Utility Maximization Research Articles

Experimental analysis and optimization of a concentrated thermo-photovoltaic collector with bi-facial receiver

In this study, a concentrated thermo-photovoltaic collector is examined experimentally and numerically, while it was geometrically optimized. The main objective is the collector's thermal performance evaluation and optical optimization for operation in Greece. Experiments were conducted in Athens, Greece, from July 10th to 17th, 2023, investigating the thermal operation of the collector in a temperature range of approximately 40–80 °C. The collector's slope was set to 12.3° for maximum solar irradiance utilization during the specified dates, considering south orientation. A numerical model was created using SolidWorks Flow Simulation and COMSOL Multiphysics, The model was validated with the experimental data, achieving mean deviation less than 6.5 % and a maximum deviation of 9.6 %. Various geometries were optically examined using Tonatiuh software. By applying a performance evaluation criterion, a new design is proposed and compared to the initial design across four different months, considering constant tilt angle. A maximum thermal efficiency of 49.19 % at the lower inlet temperature was found experimentally. The temperature of the PV cells was found to be highest where the solar rays are concentrated. Shape optimization revealed significant enhancements in optical efficiency, particularly at negative incident angles. The new geometry showed substantial improvement, with enhancements exceeding 20 % considering daily operation.

Correction: Power utility maximization with expert opinions at fixed arrival times in a market with hidden gaussian drift

Correction: Power utility maximization with expert opinions at fixed arrival times in a market with hidden gaussian drift

THE IMPACT OF RECENT LEASING ACTIVITY ON THE FINANCIAL SYSTEM IN THE REPUBLIC OF NORTH MACEDONIA

Leasing is an activity that refers to movable and immovable goods, in which the lessee determines the subject of leasing that is purchased or produced by the lessor and is given to the lessee for use for an agreed period, in exchange for payment of compensation for the use of the subject of leasing, based on the leasing agreement concluded between the provider and the lessee, according to the conditions specified in it. Leasing is an alternative way of financing where it is necessary to emphasize the use of the leased goods, and not the ownership over them (use but not possess), i.e. the philosophy of leasing arises from the idea of profitable use of an investment goods followed by a flexible method of payment that allows investment without the additional engagement of core capital, successful operation and maximum utilization of funds. In addition to the primary financing function that the leasing activity has for the lessee, if he uses the leased goods for business purposes, leasing in that case can also have an investment function. Regulated by the Law on Leasing, leasing activity in the Republic of North Macedonia has a fairly short lifespan, focusing exclusively on financial leasing. Through analysis, synthesis, and statistics, the authors processed the official data of the Ministry of Finance presented by the National Bank in the period mainly of the last decade, which offers a clear picture of the movements of the use of leasing in the country.

Inequality as determinant of donation: A theoretical modeling and empirical analysis of Korea.

Recipient financial need is a crucial factor in donation decisions. This study proposes a novel model for determining financial donations, incorporating consumption levels of both donor and recipient within a societal context. Solving our model's utility maximization problem reveals how consumption, donation, and savings are interlinked. Empirical evidence reinforces these findings, aligning with prior research and showing that larger consumption gaps between donors and recipients lead to increased donations. Our findings point towards an inherent altruistic motivation in donation, where elevating the recipient's well-being ultimately enhances the donor's own utility. This reinforces the notion that consideration of the recipient's financial hardship, as reflected by their consumption patterns, is crucial when making donation decisions. Shifting beyond traditional models, this study introduces a groundbreaking approach to financial donations. Our novel model factors in consumption levels of both the donor and recipient, along with the broader societal context, using utility maximization to unravel the intertwined decisions of consumption, donation, and savings. Real-world data validates our model, confirming known donation factors and revealing a key finding: larger disparities in consumption lead to increased giving, suggesting an altruistic drive where helping others boosts personal satisfaction.

