Long-term Balance Research Articles

Acorns: From an Ancient Food to a Modern Sustainable Resource

Acorns, the seeds of oak trees, are pivotal in the Mediterranean region, historically serving as vital sustenance for wildlife and humans. Although traditionally used for livestock, in times of scarcity, acorns were also used in human diets together with their use in traditional medicine. In this review, we explore and deepen the multifaceted significance of oak species, consolidating nutritional data while emphasizing sustainable practices for modern dietary integration and potential applications in other areas, promoting long-term ecological balance. In the Mediterranean region, notable species are Quercus ilex, Q. faginea, Q. suber, and Q. coccifera, which differ in flavor, texture, and nutritional content. Rich in carbohydrates, acorns can contain up to 50% starch as well as amino acids, proteins, and lipids. This nutritional composition favors the preparation of flour for use in bread doughs or even diverse types of processing such as roasting, which makes it a substitute for coffee. Furthermore, acorn by-products, containing tannins, find applications in leather processing. This review highlights and summarizes in detail the nutritional potential, culinary adaptability, and diverse applications of acorns, emphasizing the need to preserve and utilize natural resources sustainably. In doing so, it sheds light on the often-overlooked value of these humble seeds.

Multi-Scale Supply and Demand Relationships of Ecosystem Services Under Multiple Scenarios and Ecological Zoning to Promote Sustainable Urban Ecological Development in Arid Regions of China

Predicting and analyzing the supply and demand relationship of ecosystem services provides theoretical support for the improvement of the ecological environment. This paper takes Bortala, a typical oasis city with a fragile ecological environment in the arid northwest region, as a case study. Based on the GMOP-PLUS-InVEST coupled model, it predicts the coupling coordination and matching degree of the supply and demand connection of ecosystem services such as habitat quality (HQ), carbon storage (CS), water yield (WY), and soil erosion (SD) under four scenarios. The findings indicate that from 2020 to 2035, HQ, CS, and WY have basically achieved coupling coordination at both scales. However, there is a notable disparity in the supply and demand of water resource production and carbon emission production. To ensure the long-term balance of ecosystem service supply and demand (ESSD), the research area was ultimately divided into five ecological zones: ecological conservation zone, ecological agriculture zone, ecological moderate development zone, ecological improvement zone, and ecological protection zone. It could offer insights for guiding the sustainable growth of ecologically vulnerable zones in the future.

Investigating The Validity of The Marshall-Lerner Principle and J-Curve Theory in Relation to Real Exchange Rates and Trade Imbalances: An Empirical Study of China's Economic Dynamics

According to traditional macroeconomic theory, meeting the Marshall-Lerner condition suggests that currency devaluation could positively impact the long-term trade balance. This implies that despite initial import cost increases, enhanced export competitiveness from a weaker currency eventually leads to trade balance improvements. However, short-term negative effects, known as the J-curve effect, may occur due to trade volume adjustments lagging currency devaluations. This study aims to assess the validity of the Marshall-Lerner condition in China's economy from 1995: Q1 to 2023: Q4 and evaluate the short-term J-curve effect's magnitude. Analyzing economic indicators and exchange rate fluctuations, the research confirms the validity of the Marshall-Lerner condition and supports the existence of the J-curve effect. These findings highlight the importance of nuanced currency policymaking for sustainable economic growth and stability, considering both short-term adjustments and long-term objectives. Key Words: Marshall-Lerner Condition, J Hypothesis, Foreign Trade.

