Energy Supply Research Articles

Analysis of Heat Rate Co-firing Pacitan PLTU

Through RUEN in 2025, the government is launching a co-firing program for coal-fired power plants towards achieving net zero emissions. Biomass is one solution to replace or replace fossil fuels in the field of energy supply. Some of the energy plants commonly used for co-firing are calliandra and gamal. The aim of this research is to analyze the Heat Rate efficiency of the use of calliandra and gamal biomass. This research method in quantitative form to achieve measurable results. The results of the analysis of using calliandra biomass at a percentage of 5% produce an NHPR of 2975 kCal/kWh. This value is greater than the use of gamal biomass at a percentage of 5% with a GHPR of 2942 kCal/kWh, and using a percentage of 10% produces an NHPR of 2986 kCal/kWh and at 10% gamal co-firing it produces an NHPR of 2920 kCal/kWh, the smallest thermal efficiency value is produced when the plant uses 10% kalindran co-firing with a value of 30.9%. and the highest thermal efficiency of the generator is when 10% galvanic co-firing is used.

Interfacial Water Orientation in Neutral Oxygen Catalysis for Reversible Ampere-scale Zinc-air Batteries.

The neutral oxygen catalysis is an electrochemical reaction of the utmost importance in energy generation, storage application, and chemical synthesis. However, the restricted availability of protons poses a challenge to achieving kinetically favorable oxygen catalytic reactions. Here, we alter the interfacial water orientation by adjusting the Brønsted acidity at the catalyst surface, to break the proton transfer limitation of neutral oxygen electrocatalysis. An unexpected role of water molecules in improving the activity of neutral oxygen catalysis is revealed, namely, increasing the H-down configuration water in electric double layers rather than merely affecting the energy barriers for reaction limiting steps. The proposed porous nanofibers with atomically dispersed MnN3 exhibit record-breaking activity (EORR@1/2/EOER@10 mA = 0.85/1.65 V vs. RHE) and reversibility (2500 h), outperforming all previously reported neutral catalysts and rivaling conventional alkaline systems. In particular, practical ampere-scale zinc-air batteries (ZABs) stack are constructed with a capacity of 5.93 Ah and can stably operate under 1.0 A and 1.0 Ah conditions, demonstrating broad application prospects. This work provides a novel and feasible perspective for designing neutral oxygen electrocatalysts and reveals the future commercial potential in mobile power supply and large-scale energy storage.

Undernutrition affects metabolism and immune response in subcutaneous adipose tissue of pregnant ewes.

Pregnant ewes mobilize body fat to increase energy supply for fetal growth and development upon undernutrition, which disrupts the metabolic homeostasis of the body. However, the comprehensive metabolic changes in subcutaneous adipose tissue upon undernutrition are poorly understood. In this study, an undernutrition sheep model was established to investigate the effects of undernutrition on metabolic changes, immune response, and inflammation in subcutaneous fat through transcriptome, RT-qPCR, and metabolome analysis. Results showed that undernutrition changed the total transcriptional and metabolic profiles of adipose tissue. Compared to the controls, differentially expressed genes (DEGs) involved in fatty acid synthesis, triglyceride genesis, and lipid transport were downregulated in undernourished ewes, while DEGs related to fatty acid and triglyceride degradation were upregulated. Almost all lipid-related differential metabolites (DMs) were downregulated. DEGs and DMs involved in glucose metabolism and glycogen degradation were downregulated, while glycogen synthesis and carbohydrate transport were upregulated. DEGs linked to amino acid degradation were upregulated and some amino acids and derivatives were downregulated. KEGG pathway analysis showed complement and coagulation cascades were enriched significantly by DEGs, and DEGs related to coagulation, macrophage, and inflammation were upregulated while DEGs associated with the complement system were downregulated. Undernutrition during late gestation disrupted the metabolism of lipids, carbohydrates, and amino acids in adipose tissue, which weakened the complement system and immune response and may have ultimately led to inflammation.

