Search Results (37,796)

The prospects for long-distance space flights are becoming increasingly realistic, and one of the key factors for their implementation is the creation of sustainable systems for producing food on site. Therefore, the aim of our work is to assess the prospects for using millet in biological life support systems and to create predictive models of yield components for automating plant cultivation control. The study found that stress from hypergravity (800 g, 1200 g, 2000 g, and 3000 g) in the early stages of millet germination does not affect seedlings or yield. In a closed system, millet yield reached 0.31 kg/m², the weight of 1000 seeds was 8.61 g, and the yield index was 0.06. The paper describes 40 quantitative traits, including six leaf and trichome traits and nine grain traits from the lower, middle and upper parts of the inflorescence. The compiled predictive regression equations allow predicting the accumulation of biomass in seedlings on the 10th and 20th days of cultivation, as well as the weight of 1000 seeds, the number of productive inflorescences, the total above-ground mass, and the number and weight of grains per plant. These equations open up opportunities for the development of computer vision and high-speed plant phenotyping programs that will allow automatic correction of the plant cultivation process and modeling of the required yield. Predicting biomass yield will also be useful in assessing the load on the waste-free processing system for plant waste at planetary stations. Full article

Monitoring water quality parameters in coastal and estuarine environments is critical for assessing their ecological status and addressing environmental challenges. However, traditional in situ sampling programs are often constrained by limited spatial and temporal coverage, making it difficult to capture the complex variability in these dynamic systems. This study introduces a novel upscaling framework that leverages limited in situ measurements and airborne hyperspectral data to generate multiple conditional realizations of water quality parameter fields. These pseudo-measurements are statistically consistent with the original data and are used to calibrate inversion algorithms that relate satellite-derived reflectance data to water quality parameters. The approach was applied to Kaštela Bay, a semi-enclosed coastal area in the eastern Adriatic Sea, to map seasonal variations in water quality parameters such as Chlorophyll-a. The upscaling framework captured spatial patterns that were absent in sparse in situ observations and enabled regional mapping using Sentinel-2A satellite data at the appropriate spatial scale. By generating realistic pseudo-measurements, the method improved the stability and performance of satellite-based retrieval algorithms, particularly in periods of high productivity. Overall, this methodology addresses data scarcity challenges in coastal water monitoring and its application could benefit the implementation of European water quality directives through enhanced regional-scale mapping capabilities. Full article

This study investigates the potential of residual clays from a traditional ceramic-producing region in southern Portugal as raw materials for red ceramic applications. This work aims to support more sustainable ceramic practices through the local valorization of naturally available, underutilized clay resources. A multidisciplinary approach was employed to characterize clays, integrating mineralogical (XRD), chemical (XRF), granulometric, and thermal analyses (TGA/DTA/TD), as well as technological tests on plasticity, extrusion moisture, shrinkage, and flexural strength. These assessments were designed to capture both the intrinsic properties of the clays and their behavior across key ceramic processing stages, such as shaping, drying, and firing. The results revealed a broad diversity in mineral composition, particularly in the proportions of kaolinite, smectite, and illite, which strongly influenced plasticity, water demand, and thermal stability. Clays with higher fine fractions and smectitic content exhibited excellent plasticity and workability, though with increased sensitivity to drying and firing conditions. Others, with coarser textures and illitic or feldspathic composition, demonstrated improved dimensional stability and lower shrinkage. Thermal analyses confirmed expected dehydroxylation and sintering behavior, with the formation of mullite and spinel-type phases contributing to densification and strength in fired bodies. This study highlights that residual clays from varied geological settings can offer distinct advantages when matched appropriately to ceramic product requirements. Some materials showed strong potential for direct application in structural ceramics, while others may serve as additives or tempering agents in formulations. These findings reinforce the value of integrated characterization for optimizing raw material use and support a more circular, resource-conscious approach to ceramic production. Full article

