Search Results (3,615)

With the rapid development of large model technology, data storage as well as collection is very important to improve the accuracy of model training, and Feature Selection (FS) methods can greatly eliminate redundant features in the data warehouse and improve the interpretability of the model, which makes it particularly important in the field of large model training. In order to better reduce redundant features in data warehouses, this paper proposes an enhanced Secretarial Bird Optimization Algorithm (SBOA), called BSFSBOA, by combining three learning strategies. First, for the problem of insufficient algorithmic population diversity in SBOA, the best-rand exploration strategy is proposed, which utilizes the randomness and optimality of random individuals as well as optimal individuals to effectively improve the population diversity of the algorithm. Second, to address the imbalance in the exploration/exploitation phase of SBOA, the segmented balance strategy is proposed to improve the balance by segmenting the individuals in the population, targeting individuals of different natures with different degrees of exploration and exploitation performance, and improving the quality of the FS subset when the algorithm is solved. Finally, for the problem of insufficient exploitation performance of SBOA, a four-role exploitation strategy is proposed, which strengthens the effective exploitation ability of the algorithm and enhances the classification accuracy of the FS subset by different degrees of guidance through the four natures of individuals in the population. Subsequently, the proposed BSFSBOA-based FS method is applied to solve 36 FS problems involving low, medium, and high dimensions, and the experimental results show that, compared to SBOA, BSFSBOA improves the performance of classification accuracy by more than 60%, also ranks first in feature subset size, obtains the least runtime, and confirms that the BSFSBOA-based FS method is a robust FS method with efficient solution performance, high stability, and high practicality. Full article

Anthocyanins (ANTHs) are polyphenolic compounds with health promoting properties, being known for their strong antioxidant effects as well as for their antimicrobial properties, obesity and cardiovascular disease prevention, and anticarcinogenic activity. Being main dietary components, it is important to know the content of anthocyanins in various dietary sources and their stability in time. The total anthocyanin content (TAC) of various fresh fruits has been spectrophotometrically determined using the pH differential method. The results showed that in the analyzed samples, the TAC increased in the order: blackcurrants > blackberries > blueberries > raspberries > strawberries > plums. The degradation degree of anthocyanins extracted from blueberries (BBEs) in an ethanol/water solution in four experimental conditions was studied. Kinetic studies have been approached, fitting the experimental data recorded by UV–Vis spectrophotometric analysis in agreement with some kinetic models verified for the ANTH degradation reaction. Therefore, zero-order kinetics for BBE extract degradation exposed to sunlight were identified, while for the other storage conditions (shadow, dark, cold), the first-order kinetics were respected. The results indicate that the stability decreased as follows: (ANTH stability)_{sunlight test} << (ANTH stability)_{shadow test} ≈ (ANTH stability)_{dark test} < (ANTH stability)_{cold test}. A mechanism for BBE anthocyanin degradation was proposed and the impact on human health of the degradation products is discussed. Full article

Water scarcity necessitates desalination technologies, yet their high energy demands and brine disposal challenges hinder sustainability. This research study evaluates the energy footprint and carbon emissions of thermal- and membrane-based desalination technologies, alongside Minimal/Zero Liquid Discharge (MLD/ZLD) frameworks, with a focus on renewable energy source (RES) integration. Data revealed stark contrasts: thermal-based technologies like osmotic evaporation (OE) and brine crystallizers (BCr) exhibit energy intensities of 80–100 kWh/m³ and 52–70 kWh/m³, respectively, with coal-powered carbon footprints reaching 72–100 kg CO₂/m³. Membrane-based technologies, such as reverse osmosis (RO) (2–6 kWh/m³) and forward osmosis (FO) (0.8–13 kWh/m³), demonstrate lower emissions (1.8–11.7 kg CO₂/m³ under coal). Transitioning to RES reduces emissions by 90–95%, exemplified by renewable energy-powered RO (0.1–0.3 kg CO₂/m³). However, scalability barriers persist, including high capital costs, RES intermittency, and technological immaturity in emerging systems like osmotically assisted RO (OARO) and membrane distillation (MD). This research highlights RES-driven MLD/ZLD systems as pivotal for aligning desalination with global climate targets, urging innovations in energy storage, material robustness, and circular economy models to secure water resource resilience. Full article

