Search Results (18,935)

Environmental protection has become one of the key challenges of our time. This has led to an increase in pro-environmental activities in the field of cosmetics and household chemicals, where manufacturers are increasingly trying to meet the expectations of consumers who are aware of the potential risks associated with the production of cosmetics and household chemistry products. This is one of the most important challenges of today’s industry, given that some of the raw materials still commonly used, such as surfactants, may be toxic to aquatic organisms. Many companies are choosing to use natural raw materials that have satisfactory performance properties but are also environmentally friendly. In addition, modern products are also characterized by reduced consumption of water, resources, and energy in production processes. These measures reduce the carbon footprint and reduce the amount of plastic packaging required. In the present study, seven formulations of environmentally friendly car shampoo concentrates were developed, based entirely on mixtures of bio-based surfactants. The developed formulations were tested for application on the car body surface, allowing the selection of the two best products. For these selected formulations, an in-depth physicochemical analysis was carried out, including pH, density, and viscosity measurements. Comparison of the results with commercial products available on the market was also performed. Additionally, using the multiple light scattering method, the foamability and foam stability were determined for the car shampoos developed. The results obtained indicate the very high application potential of the products under study, which combine high performance and environmental concerns. Full article

Trachypteris picta (Pallas, 1773) is a significant pest that can cause serious damage to poplars and willows. To assess the impact of climate change on the suitable habitats of T. picta, this study conducted a comparative analysis of its global suitable habitats using climatic factors, global land use type, and global vegetation from different periods, in combination with the maximum entropy (MaxEnt) model. The results indicate that the annual mean temperature (Bio01), mean temperature of the coldest quarter (Bio11), precipitation of the coldest quarter (Bio19), and isothermality (Bio03) are the four most important climate variables determining the distribution of T. picta. Under the current climate conditions, the highly suitable areas are primarily located in southern Europe, covering an area of 2.22 × 10⁶ km². Under future climate scenarios, the suitable habitat for T. picta is expected to expand and shift towards higher latitudes. In the 2050s, the SSP5-8.5 scenario has the largest suitable area compared to other scenarios, while the SSP2-4.5 scenario has the largest suitable area in the 2090s. In addition, the centroids of the total suitable areas are expected to shift toward higher latitudes under future climate conditions. The results of this study provide valuable data for the monitoring, control, and management of this pest. Full article

Recent advancements have been made in the precise prediction of protein structures within the Protein Folding Problem (PFP), particularly in relation to minimizing the energy function to achieve stable and biologically relevant protein structures. This problem is classified as NP-hard within computational theory, necessitating the development of various techniques and algorithms. Bio-inspired algorithms have proven effective in addressing NP-hard challenges in practical applications. This study introduces a novel hybrid algorithm, termed GRSABio, which integrates the strategies of Jumping Spider Algorithm (JSOA) with the Golden Ratio Simulated Annealing (GRSA) for peptide prediction. Furthermore, the GRSABio algorithm incorporates a Convolutional Neural Network for fragment prediction (FCNN), forms an enhanced methodology called GRSABio-FCNN. This integrated framework achieves improved structure refinement based on energy for protein prediction. The proposed enhanced GRSABio-FCNN approach was applied to a dataset of 60 peptides. The Wilcoxon and Friedman statistics test were employed to compare the GRSABio-FCNN results against recent state-of-the-art-approaches. The results of these tests indicate that the GRSABio-FCNN approach is competitive with state-of-the-art methods for peptides up to 50 amino acids in length and surpasses leading PFP algorithms for peptides with up to 30 amino acids. Full article