Analysis of the Impact of Monetary Policy Instruments on Economic Growth in Indonesia by 2013 to 2023

Based on quarterly data by 2001Q1 to 2017Q2, this research and study covers theoretical debates and empirical studies on the factors that affect economic stability and their effect on the financial sector's performance. This study applies the Ordinary Least Square (O.L.S.) method to the Cointegration and Engle Granger-Error Correction Model (E.C.M.) methods. E.C.M. is done to assess the long-term validity and balance of the research model and foresee potential flaws and discrepancies among the theoretical and statistical models. Even while the M2 variable has no discernible effect on G.D.P. during the observation period, the research findings demonstrate that, over the long run, there is a balance among changes in G.D.P. and monetary variables, such as interest rates, Inflation, M2, and the rupiah value. On the other hand, the E.C.T. variable has a significant short-term effect on fluctuations in G.D.P. Interest rates, Inflation, M2, and exchange rates had no discernible effect on G.D.P. throughout this time. Thus, changes in monetary variables, particularly interest rates, Inflation, and M2, tend to effect G.D.P. The average quarterly financial deepening in Indonesia for the observation period was 3.80 per cent, according to the outcomes of the financial performance study. Furthermore, M2 growth during the same period was 3.03 per cent, compared to Indonesia's average quarterly economic growth of 1.36 per cent.

Soil Properties Classification in Sustainable Agriculture Using Genetic Algorithm-Optimized and Deep Neural Networks

Optimization of land management and agricultural practices require precise classification of soil properties. This study presents a method to fine-tune deep neural network (DNN) hyperparameters for multiclass classification of soil properties using genetic algorithms (GAs) with knowledge-based generation of hyperparameters. The focus is on classifying soil attributes, including nutrient availability (0.78 ± 0.11), nutrient retention capacity (0.86 ± 0.05), rooting conditions (0.85 ± 0.07), oxygen availability to roots (0.84 ± 0.05), excess salts (0.96 ± 0.02), toxicity (0.96 ± 0.01), and soil workability (0.84 ± 0.09), with these accuracies representing the results from classification with variations from cross-validation. A dataset from the USA, which includes land-use distribution, aspect distribution, slope distribution, and climate data for each plot, is utilized. A GA is applied to explore a wide range of hyperparameters, such as the number of layers, neurons per layer, activation functions, optimizers, learning rates, and loss functions. Additionally, ensemble methods such as random forest and gradient boosting machines were employed, demonstrating comparable accuracy to the DNN approach. This research contributes to the advancement of precision agriculture by providing a robust machine learning (ML) framework for accurate soil property classification. By enabling more informed and efficient land management decisions, it promotes sustainable agricultural practices that optimize resource use and enhance soil health for long-term ecological balance.

Cultivating stakeholders’ willingness to participate in sustainable tourism development: A research proposition

This study aims to evaluate the role of community stakeholders in fostering sustainability within tourism development, with a focus on Langkawi, Malaysia. It seeks to propose a comprehensive model that highlights the influence of residents' perceptions (as key stakeholders) of community empowerment, political trust, and place attachment on their support for sustainable tourism. This study proposes a conceptual framework based on stakeholder theory and conducts a thorough examination of stakeholders' perspectives on tourism development, considering both positive and negative impacts. A comprehensive literature review is adopted in this research. The study reveals nuanced insights into stakeholders' attitudes towards tourism development and sustainability. It identifies the intricate interplay between perceptions of community empowerment, political trust, place attachment, and support for sustainable tourism initiatives, contributing to a deeper understanding of the dynamics surrounding sustainable tourism. Findings indicate that positive perceptions of benefits encourage active resident engagement in STD. Practical implications suggest that local authorities, destination managers, and policymakers should prioritize involving residents in tourism planning, building trust, and empowering communities. By addressing both social and environmental concerns, sustainable tourism can ensure long-term success and balance development with conservation. The proposed model lays the groundwork for future empirical analyses to yield meaningful insights for governments and tourism planners, facilitating informed policy-making and decision-making processes regarding residents and tourism development in developing nations.

