Utility Maximization Research Articles

Sex Differences in the Energy System Contribution during Sprint Exercise in Speed-Power and Endurance Athletes.

Background/Objectives: A high level of specific metabolic capacity is essential for maximal sprinting in both male and female athletes. Various factors dictate sex differences in maximal power production and energy utilization. This study aims to compare the contribution of energy systems between male and female athletes with similar sport-specific physiological adaptations during a 15-s sprint exercise. Methods: The endurance group consisted of 17 males (23 ± 7 y) and 17 females (20 ± 2 y). The speed-power group included 14 males (21.1 ± 2.6 y) and 14 females (20 ± 3 y). The contribution of phosphagen, glycolytic, and aerobic systems was determined using the three-component PCr-LA-O2 method. Results: Significant differences were observed in the energy expenditure for all systems and total energy expenditure between males and females in both groups (p = 0.001-0.013). The energy expenditure in kJ for individual systems (phosphagen-glycolytic-aerobic) was 35:25:7 vs. 20:16:5 in endurance males vs. female athletes, respectively. In the speed-power group, male athletes expended 33:37:6 kJ and female athletes expended 21:25:4 kJ, respectively. The percentage proportions did not differ between males and females in any system. The contribution of the phosphagen-glycolytic-aerobic systems was 52:37:11 vs. 48:39:13 in endurance male and female athletes, respectively. For speed-power males vs. female athletes, the proportions were 42:50:8 vs. 41:50:9, respectively. Conclusions: Despite the differences in body composition, mechanical output, and absolute energy expenditure, the energy system contribution appears to have a similar metabolic effect between male and female athletes engaged in sprint exercises with similar sport-related adaptations. The magnitude and profile of sex differences are related to sports discipline.

Post-Purchase Trip Heterogeneity: Exploring the Impact of Free and Paid Return Deliveries on Shopping and Transport Mode Choices in the USA

This paper explores aspects of the post-purchase trips generated by the necessity to return purchased clothing to the shops. Particular focus is given to online shopping that has become common for clothing purchases. This study’s novelty lies in delving into the underlying reasons behind post-purchase trips, particularly those initiated when customers seek to return clothing to retailers. It examines the impact of free and paid return delivery options as key factors driving consumers’ decisions in relation to clothing returns. The study consists of two branches and leverages the random utility maximization theory. The first branch focuses on the impact of free and paid return options on the preferred shopping channels by utilizing a stated preference dataset collected from 507 US online shoppers. The second branch of this study employs the revealed preference dataset and aims to explore the return trip behavior. The willingness-to-pay values estimated for the free return delivery option are higher among female online shoppers compared with males—$7.42 and $6.65 per delivery, respectively. It was found that among the identified “returners,” 84.62% of males and 79.91% of females showed a strong reliance on private cars for their return trips. The potential environmental consequences of return trips were evaluated, focusing on the case of the USA. Additionally, the estimated marginal probability effect revealed that factors such as an aging population, car ownership, and number of children in households positively influence car usage for post-purchase trips. The study’s implications for stakeholders are discussed.

Power utility maximization with expert opinions at fixed arrival times in a market with hidden Gaussian drift

AbstractIn this paper we study optimal trading strategies in a financial market in which stock returns depend on a hidden Gaussian mean reverting drift process. Investors obtain information on that drift by observing stock returns. Moreover, expert opinions in the form of signals about the current state of the drift arriving at fixed and known dates are included in the analysis. Drift estimates are based on Kalman filter techniques. They are used to transform a power utility maximization problem under partial information into an optimization problem under full information where the state variable is the filter of the drift. The dynamic programming equation for this problem is studied and closed-form solutions for the value function and the optimal trading strategy of an investor are derived. They allow to quantify the monetary value of information delivered by the expert opinions. We illustrate our theoretical findings by results of extensive numerical experiments.

