Search Results (2,415)

Sustainable Development Reserves are organized units in the Amazon that are essential for the proper use and sustainable management of the region’s natural resources and for the livelihoods and economy of the local communities. This study aims to provide a climatic characterization of the Madeira River Sustainable Development Reserve (MSDR), offering scientific support to efforts to assess the feasibility of implementing adaptation measures to increase the resilience of isolated Amazon communities in the face of extreme climate events. Significant statistical analyses based on time series of observational and reanalysis climate data were employed to obtain a detailed diagnosis of local climate variability. The results show that monthly mean two-meter temperatures vary from 26.5 °C in February, the coolest month, to 28 °C in August, the warmest month. Monthly precipitation averages approximately 250 mm during the rainy season, from December until May. July and August are the driest months, August and September are the warmest months, and September and October are the months with the lowest river level. Cold spells were identified in July, and warm spells were identified between July and September, making this period critical for public health. Heavy precipitation events detected by the R80, Rx1day, and Rx5days indices show an increasing trend in frequency and intensity in recent years. The analyses indicated that the MSDR has no potential for wind-energy generation; however, photovoltaic energy production is viable throughout the year. Regarding the two major commercial crops and their resilience to thermal stress, the region presents suitable conditions for açaí palm cultivation, but Brazil nut production may be adversely affected by extreme drought and heat events. The results of this study may support research on adaptation strategies that includethe preservation of local traditions and natural resources to ensure sustainable development. Full article

Building-integrated photovoltaic (BIPV) windows present a viable path towards carbon neutrality in the building sector. However, conventional BIPV windows, such as semi-transparent photovoltaic (STPV) glazings, still suffer from inadequate thermal insulation, which limits their effectiveness across different climate conditions. To address this issue, the cadmium telluride-based vacuum PV glazing has been developed to enhance the thermal performance of BIPV applications. To fully understand the complex thermal behaviour under real-world operational scenarios, this study introduces a one-dimensional transient heat transfer model that can efficiently capture the time-dependent thermal dynamics of this novel glazing system. Based on the numerical solutions using the explicit finite difference method (FDM), the temperature profile of the vacuum PV glazing can be obtained dynamically. Consequently, the heat gain of the semi-transparent vacuum PV glazing can be calculated under time-varying outdoor and indoor conditions. The validated heat transfer model was applied under four different scenarios, viz. summer daytime, summer nighttime, winter daytime, and winter nighttime, to provide a detailed analysis of the dynamic thermal behaviour, including the temperature variation and the energy flow. The dynamic thermal characteristics of the vacuum PV glazing calculated by the transient heat transfer model demonstrate its excellent thermal insulation and solar control capabilities. Moreover, the thermal performance of vacuum PV glazing was compared with a standard double-pane window under various weather conditions of a typical summer day and a typical winter day. The results indicate that the vacuum PV glazing can effectively minimise both heat gain and heat loss. The fluctuation of the inner surface temperature can be controlled within a limited range away from the set point of the indoor room temperature. Therefore, the vacuum PV glazing contributes to stabilising the temperature of the indoor environment despite the fluctuating solar radiation and periodic outdoor temperature. It is suggested that the vacuum PV glazing has the potential to enhance the climate adaptability of BIPV windows under different climate backgrounds. Full article

Common ragweed (Ambrosia artemisiifolia L.) has been identified as one of the most harmful invasive weed species in Europe due to its allergenic pollen and competitive growth in diverse habitats. In the first part of this review [Common Ragweed—Ambrosia artemisiifolia L.: A Review with Special Regards to the Latest Results in Biology and Ecology], its biological characteristics and ecological behavior were described in detail. In the current paper, control strategies are summarized, focusing on integrated weed management adapted to the specific habitat where the species causes damage—arable land, semi-natural vegetation, urban areas, or along linear infrastructures. A range of management methods is reviewed, including agrotechnical, mechanical, physical, thermal, biological, and chemical approaches. Particular attention is given to the spread of herbicide resistance and the need for diversified, habitat-specific interventions. Among biological control options, the potential of Ophraella communa LeSage, a leaf beetle native to North America, is highlighted. Furthermore, innovative technologies such as UAV-assisted weed mapping, site-specific herbicide application, and autonomous weeding robots are discussed as environmentally sustainable tools. The role of legal regulations and pollen monitoring networks—particularly those implemented in Hungary—is also emphasized. By combining traditional and advanced methods within a coordinated framework, effective and ecologically sound ragweed control can be achieved. Full article