Excessive alcohol consumption is associated with systemic health risks due to the production of acetaldehyde, a primary carcinogen that not only pollutes the environment but also endangers human health. In this study, a promising bacterial strain for biodegrading both ethanol and acetaldehyde was successfully isolated from the traditional fermented food Jiaosu and identified as Acetobacter ghanensis JN01 based on average nucleotide identity (ANI) analysis. Initial ethanol of 1 g/L was completely biodegraded within 4 h, while initial acetaldehyde of 1 g/L was also rapidly removed at 2 or 1 h by whole cells or cell-free extracts (CEs) of JN01, respectively, which indicated that JN01 indeed has a strong ability in the biodegradation of both ethanol and acetaldehyde. Whole-genome sequencing revealed a 2.85 Mb draft genome of JN01 with 57.0% guanine–cytosine (GC) content and the key metabolic genes (adh1, adh2, and aldh) encoding involving alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), co-located with NADH dehydrogenase genes and ethanol-responsive regulatory motifs, supporting the metabolic pathway of transforming ethanol to acetaldehyde, and, subsequently, converting acetaldehyde to acetic acid. Furthermore, selected in vitro safety-related traits of JN01 were also assessed, which is very important in the development of microbial catalysts against both ethanol and acetaldehyde. Full article

Swietenia macrophylla King, commonly known as Brazilian mahogany, is a high-value neotropical tree species currently threatened due to intensive logging in previous decades. Technologies aimed at clonal production are essential for this species’ conservation and sustainable use at times of climate change and increasing demand for ecological restoration. The aim of the present study is to develop a low-cost protocol for mahogany clonal propagation through mini-cutting by assessing clonal mini-hedge nutrition, vegetative propagule type and indole-3-butyric acid (IBA) application effects on rooting and early clone growth. The experiment was conducted in nursery under controlled conditions based on using basal and apical mini-cuttings rooted in a low-cost mini-greenhouse subjected to three nutrient solution concentrations (50%, 100%, and 200%) and five IBA doses (0–8000 ppm). The mini-cutting technique proved efficient and led to over 90% survival after the hardening phase. The 200% nutrient solution concentration allowed balanced performance between cutting types and optimized clonal yield. IBA concentration at 4000 ppm accounted for higher root percentages at the bottom of the tube and the trend towards higher dry biomass production at 160 days. The results highlighted mini-cutting’s potential as a viable mahogany conservation and sustainable production technique. It also supported tropical forestry sector adaptation to challenges posed by climate change. Full article

Evaluation of the effectiveness of state policy instruments is a permanent element of economic science. This paper addresses the issue of investment support under the Common Agricultural Policy (CAP). Using data on Polish farms from 2015–2023, a Propensity Score Matching–Difference in Differences (PSM-DiD) analysis was conducted to assess changes in the economic results of agricultural producers that invest using this support. The comparison of the economic results achieved by supported investors with both non-investing agricultural producers and unsupported investors is a distinguishing element of this study. The relatively rarely used Competitivness Index (CI), which measures the ratio of earned income to the sum of the alternative use of the owned means of production, was used. The positive change in the CI during the analyzed period was 0.14 higher for supported investors than non-investors. No statistically significant change was found were compared to unsupported investors. A clear increase in income, total fixed assets, liabilities, and the level of production in the population of producers using support in relation to non-investors and investing without CAP support was also observed. However, in relationships with investors using their own funds, these differences were mainly due to the difference in the level of investments and were not statistically significant when introducing a correction regarding the scale of the investment. The obtained results remain in line with the results of research shown by a significant part of economists undertaking a similar issue. Full article

Dental implant components are typically fabricated using subtractive manufacturing, often involving metal materials that can be costly, inefficient, and time-consuming. This study explores the use of additive manufacturing (AM) with zirconia for dental implant overdenture bars, focusing on mechanical performance, stress distribution, and fit. Solid and lattice-structured bars were designed in Fusion 360 and produced using LithaCon 210 3Y-TZP zirconia (Lithoz GmbH, Vienna, Austria) on a CeraFab 8500 printer. Post-processing included cleaning, debinding, and sintering. A 3D-printed denture was also fabricated to evaluate fit. Thermography and optical imaging were used to assess adaptation. Custom fixtures were developed for flexural testing, and fracture loads were recorded to calculate stress distribution using finite element analysis (ANSYS R2025). The FEA model assumed isotropic, homogeneous, linear-elastic material behavior. Bars were torqued to 15 Ncm on implant analogs. The average fracture loads were 1.2240 kN (solid, n = 12) and 1.1132 kN (lattice, n = 5), with corresponding stress values of 147 MPa and 143 MPa, respectively. No statistically significant difference was observed (p = 0.578; α = 0.05). The fracture occurred near high-stress regions at fixture support points. All bars demonstrated a clinically acceptable fit on the model; however, further validation and clinical evaluation are still needed. Additively manufactured zirconia bars, including lattice structures, show promise as alternatives to conventional superstructures, potentially offering reduced material use and faster production without compromising mechanical performance. Full article