Titanium alloys such as Ti-6Al-4V are widely used in biomedical implants due to their excellent mechanical properties and biocompatibility, but their bioinert nature limits osseointegration and antibacterial performance. This study proposes a multifunctional surface coating system integrating a thermally oxidized TiO₂ interlayer with a hydroxyapatite (HAp) top layer synthesized via a green route using Hylocereus undatus extract. The HAp was deposited by electrophoretic deposition (EPD), enabling continuous coverage and strong adhesion to the pre-treated Ti-6Al-4V substrate. Structural, morphological, chemical, and electrical characterizations were performed using XRD, SEM, EDS, Raman spectroscopy, and impedance spectroscopy. Bioactivity was assessed through apatite formation in simulated body fluid (SBF), while antibacterial properties were evaluated against Staphylococcus aureus. The results demonstrated successful formation of crystalline TiO₂ (rutile phase) and calcium-rich HAp with good surface coverage. The HAp-coated surfaces exhibited significantly enhanced bioactivity and strong antibacterial performance, likely due to the combined effects of surface roughness and the bioactive compounds present in the plant extract. This study highlights the potential of eco-friendly, bio-inspired surface engineering to improve the biological performance of titanium-based implants. Full article

Catalytic upgrading of pyrolysis oils is an important step for producing replacement hydrocarbon-rich liquid biofuels from biomass and can help to advance pyrolysis technology. Catalysts play a pivotal role in influencing the selectivity of chemical reactions leading to the formation of main compounds in the final upgraded liquid products. The present work involved a systematic study of solvent-free catalytic reactions of cyclohexanone in the presence of hydrogen gas at 160 °C for 3 h in a batch reactor. Cyclohexanone can be produced from biomass through the selective hydrogenation of lignin-derived phenolics. Three types of catalysts comprising undoped NbOPO₄, 10 wt% NiO/NbOPO₄, and 30 wt% NiO/NbOPO₄ were studied. Undoped NbOPO₄ promoted both aldol condensation and the dehydration of cyclohexanol, producing fused ring aromatic hydrocarbons and hard char. With 30 wt% NiO/NbOPO₄, extensive competitive hydrogenation of cyclohexanone to cyclohexanol was observed, along with the formation of C₆ cyclic hydrocarbons. When compared to NbOPO₄ and 30 wt% NiO/NbOPO₄, the use of 10 wt% NiO/NbOPO₄ produced superior selectivity towards bi-cycloalkanones (i.e., C₁₂) at cyclohexanone conversion of 66.8 ± 1.82%. Overall, the 10 wt% NiO/NbOPO₄ catalyst exhibited the best performance towards the production of precursor compounds that can be further hydrodeoxygenated into energy-dense aviation fuel hydrocarbons. Hence, the presence and loading of NiO was able to tune the activity and selectivity of NbOPO₄, thereby influencing the final products obtained from the same cyclohexanone feedstock. This study underscores the potential of lignin-derived pyrolysis oils as important renewable feedstocks for producing replacement hydrocarbon solvents or feedstocks and high-density sustainable liquid hydrocarbon fuels via sequential and selective catalytic upgrading. Full article

The incorporation of phase change material (PCM) can enhance wall thermal performance and indoor thermal comfort, but practical applications still face challenges related to high costs and potential leakage issues. In this study, a novel dual-biomass-based shape-stabilized PCM (Bio-SSPCM) was proposed, wherein waste cooking fat and waste reed straw were, respectively, incorporated as the PCM substance and supporting material. The waste fat (lard) consisted of both saturated and unsaturated fatty acid glycerides, exhibiting a melting point about 21.2–41.1 °C and a melting enthalpy value of 40 J/g. Reed straw was carbonized to form a sustainable porous biochar supporting matrix, which was used for the vacuum adsorption of waste fat. The results demonstrate that the as-prepared dual-Bio-SSPCM exhibited excellent thermal performance, characterized by a latent heat capacity of 25.4 J/g. With the addition of 4 wt% of expanded graphite (EG), the thermal conductivity of the composite PCM reached 1.132 W/(m·K), which was 5.4 times higher than that of the primary lard. The thermal properties of the Bio-SSPCM were characterized using an analog T-history method. The results demonstrated that the dual-Bio-SSPCM exhibited exceptional and rapid heat storage and exothermic capabilities. The dual-Bio-SSPCM, prepared from waste cooking fat and reed straw, can be considered as environmentally friendly construction material for energy storage in line with the principles of the circular economy. Full article