Accurate gene expression quantification using reverse transcription quantitative PCR (RT-qPCR) requires stable reference genes (RGs) for reliable normalization. However, few studies have systematically identified RGs suitable for simultaneous high salt, alkaline, and high-temperature conditions. This study addresses this gap by evaluating the stability of eight candidate RGs in the anaerobic halophilic alkalithermophile Natranaerobius thermophilus JW/NM-WN-LF^T under combined salt, alkali, and thermal stresses. The stability of these candidate RGs was assessed using five statistical algorithms: Delta CT, geNorm, NormFinder, BestKeeper, and RefFinder. Results indicated that recA exhibited the highest expression stability across all tested conditions and proved adequate as a single RG for normalization in both RT-qPCR and droplet digital PCR (ddPCR) assays. Furthermore, recA alone or combined with other RGs (sigA, rsmH) effectively normalized the expression of seven stress-response genes (proX, opuAC, mnhE, nhaC, trkH, ducA, and pimT). This work represents the first systematic validation of RGs under polyextreme stress conditions, providing essential guidelines for future gene expression studies in extreme environments and aiding research on microbial adaptation mechanisms in halophilic, alkaliphilic, and thermophilic microorganisms. Full article

Given the rising importance of cost-effective solutions in battery research, this study employs an accessible testing approach using low-cost, sensor-equipped platforms that enable broader research and educational applications. It presents a comparative evaluation of lithium-ion battery degradation under two charging strategies: static charging (constant current at 1.2 A) and dynamic charging (stepped current from 400 mA to 800 mA) over 200 charge–discharge cycles. A custom-built, low-cost test platform based on an ESP32 microcontroller was developed to provide real-time monitoring of voltage, current, temperature, and internal resistance, with automated control and cloud-based data logging. The results indicate that static charging provides greater voltage stability and a lower increase in internal resistance (9.3%) compared to dynamic charging (30.17%), suggesting reduced electrochemical stress. Discharge time decreased for both strategies, by 6.25% under static charging and 18.46% under dynamic charging, highlighting capacity fade and aging effects. Internal resistance emerged as a reliable indicator of degradation, closely correlating with reduced runtime. These findings underscore the importance of selecting charging profiles based on specific application needs, as dynamic charging, while offering potential thermal benefits, may accelerate battery aging. Furthermore, the low-cost testing platform proved effective for long-term evaluation and degradation analysis, offering an accessible alternative to commercial battery cyclers. The insights gained contribute to the development of adaptive battery management systems that optimize performance, lifespan, and safety in electric vehicle applications. Full article

The efficiency of solar water heating systems is strongly influenced by variable weather conditions, making the optimization of control strategies essential for maximizing energy performance. This study presents the development and evaluation of a rule-based adaptive control strategy that dynamically selects one of three predefined control modes—ON–OFF, proportional, or indirect proportional control (IPC)—based on real-time weather classification. The classification algorithm assigns each day to one of four solar irradiance categories, enabling the controller to respond appropriately to current environmental conditions. The proposed adaptive controller was implemented and tested under real operating conditions and compared with a conventional commercial solar controller. Over a 40-day testing period, the adaptive system achieved a 12.7% increase in thermal energy storage efficiency. Specifically, despite receiving 4.8% less solar radiation (719 kWh vs. 755 kWh), the adaptive controller stored 453 kWh of heat in the water tank compared to 416 kWh with the traditional system. This corresponds to an efficiency improvement from 0.55 to 0.63. These results demonstrate the adaptive controller’s superior ability to utilize available solar energy across all weather scenarios. The findings confirm that intelligent control strategies not only enhance technical performance but also improve the economic and environmental value of solar thermal systems. Full article