A model of optimal digestive strategy in infrequently-feeding snakes

Abstract Organisms require energy for survival, growth, and reproduction. In a system with a finite energy supply, fluctuations in resource availability can select for plasticity in the allocation of resources between competing physiological processes. Infrequently-feeding snakes, which naturally experience extended episodes of fasting, have evolved the capacity to modulate gastrointestinal (GI) performance in response to changes in digestive load. Specifically, the gut can be downregulated during fasting to reduce metabolic maintenance costs. Some energy is, however, required to upregulate the digestive system again to allow the exploitation of captured prey. Despite significant inquiry into the relationship between sit-and-wait foraging tactics and GI plasticity, quantitative examination of the optimal digestive strategy for an infrequently-feeding snake is lacking. Here, we construct an optimisation model to quantitatively predict this strategy in terms of the length of time post-feeding after which gut downregulation occurs and the minimum prey mass required to initiate gut upregulation. Contrary to long-held assertions, our simulations predict that infrequently-feeding snakes of all sizes that practice gut downregulation benefit from consuming relatively small prey. We identify gut downregulation as an adaptive strategy when prey are small and encountered infrequently, and assert it as a critical factor in determining predator vulnerability to food scarcity. When parameterising the model, we found the distribution of potential prey body sizes to be poorly characterised in the literature. Accordingly, we identify the frequency distribution of individual body sizes within a terrestrial community as a key focus of future ecological research.

Design of Power Economic Dispatch Method Integrating Differential Evolution and PSO

As energy demand continues to grow and environmental problems become increasingly serious, optimizing the economic dispatch of the power system is crucial to ensuring the sustainability and economic benefits of energy supply. To ensure the safe operation of the power system, reduce power generation costs as much as possible, and develop a method that can adapt to the needs of different power systems, the experiment combines the differential evolution algorithm with the power economic dispatch problem and proposes a method based on improved differential evolution. Electric power economic dispatch method with particle swarm optimization algorithm. The experiment first introduces a moderate interference strategy to appropriately adjust the position of the particles; then combines the local mutation strategy to enhance the searchability of the differential evolution algorithm in the solution space and achieve good economic dispatch. The results show that when running on the F11 test set and F21 test set, when the system iterates to the 26th and 32nd times respectively, the loss function of the method constructed in the experiment begins to have a minimum value and remains stable thereafter. In addition, on the F11 test set, when the number of iterations is 150, this method has a minimum time of 0.153s. While running the loop for the first time on System 1, the total cost of this approach was only $1.01× 104. Through the actual operation of power generation equipment, under the operation of this method, the power system can ensure optimal operating power of each power generation equipment unit based on ensuring optimal cost. It can be seen from the above results that this method provides power system operators and decision-makers with a new tool to help them maximize cost-effectiveness while ensuring system stability and meeting power demand. In addition, the method's superior convergence and stability can effectively improve the solution's accuracy and speed and has strong practicality and promotion value.

Adaptive Energy Management Strategy for Sustainable xEV Charging Stations in Hybrid Microgrid Architecture

Integrating electric vehicles (EVs) into power grids presents critical energy management challenges, especially in microgrid systems powered by renewable energy sources. This study introduces a novel energy management strategy for EV charging stations utilizing an Adaptive Neuro-Fuzzy Inference System (ANFIS) controller. The system dynamically optimizes the coordination of renewable energy sources solar photovoltaic (PV) panels and wind turbines energy storage, and EV chargers. By leveraging real-time data and predictive algorithms, the ANFIS controller adapts to fluctuations in energy supply and demand, ensuring optimal performance. The innovation of this work lies in combining fuzzy logic with neural network-based learning to enhance decision-making under uncertain and variable renewable energy conditions. The proposed approach employs a robust design methodology, integrating neural network training with fuzzy logic system development, to create an adaptive and intelligent control system. Simulation results using MATLAB/Simulink demonstrate a 92% increase in energy efficiency and an 89% enhancement in load-handling capacity compared to conventional methods. The system effectively manages renewable energy variability, battery state-of-charge, and load demand, maintaining stable electrical characteristics even under dynamic wind and solar conditions. This work underscores the importance of advanced AI-driven control strategies in enabling sustainable EV charging infrastructure within microgrid environments.

