Search Results (21,425)

In the underground mine ventilation area, the absence of robust solutions for nonlinear programming models has impeded progress for decades. To overcome the enduring difficulty of solving nonlinear optimization models for mine ventilation optimization, a major technical bottleneck, we first develop an advanced linear optimization technique. This method transforms the nonlinear ventilation optimization and regulation model into a linear control model, avoiding the limitation of difficulty in solving the nonlinear mathematical model. The linear strategy opens up a new solution idea for the nonlinear calculation of the mine ventilation optimization and regulation. Furthermore, this study introduces evaluation metrics for ventilation scheme quality, including minimal energy consumption, fewest adjustment points, and optimal placement of these points, enhancing flexibility in ventilation network optimization. By analyzing the ventilation model control objectives and constraints, we formulated a linear optimization model and developed a multi-objective mixed-integer programming model for ventilation network optimization. This paper constructs and verifies a calculation example model for mine ventilation optimization, assessing its reliability based on airflow distribution calculations. Full article

Plastic pollution is an increasingly pressing environmental concern due to its persistence in ecosystems. To address this issue, this study evaluates polyethylene biodegradation and bioelectricity generation using Aspergillus ochraceopetaliformis in microbial fuel cells (MFCs). Single-chamber MFCs were designed (three) with carbon and zinc electrodes, where the fungus was cultivated in a nutrient-rich medium to enhance its metabolic activity. Parameters such as pH, power density, and FTIR spectra were monitored to assess plastic biodegradation. The results demonstrated a significant reduction in polyethylene mass and structure, along with a maximum generation of 0.921 V and 4.441 mA on day 26, with a power density of 0.148 mW/cm² and a current of 5.847 mA/cm². The optimal pH for fungal activity in the MFC was recorded at 7.059. Furthermore, FTIR analysis revealed a decrease in peak intensity at 1470 cm⁻¹ and 723 cm⁻¹, indicating structural modifications in the treated plastics. Furthermore, microbial fuel cells connected in series successfully powered an LED bulb, generating a maximum voltage of 2.78 V. These findings confirm the feasibility of using Aspergillus ochraceopetaliformis for biodegradation and bioelectricity generation, although practical applications require further optimization of system conditions and improvements in long-term stability. This research contributes to the development of biotechnological strategies for plastic waste management, sustainable integrating approaches with energy potential. Full article

Control over chemical reactivity remains a fundamental challenge in synthesis chemistry, where targeting a specific reactant represents the ultimate goal. While photoactivation is a well-established approach for selective excitation, electron-induced chemistry offers a complementary pathway with high efficacy. In this study, we investigate the effects of low-energy electron irradiation on prototypical chlorobenzene/water molecular films, demonstrating that chlorobenzene can be selectively dissociated via a resonant process occurring at ~1 eV. At higher electron energies (>6 eV), multiple reaction pathways become accessible, including the fragmentation of both water and chlorobenzene molecules. Our study provides a perspective strategy for achieving reagent-specific control in complex molecular assemblies via low-energy electrons, offering new insights into electron-driven surface chemistry and reaction dynamics at the molecular level. Full article

Aware of the nefarious effects of excessive exploitation of natural resources and the greenhouse gases emissions linked to building sector, the concept of smart buildings emerged, referring to a building that uses clean energy efficiently. This requires intelligent control systems to manage the use of residential energy consuming devices, namely the HVAC (Heating, Ventilation, Air-conditioning) system. This system consumes up to 50% of the total energy used by a building. In this paper, we introduce a RL (Reinforcement Learning) and MPC-LSTM (Model Predictive Control-Long-Short Term Memory) hybrid control system that combines DNNs (Deep Neural Networks), through RL, with LSTM’s long-short memory technique and MPC’s control characteristics. The goal of our model is to maintain thermal comfort of residents while optimizing energy consumption. Consequently, to train and test our model, we generate our own dataset using a building model of a corporate building in Casablanca, Morocco, combined with weather data of the same city. Simulations confirm the robustness of our model as it outperforms basic control methods in terms of thermal comfort and energy consumption especially during summer. Compared to conventional methods, our approach resulted in a 45.4% and 70.9% reduction in energy consumption, in winter and summer, respectively. Our approach also resulted in 26 less comfort violations during winter. On the other hand, during summer, our approach found a compromise between energy consumption and comfort with no more than 2.5 °C above ideal temperature limit. Full article