To address the limitations of single-layer nitride coatings, such as poor load adaptability and low long-term durability, MoN/TiN multilayer coatings were prepared via high-power impulse magnetron sputtering (HiPIMS). HiPIMS produces highly ionized plasmas that enable intense ion bombardment, yielding nitride films with enhanced mechanical strength, durability, and thermal stability versus conventional methods. The multilayer coating demonstrated a low coefficient of friction (COF, ~0.4) and wear rate (1.31 × 10⁻⁷ mm³/[N·m]). In contrast, both TiN and MoN coatings failed at 5 N and 10 N loads, respectively. Under increasing loads, the multilayer coating maintained stable wear rates (1.84–3.06 × 10⁻⁷ mm³/[N·m]) below 20 N, and ultimately failed at 25 N. Furthermore, the MoN layer contributes to COF reduction. Grazing-incidence X-ray diffraction analysis confirmed the enhanced crystallographic stability of the multilayer coating, thereby revealing a dominant (111) orientation. The multilayer architecture suppresses crack propagation while effectively balancing hardness and toughness, offering a promising design for extreme-load applications. Full article

Cold environments challenge the structural and functional integrity of membrane proteins, requiring specialized adaptations to maintain activity under low thermal energy. Here, we investigate the molecular basis of cold tolerance in the peptide transporter PepT1 from the Antarctic icefish (Chionodraco hamatus, ChPepT1) using molecular dynamics simulations, binding free energy calculations (MM/GBSA), and dynamic network analysis. We compare ChPepT1 to its human ortholog (hPepT1), a non-cold-adapted variant, to reveal key features enabling psychrophilic function. Our simulations show that ChPepT1 displays enhanced global flexibility, particularly in domains adjacent to the substrate-binding site and the C-terminal domain (CTD). While hPepT1 loses substrate binding affinity as temperature increases, ChPepT1 maintains stable peptide interactions across a broad thermal range. This thermodynamic buffering results from temperature-sensitive rearrangement of hydrogen bond networks and more dynamic lipid interactions. Importantly, we identify a temperature-responsive segment (TRS, residues 660–670) within the proximal CTD that undergoes an α-helix to coil transition, modulating long-range coupling with transmembrane helices. Dynamic cross-correlation analyses further suggest that ChPepT1, unlike hPepT1, reorganizes its interdomain communication in response to temperature shifts. Our findings suggest that cold tolerance in ChPepT1 arises from a combination of structural flexibility, resilient substrate binding, and temperature-sensitive interdomain dynamics. These results provide new mechanistic insight into thermal adaptation in membrane transporters and offer a framework for engineering proteins with enhanced functionality in extreme environments. Full article

Lost circulation is a major challenge in oil and gas drilling operations, severely restricting drilling efficiency and compromising operational safety. Conventional bridging and plugging materials rely on precise particle-to-fracture size matching, resulting in low success rates. Self-healing gels penetrate loss zones as discrete particles that progressively swell, accumulate, and self-repair in integrated gel masses to effectively seal fracture networks. Self-healing gels effectively overcome the shortcomings of traditional bridging agents including poor adaptability to fractures, uncontrollable gel formation of conventional downhole crosslinking gels, and the low strength of conventional pre-crosslinked gels. This work employs stearyl methacrylate (SMA) as a hydrophobic monomer, acrylamide (AM) and acrylic acid (AA) as hydrophilic monomers, and graphene oxide (GO) as an inorganic dopant to develop a GO-based self-healing organic–inorganic hybrid plugging material (SG gel). The results demonstrate that the incorporation of GO significantly enhances the material’s mechanical and rheological properties, with the SG-1.5 gel exhibiting a rheological strength of 3750 Pa and a tensile fracture stress of 27.1 kPa. GO enhances the crosslinking density of the gel network through physical crosslinking interactions, thereby improving thermal stability and reducing the swelling ratio of the gel. Under conditions of 120 °C and 6 MPa, SG-1.5 gel demonstrated a fluid loss volume of only 34.6 mL in 60–80-mesh sand bed tests. This gel achieves self-healing within fractures through dynamic hydrophobic associations and GO-enabled physical crosslinking interactions, forming a compact plugging layer. It provides an efficient solution for lost circulation control in drilling fluids. Full article