Developing and applying a single strategy for improved intestinal permeability of diverse and complex phytomolecules: nanoformulations of rutin, quercetin, thymoquinone provide proof-of-concept

Purpose: The clinical use of phytomolecules is restricted due to low oral bioavailability that may be attributed to their poor intestinal permeability owing to their complex structure, poor aqueous solubility and low biological stability. Rutin (RT), quercetin (QU), thymoquinone (TQ) are such potent and therapeutically versatile phytomolecules that await maximal utilization. Here we report a single strategy for enhanced intestinal permeation of diverse phytomolecules. Method: A simple idea with easy-to-apply method was developed that involved preparing nanoparticles of the phytomolecules RT, QU, TQ using eudragit matrix (RT-PNP, QU-PNP, TQ-PNP) and encapsulated in HPMC grade capsule shell. The PNPs were evaluated for particle characteristics, encapsulation efficiency, in vitro release kinetics, and intestinal permeability. Result: The average particle sizes of RT-PNP, QU-PNP, TQ-PNP were 446 ± 0.152, 39.6 ± 0.006 and 186 ± 0.513 nm, polydispersity indices were < 0.5 with negative zeta potential. The % release of respective phytomolecule from RT-PNP, QU-PNP, TQ-PNP was significantly higher (p<0.05) at pH 6.8 than pH 1.2. PNPs followed higuchi kinetics with non-Fickian diffusion mechanisms. The apparent intestinal permeability (Papp) of RT-PNP, QU-PNP, TQ-PNP were 14.45 ± 4.85, 12.96 ± 1.73 and 30.87 ± 8.75 µg/cm2, respectively, significantly (P <0.5) greater vs RT, QU, TQ, respectively. CLSM confirmed significantly higher (p<0.05) intestinal permeation of RT-PNP, QU-PNP, TQ-PNP vs RT, QU, TQ, respectively. Conclusion: Developed PNPs appear to be a good approach to increase the permeability of hydrophobic phytomolecules.

Variation characteristic analysis of regional agricultural water consumption under Budyko-type framework

ABSTRACT Agricultural water consumption security is crucial for maintaining food production stability. Aiming to investigate water consumption efficiency and objectives in agricultural and non-agricultural sectors, we adopted a Budyko-analogous framework to establish an optimal water allocation model based on the maximum water utilization benefits principle. The proposed Budyko framework was verified through its application in Anhui Province, China, and the difference in water utilization efficiencies among different regions was discussed. The research findings can be concluded as follows: (1) during 2011–2020, the provincial agricultural productive loss caused by per-unit water shortage was lower compared to non-agricultural sectors, and this trend was adaptive in the south but totally opposite in the north; (2) the guaranteed level of agricultural water consumption was higher compared to non-agricultural sectors in the north due to the predominance of agricultural production but totally contrary in the south. Overall, the above findings are consistent with the actual industrial structure of Anhui Province.

Exploring tourists’ preferences and willingness to pay for national park recreation improvements based on regret and utility comparison

Research on the improvement of national park recreation policies has attracted much attention to discrete choice experiments to obtain tourists’ preferences and willingness to pay. However, individual choice behavior is extremely complex, and the single Random Utility Maximization (RUM) model ignores anticipated regret and is insufficient to explain individuals’ actual choice behavior. To investigate whether regret influences tourists’ choices regarding the improvement of national park recreation attributes, this study introduces the Random Regret Minimization (RRM) model and explores the performance of polynomial logit models and hybrid latent class models in analyzing discrete choice models based on utility and regret. By constructing a hybrid utility-regret model, we examine how tourists trade off between attributes such as vegetation coverage, water clarity, amount of litter, and level of crowding in national park recreation. Results indicate that the RRM model has better goodness-of-fit and predictive ability than the RUM model, indicating that regret is a significant choice paradigm, and the hybrid model better explains respondents’ choices. Specifically, 62.5% of tourists’ choices are driven by regret, and regret-driven respondents are more inclined to increase vegetation coverage and improve water clarity, while utility-driven respondents are more inclined to reduce litter and crowding. This study not only provides a reference for managers to develop more optimal recreation improvement strategies but also offers theoretical insights for national park recreation improvement policies.

Different strategies of crop diversification between poor and non-poor farmers: Concepts and evidence from Tanzania

Crop diversification, or growing multiple crops in farmland, has received attention as a risk-reducing strategy for smallholders. This study attempts to show that poor and non-poor farmers adopt different strategies of crop diversification. We first conceptualize farmers’ heterogeneous motivations for crop diversification by introducing a subsistence constraint into a utility maximization problem under uncertainty. Using the Tanzanian National Panel Survey, we then examine whether past experiences of shocks affect the adoption of crop diversification differently between poor and non-poor farmers. We rely on a threshold model to estimate heterogeneous impacts between poor and non-poor farmers. We find that poor farmers adopt crop diversification for robust food securities in response to drought/flood and large increases in food prices for purchase. In contrast, non-poor farmers adopt crop diversification to stabilize market income in response to large increases in input prices and large declines in crop prices for sale.