Accelerated glacier mass loss in the mid-latitude Eurasia from 2019 to 2022 revealed by ICESat-2

The dynamics of glaciers serve as one of the most important indicators of climate change. Whilst current research has primarily concentrated on long-term interannual glacier mass balance and its response to climate change, glaciers may respond more rapidly to climate change, highlighting the urgent need for intra-annual mass balance estimations. Investigating seasonal or short-term variations in glacier mass balance not only enhances our understanding of the interactions between glaciers and the climate system but also provides crucial data for water resource management and ecological protection. The ICESat-2 and NASADEM datasets were used to estimate the inter- and intra-annual glacier mass balance changes in the mid-latitude Eurasia from 2019 to 2022. Additionally, the response of glacier mass balance to regional air temperature and precipitation values was analysed using ERA5-Land data and multiple regression analysis, respectively. From 2019 to 2022, glacier mass loss in mid-latitude Eurasia reached −45.02 ± 34.21 Gt per year, contributing to a global sea-level rise of 0.12 ± 0.09 mm per year. The glacier melt rate in the study area from 2019 to 2022 was 2.33 times higher than that from 2000 to 2019. With the exception of the Western Kunlun region, which experienced a weak accumulation rate of 0.04 ± 0.35 m w.e. per year, all other areas experienced ablation states. Seasonal mass balance responds differently to temperature and precipitation variations across seasons: higher temperatures in different seasons lead to more negative mass balances, while increased winter and spring precipitation can slow down glacier melt. Air temperature dominates the glacier mass balance changes in the study area. The intense heat in 2022 raised average glacier temperatures by 1.04 °C compared to 2019–2021, resulting in a more negative mass balance and an increased ice loss of −0.34 ± 1.01 m w.e. per year (−35.07 ± 103.22 Gt per year). This analysis indicates that glacier mass balance is highly sensitive to climate change, even on a seasonal scale. Moreover, the high precision and spatiotemporal resolution ICESat-2 data can facilitate the investigation of large-scale glacier mass balance on short time scales.

Accruals and Long-Term Nonfinancial Assets and Liabilities

ABSTRACT This study proposes improvements to accrual models. Existing models explain how working capital maps cash flows from operations into earnings and how this mapping reflects accounting conservatism. However, except for fixed asset depreciation, accruals associated with long-term nonfinancial balance sheet accounts (e.g., intangible assets, goodwill, deferred revenues) are not modeled. We show that these unmodeled accruals have grown in importance over time and that a significant portion of them can be explained by utilizing a fundamental property of accrual accounting: most nonfinancial assets and liabilities will eventually be transferred to earnings as accruals, especially during bad times. Using a large U.S. sample for the 1988–2019 period, we document that beginning-of-year long-term nonfinancial assets and liabilities are significantly associated with total accruals and that, consistent with conditional conservatism, a greater proportion of long-term nonfinancial assets is expensed as accruals when current performance is poor. In simulations, compared to traditional models, models that include long-term nonfinancial assets and liabilities as regressors are more likely to detect seeded discretionary accruals between 2% and 20% of total assets, suggesting that these expanded models should be used to decrease the likelihood of making erroneous inferences.

Supply chain digitalization and firms' green innovation: Evidence from a pilot program

Green innovation is essential for realizing environmental sustainability and achieving long-term ecological balance. This paper investigates the influence of supply chain digitalization on firms' green innovation in the manufacturing industry. China's 2018 Supply Chain Innovation and Application Pilot program as a quasi-natural experiment, we employ a difference-in-differences (DID) estimation approach to reach the following findings: (1) supply chain digitalization significantly enhances the quantity and quality of enterprise green innovation, with a more substantial impact on quality. (2) supply chain financing capacity and firm environmental awareness play a partial mediating role in the relationship supply chain digitalization and the quality and quantity of corporate green innovation. (3) the heterogeneity analysis reveals that the impact of supply chain digitalization on green innovation is notably heightened in firms with managers who have overseas experience, weak internal controls, and poor regional supply chain environments. This study enriches the theoretical understanding of enterprise green innovation from the perspective of supply chain digitalization, providing a theoretical basis and practical insights for green innovation practices in enterprises.