Public–Private Networks for Green Innovation: Insights From an Energy Sector Supply‐Chain Partnership

ABSTRACTThis paper examines the structure, dynamics, and outcomes of an innovative, sustainable Research & Development (R&D) project within an energy supply network. Using data from the La Graciosa Project, industry experience, media sources, and interviews with key participants, the study highlights how private firms, R&D institutions, and public administrations can effectively collaborate in green innovation initiatives through public–private networks. Key findings emphasize (i) the need for alignment with external conditions, supported by trust and incentives; (ii) the importance of a shared vision to unify diverse objectives; (iii) the value of clear contracts defining stakeholder roles and the role of neutral mediators in resolving conflicts; (iv) the potential for all partners to gain from collaborative efforts, even with varying benefits; (v) the importance of innovative thinking to advance sustainability goals; and (vi) the inclusion consumer, societal and natural well‐being. These insights provide practical guidance for managers to navigate changes in energy supply chains, including shifts in traditional producer–consumer relationships.

Ketogenic diet and cancer: multidimensional exploration and research.

The ketogenic diet (KD) has attracted attention in recent years for its potential anticancer effects. KD is a dietary structure of high fat, moderate protein, and extremely low carbohydrate content. Originally introduced as a treatment for epilepsy, KD has been widely applied in weight loss programs and the management of metabolic diseases. Previous studies have shown that KD can potentially inhibit the growth and spread of cancer by limiting energy supply to tumor cells, thereby inhibiting tumor angiogenesis, reducing oxidative stress in normal cells, and affecting cancer cell signaling and other processes. Moreover, KD has been shown to influence T-cell-mediated immune responses and inflammation by modulating the gut microbiota, enhance the efficacy of standard cancer treatments, and mitigate the complications of chemotherapy. However, controversies and uncertainties remain regarding the specific mechanisms and clinical effects of KD as an adjunctive therapy for cancer. Therefore, this review summarizes the existing research and explores the intricate relationships between KD and cancer treatment.

ENHANCING VOLTAGE STABILITY AND ENERGY OUTPUT OF PLTM SALIDO IN THE PLN DISTRIBUTION NETWORK

Distributed generation (DG) integration in PLN’s extended distribution network often encounters voltage instability issues due to high voltage drops. These challenges restrict power delivery and can lead to disconnection, particularly during peak load conditions. This study investigates methods to enhance voltage stability and optimize the energy output of PLTM Salido. Using ETAP Power Station software, various operational schemes were simulated to address the problem of low terminal voltage. The study focused on the impact of reactive power injection and governor settings optimization to maintain generator performance under high demand. Results indicate that reactive power injection significantly improves terminal voltage, ensuring continuous power delivery. Adding a third generator unit further increased energy supply capacity, leveraging the full potential of available hydropower. The optimized operation of PLTM Salido with two generators increased daily energy output by 32.2%, while introducing a third generator boosted energy delivery by 107%. This research highlights the critical role of reactive power management and system configuration in enhancing the performance of small-scale hydropower plants in rural distribution networks.