Spatiotemporal evolution of land use efficiency in 357 cities across mainland China from 2000 to 2020 based on SDG 11.3.1

High-efficiency land use facilitates the maximization of land utilization, lowers urban construction costs, and optimizes urban functional patterns. The Sustainable Development Goal 11.3.1 (SDG 11.3.1) can be used to assess land use efficiency (LUE), understand the current state of land use, and identify the potential for optimization. This study combines SDG 11.3.1 with other supplementary indicators to establish a land use efficiency evaluation system. This system provides a more precise understanding of internal city changes and enables a scientific assessment of urban LUE in Mainland China. The results showed that: (1) A significant number of cities were growing cities, particularly in the eastern region, with the population of built-up areas increased by 2.92 times from 2000 to 2020; (2) From 2000 to 2020, cities in China underwent rapid urban expansion, with the most significant urban expansion index in 2015–2020; (3) The coordination between population growth rate (PGR) and land consumption rate (LCR) worsened in the western region, while the central and eastern regions showed better coordination. (4) As the urban expansion index increased, the compactness index of the cities in the above three regions decreased and were at lower levels. This study establishes an evaluation system to assess the LUE and reveals the spatial and temporal characteristics of urban and population change. It holds paramount significance in enhancing LUE and encouraging sustainable development in Mainland China and serves as a valuable reference for global urban management.

Insights into transition metal encapsulated inside carbon aerogel for accelerated electro-peroxone oxidation: Activity evaluation and reactive oxygen species generation

Transition metals have critical influences on the generation of reactive oxygen species in activating O3 and H2O2, as the binary oxidant sources in electro-peroxone (EP). To evaluate the catalytic activity of different metals and reveal the reactive oxygen species generation in heterogeneous EP, series of metals encapsulated inside carbon aerogel spheres (M@CS, M=Fe, Co, Ni, Zn) were fabricated for strengthening EP. Atrazine was used as model pollutant due to its low reactivity with O3, and the abatement trends followed Co@CS > Fe@CS > Ni@CS > Zn@CS. Co@CS exhibited the superior catalytic activity with maximum metal active site utilization (1.28 × 103 min-1 mol-1 per mole Co atom sites at pH 7) and minimum electric energy consumption (0.106 kWh/m3-log). The catalytic activity of M@CS was related to the adsorption energies for O3 and H2O2 (Fe@CS > Co@CS > Ni@CS > Zn@CS) and the graphitization degree (Co@CS > Fe@CS > Ni@CS > Zn@CS). Verified by theoretical calculation and in-situ Fourier transformed infrared, the metal effectively promoted the adsorption and decomposition of O3 and H2O2 into the surface oxygen intermediates, finally generating ·OH/·O2-/1O2. The carbon layer was conducive to the reduction of internal metal, ensuring catalyst durability. Electronic paramagnetic resonance and kinetic model revealed the occurrence, ratio and transient concentration of ·OH/·O2-/1O2 in M@CS/EP. M@CS/EP showed good performance for pollutant removal in coexistence of anions, humic acid and real water. This study provides guidance for selecting the metal–carbon catalyst in heterogeneous EP.

A novel encryption protocol for facilitating de-identification of genomics health data

The exponential growth and affordability of genomics sequencing in the clinical landscape in recent years have intensified a challenge facing privacy experts. They grapple with how to evaluate and mitigate the significant risk of genomics data being used to re-identify individuals. The lack of clear genomics guidance in HIPAA has invited a wide spectrum of expert opinion from advocating for conservative limitations to be placed on genomics data sharing to ‘security’-based arguments that carefully calibrated technical, administrative, and legal safeguards may provide adequate protection in many cases. The need to weigh privacy concerns against the extraordinary value that genomics data offers to cancer and rare disease clinical research is compounded by the reality that conventional data modifications, such as redaction, aggregation, and perturbation, often critically undermine these important use cases. We present an innovative solution for de-identifying genomics data according to a conservative interpretation of HIPAA while still preserving maximal utility for clinical purposes. Our solution rejects the notion that privacy can be achieved directly via security. Instead, we introduce a reversible encryption protocol designed to be applied to specific combinations of genetic variants and their locations on the genome. The encrypted genomic data is fully de-identified, allowing researchers to perform analyses on the encrypted data in a secure Clean Room environment. The environment host is then able to decrypt and deliver variant-level summary statistics and aggregated outputs from the analysis to the recipient. As information in this format no longer links to patient-level data the solution remains de-identified end-to-end.