A novel choice model combining utility maximization and the disjunctive decision rules, application to two case studies

Most choice models, e.g. Multinomial Logit (MNL), rely on random utility theory, which assumes that a compensatory utility maximization decision rule explains an individual’s choice behaviour. Research has shown, however, that behaviour is sometimes better explained by non-compensatory decision rules. While some research has used Latent Class Choice Models (LCCMs) to account for multiple decision rules, many of them – such as the disjunctive rule – have yet to be explored. This paper formulates, estimates, and evaluates a LCCM that combines the MNL with a Generalised Random Disjunctive Model (GRDM), a new choice model we develop. Addressing deficiencies of existing disjunctive choice models, the GRDM allows for relative importance between attributes and is insensitive to irrelevant attributes. Unlike most non-compensatory models, it is tractable and incorporates random error terms for capturing unobserved heterogeneity across choice situations. The GRDM can be expressed as a Universal Logit (UL) model, which helps derive welfare metrics such as Marginal Rates of Substitution and elasticities and makes it possible to estimate the model with traditional software packages. The LCCM combining the GRDM and the MNL is estimated in two large-scale case studies: cyclists’ route choice and public transport route choice. Results are compared with other relevant LCCM specifications and the individual choice models, where it is found that the MNL + GRDM LCCM provides the best fit to the data. We also interpret the fitted parameters and calculate the Marginal Rates of Substitution, which align with behavioural expectations.

Industrial robot applications and individual migration decision: evidence from households in China

The integration of industrial robot application (IRA) into various sectors has catalyzed significant transformations in the labor market, reshaping the dynamics of individual migration decision (IMD). As industries increasingly adopt automation, the implications for workforce distribution and migration patterns become critical areas of study. Based on the conditional logit model and using CMDS data, this paper explores the relationship between IRA and IMD, as well as the heterogeneity effect and influencing mechanism. The findings indicate that IRA reduces the probability of the floating population choosing the city, and the results are robust after considering endogeneity and further robustness test. The impact of IRA on IMD is heterogeneous. Relatively speaking, the floating population with high education levels, health, younger, unmarried, female, agricultural household registration, state-owned enterprises, and non-routine task work does not over-think the impact of IRA during the migration process. In addition, the floating population also considers geographical location, city size, marketization level, wage level, and environmental quality when making migration decisions. the mechanism test shows that IRA attracts or suppresses the floating population through factors such as wage levels, housing price level, difficulty in finding a job, etc., depending on the result of individual utility maximization. These insights reveal the complex interplay between technological advancements in robotics and labor migration, emphasizing the need for comprehensive policy frameworks to manage these transformations effectively.

A Literature Survey of Transition Metal Boride, Carbide, Pnictide, and Chalcogenide Water Oxidation Electrocatalysts

Transition metal borides, carbides, pnictides, and chalcogenides (X-ides) are a new class of oxygen evolution reaction (OER) electrocatalysts, which have become a relevant topic for electrocatalytic energy conversion and storage research. This is because of their earth abundance, high electrical conductivity, and resultant high OER performance. Furthermore, some X-ide electrocatalysts demonstrate various degrees of oxidation resistance under OER potentials due to their differences in chemical composition, crystal structure, and morphology. Interestingly, there are three possible post-OER electrocatalyst models: a fully oxidized oxide/(oxy)hydroxide material, a partially oxidized core@shell structure, and an unoxidized material.1 In the past ten years (from 2013 to 2022), over 890 peer-reviewed research papers have focused on X-ide OER electrocatalysts. Recently, several topical reviews have been published. However, typically these literature reviews have provided limited conclusions targeted at only certain X-ides. Additionally, certain reviews omit key points, especially regarding the “catalytically active species” in X-ide OER electrocatalysts.In this work, we provide a comprehensive summary of (i) the experimental parameters (e.g., substrates, electrocatalyst loading amounts, electrocatalyst shapes, geometric overpotentials, Tafel slopes, etc.) and (ii) the details of the electrochemical stability tests and following post analyses used in all the X-ide OER electrocatalyst publications from 2013 (the birth of this research area) to 2022.2 In particular, based on the reported post-OER analytical results, we attempt to exhaustively classify all the X-ide electrocatalysts into four groups: no oxidation, partial oxidation, full oxidation, and unknown, which is relevant to the nature of the “catalytically active species” in X-ide OER electrocatalysts. After investigating the simpler X-ide systems, transition metal-based polyanion compounds/composites are also surveyed. Finally, we introduce the reported novel and special analytical techniques employed for observing X-ide reconstruction (i.e., oxidation and other phase transformations) during OER testing, which can be useful in selecting the analytical technique of maximum utility for the researchers’ purpose. Additionally, for each material sub-group (e.g., borides, carbides, nitrides, phosphides, sulfides, selenides, and tellurides), we also point out further challenges to be addressed and propose further questions yet to be answered, which may provide clues pointing to future research tasks. References B. R. Wygant, K. Kawashima, and C. B. Mullins, ACS Energy Lett., 3, 2956–2966 (2018).K. Kawashima et al., Chem. Rev., 123, 12795–13208 (2023).