Polymorphism critically influences the solid-state properties of organic molecules, affecting stability, solubility, and functionality. We investigated the polymorphic behavior of enantiomerically pure (+)-(6aS,11aS)-medicarpin through combined experimental and computational analyses. Single-crystal X-ray diffraction revealed two distinct chiral polymorphs: the previously reported monoclinic P2₁ form and a newly identified orthorhombic P2₁2₁2₁ form with a fully chiral packing arrangement. The discovery of this previously unreported polymorph underscores the subtle yet decisive effects of solvent and conformational flexibility in directing crystallization. Detailed structural analysis reveals that, whereas the P2₁ form is only stabilized by a single dominant electrostatic interaction, the P2₁2₁2₁ form features a more complex network comprising C-H···π contacts, bifurcated C-H···O hydrogen bonds, and aromatic edge-to-face interactions. Further investigation of a functionalized p-nitrobenzoate derivative corroborates the critical influence of molecular substituents and crystallization conditions on packing motifs. Lattice energy DFT calculations confirm that each polymorph is stabilized by distinct electrostatic and dispersive interaction patterns, illustrating the complex energetic landscape of polymorph selection. Altogether, this work provides a framework for understanding and anticipating which polymorph is likely to form under specific solvent and crystallization conditions, offering insights for future strategies in materials design and guiding the pursuit of patentable crystalline forms in pharmaceutical applications. Full article

Indoor environments have received increasing attention in recent years, and achieving high-quality indoor conditions has become increasingly important. Underfloor air distribution (UFAD) systems have attracted significant interest due to their potential to improve ventilation efficiency, enhance thermal comfort, and reduce energy consumption. Compared with overhead air distribution (OHAD) systems, UFAD not only offers better energy savings but also demonstrates improved thermal stratification performance. However, most previous studies have relied on numerical simulations to evaluate UFAD performance under specific system designs or scenarios. Few studies have conducted on-site measurements to investigate the combined effects of multiple air-conditioning settings, which are closely related to user control strategies. This study experimentally evaluated the cooling performance and thermal comfort of a UFAD system under different control configurations. By combining variations in airflow rate, temperature setpoints, and supply air distribution, a total of 12 test configurations were examined. The results indicate that configurations with lower temperature setpoints achieved the highest cooling performance. Most test settings produced neutral thermal conditions at heights between 120 and 180 cm, while areas at 60 cm or below were noticeably cooler. These findings provide practical guidance for users in controlling UFAD systems. Full article

The pressing global transition to sustainable energy has intensified interest in overcoming the efficiency bottlenecks of conventional solar technologies. Hybrid photovoltaic–thermoelectric generator (PV–TEG) systems have recently emerged as a compelling solution, synergistically harvesting both electrical and thermal energy from solar radiation. By converting both sunlight and otherwise wasted heat, these integrated systems can substantially enhance total energy yield and overall conversion efficiency—mitigating the performance limitations of standalone PV panels. This review delivers a comprehensive, systematic assessment of maximum-power-point tracking (MPPT) methodologies specifically tailored for hybrid PV–TEG architectures. MPPT techniques are meticulously categorized and critically analyzed within the following six distinct groups: conventional algorithms, metaheuristic approaches, artificial intelligence (AI)-driven methods, mathematical models, hybrid strategies, and novel emerging solutions. For each category, we examine operational principles, implementation complexity, and adaptability to real-world phenomena such as partial shading and non-uniform temperature distribution. Through thorough comparative evaluation, the review uncovers existing research gaps, highlights ongoing challenges, and identifies promising directions for technological advancement. This work equips researchers and practitioners with an integrated knowledge base, fostering informed development and deployment of next-generation MPPT solutions for high-performance hybrid solar–thermal energy systems. Full article

This scientific article presents an innovative approach to optimizing routes of high-altitude unmanned aerial vehicles (UAVs) for effective monitoring of smart cities. The main proposed method is based on the ant colony optimization (ACO) algorithm with the implementation of an inverse pheromone mechanism—a repulsion-based exploration strategy. Unlike standard pheromones that encourage exploitation of frequently visited paths, this approach promotes exploration of unvisited areas by repelling UAVs from undesirable route sections, allowing UAVs to adapt more efficiently to dynamic changes in the urban environment. The authors developed a simulation system in the Webots environment, taking into account numerous factors: atmospheric conditions at high altitudes, potential for improved energy efficiency, urban development features, and priority of observation zones. Simulation results demonstrate that the proposed algorithm using inverse pheromones provides more effective area coverage compared to traditional route-planning methods, which may contribute to reduced UAV energy consumption and optimizing the monitoring process in real time. The research makes a significant contribution to the development of smart city technologies, offering a solution that can be integrated with existing urban monitoring systems to improve the efficiency of urban infrastructure observation, enhance security, and optimize urban resource management. Full article