Dynamic environment UAV deployment algorithm based on potential game theory

AbstractTo address the issue of low coverage resulting from the challenge of acquiring the optimal deployment position in commonly used distributed deployment algorithms, this study presents a three‐dimensional deployment algorithm for Unmanned Aerial Vehicles (UAVs) based on potential games. First, a local mutually beneficial game model is designed to demonstrate the existence of exact potential games and Nash equilibrium. The Nash equilibrium solution corresponds to the maximum coverage. Next, drawing inspiration from exploration, a solution method called Exploration Spatial Adaptive Play is proposed. It utilizes the maximum utility function value from multiple step sizes in the exploration direction to update the action selection probability, thereby ensuring the optimal deployment position in each decision cycle. To address the issue of sensor position error, a method for processing sensor position errors is proposed. The simulation results demonstrate that the proposed distributed deployment algorithm achieves higher coverage compared to commonly used methods.

Enhancing bargaining power for energy communities in renewable power purchase agreements using Gaussian learning and fixed price bargaining

Power purchase agreements aim to secure long-term contracts between sellers and buyers, particularly in renewable energy transactions. However, successful negotiations for a fixed long-term price and energy volume while ensuring maximum utility for stakeholders remains a significant challenge. This paper introduces a comprehensive model for negotiating 24/7 power purchase agreements, focusing on hourly pricing to address deficits and surpluses throughout each day of the contract timeline. The model incorporates demand flexibility through battery storage, settling on the strike price using Nash Bargaining theory and optimal management of energy consumption relative to market price fluctuations. A soft margin support vector machine classification model determines the buyer’s maximum acceptable price. Moreover, Gaussian process classification is employed to calculate a probabilistic, risk-adjusted strike price, enabling a data-driven approach to power purchase negotiations. The proposed model’s performance is demonstrated through a detailed case study of Norway, illustrating how demand flexibility can significantly lower long-term power purchase agreement contract prices. The analysis of yearly price trends indicates that incorporating flexibility resources in long-term energy contracts may lead to a reduction in strike prices by around 25%. Moreover, such flexibility enhances demand-generation matching, thereby increasing renewable energy transactions within such agreements.

Arbitrage equilibria in active matter systems

The motility-induced phase separation (MIPS) phenomenon in active matter has been of great interest for the past decade or so. A central conceptual puzzle is that this behavior, which is generally characterized as a nonequilibrium phenomenon, can yet be explained using simple equilibrium models of thermodynamics. Here, we address this problem using a new theory, statistical teleodynamics, which is a conceptual synthesis of game theory and statistical mechanics. In this framework, active agents compete in their pursuit of maximum effective utility, and this self-organizing dynamics results in an arbitrage equilibrium in which all agents have the same effective utility. We show that MIPS is an example of arbitrage equilibrium and that it is mathematically equivalent to other phase-separation phenomena in entirely different domains, such as sociology and economics. As examples, we present the behavior of Janus particles in a potential trap and the effect of chemotaxis on MIPS.

Utility Maximization for Multi-UAV-Assisted IoT Sensor Systems With NOMA

Utility Maximization for Multi-UAV-Assisted IoT Sensor Systems With NOMA

Enhancing renewable energy utilization and energy management strategies for new energy yachts

Hydrogen energy, due to its clean and efficient nature, has shown great potential during the current transition period in the shipbuilding industry. However, the application of hydrogen energy in ship energy systems is influenced by variations in operational load and the integration of new energy sources during actual navigation. To address these issues, this paper focuses on optimizing and scheduling the operation of ships under various navigation conditions, considering the distributed nature of hydrogen energy. System simulations were conducted to model the photovoltaic (PV), proton exchange membrane fuel cells (PEMFCs), lithium batteries (LIBs), electrolytic cells (ECs), and energy storage modules of yacht energy systems. Component boundaries and objective functions were set, and two cases (excess photovoltaic state and constant power state) were designed to optimize and regulate the energy balance of hydrogen-powered yachts, enhancing their comprehensive utilization of renewable energy. By comparing the changes in ship energy under the two cases, it was concluded that case 1 ensures the maximum utilization of renewable energy. When photovoltaic power generation is insufficient, the PEMFC and LIB in the system provide the required power to achieve a supply-demand balance. Moreover, when PV power generation is sufficient, hydrogen energy is used to store renewable energy. The optimization method designed in this study can, to some extent, maximize the application of renewable energy in new energy yachts, ensuring the efficiency of the comprehensive energy system of new energy yachts, reducing emissions, and improving the sustainability and economic efficiency of the ships.