أثر ضمانات منح القروض على مخاطر القروض البنكية: دراسة تطبيقية على بنك التنمية الاجتماعية

This study focuses on a different approach to understanding the impact of loan guarantees on bank risks. In it, utility theory and the descriptive analytical approach are used appropriately to analyze various data and determine the relationship between guarantees and the level of risk. The findings of the study are important, as they show that guarantees contribute effectively to reducing bank risks and provide additional protection for banks when borrowers default. It also enhances financial stability and improves banking decisions. These conclusions also reinforce the importance of loan guarantees in the banking system. It is good that the study recommends the need to improve safeguards policies and implement innovative risk management strategies. Therefore, this will help in enhancing maximum utilization of collateral and improving the performance of banks. However, the study could benefit from adding some clarifications to the methodological part to clarify how to analyze the data and how to define the relationship between safeguards and risks more specifically. Overall, this study provides important findings about the impact of granting loan guarantees on bank risks and recommends measures to enhance banks' utilization of these guarantees. One of the most important objectives of the study is to be a reference for people seeking future loans, such as family and marriage loans.

Data sharing considerations to maximize the use of pathogen biological and genomics resources data for public health.

Public sector data associated with health are a highly valuable resource with multiple potential end-users, from health practitioners, researchers, public bodies, policy makers, and industry. Data for infectious disease agents are used for epidemiological investigations, disease tracking and assessing emerging biological threats. Yet, there are challenges in collating and re-using it. Data may be derived from multiple sources, generated and collected for different purposes. While public sector data should be open access, providers from public health settings or from agriculture, food, or environment sources have sensitivity criteria to meet with ethical restrictions in how the data can be reused. Yet, sharable datasets need to describe the pathogens with sufficient contextual metadata for maximal utility, e.g. associated disease or disease potential and the pathogen source. As data comprise the physical resources of pathogen collections and potentially associated sequences, there is an added emerging technical issue of integration of omics 'big data'. Thus, there is a need to identify suitable means to integrate and safely access diverse data for pathogens. Established genomics alliances and platforms interpret and meet the challenges in different ways depending on their own context. Nonetheless, their templates and frameworks provide a solution for adaption to pathogen datasets.

Optimization of methanol yield and carbon dioxide utilization in methanol synthesis process

The method of CO2 hydrogenation to methanol can effectively reduce carbon emission and has wide application prospects in chemical industry and environment. Therefore, methanol synthesis is an important way to save energy, reduce emission and transform energy utilization. In this paper, the mathematical model of methanol synthesis reactor is established. Under the condition of controllable cooling temperature, the optimization is carried out with maximum methanol yield and CO2 utilization rate. The results show that the methanol yield can be increased by 6.57% and CO2 utilization rate can be increased to 39.1% by adjusting the cooling temperature control strategy. The comparative study found that the optimal cooling temperatures all show up and down variations, with local minima and maxima. In addition, an industrial application method of methanol yield maximization cooling strategy is proposed. When the stage cooling at different temperatures is adopted, the methanol yield could be increased by 5.38%.

Quantifying marginal utilities of ecosystem services for sustainable management

Understanding the marginal characteristics of ecosystem services (ESs) is crucial for sustainable management. However, there is limited research on quantifying thresholds for ESs, making it challenging for policymakers to plan effectively. This study established a framework to assess the influencing factors and marginal characteristics of cultural and regulatory ecosystem services (RES) in the Taihu Lake Basin of China and its wetland parks. The framework uses a Structural Equation Model to analyze the impact of visitors' attributes on the perception of different types of cultural ecosystem services (CES). It also employed the InVEST model to quantify the spatial patterns of RES in the basin. Multiple regression analysis and marginal utility theory were used to examine the influencing factors and marginal utilities for different types of cultural and regulatory services. The findings reveal that 1) Education level, income, gender, and age significantly influence the perception of five types of CES provision, with different factors affecting each type. 2) Most park characteristics influence the CES provision score, with their maximum and marginal utility peaks. For instance, as patch density (PD) increases, the score for recreational services initially decreases, then increases, and finally decreases again, reaching a peak of 0.50 at a PD of 325.60. The marginal utility of PD follows a similar pattern, initially increasing and then decreasing, with an increase in utility observed in the range of 0 < PD < 187.80. When PD reaches 187.80, it attains its maximum utility, indicating the point of highest efficiency for PD's impact on recreational services. 3) Heterogeneity exists in the spatial distribution of RES within the basin, with different landscape features providing varying marginal benefits for services like water supply, water purification, carbon storage, and soil erosion prevention. Carbon storage demonstrates an 'increase-then-decrease’ pattern in response to rising FP (Percentage of forest area), reaching a maximum value of 13129.3 t/km2 at FP of 66.4. The marginal utility of FP also exhibits a 'rise-then-fall’ trend, increasing up to FP of 30.4, where it peaks at 230.5. This peak represents the point of maximum efficiency in FP's influence on carbon storage services. 4) The effects of park and landscape characteristics on cultural and regulatory services exhibit marginal utilities that can be used to determine the optimal scale and location of these features to maximize ecological benefits. This research aims to expand the scope of ESs assessment and provide insights from wetland parks for broader environmental planning and optimization.