Integrating renewable energy sources (RESs) such as solar and wind generation systems introduces challenges in ensuring a safe and stable power supply to the power system due to their inherent output variability. Addressing this issue requires the development of advanced technologies and methodologies to mitigate power variability while enabling the integration of high levels of renewable energy into the existing power system. One practical approach to managing the variability of RESs is incorporating an energy storage system (ESS), which enhances the reliability and stability of the power supply from RESs. This study focuses on optimized energy management and storage capacity sizing while ensuring safe operation amid output variability to maximize the benefits of combining RESs and two ESSs (i.e., primary and secondary) for a smart home energy management system. To achieve this, a linear programming (LP) model is employed to investigate the relationship between RESs, ESSs, and energy loads to determine the storage capacity under safety conditions. Here, safety refers to preserving the capacity limitations of each ESS in the power system against fluctuations. The optimization problem is mathematically formulated, and a feasible solution is found using the LP Solver in MATLAB.To validate the proposed optimal sizing of ESS and energy balancing against fluctuations, power generation, and consumption data from apartment facility, iHouse smart apartment facilities are employed during all seasons, i.e., spring, summer, winter, and autumn. Additionally, several case studies are analyzed, representing a distinct physical arrangement of connectivity between power devices, from the most densely connected to the least connected. The results indicate that the strategic power distribution significantly reduces the total ESS size, including the primary and secondary storage systems, for each season. The optimal secondary ESS size decreased to 25.7 % for the spring season, 17.29% for the summer season, 6.79 % for the winter season, and 7.01 % for the autumn season from the least connectivity from power devices to dense connectivity. The findings highlight the seasonal variations of generation and consumption and their impact on ESS sizing while preserving the limitations and ensuring the safety of the power system. Hence, it is a novel methodology for seasonal storage sizing and strategic energy management, guaranteeing stable and resilient power system operation. Full article

This study evaluates the potential of integrating visible and near-infrared (visNIR) spectroscopy, color analysis, and firmness testing for non-destructive tomato quality assessment and shelf-life prediction. Tomato fruit (cv. HM1823) harvested at four ripening stages were monitored over 12 days at 22 °C to investigate ripening stage-specific variations in key quality parameters, including color (hue angle), firmness (compression), and nutritional composition (pH, soluble solids content, and titratable acidity ratio). Significant changes in these parameters during storage highlighted the need for advanced tools to monitor and predict quality attributes. Spectral data (340–2500 nm) captured using advanced and cost-effective portable spectroradiometers, coupled with chemometric models such as partial least squares regression (PLSR), demonstrated reliable predictions of shelf-life and nutritional quality. The near-infrared spectrum (900–1700 nm) was particularly effective, with variable selection methods such as genetic algorithm (GA) and variable importance in projection (VIP) scores enhancing model accuracy. This study highlights the promising role of visNIR spectroscopy as a rapid, non-destructive tool for optimizing postharvest management in tomato. By enabling real-time quality assessments, these technologies support sustainable agricultural practices through improved decision-making, reduced postharvest losses, and enhanced consumer satisfaction. The findings also validate the utility of affordable spectroradiometers, offering practical solutions for stakeholders aiming to balance cost efficiency and reliability in postharvest quality monitoring. Full article

The adoption rate of battery electric vehicles (EVs) is rapidly increasing. Electric vehicles differ significantly from conventional internal combustion engine vehicles and vary widely across different manufacturers. Emergency responders (ERs) and recovery personnel may have less experience with EVs and lack timely access to critical information such as the extent of the stranded energy present, high-voltage safety hazards, and post-crash handling procedures in a user-friendly manner. This paper presents a software/hardware interactive tool named Electric Vehicle Information for Incident Response Solutions (EVIRS) to aid in the quick access to emergency response and recovery information. The current prototype of EVIRS identifies EVs using the VIN or Make, Model, and Year, and offers several useful features for ERs and recovery personnel. These features include integration and easy access to emergency response procedures tailored to an identified EV, vehicle structural schematics, the quick identification of battery pack specifications, and more. For EVs that are not severely damaged, EVIRS can perform calculations to estimate stranded energy in the EV’s battery and discharge time for various power loads using either EV dashboard information or operational data accessed through the CAN interface. Knowledge of this information may be helpful in the post-crash handling, management, and storage of an EV. The functionality and accuracy of EVIRS were demonstrated through laboratory tests using a 2021 Ford Mach-E and associated data acquisition system. The results indicated that when the remaining driving range was used as an input, EVIRS was able to estimate the pack voltage with an error of less than 3 V. Conversely, when pack voltage was used as an input, the estimated state of charge (SOC) error was less than 5% within the range of 30–90% SOC. Additionally, other features, such as retrieving emergency response guides for identified EVs and accessing lessons learned from archived incidents, have been successfully demonstrated through EVIRS for quick access. EVIRS can be a valuable tool for emergency responders and recovery personnel, both in action and during offline training, by providing crucial information related to assessing EV/battery safety risks, appropriate handling, de-energizing, transport, and storage in an integrated and user-friendly manner. Full article