Economic systems face critical challenges, including widening income inequality, unemployment driven by automation, mounting public debt, and environmental degradation. This study introduces Economocracy as a transformative framework aimed at addressing these systemic issues by integrating democratic principles into economic decision-making to achieve social equity, economic efficiency, and environmental sustainability. The research focuses on two core mechanisms: Economic Productive Resets (EPRs) and Economic Periodic Injections (EPIs). EPRs facilitate proportional redistribution of resources to reduce income disparities, while EPIs target investments to stimulate job creation, mitigate automion-related job displacement, and support sustainable development. The study employs a theoretical and analytical methodology, developing mathematical models to quantify the impact of EPRs and EPIs on key economic indicators, including the Gini coefficient for inequality, unemployment rates, average wages, and job displacement due to automation. Hypothetical scenarios simulate baseline conditions, EPR implementation, and the combined application of EPRs and EPIs. The methodology is threefold: (1) a mathematical–theoretical validation of the Cycle of Money framework, establishing internal consistency; (2) an econometric analysis using global historical data (2000–2023) to evaluate the correlation between GNI per capita, Gini coefficient, and average wages; and (3) scenario simulations and Difference-in-Differences (DiD) estimates to test the systemic impact of implementing EPR/EPI policies on inequality and labor outcomes. The models are further strengthened through tools such as OLS regression, and Impulse results to assess causality and dynamic interactions. Empirical results confirm that EPR/EPI can substantially reduce income inequality and unemployment, while increasing wage levels, findings supported by both the theoretical architecture and data-driven outcomes. Results demonstrate that Economocracy can significantly lower income inequality, reduce unemployment, increase wages, and mitigate automation’s effects on the labor market. These findings highlight Economocracy’s potential as a viable alternative to traditional economic systems, offering a sustainable pathway that harmonizes growth, social justice, and environmental stewardship in the global economy. Economocracy demonstrates potential to reduce debt per capita by increasing the efficiency of public resource allocation and enhancing average income levels. As EPIs stimulate employment and productivity while EPRs moderate inequality, the resulting economic growth expands the tax base and alleviates fiscal pressures. These dynamics lead to lower per capita debt burdens over time. The analysis is situated within the broader discourse of institutional economics to demonstrate that Economocracy is not merely a policy correction but a new economic system akin to democracy in political life. Full article

The rapid development of digital technology is reshaping the global economic landscape. However, its impact on firms’ capacity utilization rate (CUR), particularly through technological innovation, remains unclear. This study investigates this issue by developing an endogenous growth model that connects digital technology to CUR. The empirical analysis is based on data from Chinese A-share manufacturing firms. The methods employed include quantile regression, instrumental variable techniques, and various tests to explore underlying mechanisms. CUR is calculated using a special model that looks at random variations, and digital transformation is assessed using text analysis powered by machine learning. The findings indicate that digital transformation significantly enhances CUR, especially for firms with average capacity utilization levels, but has a limited effect on low- and high-end firms. Moreover, technological innovation mediates this relationship; however, factors like “double arbitrage” (involving policy and capital markets) and “herd effects” tend to prioritize quantity over quality, which constrains innovation potential. Improvements in CUR lead to enhanced firm performance and productivity, generating industry spillovers and demonstrating the broader economic externalities of digitalization. This study uniquely applies endogenous growth theory to examine the role of digital transformation in optimizing CUR. It introduces the “quantity-quality” technology innovation paradox as a crucial mechanism and highlights industry spillovers to address overcapacity while offering insights for fostering sustainable economic and social development in emerging markets. Full article