Long-term renovation strategies (LTRSs) play a central role in achieving the European Union’s objective of a climate-neutral building stock by 2050. In Poland, the challenge is particularly acute: a majority of the building stock was constructed before 1990 and does not even meet basic thermal performance standards. In view of the state of the buildings in Poland and the assumptions made about obtaining the necessary energy parameters in the coming years, it is necessary to undertake thermal modernization measures. The purpose of the paper is to assess the economic efficiency of the variants of modernization of building stock in Poland, taking into account the constraints related to improving energy efficiency. Additionally, the article also points out the problem of discrepancies resulting from climate zones that may significantly affect the final primary energy results (on average, 5–15%). In order to achieve the objectives, the paper focuses on the analysis of energy sources. According to the overall score in the analytic hierarchy process (AHP) method, the best solutions, with a global priority of 0.46, are renewable energy sources (RESs). The evaluation of selected fuel types in the 2055 perspective, using the technique for order preference by similarity to ideal solution (TOPSIS) method, indicate favorable environmental performance by sources based on electricity, i.e., air-source heat pumps, ground-source heat pumps, and electric heating, which achieved the highest relative closeness to the ideal solution. Heat pump systems can reduce energy consumption by 26–41% depending on the building and heat pump type. The final analysis in the paper concerns different options for thermal modernization of a model single-family house, taking into account different energy sources and stages of thermal modernization work. The scenario involves the simultaneous implementation of all renovation measures at an early stage, resulting in the lowest investment burden over time and the most favorable economic performance. Full article

This study investigates the integration of green hydrogen into building energy systems using local solar power, with the electricity grid serving as a backup plan. A comprehensive bottom-up analysis compares six energy system configurations: the natural gas grid boiler system, all-electric heat pump system, natural gas and hydrogen blended system, hydrogen microgrid boiler system, cogeneration hydrogen fuel cell system, and hybrid hydrogen heat pump system. Energy efficiency evaluations were conducted for 25 homes within one block in a neighborhood across five typological house stocks located in Stoke-on-Trent, UK. This research was modeled using a spreadsheet-based approach. The results highlight that while the all-electric heat pump system still demonstrates the highest energy efficiency with the lowest consumption, the hybrid hydrogen heat pump system emerges as the most efficient hydrogen-based solution. Further optimization, through the implementation of a peak-shaving strategy, shows promise in enhancing system performance. In this approach, hybrid hydrogen serves as a heating source during peak demand hours (evenings and cold seasons), complemented by a solar energy powered heat pump during summer and daytime. An hourly operational configuration is recommended to ensure consistent performance and sustainability. This study focuses on energy performance, excluding cost-effectiveness analysis. Therefore, the cost of the energy is not taken into consideration, requiring further development for future research in these areas. Full article

This paper systematically reviews and analyzes various energy management strategies, as well as the characteristics, core challenges, and general processes of energy management for hybrid vehicles, aircraft, and ships. It also Analyzes the application scenarios, advantages, and limitations of rule-based energy management strategies. Based on the characteristics, design challenges, and general processes of optimized energy management strategies, a comparative analysis was conducted of mainstream strategies such as dynamic programming algorithms, Pontryagin’s minimum principle, equivalent energy consumption minimization, and multi-objective prediction. The focus was on analyzing intelligent control energy management strategies, including hybrid power system energy management strategies and their control effects based on neural network control, adaptive dynamic programming, reinforcement learning, and deep reinforcement learning. Finally, this paper addresses the challenges in applying energy management strategies, the limitations of modeling approaches, the validation of their effectiveness, and future research directions. Full article