An information system (IS) is an organic system that integrates personnel, technology, data, and other resources for information collection, processing, storage, transmission, and utilization, supporting organizational decision making, management, and business development. Against the backdrop of sustainable development being integrated into the strategic goals of enterprises, the impact of accounting information systems (AISs) on corporate sustainability performance has garnered significant attention. This study employs the IS success model as its theoretical underpinning and incorporates both the quality of AISs and sustainability performance into the research framework. Likert scales were adopted to collect data, and structural equation modeling was conducted to test our hypotheses. The findings reveal that information quality and service quality exert a notably positive influence on intention to use and satisfaction. Meanwhile, system quality only positively impacts intention to use. There exists an interactive relationship between intention to use and satisfaction. Satisfaction positively contributes to corporate sustainability performance, whereas intention to use only positively affects environmental performance. This research offers a theoretical foundation and practical guidelines for enterprises aiming to optimize their AISs and enhance sustainability performance. Full article

The carbon stock in terrestrial ecosystems is closely linked to changes in land use. Understanding how land use alterations affect regional carbon stocks is essential for maintaining the carbon balance of ecosystems. This research leverages land use and driving factor data spanning from 2000 to 2020, utilizing the Patch-generating Land Use Simulation (PLUS) model alongside the InVEST ecosystem services model to examine the temporal and spatial changes in carbon storage across Beijing. Additionally, four future scenes for 2030—urban development, natural development, cropland protection, as well as eco-protection—are explored, with the PLUS and InVEST models employed to emulate dynamic land use changes and the corresponding carbon stock variations. The results show that the following: (1) Between 2000 and 2020, changes in land use resulted in a significant decline in carbon storage, with a total reduction of 1.04 × 10⁷ tons. (2) From 2000 to 2020, agricultural, forest, and grassland areas in Beijing all declined to varying extents, while built-up land expanded by 1292.04 km² (7.88%), with minimal changes observed in water bodies or barren lands. (3) Compared to the carbon storage distribution in 2020, carbon storage in the 2030 urban development scenario decreased by 6.99 × 10⁶ tons, highlighting the impact of rapid urbanization and the expansion of built-up areas on the decline in carbon storage. (4) In the ecological protection scenario, the optimization of land use structure resulted in an increase of 6.01 × 10⁵ tons in carbon storage, indicating that the land use allocation in this scenario contributes to the restoration of carbon storage and enhances the carbon sink capacity of the urban ecosystem. This study provides valuable insights for policymakers in optimizing ecosystem carbon storage from a land use perspective and offers essential guidance for the achievement of the “dual carbon” strategic objectives. Full article

Emerging trends in heat pump (HP) and electric vehicle (EV) adoption within communities aim to reduce carbon emissions in the heating and transportation sectors. However, these technologies rely on grid electricity, whose carbon intensity varies over time. This study explores how the carbon-saving potential of these technologies can be further enhanced through demand-shifting operations and renewable energy integration. The research compares photovoltaic–thermal (PV/T) and hybrid solar heat pump systems that integrate EV charging and PCM-enhanced heat storage to improve space heating efficiency under low solar irradiance in the UK while reducing CO₂ emissions. The study simulates solar collector configurations and sizes, combining PV modules and heat pumps to enhance system performance. Control systems synchronize operations with periods of low grid CO₂ intensity, minimizing the environmental impact. The analysis evaluates PV/T systems, separate PV and thermal collectors, highlighting their energy efficiency and CO₂ reduction potential. Control systems further optimize HP operation and EV charging during periods of high renewable energy availability, preventing uncontrolled use that could result in elevated emissions. Using real weather data and a detailed building model, the findings show that a solar-assisted HP with 100% thermal collectors achieves a daily COP of 3.49. Reducing thermal collectors to 60% lowers the COP to 2.57, but PV output compensates, maintaining similar emission levels. The system achieves the lowest emission with high-efficiency evacuated flat plate PV/T collectors. Full article