This research contributes to advance the sustainable production of biofuels and provides insights into the energy and exergy assessment of bio-oil, which is essential for developing environmentally friendly energy production solutions. Energy and exergy analyses were performed to evaluate the pyrolysis of beech wood biomass at 500 °C in an Auger reactor. To improve the quality of the obtained bio-oil, its catalytic deoxygenation was performed within an in-line fluidized catalytic bed reactor using a catalyst based on HZSM5 zeolite modified with 5 wt.% Iron (5%FeHZSM-5). A thermodynamic analysis of the catalytic and non-catalytic pyrolysis system was carried out, as well as a comparative study of the calculation methods for the energy and exergy evaluation for bio-oil. The required heat for pyrolysis was found to be 1.2 MJ/kg_biomass in the case of non-catalytic treatment and 3.46 MJ/kg_biomass in the presence of the zeolite-based catalyst. The exergy efficiency in the Auger reactor was 90.3%. Using the catalytic system coupled to the Auger reactor, this efficiency increased to 91.6%, leading to less energy degradation. Calculating the total energy and total exergy of the bio-oil using two different methods showed a difference of 6%. In the first method, only the energy contributions of the model compounds, corresponding to the major compounds of each chemical family of bio-oil, were considered. In contrast, in the second method, all molecules identified in the bio-oil were considered for the calculation. The second method proved to be more suitable for thermodynamic analysis. The novelties of this work concern the thermodynamic analysis of a coupled system of an Auger biomass pyrolysis reactor and a fluidized bed catalytic deoxygenation reactor on the one hand, and the use of all the molecules identified in the oily phase for the evaluation of energy and exergy on the other hand. Full article

Precipitation concentration reflects the uneven temporal distribution of rainfall. It plays a critical role in water resource management and flood–drought risk under climate change. However, its long-term trends, associations with atmospheric teleconnections as potential drivers, and links to extreme heavy precipitation events remain poorly understood in complex basins like the Yangtze River Basin. This study analyzes these aspects using ground station data from 1960 to 2019 and conducts a comparison using the Global Precipitation Measurement Integrated Multi-satellitE Retrievals for GPM (GPM IMERG) satellite product. We calculated three indices—Daily Precipitation Concentration Index (PCID), Monthly Precipitation Concentration Index (PCIM), and Seasonal Precipitation Concentration Index (SPCI)—to quantify rainfall unevenness, selected for their ability to capture multi-scale variability and associations with extremes. Key methods include Mann–Kendall trend tests for detecting changes, Hurst exponents for persistence, Pettitt detection for abrupt shifts, random forest modeling to assess atmospheric teleconnections, and hot spot analysis for spatial clustering. Results show a significant basin-wide decrease in PCID, driven by increased frequency of small-to-moderate rainfall events, with strong spatial synchrony to extreme heavy precipitation indices. PCIM is most strongly associated with El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). GPM IMERG captures PCIM patterns well but underestimates PCID trends and magnitudes, highlighting limitations in daily-scale resolution. These findings provide a benchmark for satellite product improvement and support adaptive strategies for extreme precipitation risks in changing climates. Full article

Augmented reality (AR) in industry improves training and technical assistance by overlaying digital information on real environments, facilitating the visualisation and understanding of complex processes. It also enables more effective remote collaboration, optimising problem solving and decision making in real time. This paper proposes a scoping review, using PRISMA guidelines, on the optimisation of industrial processes through the application of AR. The objectives of this study included characterising successful implementations of AR in various industrial processes, comparing different hardware, graphics engines, associated costs, and determining the percentage of optimisation achieved through AR. The databases included were Scopus, SpringerLink, IEEExplore, and MDPI. Eligibility criteria were defined as English-language articles published between 2019 and 2024 that provide significant contributions to AR applications in engineering. The Cochrane method was used to assess bias. The rigorous selection process resulted in the inclusion of 38 articles. Key findings indicate that AR reduces errors and execution times, improves efficiency and productivity, and optimises training and maintenance processes, leading to cost savings and quality improvement. Unity 3D is the most widely used graphics engine for AR applications. The main applications of AR are in maintenance, assembly, training and inspection, with maintenance being the most researched area. Challenges include the learning curve, high initial costs, and hardware limitations. Full article

The market for plant-based alternatives to animal foods has increased rapidly in the past decade, mainly due to consumer demand. Little evidence is available regarding nutritional impacts, drivers, and barriers to using these products as substitutes for animal foods in real-life conditions. This pilot study followed 16 Danish adults (30 ± 11 years old; 11 females) for 4 weeks with substituting milk, cheese, and yogurt with plant-based analogues to dairy (PBADs) and assessed their drivers and barriers to applying the intervention with a mixed-method approach. PBADs are constantly compared to their animal counterparts, both regarding product characteristics, such as price and sensory properties, as well as cultural roles and subjective memories. The mixed methods showed dairy attachment, price, and taste were the main barriers to consuming PBAD, while changes in life and social circles were drivers (qualitative data). As for the liking of PBADs, plant-based yoghurt was the preferred intervention product (73.5/100, p < 0.05), followed by plant-based drinks (65.9/100), while plant-based cheese was the lowest rated (47.9/100, p < 0.05). As for dietary changes, a lower average intake of sugars, saturated fatty acids, cholesterol, calcium, phosphorus, and zinc was observed after the intervention. Additionally, this study describes the attachment of the study population to milk and dairy products. It shows that choosing dairy is beyond nourishment but is connected to tradition, culture, pleasure, memories, and a sense of belonging. In contrast, there is no history or attachment to PBADs. Full article