U.S. Foreign Policy in the Middle East: Strategic Goals, Oil Interests, and the Promotion of Democracy

This research explores the historical and contemporary role of U.S. intervention in the Middle East, with a particular focus on oil interests, political strategies, and regional stability. The study examines key agreements like the "fifty-fifty" profit-sharing deal in Saudi Arabia and the broader implications of U.S. involvement in Gulf politics. The strategic importance of oil to U.S. national security is a central theme, illustrating how energy concerns have shaped U.S. foreign policy in the region. A significant portion of the research delves into the tension between promoting democracy and securing U.S. strategic interests, highlighting the challenges faced in balancing these often conflicting goals. Methodologically, the research utilizes both quantitative and qualitative approaches, drawing on historical documents, diplomatic records, and contemporary analyses. The findings suggest that while the U.S. has made efforts to foster democratic reforms in the region, its interventions—such as the Iraq invasion—have often resulted in instability, sectarian violence, and the resurgence of authoritarian regimes. The research argues that the U.S. has maintained a strong presence in the Middle East primarily to safeguard its economic and security interests, understanding that the region is vital to both its energy supply and broader geopolitical strategy. The conclusion underscores that U.S. involvement in the Middle East will likely continue in the future, driven by the desire to secure energy resources, maintain regional influence, and counter rivals like Iran, China, and Russia. The research suggests that while U.S. efforts to promote democracy have been largely unsuccessful, its strategic interests will remain dominant in shaping its regional policies.

Untargeted Metabolomics Reveals Key Differences Between Yak, Buffalo, and Cow Colostrum Based on UHPLC-ESI-MS/MS

Background: Colostrum, abundant in immunoglobulins and growth factors, plays a vital role in supporting immunity. Both yak and buffalo milk are characterized by their high protein and fat content. However, the metabolomic profiles of yak colostrum (YC), buffalo colostrum (BC), and bovine colostrum (CC) remain largely unexplored. The objective of this study is to identify unique metabolites that may impact the nutritional value of colostrum. Methods: This study employed ultra-high performance liquid chromatography-electrospray ionization tandem mass spectrometry (UHPLC-ESI-MS/MS) for untargeted metabolomics analysis of YC, BC, and CC. Results: The analysis revealed 97, 70, and 75 differentially expressed metabolites in the YC-CC, BC-CC, and YC-BC comparisons, respectively. In comparison to CC, both YC and BC shared common features, including reduced choline levels and elevated O-acetylcarnitine. Moreover, metabolites such as 2-hydroxy-6-pentadecylbenzoic acid, DL-glycerol-1-phosphate, thiamine, L-carnitine, methyl β-D-galactoside, and uridine diphosphate (UDP) were identified as potential biomarkers for YC, while 21-deoxycortisol, D-synephrine, uridine, mannitol-1-phosphate, nonadecanoic acid, and perillic acid were specific to BC. Conclusions: YC has greater advantages in energy supply, antioxidant activity, immune regulation, and cell homeostasis, and BC holds unique significance in physical development and energy balance regulation. These findings provide valuable insights, enabling the selection of unique bioactive metabolites to develop targeted functional foods from colostrum, catering to diverse nutritional needs.

Hybrid stochastic and robust optimization of a hybrid system with fuel cell for building electrification using an improved arithmetic optimization algorithm

This paper proposes a hybrid stochastic-robust optimization framework for sizing a photovoltaic/tidal/fuel cell (PV/TDL/FC) system to meet an annual educational building demand based on hydrogen storage via unscented transformation (UT), and information gap decision theory-based risk-averse strategy (IGDT-RA). The hybrid framework integrates the strengths of UT for scenario generation and IGDT-RA (hybrid UT-IGDT-RA) for optimizing the system robustness and maximum uncertainty radius (MRU) of building energy demand and renewable resource generation. The deterministic model focuses on minimizing the cost of energy production over the project’s lifespan (CEPLS) and considers a reliability constraint defined as the demand shortage probability (DSHP). The study utilizes an improved arithmetic optimization algorithm (IAOA) to optimize component sizes and MRUs, incorporating a neighborhood search operator to enhance performance and prevent premature convergence. The deterministic findings revealed that the PV/TDL/FC system configuration offers the lowest CEPLS and the highest reliability level (lowest DSHP) compared to the hybrid PV/FC and TDL/FC configurations. Additionally, these results indicated that enhancing the reliability of the energy supply for the educational building entails higher CEPLS, particularly due to increased costs associated with hydrogen storage. The robust framework findings for the PV/TDL/FC system using IGDT-RA show that for an uncertainty budget of 21%, the MRUs for educational building demand and renewable generation are obtained at 10.34% and 2.65%, respectively, which are higher compared to other configurations. This indicates that the hybrid PV/TDL/FC system is more robust in handling worst-case scenario uncertainties. Furthermore, the hybrid UT-IGDT-RA outcomes found that the stochastic scenarios incorporated to simulate a range of uncertainties beyond the conventional IGDT-RA based-nominal scenario, and it provides a broader range of robust solutions, enabling operators to align strategies with their risk tolerance and improves system flexibility, and decision-making precision in the face of uncertainties.