Optimal premium pricing in a competitive stochastic insurance market with incomplete information: A Bayesian game-theoretic approach

This paper examines a stochastic one-period insurance market with incomplete information. The aggregate amount of claims follows a compound Poisson distribution. Insurers are assumed to be exponential utility maximizers, with their degree of risk aversion forming their private information. A premium strategy is defined as a mapping between risk-aversion types and premium rates. The optimal premium strategies are denoted by the pure-strategy Bayesian Nash equilibrium, whose existence and uniqueness are demonstrated under specific conditions on the insurer-specific demand functions. Boundary and monotonicity properties for equilibrium premium strategies are derived.

Resource-rational psychopathology.

Psychopathology is vast and diverse. Across distinct disease states, individuals exhibit symptoms that appear counter to the standard view of rationality (expected utility maximization). We argue that some aspects of psychopathology can be described as resource-rational, reflecting a rational trade-off between reward and cognitive resources. We review work on two theories of this kind: rational inattention, where a capacity limit applies to perceptual channels, and policy compression, where the capacity limit applies to action channels. We show how these theories can parsimoniously explain many forms of psychopathology, including affective, primary psychotic, and neurodevelopmental disorders, as well as many effects of psychoactive medications on these disorders. While there are important disorder-specific differences and the theories are by no means universal, we argue that resource rationality offers a useful new perspective on psychopathology. By emphasizing the role of cognitive resource constraints, this approach offers a more inclusive picture of rationality. Some aspects of psychopathology may reflect rational trade-offs rather than the breakdown of rationality. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

In-situ grown ternary metal hydroxides@3D oriented crumpled V2C MXene sheets for improved electrocatalytic oxygen evolution reaction

High valence multi transition metal hydroxides are greatly enriched with OER redox active sites due to strong synergy of heteroatomic nuclei. The efficiency of these redox active sites could be efficiently improved by coupling with highly conductive substrate. The advanced three-dimensional (3D) architecture and hydrophilic terminal functionalities of MXene (MX) considerably enhance the maximum utilization rate of anchored redox active sites by triggering the direct growth of these at MX substrate. Here-in, the freeze-dried 3D network of crumpled Vanadium-Carbide (V2C) MX sheets regulates the crystallization of in-situ grown NiFeCr multi transition metal hydroxides on MX scaffold through co-precipitation process. The XPS results suggest a synergistic chemical interaction of 3D MX scaffold with NiFeCr that modifies the electronic structure of the composite ensuring reduced charge transfer resistance. Besides, as found in FESEM morphological investigation, the well-dispersed NiFeCr multi-transition metal hydroxides are immobilized on open pores like structure of V2C-MX facilitate thoroughly accessible active sites. As a result, the NiFeCr@3D V2C-MX composite has shown an excellent electrocatalytic activity with an overpotential of 410 mV at a current density of 200 mA cm−2, Tafel slope of 100 mV dec in 1M KOH. Besides, the significant interaction between metallic centers and MXene support prevent detachment or agglomeration of active centers providing maximum interaction with the electrolytic ions, quick ionic OH− transportation, speedy and stable electron transfer channels thus ensure the long-term stability of NV-5MX during 53 h continuous operation of OER. Furthermore, we have utilized a more accurate value of half-cell standard reduction potential of the Hg/HgO electrode in the Nernst equation to represent all test voltages and to determine the overpotential values. In essence, this study features a facile approach for the confined growth of multi transition metal hydroxides in the presence of morphologically unique 3D crumpled V2C MXene architectures. Consequently, the increased OER reaction kinetics and improved stability of the synthesized composites are potentially due to synergistic interplay between well dispersed active sites and the conductive substrate.