The growing demand for sustainable energy storage devices requires the fabrication of novel materials for rechargeable metal-ion batteries. The stability of the materials incorporated in the electrochemical cells plays a crucial role in the specific capacity and cycling stability of energy storage devices. The processes that occur inside such systems are fairly complex; hence, the identification of unwanted side reactions affecting the electrochemical stability is not a trivial task. The present study combines cheminformatics and quantum chemistry approaches to create an algorithm that generates diverse viable side products of redox reactions that a given electrochemical system, e.g., different cathode or anode materials, electrolytes, solvents, etc., can undergo. Two case studies of electrolyte degradation are presented: namely, ethylene carbonate (EC) and diglyme (DG). The effect of the electrode surface is modeled by the dehydrogenation reactions of the electrolyte solvents. The predicted degradation products after reduction and oxidation are validated using previously reported experimental data. For EC, the predicted products are CO, CO₂, ethene, ethylene oxide, [CO₂]^•−, and [CO₂]^•+, while for DG alkoxy anions are mainly anticipated. The number of gaseous products formed upon DG degradation is significantly smaller than the number of gaseous species formed by EC fragmentation. The proposed algorithm opens new avenues for the rapid deduction of degradation products of novel electrolyte solvents for which no experimental data are available and can easily be adapted to predict the degradation of other materials. Full article

This study focuses on the Xiaoxing’an Mountains, examining the evolution of ecological security patterns and suggesting optimization strategies by integrating carbon storage and landscape connectivity, using multi-source data from 2000, 2010, and 2020. The study provides a comprehensive assessment of the region’s ecological security by estimating carbon stocks using the InVEST model, analyzing landscape connectivity through MSPA, and spatially extracting ecological corridors and nodes using circuit theory. The key findings are as follows: (1) High-value areas for carbon storage and landscape connectivity are primarily concentrated in the southeastern and northwestern forested mountain regions; (2) Ecological source areas are predominantly concentrated in the southeast and dispersed in the north, with the total area peaking in 2010 at 47,054.10 km²; (3) Northern ecological corridors are dense, radiating in a spider-web pattern, with pinch points concentrated at the corridor termini; southeastern corridors are sparse, mainly short, with fewer pinch points; (4) The area of ecological barriers increased by 280% over the past 20 years. Four major barrier zones were identified, all located at the junction of forest and farmland in the northwest, primarily composed of wetlands, drylands, and rural residential areas; (5) Based on the evolutionary characteristics of the Ecological Security Pattern over the past 20 years, an “axis, two belts, four zones, and multiple cores” ecological security planning framework was proposed, along with corresponding strategies. This study provides theoretical support and practical guidance for enhancing regional ecological network stability, optimizing landscape connectivity, and strengthening carbon sink functions. Full article

This work investigates the potential of a sorption-based thermal energy storage (TES) system for enhancing the integration of renewable energy and waste heat recovery in key sectors—industry, transport, and buildings. Sorption-based TES systems, which utilize reversible sorbent–sorbate reactions to store and release thermal energy, offer long-term storage capabilities with minimal losses. In particular, the aim of the study is to evaluate the efficiency of an adsorption TES system for various working pairs under different operating conditions, by means of a thermodynamic model (supported by experimental data). Key findings demonstrate that water-based solutions (e.g., zeolite and silica gel composites) perform well for residential and transport applications, while methanol-based solutions, such as LiCl-silica/methanol, maintain higher efficiency in industrial contexts. Short-term storage shows higher energy efficiencies compared to long-term applications, and the choice of working pairs significantly influences performance. Industrial applications face unique challenges due to extreme operating conditions, limiting the viable solutions to water-based working pairs. This research highlights the capability of sorption-based TES systems to reduce greenhouse gas emissions, improve energy efficiency, and facilitate a transition to sustainable energy practices. The findings contribute to developing cost-effective and reliable solutions for energy storage and renewable integration in various applications. Full article