Vegetation dynamics are complexly influenced by multiple factors such as climate, human activities, and topography. In recent years, the frequency, intensity, and diversity of human activities have increased, placing substantial pressure on the growth of vegetation. Arid and semi-arid regions are particularly sensitive to climate change, and climate change and large-scale ecological restoration have led to significant changes in the dynamic of dryland vegetation. However, few studies have explored the nonlinear relationships between these factors and vegetation dynamic. In this study, we integrated trend analysis (using the Mann–Kendall test and Theil–Sen estimation) and machine learning algorithms (XGBoost-SHAP model) based on long time-series remote sensing data from 2001 to 2020 to quantify the nonlinear response patterns and threshold effects of bioclimatic variables, topographic features, soil attributes, and anthropogenic factors on vegetation dynamic. The results revealed the following key findings: (1) The kNDVI in the study area showed an overall significant increasing trend (p < 0.01) during the observation period, of which 26.7% of the area showed a significant increase. (2) The water content index (Bio 23, 19.6%), the change in land use (15.2%), multi-year average precipitation (pre, 15.0%), population density (13.2%), and rainfall seasonality (Bio 15, 10.9%) were the key factors driving the dynamic change of vegetation, with the combined contribution of natural factors amounting to 64.3%. (3) Among the topographic factors, altitude had a more significant effect on vegetation dynamics, with higher altitude regions less likely to experience vegetation greening. Both natural and anthropogenic factors exhibited nonlinear responses and interactive effects, contributing to the observed dynamic trends. This study provides valuable insights into the driving mechanisms behind the condition of vegetation in arid and semi-arid regions of China and, by extension, in other arid regions globally. Full article

The aim of this study is to evaluate the effects of different types of sourdough (I to IV), developed with a specific starter culture (including Lactiplantibacillus plantarum, Levilactobacillus brevis, and Candida famata), on bread fermentation performance and shelf-life. Real-time tracking of multiple parameters (pH, dough rising, ethanol release, and total titratable acidity) was monitored by a smart fermentation oven. The impact of the different treatments on the lactic acid, acetic acid, and ethanol content of the breads were quantified by high performance liquid chromatography analysis. In addition, the bio-preservation capacity of the breads contaminated with fungi was analyzed. The results show that liquid sourdough (D3: Type 2) and backslopped sourdough (D4: Type 3) increased significantly (p < 0.05) in dough rise, dough acidification (lower pH, higher titratable acidity), production of organic acids (lactic and acetic), and presented the optimal fermentation quotient. These findings were substantiated by chemometric analysis, which successfully clustered the starters based on performance and revealed a strong positive correlation between acetic acid production and dough-rise, highlighting the superior heterofermentative profile of D3 and D4. These types of sourdough also stood out for their antifungal capacity, preventing the visible growth of Aspergillus niger and Penicillium commune for up to 10 days after inoculation. Full article

Enhancing the nutritional content of crops is crucial for safeguarding human health and mitigating global hunger. A viable method for attaining this goal is the planned implementation of various agronomic practices, including tillage and nutrient provision. A field experiment was executed at the Hungarian University of Agriculture and Life Sciences in Gödöllő in the 2023 and 2024 growing seasons. The study aimed to assess the effects of foliar nutrient supply and soil tillage methods on the grain nutritional composition and mineral content of winter barley. Employing a split-plot design with three replications, the experiment included four nutrient treatments (control, bio-cereal, bio-algae, and MgSMnZn blend) and two soil tillage types (i.e., plowing and cultivator). The results indicated that while protein content was not influenced by the main effects of nutrients and tillage, the levels of β-glucan, starch, crude ash, and moisture content were significantly (p < 0.05) affected by the nutrient treatments and by growing year, treated as a random factor. Notably, bio-algae and bio-cereal nutrients, combined with cultivator tillage, enhanced β-glucan content. All applied nutrient treatments increased the level of starch compared to the control. With regard to grain mineral content, the iron and zinc content responded to the nutrient supply, tillage, and growing year. However, applying a multiple-nutrient composition-based treatment did not increase iron and zinc levels, suggesting that individual applications may be more effective for increasing the content of these minerals in grains. Cultivator tillage improved iron and zinc levels. Moreover, manganese (Mn) and copper (Cu) were predominantly affected by nutrient availability and by growing seasons as a random factor. Therefore, to improve grain quality, this study emphasizes the significance of proper nutrient and tillage methods by focusing on the intricate relationships between agronomic techniques and environmental factors that shape barley’s nutritional profile. Full article

