Complex Routing Research Articles

A bi-objective optimization model of metro trains considering energy conservation and passenger waiting time

Continuous growth of energy consumption for metro systems has raised the public's concern. Meanwhile, both operators and passengers pursue for efficient metro services, especially during peak hours. This paper aims at designing a bi-objective optimization model and a new solution approach so that the energy conservation of metro trains and less passenger waiting time can be achieved. Firstly, considering complex routes, a multi-particle train operation model with the objectives of punctuality, parking accuracy, energy efficiency and safety provided is established for the minimization of traction energy consumption through investigating the optimal force coefficients and coast positions, while suitable dwell times and headway times of metro trains are found trough building a timetable model, which balances the regenerative energy, transfer and non-transfer passenger waiting time. Secondly, a deep reinforcement learning (DRL) and non-dominated sorting genetic algorithm II (NSGA-II) based two-layer solution approach is introduced for model calculation. Finally, comparison shows that the proposed model can achieve the energy conservation of metro trains by 9.16% with passenger waiting time decreased by 15.88%. More experiments further demonstrate the superiority of the developed model and solution approach.

Combating modern methods of legalisation (laundering) of the funds obtained by criminal means with the use of cryptocurrency

The problems of combating corruption have not lost their relevance over the years. Tolerant attitudes to corruption as a way to quickly solve everyday problems give rise to new ways of developing illegal activities in various spheres of public life. At the same time, while fully condemning corruption as a means of illicit enrichment, the majority of the population still follows the old path. Consequently, the interests of individuals aimed at enriching themselves by any means, including illegal means, are becoming a counterweight to the development of society.
 Money laundering remains a significant problem in the area of combating corruption. Unfortunately, the methods and means of carrying out illegal activities in order to conceal them and avoid responsibility for their commission are being updated on a daily basis. Successful money laundering requires high intelligence and an understanding of the processes of working with modern financial technologies. One of the areas of money laundering is the use of various types of cryptocurrencies and NFTs. The funds held by the offender go through a complex route before reaching their final destination. Illegally obtained funds introduced into the legal financial system in such a way as to avoid unnecessary questions about the origin of the money, through a significant number of transactions, are integrated into the financial system and can be used for any purpose.
 The current state of research on the development of cryptocurrencies as a tool for money laundering is not sufficiently disclosed at the national level. Most of the scientific works are of foreign origin. The article is aimed at finding ways to improve the current anti-corruption legislation. The author outlines the main features of the development of money laundering schemes using cryptocurrency as an instrument of such schemes. The author defines the main definitional categories of such concepts as “cryptocurrency”, “NFT”, “smurfs”, “drops”, etc. The main shortcomings of the institutional and regulatory mechanism for detecting and investigating this category of offences have been highlighted, taking into account the use of modern financial technologies. The study may be useful in improving legislation in the field of corruption prevention.

Digital technologies of transportation-related communication: Review and the state-of-the-art

Information and communication technologies (ICTs) play a significant role in transportation systems as they provide the connection between transportation system users, system planners, operators, and managers. Over the last few years, with advancements in ICTs, there has been a rapid change in travel behaviour. However, little is known about how ICTs and other emerging digital technologies are being utilised in transportation-related communication for public, private, and active transportation. To bridge this gap, this study aims to explore academic and grey literature focused on the use of digital technologies in transportation-related communication. The methodological approach employs a systematic literature review, with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) protocol, to identify digital technologies that are found promising among scholars and practitioners for research, testing and deployment. The study analysed 158 publications and identified some common themes of how these digital technologies can be implemented to improve access to transportation communication. The study finds that: (a) The main literature focus is how information is gathered and shared with transportation users; (b) Advances in mobile applications afford real-time route updates, easy navigation of complex routes, and personalised journey planning; (c) Some notable knowledge gaps exist in how these technologies are implemented—including, willingness to use and digital literacy to understand them; (d) Many digital technologies are at the trial or development phases, which have potential to improve how transportation information can be made readily accessible to all users.