The decarbonization and automation of port operations are emerging as key strategies to enhance the sustainability and efficiency of maritime logistics. This study proposes a simulation-based framework to assess the operational and environmental impacts of transitioning from traditional Internal Combustion Engine (ICE) tractors to Battery Electric Tractors (BET) and Automated Electric Guided Tractors (e-AGT) in Roll-on/Roll-off (Ro–Ro) port terminal operations. The proposed framework is applied to simulate a full vessel turnaround at the Ro–Ro terminal of the Port of Ravenna (Italy). A set of Key Performance Indicators (KPIs) is defined to evaluate turnaround time, vehicle productivity, energy consumption and CO₂ emissions across three scenarios. The results indicate that both BET and e-AGT configurations significantly reduce emissions compared to ICE, with reductions up to 40%. However, the e-AGT scenario reveals operational drawbacks, including increased unloading time and reduced fleet availability due to charging constraints and routing limitations. These findings highlight the environmental potential of automation and electrification but also emphasize the need for integrated planning of fleet size, charging infrastructure and circulation specifications. The proposed framework provides a replicable decision-support tool for port authorities and logistics operators to evaluate alternative handling technologies under realistic conditions. Full article

Since the discovery of the ‘Warburg effect’ in cancer, lactate is no longer considered merely a metabolic byproduct. It serves as both a metabolic fuel involved in the energy cycle and a signaling molecule that modulates cellular signal transduction. Recent studies have demonstrated that lactate participates in protein lactylation, regulates energy metabolism, reshapes the tumor microenvironment, and facilitates the metastasis of pancreatic cancer. Therefore, targeting lactate metabolism has emerged as a promising strategy to improve therapeutic efficacy and survival rates in pancreatic cancer. In this review, we outline aberrant lactate metabolism and recent advancements in lactylation, and elucidate the biological functions of lactate metabolism in pancreatic cancer, focusing on metabolic reprogramming, angiogenesis, and immune evasion. Additionally, we discuss diagnostic and therapeutic approaches targeting lactate metabolism in pancreatic cancer. Research in this field is critical for understanding the mechanisms driving pancreatic cancer progression and is anticipated to develop novel therapeutic strategies for clinical practice. Full article

As the hub of energy metabolism and the cell’s fate arbiter, mitochondria are essential for preserving cellular homeostasis and converting it from pathological states. Therefore, through mechanisms that drive metabolic reprogramming, oxidative stress, and apoptosis resistance, mitochondrial dysfunction (including mitochondrial DNA mutations, mitochondrial dynamics imbalance, mitochondrial autophagy abnormalities, mitochondrial permeability abnormalities, and metabolic disorder) can promote the progression of thyroid cancer (TC), resistance to treatment, and reshaping of the immune microenvironment. This article reviews the molecular mechanisms and characteristic manifestations of mitochondrial dysfunction in TC. It focuses on providing a summary of the main strategies currently used to target the mitochondria, such as dietary intervention and targeted medications like curcumin, as well as the clinical translational value of these medications when used in conjunction with current targeted therapies for TC and radioactive iodine (RAI) therapy in patients with advanced or RAI-refractory TC who rely on targeted therapies. The application prospects and existing challenges of emerging therapeutic methods, such as mitochondrial transplantation, are also discussed in depth, aiming to provide new perspectives for revealing the molecular mechanisms by which mitochondrial dysfunction drives the progression of TC, drug resistance, and the reshaping of its immune microenvironment, as well as providing new diagnostic and therapeutic strategies for patients with advanced or RAI-refractory TC who are reliant on targeted therapies. Full article

Acute Myeloid Leukemia (AML) is a genetically and clinically heterogeneous malignancy marked by poor prognosis and limited therapeutic options, especially in older patients. While conventional treatments such as the “7 + 3” chemotherapy regimen and allogeneic stem cell transplantation remain standard care options, the advent of next-generation sequencing (NGS) has transformed our understanding of AML’s molecular complexity. Among the emerging hallmarks of AML, metabolic reprogramming has gained increasing attention for its role in supporting leukemic cell proliferation, survival, and therapy resistance. Distinct AML subtypes—shaped by specific genetic alterations, including FLT3, NPM1, and IDH mutations—exhibit unique metabolic phenotypes that reflect their underlying molecular landscapes. Notably, FLT3-ITD mutations are associated with enhanced reactive oxygen species (ROS) production and altered energy metabolism, contributing to disease aggressiveness and poor clinical outcomes. This review highlights the interplay between metabolic plasticity and genetic heterogeneity in AML, with a particular focus on FLT3-driven metabolic rewiring. We discuss recent insights into how these metabolic dependencies may be exploited therapeutically, offering a rationale for the development of metabolism-targeted strategies in the treatment of FLT3-mutated AML. Full article