Comprehensive Analysis of Impedance Source Converters and Quasi-Z-Source Converters for Renewable Power Generation

As global attention on renewable energy continues to grow, impedance source converters (ISCs), including Z-source converters (ZSCs) and quasi-Z-source converters (QZSCs), have become focal points in research on renewable energy generation systems. These converters are valued for their adaptability to a broad range of voltage fluctuations, as well as their ability to enhance system efficiency and stability. Building upon the foundations of ZSCs and QZSCs, this paper explores and summarizes their applications in several pivotal areas of renewable energy research. These include addressing challenges such as low and fluctuating input voltages in hybrid renewable energy supply systems, their application in batteries of electric vehicles, and the implementation of high-performance buck-boost DC-DC converters. Additionally, the paper analyzes the strengths and weaknesses associated with various applications. Ultimately, the paper concludes with recommendations and future outlooks for improving the stability and efficiency of ZSCs and QZSCs in practical applications.

Mitochondrial dysfunction is a major cause of thromboinflammation and inflammatory cell death in critical illnesses.

Mitochondria generate the adenosine triphosphate (ATP) necessary for eukaryotic cells, serving as their primary energy suppliers, and contribute to host defense by producing reactive oxygen species. In many critical illnesses, including sepsis, major trauma, and heatstroke, the vicious cycle between activated coagulation and inflammation results in tissue hypoxia-induced mitochondrial dysfunction, and impaired mitochondrial function contributes to thromboinflammation and cell death. A computer-based online search was performed using the PubMed and Web of Science databases for published articles concerning sepsis, trauma, critical illnesses, cell death, mitochondria, inflammation, coagulopathy, and organ dysfunction. Mitochondrial outer membrane permeabilization triggers apoptosis by releasing cytochrome c and activating caspases. Apoptosis is a non-inflammatory programmed cell death but requires sufficient ATP supply. Therefore, conversion to inflammatory necrosis may occur due to a lack of ATP in critical illness. Severely damaged mitochondria release excess reactive oxygen species and injurious mitochondrial DNA, inducing cell death. Besides non-programmed necrosis, mitochondrial damage can trigger programmed inflammatory cell death, including necroptosis, pyroptosis, and ferroptosis. Additionally, a unique form of DNA-ejecting cell death, known as etosis, occurs in monocytes and granulocytes following external stimuli and mitochondrial damage. The type of cell death chosen remains uncertain but is known to depend on the cell type, the nature of the injury, and the degree of damage. Mitochondria damage is the major contributor to the cell death mechanism that leads to organ damage in critical illnesses. Regulating and restoring mitochondrial function holds promise for developing new therapeutic approaches for mitigating critical diseases.