Neural Network Estimators for Optimal Tour Lengths of Traveling Salesperson Problem Instances with Arbitrary Node Distributions

It is essential to solve complex routing problems to achieve operational efficiency in logistics. However, because of their complexity, these problems are often tackled sequentially using cluster-first, route-second frameworks. Unfortunately, such two-phase frameworks can suffer from suboptimality due to the initial phase. To address this issue, we propose leveraging information about the optimal tour lengths of potential clusters as a preliminary step, transforming the two-phase approach into a less myopic solution framework. We introduce quick and highly accurate Traveling Salesperson Problem (TSP) tour length estimators based on neural networks (NNs) to facilitate this. Our approach combines the power of NNs and theoretical knowledge in the routing domain, utilizing a novel feature set that includes node-level, instance-level, and solution-level features. This hybridization of data and domain knowledge allows us to achieve predictions with an average deviation of less than 0.7% from optimality. Unlike previous studies, we design and employ new instances replicating real-life logistics networks and morphologies. These instances possess characteristics that introduce significant computational costs, making them more challenging. To address these challenges, we develop a novel and efficient method for obtaining lower bounds and partial solutions to the TSP, which are subsequently utilized as solution-level predictors. Our computational study demonstrates a prediction error up to six times lower than the best machine learning (ML) methods on their training instances and up to 100 times lower prediction error on out-of-distribution test instances. Furthermore, we integrate our proposed ML models with metaheuristics to create an enumeration-like solution framework, enabling the improved solution of massive-scale routing problems. In terms of solution time and quality, our approach significantly outperforms the state-of-the-art solver, demonstrating the potential of our features, models, and the proposed method. History: This paper has been accepted for the Transportation Science Special Issue on Machine Learning Methods and Applications in Large-Scale Route Planning Problems. Supplemental Material: The online appendix is available at https://doi.org/10.1287/trsc.2022.0015 .

Risk Factors for the Anal and Oral Human Papillomavirus (HPV) Infections among Women with Severe Cervical Lesions: A Prospective Case-Control Study.

The carcinogenicity of HPV infection in the anogenital and oropharyngeal regions is broadly accepted. The aim of the study was to define risk factors for anal and oral HPV infections in high-risk patients with biopsy-proven severe cervical lesions (CIN2+). Altogether immunocompetent 473 females with CIN2+ were categorized into the study group and another 245 women into the control group. The strongest risk factor for anal HPV infection was the presence of cervical HPV infection (p < 0.001). Furthermore, ten or more lifetime sexual partners (p = 0.013), a sexual non-coital contact with the anal area (p < 0.001), and actively practicing anal-penetrative intercourse (p < 0.001) were significantly associated with anal HPV. A history of genital warts in the woman (p = 0.010) and the presence of genital warts in the male partner (p = 0.029) were found statistically significant for the risk of oral HPV infection. Our data suggest that the presence of HPV infection, especially high-risk genotypes, in one anatomical site poses the greatest risk for HPV infection in another anatomical site. The cervix is the main reservoir of infection, but the risk factors for anal and oral HPV infections are dissimilar according to different anatomical distances and more complex routes of transmission.

Circularly Polarized Light Emission from Nonchiral Perovskites Incorporated into Nanoporous Cholesteric Polymer Templates.

Chiral perovskites have garnered significant attention, owing to their chiroptical properties and emerging applications. Current fabrication methods often involve complex chemical synthesis routes. Herein, an alternative approach for introducing chirality into nonchiral hybrid organic-inorganic perovskites (HOIPs) using nanotemplates composed of cholesteric polymeric networks is proposed. This method eliminates the need for additional molecular design. In this process, HOIP precursors are incorporated into a porous cholesteric polymer film, and two-dimensional (2D) HOIPs grow inside the nanopores. Circularly polarized light emission (CPLE) was observed even though the selective reflection band of the cholesteric polymer films containing a representative HOIP deviated from the emission wavelength of the 2D HOIP. This effect was confirmed by the induced circular dichroism (CD) observed in the absorbance band of the HOIP. The observed CPLE and CD are attributed to the chirality induced by the template in the originally nonchiral 2D HOIP. Additionally, the developed 2D HOIP exhibited a long exciton lifetime and good stability under harsh conditions. These findings provide valuable insights into the development and design of innovative optoelectronic materials.