Patient safety (PS) is essential in medical care, and preventing medication errors (MEs) is key to guaranteeing it. In Colombia, pharmaceutical services must comply with regulations that require adequate environmental monitoring to ensure medication quality. This study aims to propose an IoT-based smart system that automatizes temperature and relative humidity monitoring in the Colombian pharmaceutical service (CPS). Using the model for IoT platform design as a methodology, an efficient and flexible architecture that integrates data quality management (DQM) dimensions to improve the accuracy and reliability of the system was designed. In addition, tests based on the agile quadrant methodology demonstrate, as a result, its effectiveness, highlighting its ability to optimize environmental monitoring, prevent MEs, and improve PS. The successful implementation of this IoT-based smart system shows its potential in the pharmaceutical sector, offering an innovative solution that reduces risks and improves the quality of drug storage. Full article

Land use and cover change (LUCC) profoundly impacts the carbon cycle and carbon storage. Under the goal of “carbon neutrality”, studying the mechanisms linking LUCC with terrestrial ecosystem carbon storage is of significant importance for ecological protection and regional development. Using the central Shanxi urban agglomeration as a case study, this research employs various quantitative models based on land cover data to analyze changes in LUCC and carbon storage from 2000 to 2035. The study scientifically explores the impact of the spatial and temporal distribution characteristics of LUCC on carbon storage. The study indicates the following: (1) Over the past 20 years, the land types in the central Shanxi urban agglomeration are primarily grassland, cropland, and forest land. The two primary land transformations are the conversion of cropland to grassland and the conversion of grassland to cropland and forest land; (2) The carbon storage in the study area has shown a declining trend over the past two decades. Spatially, this decline exhibits a “two mountains and one valley” distribution pattern influenced by land use types. The reduction of grassland and cropland is the primary reason for the decline in carbon storage; (3) By 2035, under three different scenarios, carbon storage is projected to decrease compared to 2020. Among these, the scenario focused on cropland protection (CP) shows the least decline, while the naturally developing scenario (ND) shows the most significant decline. The research demonstrates that under scenarios of cropland protection and ecological conservation, strategies such as environmental restoration, development of unused land, and reclamation of built-up land for greening significantly enhance regional carbon storage and improve carbon sequestration capacity. Full article

In recent years, flood hazards have occurred increasingly worldwide, posing significant threats to the safety of life and property in lacustrine and riverine environments. To mitigate the devastating impacts of floods, it is crucial to explore optimal strategies for joint flood diversion of flood diversion and storage measures (FDSM). The FDSM management of Poyang Lake in China focuses on studying semi-restoration polder areas (SR Polders) and flood storage and detention areas (FS Detentions), which are subjects of ongoing research. Existing studies primarily focus on SR Polders or FS Detentions, with limited research on the joint flood diversion potential of these two measures, particularly regarding optimal scheduling. This study takes 185 SR Polders and the Kangshan flood storage and detention area (KS Detention) as the primary research objects. By integrating hydraulic theory, numerical simulation techniques, and survey data, we develop a hydraulic model for the SR Polders and a hydrodynamic model for the KS Detention to carry out flood diversion simulation. The 1998 flood is chosen as a typical case to simulate and analyze their flood diversion processes under various schemes. The results indicate that altering the operation criteria for FDSM influences both the maximum diversion discharge and the timing of the main diversion period. For the SR Polders, under the current flood control scheme, raising the operation water level (OWL) of SR Polders-I by 1.0 m increases the maximum diversion discharge by 894 m³/s. Additionally, raising the OWL of SR Polders-II by 0.37 m delays the main diversion period by one day. For the KS Detention, higher flood diversion water levels correspond to greater discharge capacities. Furthermore, a fuzzy optimization method is applied to optimize nine joint schemes of the SR Polders and KS Detention. The results indicate that the optimal joint flood diversion strategy for Poyang Lake is operating SR Polders-I, SR Polders-II, and KS Detention at a Hukou water level of 21.65 m, 22.05 m, and 22.50 m, respectively. Finally, the study provides insights and recommendations for flood control management at Poyang Lake. The results of this study not only have important guiding significance for flood control management of large plain lakes but also provide references for the joint operation of flood diversion and storage areas in other regions. Full article