THEORETICAL FRAMEWORK OF THE GREEN REGIONAL ECONOMY DOCTRINE FORMATION

This article explores the theoretical underpinnings of the green regional economy, a crucial concept within the broader framework of sustainable development, particularly in light of increasing global environmental challenges. The authors delve into the evolution of economic thought regarding the integration of environmental and economic objectives, highlighting the importance of balancing ecological sustainability with regional economic growth. The study identifies key factors and principles that underpin the green economy at the regional level, such as the efficient use of natural resources, the promotion of renewable energy, and the development of eco-friendly technologies. The article emphasizes the need to tailor global green initiatives to the specific needs and characteristics of individual regions, considering factors such as natural resource endowments, industrial structure, and socio-economic conditions. A significant focus is placed on the challenges of fostering environmentally sustainable economic development, with a particular emphasis on policy formulation that promotes ecological security and economic resilience. The article also discusses the role of green innovations, the mobilization of social capital, and regional governance in advancing the green economy. Furthermore, the authors propose a theoretical framework for the development of a green economy doctrine that incorporates key strategic initiatives, such as the transition to a circular economy, the integration of sustainability metrics into regional development plans, and the creation of green jobs. These elements are critical for fostering long-term ecological balance while ensuring economic growth and improving the quality of life at the regional level. The paper concludes with recommendations for further research and practical implementation of the green regional economy doctrine, underscoring the need for interdisciplinary approaches and collaboration between governments, businesses, and civil society to achieve sustainable development goals.

Research on the thermal balance of a novel independent heat extraction-release double helix energy pile in long-term operation

Ground source heat pump buried pipes offer potential in civil defense due to their concealment and reliability, yet face thermal imbalance issues. This paper adopts a double helix energy pile with independent heat extraction-release capacity and develops an experiment to compare the performance of independent operation versus joint operation. Furthermore, a verified 2D model facilitated extensive simulations for long-term thermal balance, integrating refrigeration load, principles of water use in an underground engineering, and heat pump model. Comparative experiments show that joint operation can effectively alleviate soil heat accumulation by more than 20%. Extended simulations reveal that as accumulated heat is removed, the unit's performance is improved, and soil heat accumulation can boost heat extraction. However, under domestic water heat extraction, the heat-extracting pipe shows low flow rates, leading to thermal accumulation, necessitating the use of water for equipment or additional feed water to improve heat extraction. Compared to uniform enhancement heat extraction, centralized enhanced heat extraction boosts overall heat extraction capacity by 35.1%, which can more effectively mitigate thermal imbalances and improve unit performance, and achieving thermal balance in the geotechnical area requires an enhanced extraction flow rate above 10.5 L/h, with over 56 m3 of water passing through the heat-extracting pipe.

Environmental Impacts of the China-Pakistan Economic Corridor (CPEC): An analysis of Climate Change Mitigation and Adaptation Strategies

This article explores the complex environmental impacts of the China-Pakistan Economic Corridor (CPEC) and suggests sustainable development strategies. Our study reveals significant changes in land use patterns, including loss of important habitat, which is contributing to biodiversity decline. Analysis of air quality data shows increased levels of pollutants in urban areas along the corridor, which are exacerbated by construction activity and increased traffic. Water resource assessments highlight issues related to quality and availability, especially in areas with high industrial activity. In response to these findings, we suggest methods for mitigating and adapting to climate change along the corridor. Interpreting these findings, we argue that these assessments are critical for identifying potential environmental problems and ensuring that development initiatives are built with long-term sustainability in mind. Recommendations for mitigating climate change include international cooperation, increasing public awareness, and using resilient design principles. For future development projects, we include sustainable practices, community involvement and compliance with environmentally friendly standards as important elements in economic growth. We draw conclusions by emphasizing the need for future studies to track long-term impacts, evaluate socio-economic implications, and implement environmentally friendly strategies, maintaining a long-term balance between economic development and environmental conservation in CPEC and other international projects.

Hubungan Jangka Pendek dan Jangka Panjang antara Pembiayaan Perbankan Syariah dan GDP di Indonesia dengan menggunakan metode Vector Error Correction Model

This research analyzes the relationship between Islamic bank financing and economic growth as measured by Gross Domestic Product (GDP) using the Vector Error Correction Model (VECM) to explain the short-term and long-term relationship dynamics between these two variables. The results of this research found that there is a long-term negative relationship between Islamic bank financing and GDP. These findings indicate that, although Sharia financing is expected to support economic growth through Sharia-based financial principles, the reality shows that the direct effect on overall economic growth is more complex and not always unidirectional. Apart from that, this research also finds that in the short term, both sharia financing and GDP adjust back to long-term balance after experiencing deviations, which means a strong economic correction mechanism exists. The stable VAR stability test results validate the model's reliability in describing the accurate relationship between sharia financing and economic growth in Indonesia. These findings provide important insights for policymakers and Islamic banking practitioners in developing more effective strategies to encourage inclusive economic growth.