Analyzing the electrochemical reduction of CO and CO2 as reactants to C1 and C2 products on copper-based flow-through gas diffusion electrodes

Electrochemical CO2 reduction (eCO2R) into useful chemicals and fuels is extensively studied, but it faces challenges such as high activation energy, carbonation, lower reaction rate, and unstable operation in alkaline conditions. In contrast, electrochemical CO reduction (eCOR) can efficiently produce C2+ products through a two-step conversion process without requiring high activation energy and involving complex reaction routes like CO2 electroreduction. Therefore, Converting CO2 to CO and then to C2+ products can be a strategic approach to enhance activity, selectivity, and economic viability. However, eCOR demonstrates lower reaction rates and sluggish kinetic with planar electrodes due to its lower solubility and poor mass transport to the electrode surface, therefore, industrially relevant current densities are still far to reach. Flow-through gas diffusion electrodes (FTGDEs) can potentially solve the issue of poor mass transport due to their abundant surface area, porous structure, and improved triple-phase interface. Herein, electrochemical CO reduction to C2+ products is investigated using Cu-based FTGDEs. A comparison of eCOR with eCO2R is also carried out to study the catalytic activity, selectivity, and stability. To demonstrate the influence of particle size, FTGDEs are designed using varying Cu particle sizes i.e. 10 nm, 100 nm, and 10 µm. The eCOR produced C2+ products with ethylene being the main product achieving 474 mA/cm2 current density and 72% faradaic efficiency at − 0.9 V vs. RHE, while eCO2R yielded more C1 products with lower catalytic activity and selectivity. Compared to gas diffusion configuration, the poor catalytic activity and selectivity of eCOR are observed in non-gas diffusion configuration which signifies that, due to higher local CO concentration and improved triple-phase generation, higher performance of FTGDEs can be obtained from gas diffusion configuration. Finally, the stable operation of Cu electrodes during eCOR highlights its promise as a highly suitable candidate for enhancing eCOR towards higher carbon products.

A compartment model to predict in vitro finite dose absorption of chemicals by human skin

Dermal uptake is an important and complex exposure route for a wide range of chemicals. Dermal exposure can occur due to occupational settings, pharmaceutical applications, environmental contamination, or consumer product use. The large range of both chemicals and scenarios of interest makes it difficult to perform generalizable experiments, creating a need for a generic model to simulate various scenarios. In this study, a model consisting of a series of four well-mixed compartments, representing the source solution (vehicle), stratum corneum, viable tissue, and receptor fluid, was developed for predicting dermal absorption. The model considers experimental conditions including small applied doses as well as evaporation of the vehicle and chemical. To evaluate the model assumptions, we compare model predictions for a set of 26 chemicals to finite dose in-vitro experiments from a single laboratory using steady-state permeability coefficient and equilibrium partition coefficient data derived from in-vitro experiments of infinite dose exposures to these same chemicals from a different laboratory. We find that the model accurately predicts, to within an order of magnitude, total absorption after 24 h for 19 of these chemicals. In combination with key information on experimental conditions, the model is generalizable and can advance efficient assessment of dermal exposure for chemical risk assessment.