As the demand for energy-efficient homes continues to rise, the importance of advanced mechanical ventilation systems in maintaining indoor air quality (IAQ) has become increasingly evident. However, challenges related to energy balance, IAQ, and occupant thermal comfort persist. This review examines the performance of mechanical ventilation systems in regulating indoor climate, improving air quality, and minimising energy consumption. The findings indicate that demand-controlled ventilation (DCV) can enhance energy efficiency by up to 88% while maintaining CO₂ concentrations below 1000 ppm during 76% of the occupancy period. Heat recovery systems achieve efficiencies of nearly 90%, leading to a reduction in heating energy consumption by approximately 19%. Studies also show that employing mechanical rather than natural ventilation in schools lowers CO₂ levels by 20–30%. Nevertheless, occupant misuse or poorly designed systems can result in CO₂ concentrations exceeding 1600 ppm in residential environments. Hybrid ventilation systems have demonstrated improved thermal comfort, with predicted mean vote (PMV) values ranging from –0.41 to 0.37 when radiant heating is utilized. Despite ongoing technological advancements, issues such as system durability, user acceptance, and adaptability across climate zones remain. Smart, personalized ventilation strategies supported by modern control algorithms and continuous monitoring are essential for the development of resilient and health-promoting buildings. Future research should prioritize the integration of renewable energy sources and adaptive ventilation controls to further optimise system performance. Full article

The Life Cycle Cost Assessment (LCCA) methodology is widely used to determine the optimal thickness of thermal insulation for walls and roofs. The results depend on several factors, such as the degree day calculations method, the ambient or sol–air temperature, base temperature variations, and the heat capacity of the thermal envelope elements. This study aims to analyze the impact of solar radiation on mass walls with different orientations in five cities in northern Chile, which have severe solar climates. The goal is to determine the optimal thickness of expanded polystyrene insulation using the LCCA method, considering solar radiation, a varying base temperature, and validating results by analyzing the energy demand for heating and cooling of a typical house. The findings show that excluding solar radiation in the LCCA methodology can lead to an underestimation of the optimal insulation thickness by 21–39% for walls in northern Chile. It was also found that using variable monthly threshold temperatures for heating and cooling based on the adaptive thermal comfort model results in a slight underestimation (1–3%) of the optimal thickness compared to a constant annual temperature. An energy simulation of a typical house in five cities in northern Chile showed that neglecting the effect of solar radiation when determining the thermal insulation thickness for the studied wall can lead to a minor increase in heating and cooling energy demand, ranging from approximately 1% to 9%. However, this study emphasizes the importance of applying optimal insulation thickness for cities with more continental climates like Santiago and Calama, where the heating demand is higher than cooling. Full article

The construction industry is one of the main areas of energy consumption and carbon emissions, and strengthening research on the thermal performance of building facades can effectively promote energy conservation and emission reduction. Compared with traditional static enclosure structures, dynamic skin can adapt its functions, characteristics, and methods based on constantly changing environmental conditions and performance requirements. It has great potential in adapting to the environment, reducing energy consumption, adjusting shading and natural ventilation, and improving human thermal and visual comfort. To comprehensively understand the key technologies of dynamic skin energy-saving design, previous research results were comprehensively compiled from relevant databases. The research results indicate that various types of dynamic skins, intelligent materials, multi-layer facades, dynamic shading, and biomimetic facades are commonly used core technologies for dynamic facades. Parametric modeling, computer simulation, and multi-objective algorithms are commonly used to optimize the performance of dynamic skin. In addition, integrated technology design, interaction design, and lifecycle design should be effective methods for improving dynamic skin energy efficiency, resident satisfaction, and economic benefits. Despite current challenges, dynamic skin energy-saving technology remains one of the most effective solutions for future sustainable building design. Full article