Mycoplasmal pneumonia of sheep (MPS), caused by Mesomycoplasma (Mycoplasma) ovipneumoniae, profoundly impacts ovine productivity and survival. Although gut–lung microbiota interactions are increasingly recognized in respiratory diseases, whether similar crosstalk occurs between the lung and rumen microbiota in MPS-affected sheep remains unknown. To investigate alterations in the lung and rumen microbiota of sheep with MPS, the crosstalk between these microbial communities, and their impacts on growth phenotypes. From a cohort of 414 naturally infected six-month-old male Hu sheep, we selected 10 individuals with severe pulmonary pathology and 10 healthy controls for detailed phenotypic and microbiome analyses. Assessment of 359 phenotypic traits revealed that MPS significantly impairs feed efficiency and growth rate (p < 0.05). Through 16S rRNA gene sequencing, we found that MPS significantly altered the pulmonary microbiota community structure (p < 0.01), with a noticeable impact on the rumen microbiota composition (p = 0.059). Succinivibrionaceae_UCG-001 was significantly depleted in both the rumen and lungs of diseased sheep (p < 0.05) and strongly associated with reduced average daily feed intake (p < 0.05). In addition, pulmonary Pasteurella and ruminal Succinivibrionaceae_UCG-002 were significantly enriched in MPS-affected sheep, showed a strong positive correlation (p < 0.05), and were both negatively associated with feed efficiency (p < 0.05). Notably, Pasteurella multocida subsp. gallicida may act as a keystone species influencing feed efficiency. These findings point to a previously unrecognized rumen-lung microbial axis that may modulate host productivity in sheep affected by MPS. This work provides new insights into the pathogenesis of MPS and offers potential targets for therapeutic intervention and management. Full article

Plant genders could express different functional strategies to compensate for different reproductive costs, as females have an additional role in fruit and seed production. Secondary sexual dimorphism (SSD) expression is frequently greater under stress than under optimal growth conditions. The early gender identification in papaya may help to reduce orchard costs because the most desirable fruit shape is formed by hermaphrodite plants. We hypothesized that (a) gender ecophysiological phenotyping can be an alternative to make gender segregations in papaya seedlings, and (b) such gender segregation will be more efficient after a short drought exposure than under adequate water conditions. To test such hypotheses, seedlings of two papaya varieties (‘Candy’ and ‘THB’) were exposed to two kind of treatments: (1) water shortage (WS) for 45 h, after which they were well watered, and (2) continuously well-watered (WW). Study assessed the ecophysiological responses, such as stomatal conductance (g_s), SPAD index, optical reflectance indices, morphological traits, and biomass accumulation in females (F) and hermaphrodites (H). In WS treatment, the SSD was expressed in 14 of 18 traits investigated, while in WW treatment, the SSD was expressed only in 7 of 18 traits. As tools for SSD expression, g_s and simple ratio pigment index (SRPI) must be measured on the first or second day after the imposed WS was interrupted, respectively, while the other parameters must be measured after a period of four days. In some traits, the SSD was expressed in only one variety, or the response of H and F plants were of opposite values for two varieties. The choice of the clearest responses of gender segregation in WS treatment will be greenness index, combination of normalized difference vegetation index (CNDVI), photochemical reflectance index (PRI), water band index (WBI), SRPI, leaf number, leaf dry mass, and leaf mass ratio. If the WW conditions are maintained for papaya seedling production, the recommendation in gender segregation will be the analysis of CNDVI, carotenoid reflectance index 2 (CRI2), WBI, and SRPI. The non-destructive optical leaf indices segregated papaya hermaphrodites from females under both water conditions and eventually could be adjusted for wide-scale platform evaluations, with planned space arrangements of seedlings, and sensor’s set. Full article