The development of active food packaging has evolved rapidly in recent years, offering innovative solutions to enhance food preservation and safety while addressing sustainability challenges. This review compiles and analyzes recent advancements (2019–2024) in release-type active packaging, focusing on essential oils, natural extracts, and phenolic compounds as active agents. Primarily plant-derived, these compounds exhibit significant antioxidant and antimicrobial activities, extending shelf life and enhancing food quality. Technological strategies such as encapsulation and polymer blending have been increasingly adopted to overcome challenges related to volatility, solubility, and sensory impact. Integrating bio-based polymers, including chitosan, starch, and polylactic acid, further supports the development of environmentally friendly packaging systems. This review also highlights trends in compound-specific research, release mechanisms, and commercial applications, including a detailed analysis of patents and case studies across various food matrices. These developments have already been translated into practical applications, such as antimicrobial sachets for meat and essential oil-based pads for fresh produce. Moreover, by promoting the valorization of agro-industrial by-products and the use of biodegradable materials, emission-type active packaging contributes to the principles of the circular economy. This comprehensive overview underscores the potential of natural bioactive compounds in advancing sustainable and functional food packaging technologies. Full article

Since the initial use of biological ion channels to detect single-stranded genomic base pair differences, label-free and highly sensitive resistive pulse sensing (RPS) with nanopores has made remarkable progress in single-molecule analysis. By monitoring transient ionic current disruptions caused by molecules translocating through a nanopore, this technology offers detailed insights into the structure, charge, and dynamics of the analytes. In this work, the RPS platforms based on biological, solid-state, and other sensing pores, detailing their latest research progress and applications, are reviewed. Their core capability is the high-precision characterization of tiny particles, ions, and nucleotides, which are widely used in biomedicine, clinical diagnosis, and environmental monitoring. However, current RPS methods involve bottlenecks, including limited sensitivity (weak signals from sub-nanometer targets with low SNR), complex sample interference (high false positives from ionic strength, etc.), and field consistency (solid-state channel drift, short-lived bio-pores failing POCT needs). To overcome this, bio-solid-state fusion channels, in-well reactors, deep learning models, and transfer learning provide various options. Evolving into an intelligent sensing ecosystem, RPS is expected to become a universal platform linking basic research, precision medicine, and on-site rapid detection. Full article

Natural fiber-based biocomposites are rapidly gaining traction in sustainable manufacturing. However, their supply chain (SC) designs at the feedstock pre-processing stage often lack robust multicriteria decision-making evaluations, which can impact downstream processes and final product quality. This case study proposes a sustainability-driven multicriteria decision-making framework for selecting pre-processing equipment configurations within a hemp-based biocomposite SC. Using a cradle-to-gate system boundary, four alternative configurations combining balers (square vs. round) and hammer mills (full-screen vs. half-screen) are evaluated. The analytical network process (ANP) model is used to evaluate alternative SC configurations while capturing the interdependencies among environmental, economic, social, and technical sustainability criteria. These criteria are further refined with the inclusion of sub-criteria, resulting in a list of 11 key performance indicators (KPIs). To evaluate ranking robustness, a non-linear programming (NLP)-based sensitivity model is developed, which minimizes the weight perturbations required to trigger rank reversals, using an IPOPT solver. The results indicated that the Half-Round setup provides the most balanced sustainability performance, while Full-Square performs best in economic and environmental terms but ranks lower socially and technically. Also, the ranking was most sensitive to the weight of the system reliability and product quality criteria, with up to a 100% shift being required to change the top choice under the ANP model, indicating strong robustness. Overall, the proposed framework enables decision-makers to incorporate uncertainty, interdependencies, and sustainability-related KPIs into the early-stage SC design of bio-based composite materials. Full article

