hypothesis that brings error-monitoring and emotional processing systems as key elements for self-awareness, with distinct impacts on the emergence of anosognosia in AD. Proceeding from the notion of anosognosia as a dimensional syndrome, ranging from the lack of concern about one's own deficits (i.e., anosodiaphoria) to the complete lack of awareness of deficits, our hypothesis states that (i) unawareness of deficits would result from a failure in the error-monitoring system, whereas (ii) anosodiaphoria would more likely result from an imbalance between emotional processing and error-monitoring systems. In the first case, a synaptic failure in the error-monitoring system, in which the cingulate cortex plays a major role, would have a negative impact on error (or deficits) awareness, preventing patients from becoming aware of their condition. In the second case, an impairment in the emotional processing system, in which the amygdala and orbitofrontal cortex play a major role, would prevent patients from monitoring the internal milieu for relevant errors (or deficits) and assigning appropriate value to them, thus biasing their impact on the error-monitoring system. Our hypothesis stems from two scientific premises. One comes from preliminary results in AD patients showing a synaptic failure in the error-monitoring system and decline of awareness at the time of diagnosis. Another comes from the somatic marker hypothesis, which proposes that emotional signals are critical to adaptive behavior. Further exploration will be of great interest to illuminate the foundations of self-awareness and improve our understanding of the underlying mechanisms of anosognosia in AD.
A network-based biomarkers discovery of Cold/Hot ZHENG chronic gastritis and Cold/Hot herbs of formulae
Authors: Boyang Wang, Pan Chen, Peng Zhang, Shao Li
Date: 2023-02-10 00:00:00

Objective: To discover biomarkers and uncover the mechanism of Cold/Hot ZHENG (syndrome in traditional Chinese medicine) chronic gastritis (CG) and Cold/Hot herbs in traditional Chinese medicine (TCM) formulae on systematic biology. Background: CG is a common inflammatory disease and the diagnosis of CG in TCM can be classified into Cold ZHENG (Asthenic Cold) and Hot ZHENG (Excess Hot). However, the molecular features of Cold/Hot ZHENG in CG and the mechanism of Cold/Hot herbs in formulae for CG remained unclear. Methods: Based on data of 35 patients of Cold/Hot ZHENG CG and 3 scRNA-seq CG samples, we conduct analysis with transcriptomics datasets and algorithms, to discover biomarkers for Cold/Hot ZHENG CG. And we collected 25 formulae (with traditional effects related to Cold/Hot ZHENG) for CG and corresponding 89 Cold/Hot herbs (including Warm/Cool herbs) to discover features and construct target networks of Cold/Hot herbs on the basis of network target and enrichment analysis. Results: Biomarkers of Cold/Hot ZHENG CG represented by CCL2 and LEP suggested that Hot ZHENG CG might be characterized by over-inflammation and exuberant metabolism, and Cold ZHENG CG showed a trend of suppression in immune regulation and energy metabolism. And biomarkers of Cold/Hot ZHENG showed also significant changes in the progression of gastric cancer. And biomarkers and pathways of Hot herbs intend to regulate immune responses and energy metabolism, while those of Cold herbs were likely to participate in anti-inflammation effect. Conclusion: In this study, we found that the biomarkers and mechanism of Cold/Hot ZHENG CG and those of Cold/Hot herbs were closely related to the regulation of immune and metabolisms. These findings may reflect the mechanism, build bridges between multiple views of Cold/Hot ZHENG and Cold/Hot herbs, and provide a research paradigm for further achieving precision TCM.
An Algebraic Discussion of Bisexual Populations with Wolbachia Infection I: Discrete Dynamical System Approach
Authors: Barış Özdinç, Songül Esin, Müge Kanuni
Date: 2023-02-13 00:00:00

This is the first paper in the sequel studying the Wolbachia-infection in bisexual populations. This paper considers the behavior of the population as a discrete dynamical system. The recurrence relation is obtained as a function of the initial infected male/female frequencies and the cytoplasmic incompatibility of the population. The experimental data from Wolbachia-infected terrestrial isopod populations and the model proposed in Wolbachia-infected mosquitoes from literature is compared with the discrete dynamical system achieved.
Physiologically-Based Pharmacokinetic Modeling of Blood Clearance of Liver Fluorescent Markers for the Assessment of the Degree of Hepatic Ischemia-Reperfusion Injury
Authors: Christopher Monti, Said H. Audi, Justin Womack, Seung-Keun Hong, Yongqiang Yang, Joohyun Kim, Ranjan K. Dash
Date: 2023-02-10 00:00:00

During liver transplantation, ischemia-reperfusion injury (IRI) is inevitable and decreases the overall success of the surgery. While guidelines exist, there is no reliable way to quantitatively assess the degree of IRI present in the liver. Our recent study has shown a correlation between the bile-to-plasma ratio of FDA-approved sodium fluorescein (SF) and the degree of hepatic IRI, presumably due to IRI-induced decrease in the activity of the hepatic multidrug resistance-associated protein 2 (MRP2); however, the contribution of SF blood clearance via the bile is still convoluted with other factors, such as renal clearance. In this work, we sought to computationally model SF blood clearance via the bile. First, we converted extant SF fluorescence data from rat whole blood, plasma, and bile to concentrations using calibration curves. Next, based on these SF concentration data, we generated a liver-centric, physiologically-based pharmacokinetic (PBPK) model of SF liver uptake and clearance via the bile. Model simulations show that SF bile concentration is highly sensitive to a change in the activity of hepatic MPR2. These simulations suggest that SF bile clearance along with the PBPK model can be used to quantify the effect of IRI on the activity of MRP2.
Long-term option pricing with a lower reflecting barrier
Authors: R. Guy Thomas
Date: 2023-02-11 00:00:00