O79 DAILY URINARY POTASSIUM EXCRETION IS NOT A FIXED PERCENTAGE OF DAILY POTASSIUM INTAKE

Background and Objective: High potassium intake is associated with a lower blood pressure and lower incidence of cardiovascular events. For estimation of potassium intake, the World Health Organization advices to multiply the 24-hour renal potassium excretion by 1.3, considering the substantial fecal potassium loss. We examined the variation in the required conversion factor in healthy volunteers and evaluated the effect of factors associated with tissue cation storage on the renal potassium excretion. Methods: We performed a post-hoc analysis of the Mars long-term sodium balance studies. Healthy male participants consumed a fixed amount of salt (6, 9 and 12 grams/day for >29 days) and potassium (4 grams/day) for 105 (n=4) and 205 days (n=6). All urine was collected in 24-hour aliquots. We calculated the percentage of potassium intake that was excreted in the corresponding 24-hour urine collection during steady-state. A multivariable mixed-effects model was used to assess associations of this percentage with sodium intake, potassium intake, urinary aldosterone, urinary cortisol and urine volume. Results: The median renal potassium excretion was 80% of potassium intake (IQR 65-97%, range 24-304%), corresponding to a conversion factor of 1.25 (IQR 1.03-1.54). Within individual subjects we also observed a marked day-to-day variation in the percentage of renal potassium excretion: the average intraperson width of the IQR was 25%. Sodium intake (figure A), urinary aldosterone (figure B), urinary cortisol (figure C) and urine volume (figure D) were positively associated with the percentage of renal potassium excretion, whereas potassium intake showed a negative association (figure A). A significant positive interaction between the effects of sodium and potassium intake was present (P<0.001). Conclusions: The percentage of dietary potassium that is excreted via urine varies considerably. During steady-state, this percentage is independently affected by sodium intake, potassium intake, urinary aldosterone, urinary cortisol, and urine volume. Our results suggest that the WHO's fixed 1.3 conversion factor may lead to inaccurate estimations of potassium intake.

P176 SPOT URINE FORMULAS OVERESTIMATE DIETARY SODIUM INTAKE DURING LOW SODIUM CONSUMPTION

Background and objective: Long-term sodium balance studies have revealed a phenomenon of temporary storage of sodium in tissues. Consequently, relying on an individual's single 24-hour urine collections may lead to an unreliable estimation of sodium intake. Our recent research has shown that the accuracy of repeated spot urine collections is equal to that of a single 24-hour urine collection at a sodium intake level of 5 gram/day. Since no data is available about the performance at recommended sodium intake (i.e., <2 grams/day), we determined their accuracy during low sodium consumption. Methods: We performed a post-hoc analysis on data from a metabolic ward study in which 16 healthy male adults consumed a diet with a fixed sodium content of 50 or 200 mmol/day for 7 days. Each day, urine was collected in 4 intervals (7:00-13:00 h, 13:00-19:00 h, 19:00-23:00 h, 23:00-07:00 h). We estimated sodium intake by the European Toft formula using urines of the same interval on 3 consecutive days during steady state (day 5-7). In sensitivity analyses we applied the Tanaka and Kawasaki formulas. Results: During a 200-mmol sodium intake, the Toft formula estimates appeared the most accurate, deviating 10 [IQR 3-14], 8 [6-19], 36 [16-49] and 20 [10-43] mmol from the intake for intervals 7:00-13:00 h, 13:00-19:00 h, 19:00-23:00 h, 23:00-07:00 h, respectively (Figure 1A). This accuracy did not significantly differ from a single 24-hour urine (20 [12-55] mmol). However, at a 50-mmol sodium intake, the Toft formula estimates deviated 62 [IQR 45-69], 75 [67-97], 99 [90-109] and 51 [45-61] mmol from the intake for similar intervals (Figure 1B). These estimates were significantly less accurate than a single 24-hour urine (9 [6-23] mmol). Although the Tanaka equation outperformed the Toft equation, this formula was also significantly inferior to a 24-hour urine collection. Conclusions: Repeated spot urine collection substantially overestimates sodium intake when sodium intake is low, whereas it performs similarly to a 24-hour urine collection at an average sodium intake.