Heart failure (HF) poses a substantial global burden due to its high morbidity, mortality, and healthcare costs. Accurate prognostication is crucial for optimizing treatment, resource allocation, and patient counseling. Prognostic tools range from simple clinical scores such as ADHERE and MAGGIC to more complex models incorporating biomarkers (e.g., NT-proBNP, sST2), imaging, and artificial intelligence techniques. In acute HF, models like EHMRG and STRATIFY aid early triage, while in chronic HF, tools like SHFM and BCN Bio-HF support long-term management decisions. Despite their utility, most models are limited by poor generalizability, reliance on static inputs, lack of integration into electronic health records, and underuse in clinical practice. Novel approaches involving machine learning, multi-omics profiling, and remote monitoring hold promise for dynamic and individualized risk assessment. However, these innovations face challenges regarding interpretability, validation, and ethical implementation. For prognostic models to transition from theoretical promise to practical impact, they must be continuously updated, externally validated, and seamlessly embedded into clinical workflows. This review emphasizes the potential of prognostic models to transform HF care but cautions against uncritical adoption without robust evidence and practical integration. In the evolving landscape of HF management, prognostic models represent a hopeful avenue, provided their limitations are acknowledged and addressed through interdisciplinary collaboration and patient-centered innovation. Full article

Electroless nickel deposition (ELD) is an autocatalytic technique extensively used to impart conductive, protective, and mechanical functionalities to inherently non-conductive synthetic substrates. This review systematically explores the fundamental mechanisms of electroless nickel deposition, emphasising recent advancements in surface activation methods, solvent systems, and microstructural control. Critical analysis reveals that bio-inspired activation methods, such as polydopamine (PDA) and tannic acid (TA), significantly enhance coating adhesion and durability compared to traditional chemical etching and plasma treatments. Additionally, solvent engineering, particularly using polar aprotic solvents like dimethyl sulfoxide (DMSO) and ethanol-based systems, emerges as a key strategy for achieving uniform, dense, and flexible coatings, overcoming limitations associated with traditional aqueous baths. The review also highlights that microstructural tailoring, specifically the development of amorphous-nanocrystalline hybrid nickel coatings, effectively balances mechanical robustness (hardness exceeding 800 HV), flexibility, and corrosion resistance, making these coatings particularly suitable for wearable electronic textiles and smart materials. Furthermore, commercial examples demonstrate the real-world applicability and market readiness of nickel-coated synthetic fibres. Despite significant progress, persistent challenges remain, including reliable long-term adhesion, internal stress management, and environmental sustainability. Future research should prioritise environmentally benign plating baths, standardised surface activation protocols, and scalable deposition processes to fully realise the industrial potential of electroless nickel coatings. Full article

The Set Coverage Problem (SCP) is an important combinatorial optimization problem known to be NP-complete. The use of metaheuristics to solve the SCP includes different algorithms. In particular, binarization techniques have been explored to adapt metaheuristics designed for continuous optimization problems to the binary domain of the SCP. In this work, we present a new approach to solve the SCP based on the Secretary Bird Optimization Algorithm (SBOA). This algorithm is inspired by the natural behavior of the secretary bird, known for its ability to hunt prey and evade predators in its environment. Since the SBOA was originally designed for optimization problems in continuous space and the SCP is a binary problem, this paper proposes the implementation of several binarization techniques to adapt the algorithm to the discrete domain. These techniques include eight transfer functions and five different discretization methods. Taken together, these combinations create multiple SBOA adaptations that effectively balance exploration and exploitation, promoting an adequate distribution in the search space. Experimental results applied to the SCP together with its variant Unicost SCP and compared to Grey Wolf Optimizer and Particle Swarm Optimization suggest that the binary version of SBOA is a robust algorithm capable of producing high quality solutions with low computational cost. Given the promising results obtained, it is proposed as future work to focus on complex and large-scale problems as well as to optimize their performance in terms of time and accuracy. Full article