Wireless-Enabled Asynchronous Federated Fourier Neural Network for Turbulence Prediction in Urban Air Mobility (UAM)

To meet the growing mobility needs in intra-city transportation, the concept of urban air mobility (UAM) has been proposed in which vertical takeoff and landing (VTOL) aircraft are used to provide a ride-hailing service. In UAM, aircraft can operate in designated air spaces known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">corridors</i> , that link the aerodromes, thus avoiding the use of complex routing strategies such as those of modern-day helicopters and alleviating the burden on the ground transportation system. For safety, a UAM aircraft must use air-to-ground communications to report flight plan, off-nominal events, and real-time movement to ground base stations (GBSs). A reliable communication network between GBSs and aircraft enables UAM to adequately utilize the airspace and create a fast, efficient, and safe transportation system. In this paper, to characterize the wireless connectivity performance for UAM, a suitable spatial model is proposed. For the considered setup, assuming that any given aircraft communicates with the closest GBS, the distribution of the distance between an arbitrarily selected GBS and its associated aircraft and the Laplace transform of the interference experienced by the GBS are derived. Using these results, the signal-to-interference ratio (SIR)-based connectivity probability is determined to capture the connectivity performance of the UAM aircraft-to-ground communication network. Then, leveraging these connectivity results, a wireless-enabled asynchronous federated learning (AFL) framework that uses a Fourier neural network is proposed to tackle the challenging problem of turbulence prediction during UAM operations. For this AFL scheme, a staleness-aware global aggregation scheme is introduced to expedite the convergence to the optimal turbulence prediction model used by UAM aircraft. Simulation results validate the theoretical derivations for the UAM wireless connectivity. The results also demonstrate that the proposed AFL framework converges to the optimal turbulence prediction model faster than the synchronous federated learning baselines and a staleness-free AFL approach. Furthermore, the results characterize the performance of wireless connectivity and convergence of the aircraft’s turbulence model under different parameter settings, offering useful UAM design guidelines.

Intelligent Vehicle Systematic Design Based on Arduino and Raspberry Pi

The intelligent vehicle designed in this paper can realize functions, such as safety detection, visual identification, remote control and manipulator grasping, and so on. Arduino MEGA is used as the main control board to send signal messages to drive vehicles. Wi-Fi module is used to receive messages to remote control vehicles. The ultrasonic and infrared module is used to realize object detection around vehicles. To realize complex route movement, raspberry pie is used for visual recognition and path planning. Data is sent to Arduino for judgment in real time. Finally, it is verified that the design effectively improves the path-planning ability and obstacle-avoidance function in a sample vehicle.

Odesa - Paris - Lima: the complex route of the architect Malachowski

The article considers introduces the life and creative work of Ryszard (Ricardo) Malachowski - an architect who was born and grew up in Kherson region, and later became an outstanding Peruvian architect of the 20th century and gained fame on the American continent, practically defining the face of the most modern and richest city at that time South America - Lima. His work led to a significant transformation of the Peruvian capital, paving the way for the development of the modern metropolis for decades to come. The creative, scientific and life path of the architect was extremely interesting and fruitful, and his legacy includes several hundred projects, most of which have a very significant architectural and urban planning value and have been declared monuments of the cultural heritage of Peru. Malachowski is also no less famous as an artist, the founder of the Peruvian architectural school, the author of the treatise "Lessons of Elements and Theory of Architecture" and the founder of a great dynasty, which even today largely shapes the architectural landscape of the Peruvian capital. Despite his extremely great achievements, Ricardo Malachowski is still unknown in his homeland. In order to supplement the biographical data, the materials of the State Archives of Odesa region of Ukraine, which is the place of birth and primary education of the architect, and the family archive of the Malachowskies were analyzed, which made it possible to discover and systematize the data of the pre-emigration period of the architect's life and to correct inaccuracies assumed by previous biographers.

Medium and long-term hydrogen production technology routes and hydrogen energy supply scenarios in Guangdong Province

Hydrogen is a type of clean secondary energy, and the hydrogen energy supply is vital to regional energy development. Guangdong is at the forefront of hydrogen energy deployment in China, and aims to achieve peak carbon by 2030. However, hydrogen production research is challenging due to complex technical routes, technical maturity levels, life-cycle carbon emissions, and costs. Multi-time-scale research is necessary to explore optimal production paths and their contributions to CO2 emission reduction. This study discussed key technologies and the technical maturity of five hydrogen production routes: production from industrial byproducts and coal, wind, hydro-, and photovoltaic power. Policy scenarios were designed to investigate the potential of these routes and technology deployment intensity under medium- and long-term scenarios. This paper proposes a roadmap for hydrogen development and provides a reference for hydrogen production planning in Guangdong. This methodology can be applied in other regions for hydrogen energy development research.