Global warming raises surface water temperatures, impacting fish alongside pollutants, such as ubiquitous xenoestrogens. Combined stressor effects are poorly studied but likely to worsen impacts and hinder biota adaptation, warranting further research. Unadapted fish face heightened risks. The liver is a vital metabolic organ, sensitive to temperature and xenoestrogens, eventually adjusting hepatocyte size and number to ensure survival, growth, and reproduction. This study assessed, for the first time, the impact of exposure (45 days) to thermal stress (29 °C versus 26 °C) and ethinylestradiol (EE2, 5 ng/L) on male guppies, primarily on body and quantitative liver morphology. Higher temperature reduced body mass (14%) and standard length (3.6%) gain. EE2 exposure reduced body mass increase (14%), hepatosomatic index (20%), and the volumes of the liver (32%), hepatocytes (16%), and their nuclei (17%). The nucleus-to-cytoplasm ratio and total hepatocyte number remained stable. No histopathological lesions existed. Guppies appear to have adapted to stressors by reducing hepatocyte size and utilizing lipid reserves, yet they exhibited deficits in body growth and hepatosomatic index. Gonadal maturation was unaffected. Only under EE2 at 29 °C did hepatocytes show minimal lipid droplet content (less vacuolation). This indicated exhausted reserves, reinforcing how heat and toxicants interact to exacerbate impacts. Full article

Temperature is one of the critical factors influencing the survival, growth, and reproduction of organisms. The molting and developmental mechanisms of crustaceans are highly sensitive to temperature, yet the regulatory mechanisms underlying their thermal adaptation remain unclear. In this work, transcriptome sequencing was performed to analyze the gene expression profiles of Eriocheir sinensis under normal temperature (22 °C) and high-temperature (27 °C and 32 °C) conditions. A total of 377 differentially expressed genes (DEGs) were identified, including 149 up-regulated and 227 down-regulated genes. Through Gene Ontology (GO) enrichment analysis of these DEGs, 11 significantly temperature-regulated signaling pathways were identified, including the estrogen and androgen receptor signaling pathways, and two neurotransmission signaling pathways. These findings suggest that temperature may influence sex regulation in E. sinensis, while the dopamine receptor and neuropeptide signaling pathways may play a role in its thermal adaptation. Further validation via RT-qPCR of DEGs involved in neurotransmission signaling pathways revealed that crustacean hyperglycemic hormone (CHH) and excitatory amino acid transporter 3 (EAA3) genes are likely involved in the thermal adaptation of E. sinensis. In addition, the hemolymph glucose levels associated with the elevated temperatures were detected and consistent variations between glucose levels and CHH expressions were found. This indicates that the eyestalk CHH is strongly correlated with the hemolymph glucose levels and likely mediates the response to temperature changes by regulating blood glucose in E. sinensis. The results of this study not only provide key molecular targets for elucidating the mechanisms by which temperature affects molting and development in E. sinensis, but also establish a theoretical foundation for further research into thermal adaptation strategies in crustaceans. Full article

This study presents a hybrid adaptive control strategy that integrates genetic algorithm (GA) optimization with an adaptive neuro-fuzzy inference system (ANFIS) for precise thermal regulation of single-photon avalanche diodes (SPADs). To address the nonlinear and disturbance-sensitive dynamics of SPAD systems, a performance-oriented dataset is constructed through multi-scenario simulations using settling time, overshoot, and steady-state error as fitness metrics. The genetic algorithm (GA) facilitates broad exploration of the proportional–integral–derivative (PID) controller parameter space while ensuring control stability by discarding low-performing gain combinations. The resulting high-quality dataset is used to train the ANFIS model, enabling real-time, adaptive tuning of PID gains. Simulation results demonstrate that the proposed GA-ANFIS-PID controller significantly enhances dynamic response, robustness, and adaptability over both the conventional Ziegler–Nichols PID and GA-only PID schemes. The controller maintains stability under structural perturbations and abrupt thermal disturbances without the need for offline retuning, owing to the real-time inference capabilities of the ANFIS model. By combining global evolutionary optimization with intelligent online adaptation, this approach improves both accuracy and generalization, offering a practical and scalable solution for SPAD thermal management in demanding environments such as quantum communication, sensing, and single-photon detection platforms. Full article