Prediction of microbial crude protein flow from the rumen of dairy cattle by means of dietary characteristics – a meta-analysis

ABSTRACT Protein supply to ruminants relies mainly on the flow of microbial crude protein (MCP) from the rumen, which is commonly assumed to primarily depend on energy supply. This study evaluated this assumption with recent data and tested if ruminally fermented organic matter (FOM) was a better predictor of MCP flow than total-tract digestible organic matter (DOM) and if more variables could improve the prediction of MCP flow. A previously published data set was extended by additional studies resulting in a data set of 139 studies including 407 treatment means, typical to Central European rations. Either DOM or FOM had to be reported and estimates of MCP were all based on gastrointestinal measurements. Dietary treatments were restricted to a maximum concentrate proportion of 0.6 and a CP concentration from 10% to 20% of dietary dry matter (DM). Treatments with more than 1% of animal by-products were excluded. Mixed models with “study” as random effect were used to test the ratios between MCP and DOM or FOM. Dietary characteristics including DM intake, OM digestibility (OMD), OM fermentability (OMF), and ruminal N balance and dietary concentrations of CP, rumen-degraded CP (RDP), rumen-undegraded CP (RUP), neutral detergent fibre, starch, and ether extract were evaluated as additional variables to improve prediction accuracy. Regression of MCP flow against DOM (n = 324) or FOM (n = 349) revealed estimates of 139 g ± 36 g and 164 g ± 40 g of MCP for each kg of DOM or FOM, respectively. The best-fitting mixed model estimating MCP/DOM [g/kg] was 312–2.75 · OMD − 0.229 · RUP + 0.290 · RDP whereas MCP/FOM [g/kg] may be calculated as 294–2.80 · OMF + 0.401 · RDP, with OMD and OMF in [%] and RDP and RUP in [g/kg DM]. Microbial CP flow [g/d] was most accurately described as 1896 + 110 · DOM − 23.7 · OMD − 0.164 · RUP + 0.153 · RDP, with DOM in [kg], OMD in [%] and RDP and RUP in [g/d]. Predictions based on DOM were at least as precise as FOM-based predictions and comparison with published models revealed that the presented models were of similar accuracy as the ones from literature.

Lipid metabolism and microbial regulation analyses provide insights into the energy-saving strategies of hibernating snakes

Hibernation is a necessary means for animals to maintain survival while coping with low temperatures and food shortages. While most studies have largely focused on mammalian hibernation, its reptilian equivalent has been less studied. In order to provide insights into the energy metabolism and potential microbial regulatory mechanisms in hibernating snakes, the serum, liver, gut content samples were measured by multi-omic methods. Here we show the active snakes have more vigorous lipid metabolism, whereas snakes in hibernation groups have higher sphingolipid metabolism. Furthermore, the results indicate that the potential energy supply pathway was gluconeogenesis. Microbial analysis reveals that Proteobacteria and Firmicutes showed dynamic changes with the transformation among active, pre-hibernation and hibernation periods. The correlation analysis reveals the potential role of Romboutsia, Providencia and Vagococcus in regulating above metabolism by producing certain metabolites. The results advance the understanding of the complex energy-saving strategy in hibernating poikilotherms.

Damp‐Heat–Induced Degradation of Lightweight Silicon Heterojunction Solar Modules With Different Transparent Conductive Oxide Layers

ABSTRACTLightweight photovoltaic applications are essential for diversifying the solar energy supply. This opens up vast new scenarios for solar modules and significantly boosts the capacity of renewable energy. To ensure high efficiency and stability of the solar modules, several challenges need to be overcome. Degradation due to elevated temperature and/or humidity is a critical concern for silicon heterojunction (SHJ) solar modules. Here, we investigated the stability and degradation mechanism of encapsulated cells with lightweight configurations where the cells are based on three different types of transparent‐conductive oxide (TCO): indium tin oxide (ITO), aluminum‐doped zinc oxide (AZO), and a combination of ITO/AZO/ITO under humid and thermal environmental conditions. A damp heat (DH) test at a temperature of 85°C and relative humidity (RH) of 85% was performed on lightweight modules for 1000 h. Our results show that AZO is the most susceptible to DH degradation. The AZO film was damaged by the combined effects of moisture ingress and delamination of the interconnection foil, resulting in a decrease in the conductivity of the AZO film, leading to a dramatic increase in Rs and a decrease in FF of the modules. Consequently, moisture has a greater chance of percolating through the damaged AZO layer into the a‐Si:H passivation layer, causing passivation degradation, which leads to an increase in recombination, resulting in a decrease in Voc of the modules. In particular, after capping the AZO film with an ITO film, the efficiency loss of the ITO/AZO/ITO module was significantly reduced. This suggests that the ITO film could be a promising protective capping layer for the AZO‐based solar cells.