Harberger-Laursen-Metzler Hypothesis: An Analysis with ARDL Bounds Test Approach

The Harberger, Laursen, and Metzler (HLM) hypothesis posits that a positive (negative) change in terms of trade, ceteris paribus, will lead to positive (negative) movements in the trade balance. When tested on developing countries, the hypothesis yields varying results. Some studies validate the hypothesis, while others suggest it is not applicable. Additionally, causality tests examining long-term relationships also produce different outcomes. Türkiye ranks among the countries with significant trade deficit issues. Therefore, testing the validity of the HLM hypothesis in the context of Türkiye is of great importance. The motivation of this study is to examine the impact of changes in terms of trade on the long-term trade balance in Türkiye from 2013 to 2023. In this context, both the volume and unit value of the terms of trade are considered. According to the findings, there is a positive relationship from terms of trade to the trade balance. Short-term deviations are found to be corrected within approximately three months. The causality test indicates that terms of trade are a Granger cause of the trade balance, and this causality is unidirectional. In this study, Türkiye's terms of trade and trade balance data for the specified periods were meticulously analyzed, and the validity of the HLM hypothesis was carefully tested. The analysis results provide strong evidence supporting the HLM hypothesis. These findings offer significant insights for Türkiye's economy and trade policies.

THE DYNAMICS OF EXCHANGE RATES, INFLATION, AND TRADE BALANCE IN A SMALL OPEN ECONOMY (CASE STUDY OF SIERRA LEONE)

Sierra Leone experiences a persistent trade deficit problem. Currently, there is a vacuum in the literature employing recent data and suitable approaches to address the issue of non-stationarity and dynamic interaction between macroeconomic variables in influencing the trade deficit in Sierra Leone. This study examines the relationship between Sierra Leone's trade balance, inflation, and exchange rate using quarterly data from 2005 Q1 to 2023 Q3. The focus is on understanding how the exchange rate and inflation impact Sierra Leone's trade balance in both the short and long term. To achieve this, the study utilizes the VAR/VECM model to depict the dynamic interaction between the trade balance, exchange rate, and inflation. It also employs Granger Causality analysis to determine the most appropriate ordering among the macroeconomic variables in the model and Impulse Response Function (IRF) analysis to test the hypotheses regarding the trade balance response to exchange rate shocks and inflation. The empirical results confirm the existence of cointegration, indicating a long-term balance between the trade balance, exchange rate, inflation, and other macroeconomic variables such as GDP growth and interest rate differentials. Moreover, the dynamic prediction analysis using the IRF method supports the J-curve hypothesis in Sierra Leone and suggests that inflation can reduce the performance of the trade balance. These findings highlight the need for Sierra Leone to implement a comprehensive strategy to adjust the exchange rate and curb inflation to improve the trade balance and enhance external economic stability.

Enhancing Economic, Social, and Ecological Resilience Through Sustainable Waterfront Development in Penang