Assessment of the effectiveness of measures to improve the patient routing system in the provision of planned medical care (experience of Tomsk region)

Introduction. This article reviews the results of the development and implementation of organizational solutions aimed at reducing the time of providing routine medical care to patients in outpatient settings and increasing its availability. Among the reasons negatively affecting the waiting times for medical care are complex routing schemes and the high level of administrative overhead that accompanies each stage of the treatment and diagnostic process.Aim: To develop and evaluate the effectiveness of measures to improve the system of organization of planned medical care on the example of medical organizations of Tomsk region.Material and Methods. The study included medical organizations providing primary health care in outpatient settings (31 institutions). The study was conducted in stages: 2018–2019 the main set of measures (creation of offices of the organization of planned care) was developed and implemented, 2020–2021 – summarized interim results, 2022 – performance assessment was carried out. For comparative analysis all medical organizations were divided into 2 groups (group A and group B) depending on implementation of planned activities. Statistical processing was performed using the Statistica 10.0.228.8 software package.Results. It was found that the waiting time for a doctor’s consultation Group A reduced by 5.5% (p = 0.025) in 2019 compared with 2018, in contrast to Group B. The waiting time for a routine diagnostic examination in Group A also reduced by 16.6% in 2019 compared to 2018 (p = 0.041), while no differences were found between waiting times for routine diagnosis in Group B for the same period (p = 0.101).Summary. The study has shown that the problems of accessibility of planned medical care can be effectively solved through the creation of a patient flow management system at all stages of the treatment and diagnostic process.

Cocontinuous Nanostructures by Microphase Separation of Statistically Cross-Linked Polystyrene/Poly(2-vinylpyridine) Networks.

Cocontinuous polymeric nanostructures have drawn considerable attention due to their ability to combine distinct, percolation-dependent properties of two different polymer domains. Randomly end-linked copolymer networks (RECNs) have previously been shown to support the formation of disordered cocontinuous nanostructures across wide composition windows in a robust way. However, achieving highly efficient linking of telechelic polymers with excellent end-group fidelity often requires complex synthetic routes. As an alternative, we study here statistically cross-linked copolymer networks (SCCNs) composed of polystyrene and poly(2-vinylpyridine) (PS and P2VP) with cross-linkable allyl pendent groups that are conveniently synthesized by controlled radical copolymerization. Via selective extraction of P2VP, coupled with gravimetry, small-angle X-ray scattering, and electron microscopy, we find disordered cocontinuous phases across wide composition ranges (up to ≈ 35 wt %), approaching values previously determined for RECNs. Remarkably, even for samples that appear to exhibit full percolation, a substantial fraction of P2VP (≈ 20-30 wt %) cannot be removed, which we ascribe to short strands between nearby cross-linkers that are physically embedded within PS domains. The resulting PS porous monoliths with residual surface P2VP layers enable facile surface modification to resist protein adsorption and templating of porous gold nanostructures.

A study on the possibility of a BUS route network with connections based on an analysis of the efficiency of the BUS route network and resistance OF BUS users to transfer