Learning Coupled Meteorological Characteristics Aids Short-Term Photovoltaic Interval Prediction Methods

In response to the challenges posed by renewable energy integration, this study introduces a hybrid Attention-TCN-LSTM model for short-term photovoltaic (PV) power forecasting. The LSTM captures the sequence characteristics of PV output, which are then combined with the meteorological sequence features extracted by the Attention-TCN module. The model leverages the strengths of the TCN, the LSTM, and the self-attention mechanism to enhance prediction accuracy and construct reliable prediction intervals. Aiming to optimize both performance and efficiency, the PSO algorithm is used for hyperparameter optimization. Ablation studies and comparisons with other models confirm the effectiveness, accuracy and robustness of the proposed model. This hybrid approach contributes to improved renewable energy integration, offering a more stable and reliable energy supply. Future work will focus on incorporating intelligent systems for autonomous risk management and real-time control of dynamic PV output fluctuations.

Synchronous Interference of Dual Metabolic Pathways Mediated by H2S Gas/GOx for Augmenting Tumor Microwave Thermal Therapy.

Sublethal tumor cells have an urgent need for energy, making it common for them to switch metabolic phenotypes between glycolysis and oxidative phosphorylation (OXPHOS) for compensatory energy supply; thus, the synchronous interference of dual metabolic pathways for limiting energy level is essential in inhibiting sublethal tumor growth. Herein, a multifunctional nanoplatform of Co-MOF-loaded anethole trithione (ADT) and myristyl alcohol (MA), modified with GOx and hyaluronic acid (HA) was developed, namely, CAMGH. It could synchronously interfere with dual metabolic pathways including glycolysis and OXPHOS to restrict the adenosine triphosphate (ATP) supply, achieving the inhibition to sublethal tumors after microwave (MW) thermal therapy. Under low-power MW irradiation, CAMGH induced certain tumor thermal damage while ensuring the safety of the surrounding normal tissues. The loaded GOx consumed glucose in tumors, undoubtedly blocking the main energy supply pathway, the glycolytic pathway. Then, H2O2 generated from GOx reacted with Co2+ to produce cytotoxic ·OH, combining with the released H2S from ADT to co-obstruct OXPHOS and then synergy with the above glycolysis blocking for a more effective ATP inhibition. The powerful depletion of ATP caused significant suppression of damage resistance protein upregulated after thermal stimulation, i.e., HSP90, and then the activation of caspase-3, achieving the simultaneous reversal of heat resistance and apoptosis resistance. Altogether, the CAMGH-based synchronous interference of dual metabolic pathways shows the potential to break down tumor self-repair, presenting an alternative strategy to enhance the therapeutic effect of tumor MW thermal therapy.

Changing Energy Suppliers of Residential Consumers: The Case of Poland

During the Russian-Ukrainian conflict, energy prices are rising. Such a situation would suggest high customer turnover, especially since the environment has a strong influence on population behaviour at the individual level. The purpose of this paper is to model the barriers and preferences of individual customers in switching energy suppliers according to the level of satisfaction in a dynamically changing environment. We statistically designed the study using Eta index calculations, test: KruskalWallis, post hoc Dunn’s test with Bonferroni correction. Two models were obtained: barriers and preferences for changing energy retailers among residential customers, depending on the level of satisfaction in a dynamically changing environment. We demonstrated the relationship between barriers to switching energy vendors and customer satisfaction levels. We investigated whether the level of satisfaction influences energy seller switching preferences among customers. We demonstrated the relationship between barriers to switching energy vendors and individual customer preferences and satisfaction levels