This paper considers the pricing of long-term options on assets such as housing, where either government intervention or the economic nature of the asset is assumed to limit large falls in prices. The observed asset price is modelled by a geometric Brownian motion (the 'notional price') reflected at a lower barrier. The resulting observed price has standard dynamics but with localised intervention at the barrier, which allows arbitrage with interim losses; this is funded by the government's unlimited powers of intervention, and its exploitation is subject to credit constraints. Despite the lack of an equivalent martingale measure for the observed price, options on this price can be expressed as compound options on the arbitrage-free notional price, to which standard risk-neutral arguments can be applied. Because option deltas tend to zero when the observed price approaches the barrier, hedging with the observed price gives the same results as hedging with the notional price, and so exactly replicates option payoffs. Hedging schemes are not unique, with the cheapest scheme for any derivative being the one which best exploits the interventions at the barrier. The price of a put is clear: direct replication has a lower initial cost than synthetic replication, and the replication portfolio always has positive value. The price of a call is ambiguous: synthetic replication has a lower initial cost than direct replication, but the replication portfolio may give interim losses, and so the preferred replication strategy (and hence price) of a call may depend on what margin payments need to be made on these losses.
The Construction of Reality in an AI: A Review
Authors: Jeffrey W. Johnston
Date: 2023-02-03 00:00:00
Tasks: Lifelong learning, Survey

AI constructivism as inspired by Jean Piaget, described and surveyed by Frank Guerin, and representatively implemented by Gary Drescher seeks to create algorithms and knowledge structures that enable agents to acquire, maintain, and apply a deep understanding of the environment through sensorimotor interactions. This paper aims to increase awareness of constructivist AI implementations to encourage greater progress toward enabling lifelong learning by machines. It builds on Guerin's 2008 "Learning Like a Baby: A Survey of AI approaches." After briefly recapitulating that survey, it summarizes subsequent progress by the Guerin referents, numerous works not covered by Guerin (or found in other surveys), and relevant efforts in related areas. The focus is on knowledge representations and learning algorithms that have been used in practice viewed through lenses of Piaget's schemas, adaptation processes, and staged development. The paper concludes with a preview of a simple framework for constructive AI being developed by the author that parses concepts from sensory input and stores them in a semantic memory network linked to episodic data. Extensive references are provided.
Awareness requirement and performance management for adaptive systems: a survey
Authors: Tarik A. Rashid, Bryar A. Hassan, Abeer Alsadoon, Shko Qader, S. Vimal, Amit Chhabra, Zaher Mundher Yaseen
Date: 2023-01-22 00:00:00
Tasks: Management, Survey

Self-adaptive software can assess and modify its behavior when the assessment indicates that the program is not performing as intended or when improved functionality or performance is available. Since the mid-1960s, the subject of system adaptivity has been extensively researched, and during the last decade, many application areas and technologies involving self-adaptation have gained prominence. All of these efforts have in common the introduction of self-adaptability through software. Thus, it is essential to investigate systematic software engineering methods to create self-adaptive systems that may be used across different domains. The primary objective of this research is to summarize current advances in awareness requirements for adaptive strategies based on an examination of state-of-the-art methods described in the literature. This paper presents a review of self-adaptive systems in the context of requirement awareness and summarizes the most common methodologies applied. At first glance, it gives a review of the previous surveys and works about self-adaptive systems. Afterward, it classifies the current self-adaptive systems based on six criteria. Then, it presents and evaluates the most common self-adaptive approaches. Lastly, an evaluation among the self-adaptive models is conducted based on four concepts (requirements description, monitoring, relationship, dependency/impact, and tools).
Outlier-Based Domain of Applicability Identification for Materials Property Prediction Models
Authors: Gihan Panapitiya, Emily Saldanha
Date: 2023-01-17 00:00:00
Tasks: Prediction, Property Prediction

Machine learning models have been widely applied for material property prediction. However, practical application of these models can be hindered by a lack of information about how well they will perform on previously unseen types of materials. Because machine learning model predictions depend on the quality of the available training data, different domains of the material feature space are predicted with different accuracy levels by such models. The ability to identify such domains enables the ability to find the confidence level of each prediction, to determine when and how the model should be employed depending on the prediction accuracy requirements of different tasks, and to improve the model for domains with high errors. In this work, we propose a method to find domains of applicability using a large feature space and also introduce analysis techniques to gain more insight into the detected domains and subdomains.
Deep-Learning Quantitative Structural Characterization in Additive Manufacturing
Authors: Amra Peles, Vincent C. Paquit, Ryan R. Dehoff
Date: 2023-01-20 00:00:00
Tasks: Deep Learning, Image-to-Image Translation, Translation

With a goal of accelerating fabrication of additively manufactured components with precise microstructures, we developed a method for structural characterization of key features in additively manufactured materials and parts. The method utilizes deep learning based on an image-to-image translation conditional Generative Adversarial Neural Network architecture and enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing induced defects visible in etched optical images. These structural details are heterogeneous in nature. Our method specifies the microstructure state of an additive built via statistical distribution of structural details, based on an ensemble of collected images. Extensions of the method are proposed to address Artificial Intelligence implementation of developed machine learning model for in real time control of additive manufacturing.