Kinetic investigation of discharge performance for Xe, Kr, and Ar in a miniature ion thruster using a fast converging PIC-MCC-DSMC model

Abstract The present work develops a full particle-based model that couples the particle-in-cell plus Monte Carlo collision (PIC-MCC) simulation for plasma dynamics and the direct simulation Monte Carlo (DSMC) method for neutral dynamics in a synergistic iterative manner. This new model overcomes the slow convergence issue in the conventional direct coupling approach caused by the disparity of the time scales between the plasma and neutral dynamics. This model is applied to simulate the behavior of xenon (Xe) and its potential alternatives, krypton (Kr) and argon (Ar), in the discharge chamber of a miniature direct current (DC) ion thruster. The results show that a stable discharge is difficult to achieve for Kr and Ar under the operating conditions optimal for Xe. While increasing the discharge voltage can effectively improve the stability of discharge for Kr and Ar, other common strategies such as changing the magnetic field strength, propellant flow rate, and cathode current are not successful. The propellant utilization efficiency and discharge efficiency are affected by both discharge voltage and propellant flow rate. A maximum utilization efficiency and an optimal discharge efficiency are observed for all three propellants, with the values decreasing in the order of Xe, Kr, and Ar. Moreover, the discharge voltage corresponding to the optimal efficiency is inversely proportional to the square root of the propellant mass, indicating that the ion diffusional loss to the wall, rather than the ionization energy, is the dominant factor affecting the discharge performance for alternative propellants in a miniature DC thruster.

Optimizing nitrite content in powders from plasma-activated egg whites for meat preservation using response surface methodology

The study optimized the production of powders from two types of egg whites to be used as a nitrite source for meat curing, establishing a maximum utilization limit of 2%. The necessary quantity of nitrite was established through response surface methodology to guarantee its efficacy as a preservative agent and adherence to regulatory standards. High R2 values (0.9946 for hen, 0.9962 for ostrich) validated critical factors: plasma treatment time and distance, with minimal impact from drying temperature. Under specific experimental conditions (155.93 min, 16.84 cm, 41.10 °C), obtained nitrite concentration of 4000 mg kg⁻1 was confirmed through experiments. Stability tests showed that nitrite levels remained stable over four weeks under different conditions including vacuum and air-sealed packaging, as well as different temperatures (−18 °C, 4 °C, and 26 °C). Future research should investigate long-term stability, the formation of additional compounds, and the functional properties of powders to confirm their potential for food applications.

Valor económico objetivo?

This is a heterodox review on the economic relationship between “utility” and “value”. Theoretical and methodological frameworks are based on the subject of Religion & Economics, with special attention given to the discussion between Christian economists and secular economists. Economics as a science is in sore modern need of Christian axiology. This relation was maintained in the West until the fall of the Moral Economy defended by the School of Salamanca. Since the advent of the utilitarian school, economists usually have used prices (and therefore money) as the numeraire for utility maximization, fallen in the capital twist, with a revival in the 1950s during the Cambridge dispute. This paper offers a solution which helps in the dialogue between religious and secular economists.

Optimized Selective Assembly using Hungarian Algorithm

Assembly of discrete parts guided by hardware design specification constitutes the final phase in product manufacturing. In the course of mass production of components, mating parts with geometric or dimensional deviation from their intended design can be made acceptable by the identification of suitable pairs after analysing design fit and tolerance limits. By transforming this application-specific problem into a unified mathematical model, an optimal solution can be achieved that minimizes the rejection of non-conforming fabricated parts. Regardless of the type and range of a design fit, the problem can be mapped into a matrix using a ranking function defined by the user. The ranking function is modifiable as per the user requirements and may vary based on the selection criteria for an assembly. Based on the type of ranking function used, the tabulated matrix is solved using the Hungarian minimization/maximization algorithm, which is a powerful combinatorial optimization algorithm that solves the classical assignment problem in mathematics. This approach ensures maximum number of suiting pairs as well as nominal suiting of parts with each other resulting in high-quality products and maximum utilization of fabricated resources.