The global economic disruption caused by the COVID-19 pandemic has significantly impacted development across various regions, including Penang, where supply chain disruptions, restricted cash flow, and delayed progress have led to reduced economic growth for stakeholders and communities alike. This study aims to explore the interconnected economic, social, and ecological (ESE) systems within the context of sustainable waterfront development in Penang, focusing on how these systems contribute to economic resilience and dynamism. The land and water resources of Penang, strategically situated along vital maritime routes, present substantial potential for economic revitalization. A quantitative research approach was employed, gathering data from questionnaire surveys, revealing a positive correlation between ESE variables. Key attributes such as local authority governance, development scale and impact, business operations, place identity, heritage preservation, and waste management were found to play crucial roles in shaping sustainable waterfront initiatives. The study highlights that Penang’s core economic sectors—agriculture, mining and quarrying, manufacturing, construction, and services—have historically driven the local economy, but the growing focus on waterfront development offers new avenues for economic recovery and growth. The results validate the chosen quantitative methodology and underscore the importance of adopting integrated strategies to address land and water management challenges. By aligning with sustainability goals and adopting a holistic approach, Penang's waterfront development can foster resilience, ensuring long-term socio-economic and ecological balance. The insights provided contribute to a broader understanding of sustainable urban development and offer actionable strategies for policymakers and stakeholders involved in Penang's waterfront projects.

Correcting for Plasma Aldosterone Improves the Accuracy of Repeated Timed Urine Sampling for Estimation of Dietary Sodium Intake.

Long-term sodium balance studies show that sodium can be temporarily stored and released in tissues, mediated by circaseptan rhythms of aldosterone and cortisol. This complicates the reliability of a single 24-h urine collection to estimate individual sodium intake. We investigated whether repeated timed urine collection with and without correction for plasma aldosterone is a more accurate alternative for estimating daily sodium intake. We conducted a post hoc analysis of a metabolic ward study in which 16 healthy male adults consumed a diet with a fixed sodium content (50 or 200 mmol/day) for 7 days. Each day, urine was collected in 4 intervals (7:00-13:00 h, 13:00-19:00 h, 19:00-23:00 h, and 23:00-07:00 h). Plasma aldosterone was measured at 6:30 h, 12:30 h, and 18:30 h. Sodium intakes were estimated by various formulas using 3 timed urines of day 5-7. During a 200-mmol daily sodium intake, sodium intake estimates based on three repeated timed urine samples and the Toft equation differed 10 [IQR: 3-14], 8 [6-19], 36 [16-49], and 20 [10-43] mmol from the actual intake for intervals 7:00-13:00 h, 13:00-19:00 h, 19:00-23:00 h, 23:00-7:00 h, respectively. These measurements did not significantly differ from a single 24-h urine (20 [12-55] mmol). During a 50-mmol daily sodium intake, repeated timed urine collection performed worse than a single 24-h urine collection. On both diets, correction for plasma aldosterone increased accuracy and sodium intake estimates were significantly more accurate than a single 24-h urine. In a controlled environment, repeated timed urine collection corrected for plasma aldosterone is more accurate than a single 24-h urine collection.

Integrated energy hub dispatch with a multi-mode CAES–BESS hybrid system: An option-based hierarchical reinforcement learning approach

The high penetration of renewable energy sources (RES) in power generation has driven demand for advanced integrated energy management systems (IEMS). In this study, to address the challenges of insufficient adaptability to dynamic supply–demand, a multi-type energy IEMS combining compressed air energy storage (CAES) and a battery energy storage system (BESS) is proposed, which operates under a multi-mode energy storage (MES) mechanism with rapid response, long-term balance, and synergic adjustment modes. To address the complexity of sequential decisions, an option-critic based twin delayed deep deterministic policy gradient (OCTD3) algorithm is firstly proposed within the hierarchical reinforcement learning (HRL) framework, enhancing efficiency through encapsulation of subtasks within ”options”. Additionally, model precision is refined by fitting the electricity–gas–heat conversion dynamics of CAES under off-design conditions. Dispatch tasks are modeled as an option-based Semi-Markov Decision Process (SMDP) and optimized by the OCTD3 to improve the power fluctuations index (PFI), comprehensive costs index (CCI), and system response synergy index (SRSI). Comparative simulations reveal that the MES mechanism boosts SRSI by 91.8%, showcasing high adaptability to varied supply–demand scenarios. The OCTD3 algorithm develops five hybrid strategies for CAES–BESS across three modes, effectively cutting costs by reducing electricity purchases and fluctuations expenses, and lowering PFI by 42.2% through balancing peak–valley loads and swiftly responding to transient shifts.