Improving Financial Performance through Financial Risk and Intellectual Capital

This research aims to analyze the influence of financial risk and intellectual capital on financial performance and the influence of financial risk and intellectual capital on financial performance. This research method is explanatory research and causality research design. The population in this research is all manufacturing companies listed on the Indonesia Stock Exchange from 2019 to 2021. The data analysis technique uses path analysis with two substructure equations and testing classical assumptions. This research method is descriptive analysis research. Research data uses secondary data obtained from information in the annual reports of each manufacturing company on the Indonesia Stock Exchange during the research period with data analysis techniques using path analysis. This research shows that financial risk significantly and negatively affects the company's financial performance. The use of capital originating from debt has a negative impact. The company experienced a reduction in its profit target because it had an obligation to pay interest on debt. The greater the use of leverage, the more significant the reduction in the rate of return on its capital. Intellectual capital significantly and positively affects a company's financial performance. Intellectual capital efficiency is substantially and positively related to a company's financial performance. In the future, it is hoped that the company's financial performance will be achieved through effective risk management policies and maximum utilization of intellectual capital, which will impact increasing company value.

Co-upcycling of Plastic Waste and Biowaste via Tandem Transesterification Reactions.

Polyethylene terephthalate (PET) and glycerol are prevalent forms of plastic and biowaste, necessitating facile and effective strategies for their upcycling treatment. Herein, we present an innovative one-pot reaction system for the concurrent depolymerization of PET plastics and the transesterification of glycerol into dimethyl terephthalate (DMT), a valuable feedstock in polymer manufacturing. This process occurs in the presence of methyl acetate (MA), a byproduct of the industrial production of acetic acid. The upcycling of biowaste glycerol into glycerol acetates renders them valuable additives for application in both the biofuel and chemical industries. This integrated reaction system enhances the conversion of glycerol to acetins compared with the singular transesterification of glycerol. In this approach, cost-effective catalysts, based on perovskite-structured CaMnO3, were employed. The catalyst undergoes in situ reconstruction in the tandem PET/glycerol/MA system due to glycerolation between the metal oxides and glycerol/acetins. This process results in the formation of small metal oxide nanoparticles confined in amorphous metal glycerolates, thereby enhancing the PET depolymerization efficiency. The optimized coupled reaction system can achieve a product yield exceeding 70% for glycerol acetates and 68% for PET monomers. This research introduces a tandem pathway for the simultaneous upcycling of PET plastic waste and biowaste glycerol with minimal feedstock input and maximal reactant utilization efficiency, promising both economic advantages and positive environmental impacts.

Determinants of adoption of food safety practices among clam sellers in Kpong and Atimpoku, Ghana

The food safety practices used by clam merchants in Kpong and Atimpoku, Ghana, pose a risk to public health. The study sought to identify factors affecting food safety practices, obstacles to their implementation, and ways of improving them to avoid food-borne infections and promote sustainable practices and development among clam sellers in Kpong and Atimpoku, Ghana. The cross-sectional survey combined purposive and random sampling methods. Sixty-three clam merchants were interviewed face-to-face using a structured questionnaire. Response bias and generalizability to other Ghanaian regions form the study's limitations. Utility maximizing is used to examine how clam vendors adopt food safety procedures. The discrete choice logit model is used to identify food safety decision-making elements. The study examines the extent and significance of relationships between independent factors such as public health officer visits and formal access to credit. The utility maximization paradigm helped to explain clam dealers' food safety measures in Ghana. The study found that age and household size influence worker's decisions to cover clams and wear clean aprons or not. Credit and income-generating activities encourage the wearing of clean aprons. Public health officer visits, clam selling association membership, selling hours per day, availability to finance, and household size on the other hand affect food safety measures when diarrhoea strikes. It is therefore concluded that credit and household size promote better clam seller hygiene. Therefore to promote food safety, policy-makers and stakeholders should offer support, education, and training. This study adds to the literature and emphasizes the significance of food safety standards to safeguard customers and public health.