In this study, data envelopment analysis (DEA) was used to evaluate the efficiency of the bus route network in Akita City, Akita Prefecture, Japan. The DEA efficiency indices utilized route length (km) and overlap index (number of lines/km) as input values for the network efficiency, while the number of buses per year was used as the output value for the deployment efficiency. Operating costs (yen) were used as the input value for the revenue efficiency, and Operating costs (yen) and fare revenue (yen) were used as input and output values, respectively, for the revenue efficiency. The results of this study show that the overall network efficiency is low, indicating that complex and radial bus routes are inefficient and can be improved. Next, we surveyed the attitudes of residents of Akita City, regarding the use of bus routes. The results showed that 18.5% of the respondents did not want to transfer between bus trips, whereas 69.7% could tolerate transferring up to once. Furthermore, 2.7% of the respondents were unwilling to wait for the bus, whereas 52.4% were willing to wait within 10 min, while 38.6% were willing to wait between 10 and 20 min.Based on the results of this analysis, which was conducted by a university laboratory, suggestions were made to the local government on how to provide an efficient network. The bus routes in Akita City are operated by private operators but managed by the local government. Thus, efficient bus routes with connections can be constructed through proposals to local governments.Inefficient bus routes were identified using DEA, and a network with transfers was examined for their improvement. When examining such a network, the attitudes of the users toward transfers must be understood; the relationship involves understanding the attitudes of the users toward inefficient bus routes using DEA. This study revealed that a large number of people could tolerate up to one transfer. The transit time is a significant factor in the acceptance.

LTM-LoRaWAN: A Multi-Hop Communication System for LoRaWAN

Coverage limitation due to signal attenuation is one of the main challenges facing single-hop LoRaWAN when deployed in IoT applications that require low power consumption and operate over a wide area network. The challenge can be figured out using the dense deployment of typical LoRaWAN gateways to ensure devices can transfer their data to the network server successfully. However, this is considered a costly path because of the requirement of deploying a larger number of gateways. To cope with this, a multi-hop communication strategy can be utilized to extend the coverage of employed LoRaWAN networks, eliminating the need for dense gateway deployment. Thus, this paper proposes a Listen-To-Talk-based Multi-hop LoRaWAN LTM-LoRaWAN, a multi-hop relaying system for a wide area LoRaWAN network. It supports out-of-range devices to deliver their traffic to the gateway without using complex routing mechanisms or routing topology construction. Moreover, the proposed system is dynamic and does not require any special entities or assign specific tasks to specific devices. The paper provides a detailed description of the design and configuration of the proposed LTM-LoRaWAN. Using simulation, the feasibility of the proposed system was demonstrated. The evaluation result showed that the proposed system outperformed one-hop LoRaWAN and achieved better reliability in traffic delivery.

Delay/Disruption-Tolerant Networking-based the Integrated Deep-Space Relay Network: State-of-the-Art

Communication with deep-space elements poses significant challenges due to vast distances, orbital motions, and harsh environmental conditions that restrict point-to-point or end-to-end communication. Disruption/Delay-Tolerant Networking (DTNs) is a special kind of computer network architecture, that overcomes the shortcomings of the TCP/IP suite in meeting deep-space networking requirements with intermittent end-to-end connectivity. In DTN, data transmission follows a store-carry-forward approach, where bundles (data) are transferred as custody between relay nodes. This necessitates more complex routing strategies involving additional route computations and network resource consumption but provides greater flexibility for unstable connectivity. This study is an updated literature review in the context of DTN-based deep-space communication. It covers the recent studies that address the architecture of current and future deep-space communication systems, the environmental challenges of deep-space communication, various implementations and demonstrations of DTN's architecture, and the validation of its related routing strategies over the Deep Space Relay network. Additionally, this review explores the integration of machine learning techniques into DTN routing strategies, along with ongoing research directions and open issues in DTN-based DSN. Examining the state-of-the-art literature reveals that developing an intelligent unified n-copy-based forwarding routing scheme holds promise for effectively integrating into deep space communications and achieving optimal networking among the diverse segments of the future unified Interplanetary Internet.