Ideal performance assessment of non-recirculating anaerobic fluidized bed reactors treating low to high strength organic loads with low retention time

This study investigated the ideal performance of non-recirculating Anaerobic Fluidized Bed Reactors (AnFBRs) for treating organic wastewater of varying strengths under low Hydraulic Retention Time (HRT). Four 4.58 L AnFBRs were used to treat synthetic wastewater with an Organic Loading Rate (OLR) ranging from 4.50 to 40.11 gCOD/L-d, and HRT between 1.1 and 4.4 hours. The AnFBRs achieved high removal efficiencies ranging from 83 % to 96 % at steady state, except during the organic shock load, which reduced removal performance to 12 %. Shortened HRT conditions led to a decreasing trend in reactor pH due to an incomplete anaerobic cycle. The modified Stover-Kincannon model estimated the maximum substrate utilization rate of AnFBR's to be 196.08 gCOD/L-d, with a correlation coefficient of 0.98. Under shortended HRT, microbial diversity analysis identified predominant non-filamentous bacterial families, such as Streptococcaceae and Veillonellaceae, which collaborate during biofilm development in anaerobic environments. It was suggested that the porous media provided secure attachment sites for the biomass growth and biofilm formation under shock load and high shear force conditions. While these results offer valuable insights, further studies are needed to confirm these findings and enhance the understanding of the use porous media in non-recirculating AnFBRs.

Hidden Impurities Generate False Positives in Single Atom Catalyst Imaging

AbstractSingle‐atom catalysts (SACs) are an emerging class of materials, leveraging maximum atom utilization and distinctive structural and electronic properties to bridge heterogeneous and homogeneous catalysis. Direct imaging methods, such as aberration‐corrected high‐angle annular dark‐field scanning transmission electron microscopy, are commonly applied to confirm the atomic dispersion of active sites. However, interpretations of data from these techniques can be challenging due to simultaneous contributions to intensity from impurities introduced during synthesis processes, as well as any variation in position relative to the focal plane of the electron beam. To address this matter, this paper presents a comprehensive study on two representative SACs containing isolated nickel or copper atoms. Spectroscopic techniques, including X‐ray absorption spectroscopy, were employed to prove the high metal dispersion of the catalytic atoms. Employing scanning transmission electron microscopy imaging combined with single‐atom‐sensitive electron energy loss spectroscopy, we scrutinized thin specimens of the catalysts to provide an unambiguous chemical identification of the observed single‐atom species and thereby distinguish impurities from active sites at the single‐atom level. Overall, the study underscores the complexity of SACs characterization and establishes the importance of the use of spectroscopy in tandem with imaging at atomic resolution to fully and reliably characterize single‐atom catalysts.

Hidden Impurities Generate False Positives in Single Atom Catalyst Imaging.

Single-atom catalysts (SACs) are an emerging class of materials, leveraging maximum atom utilization and distinctive structural and electronic properties to bridge heterogeneous and homogeneous catalysis. Direct imaging methods, such as aberration-corrected high-angle annular dark-field scanning transmission electron microscopy, are commonly applied to confirm the atomic dispersion of active sites. However, interpretations of data from these techniques can be challenging due to simultaneous contributions to intensity from impurities introduced during synthesis processes, as well as any variation in position relative to the focal plane of the electron beam. To address this matter, this paper presents a comprehensive study on two representative SACs containing isolated nickel or copper atoms. Spectroscopic techniques, including X-ray absorption spectroscopy, were employed to prove the high metal dispersion of the catalytic atoms. Employing scanning transmission electron microscopy imaging combined with single-atom-sensitive electron energy loss spectroscopy, we scrutinized thin specimens of the catalysts to provide an unambiguous chemical identification of the observed single-atom species and thereby distinguish impurities from active sites at the single-atom level. Overall, the study underscores the complexity of SACs characterization and establishes the importance of the use of spectroscopy in tandem with imaging at atomic resolution to fully and reliably characterize single-atom catalysts.

Dynamic computation scheduling for hybrid energy mobile edge computing networks

The rapid expansion of Mobile Edge Computing (MEC) is driven by the growing demand for resource-intensive applications within the Internet of Things. Computation offloading allows these applications to be executed at the network edge, but it leads to significant electricity expenses for network operators. To mitigate these costs, one promising solution is to power base stations (BSs) with a hybrid energy supply that combines unpredictable harvested energy with stable energy from the smart grid. This paper investigates joint computation scheduling for mobile devices (MDs) and resource allocation in a MEC network incorporating hybrid energy sources. Our objective is to maximize long-term time-averaged service utility by optimizing parameters such as BS battery supply, harvestable energy, CPU frequency, transmission power, task-partition factor, and MD-BS associations. To tackle this complex problem, we exploit the Lyapunov optimization framework to decompose it into deterministic subproblems for each time slot and propose an online network service utility maximization scheduling (NSUMS) algorithm. Experimental results show that our algorithm outperforms benchmark schemes in service utility and energy expenditure, improving the completion ratio by 32%, reducing the failure rate by 80%, and decreasing MD energy consumption by 28%.