Molecular mass engineering for filaments in material extrusion additive manufacture

Abstract3D printing of thermoplastics through local melting and deposition via material extrusion additive manufacturing provides a simple route to the near net‐shape manufacture of complex objects. However, the mechanical properties resulting from these 3D printed structures tend to be inferior when compared to traditionally manufactured thermoplastics. These unfavorable characteristics are generally attributed to the structure of the interface between printed roads. Here, we illustrate how the molecular mass distribution for a model thermoplastic, poly(methyl methacrylate) (PMMA), can be tuned to enhance the Young's modulus of 3D printed plastics. Engineering the molecular mass distribution alters the entanglement density, which controls the strength of the PMMA in the solid state and the chain diffusion in the melt. Increasing the low molecular mass tail increases Young's modulus and ultimate tensile strength of the printed parts. These changes in mechanical properties are comparable to more complex routes previously reported involving new chemistry or nanoparticles to enhance the mechanical performance of 3D printed thermoplastics. Controlling the molecular mass distribution provides a simple route to improve the performance in 3D printing of thermoplastics that can be as effective as more complex approaches.

“Nothing is funnier than suffering”. Sport as a comic and perverse aesthetic practice

ABSTRACT The article takes up diverse strands of psychoanalytic thinking to investigate how desire is manifested in male team sporting environments. In particular, it is posited that sporting desire shares a remarkable structural similarity to the joking relationship in that they both work through the overcoming of obstacles. In doing so unconscious desires are long-circuited and only emerge in radically altered form, upending traditional gender and sexual subjectivities in the process. The paper explores the concept of desire from perspectives that are either straightforwardly psychoanalytic or heavily influenced by psychoanalytic thought. Initially, I examine desire from a Freudian viewpoint before looking at how Jacques Lacan extended Freudian analysis through a linguistic lens. I then explore desire in terms developed by Gilles Deleuze before turning, in the second part of the paper, to an examination of the work of George Bataille to consider the desire of sport through the mechanism of the joke to trace the complex routing that it often takes.

Characterization of Pharmacokinetics, Biotransformation and Elimination of Pomotrelvir Orally Administered in Healthy Male Adults Using Two [14C]-labeled Microtracers with Separate Labeling Positions.

Pomotrelvir is an orally bioavailable, target antiviral inhibitor of the main protease (Mpro) of coronaviruses (CoVs), including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). The pharmacokinetics, metabolism and elimination of two [14C]-labeled microtracers of 5 µCi/700 mg pomotrelvir with separate labeling positions (isotopomers), [lactam carbonyl-14C-pomotelvir] and [benzene ring-U-14C-pomotrelvir], following a single oral dose in healthy adult males was evaluated in two separate cohorts. Pomotrelvir was rapidly absorbed and eliminated primarily through metabolism and subsequently excreted via urine and feces. There were no differences in pomotrelvir pharmacokinetics between the two cohorts. The mean total radioactive dose recovered was 93.8% (n=8) in the lactam cohort (58% in urine and 36% in feces) and 94.2% (n=8) in the benzene cohort (75% in urine and 19% in feces), with {greater than or equal to} 80% of [14C] recovered within 96 hours after dosing. About 5% and 3% of the intact pomotrelvir was recovered in feces and urine, respectively. Eleven major metabolites were detected and characterized using LC-accelerator mass spectrometry (AMS) and LC-MS/MS methods, with 3 and 6 different metabolites elucidated in the samples collected from lactam and benzene cohorts, respectively, and 2 metabolites observed in both cohorts. The major metabolism pathway of pomotrelvir is through hydrolysis of its peptide bonds followed by phase II conjugations. These results support that the application of two radiolabeled isotopomers provided a comprehensive metabolite profiling analysis and was a successful approach in identifying the major disposition pathways of pomotrelvir that has complex routes of metabolism. Significance Statement An unconventional approach using two differentially labeled [14C] microtracers, [lactam carbonyl-14C-pomotrelvir] and [benzene ring-U-14C-pomotrelvir] evaluated the mass balance of orally administered pomotrelvir in healthy adult males in two separate cohorts. The radioactive dose recovered in excreta was about 94% for both cohorts. While the two isotopomers of the radiolabeled-pomotrelvir showed no major differences in pharmacokinetics overall, they allowed for differential detection of their radiolabeled metabolites and appropriate characterization of their plasma exposure and excretion in urine and feces.