Search Results (3,188)

After numerous false starts, the global microalgae industry is re-emerging, driven by its potential to address critical challenges in food and nutrition, sustainable energy, nutraceuticals, cosmetics and pharmaceuticals, and climate change mitigation. Although technical advances in microalgae production show value adding potential, progressing from innovation to product launch and competitiveness is complex. It requires an integrated understanding of technology readiness, regulatory compliance, financial necessities, and market competition. This study presents a novel analytical framework underpinning a data-enabled, evidence-based approach to navigating the innovation pathways to market and beyond. The framework integrates value-add opportunities, identifying key stages faced in pre-competitive (including Technology Readiness Level (TRL), R&D spend, and patent trends), and competitive market stages (including product launches, product claims, market size, market share, growth/maturity, international markets, distribution channels, sectoral profile, and competitive landscape), aligned with regulatory requirements. Although not without limitations, such as incomplete data for emerging products, as well as reliance on secondary sources for product stage determination and market size estimates which can influence the accuracy of TRL classification and market potential estimates. This integration of multiple analyses can help in identifying market opportunities and business competitiveness via product, business, and industry level analyses in the pre-competitive (pre-market launch) and competitive (on market) landscapes. Building on the team’s interdisciplinary experience of developing interactive dashboards for food and beverage industries, and microalga processes, this paper provides an overview of the framework, which was designed to guide businesses and researchers in an emerging microalgae industry through the complex landscape of product development along regulatory and commercial pathways. Full article

Background/Objectives: Energy availability (EA) is associated with Relative Energy Deficiency in Sport syndrome. This study assessed the EA, body composition, and phase angle (φ) of adolescent artistic gymnasts during a competitive season. Methods: Thirty non-elite artistic gymnasts aged 11–14 years participated in this cross-sectional study. Anthropometric data were collected and body mass index (BMI) was assessed using the World Health Organization growth charts. Bioelectrical impedance analysis was performed and diet and physical activity were recorded for three days. Dietary and physical activity records were analyzed to estimate energy intake, total energy expenditure (TEE), and exercise energy expenditure, from which energy balance (EB) and EA were calculated. The 95% confidence ellipses of the impedance (Z) vectors were compared with a reference population using the two-sample Hotelling’s T² test. Correlations between variables were examined by Pearson’s or Spearman’s correlation analysis. Statistical significance was set at α = 0.05. Results: All participants were classified within the normal BMI category, except for one who was classified as being overweight. Mean (± SD) fat mass, fat-free mass (FFM), and φ were 16.1 ± 3.4%, 83.9 ± 3.4%, and 6.0 ± 0.6°, respectively. The 95% confidence ellipses of Z vectors differed significantly from the reference population. Energy balance was 32 ± 223 kcal/day and EA was 49.2 ± 11.4 kcal/kg FFM/day. Energy availability was significantly correlated with EB, TEE, and body composition variables. Conclusions: Adolescent non-elite artistic gymnasts showed no clear indications of LEA and exhibited a normal body composition and φ during the competitive season, consistent with their EA. Full article

Understanding interactions among sympatric mesocarnivore populations is essential for making sound management decisions. The golden jackal has rapidly expanded in Europe, raising questions about its potential intraguild effects. Using long-term hunting bag data (1997–2024) from Hungary, we investigated spatiotemporal population trends of the European badger, red fox, and golden jackal. We examined pairwise associations in their annual growth rates. Generalised additive models and Pearson correlation analyses revealed strong species-specific temporal and spatial trends and weak to moderate positive relationships among the species’ population growth rates at the national scale and within regions of high jackal population density. We found no evidence of jackal suppression of foxes or badgers. Additionally, badgers showed the strongest positive association with fox populations. Our large-scale analyses suggest that these mesocarnivores coexist without substantial competitive interference, likely due to local spatial heterogeneity and fine-scale temporal partitioning that are not detectable in annual, broad-scale (national) data. These findings highlight the importance of integrating broad-scale population data with finer-scale behavioural studies to better understand coexistence mechanisms in expanding mesocarnivore assemblages. Full article

Analysis of game management and trophy game populations in Osijek-Baranja County shows that this region is one of the most valuable hunting areas in Croatia, with rich populations of red deer, roe deer, and wild boar, as well as stable annual population growth. The methodological framework included products and services in hunting based on data analysis from the Croatian Hunting Association, big-game trophy records (ETD forms), the Central Hunting Register, and the official price list of game culling and hunting services. Data on harvests and trophy values indicate long-term population stability and high economic potential of hunting, with red deer generating the highest total revenue (EUR 7.29 million), while roe deer and wild boar contribute to overall stability and harvest volume. The total trophy value over 12 hunting seasons reaches EUR 11.99 million, underscoring the economic importance of hunting tourism for local communities. Differences among hunting ground users suggest that private companies and the state company Croatian Forests Ltd. often achieve higher trophy values, while county hunting associations report more modest results. However, regression analysis shows there is not a strong statistical correlation between management structure and trophy outcomes, highlighting the significant influence of ecological and spatial factors on game quality. International hunters, primarily from Germany and Austria, represent a key segment of demand, confirming the market potential for further development of hunting tourism. Despite the rich natural base, results indicate the need for better marketing approach, digital visibility, and integration of hunting products with other forms of tourism, such as gastronomic, wine, and nature tourism. Effective positioning of Croatia as a competitive hunting destination requires adaptation to contemporary market trends and adherence to international sustainable management guidelines (FAO, ELC, CBD). In conclusion, hunting in Croatia represents an important non-wood forest product and a vital resource for rural and economic development. Sustainable population management, quality promotion, and integration of traditional and innovative practices are essential for reinforcing biodiversity conservation, supporting community livelihoods, and strengthening Croatia’s role in the European and global hunting-tourism market. Full article

The Chongming Dongtan wetland, a representative coastal wetland in East Asia, faces a significant ecological threat from the invasive species Spartina alterniflora. The mixed ecotone formed between this invasive species and the native Phragmites australis serves as a highly sensitive and critical indicator of alterations in wetland ecosystem structure and function. Using spring and autumn Sentinel-2 imagery from 2016 to 2023, this study developed an integrated method that combines a three-dimensional feature space with multi-threshold Otsu segmentation to accurately extract the mixed S. alterniflora–P. australis ecotone. The spatiotemporal dynamics of the mixed ecotone were analyzed at multiple temporal scales using a centroid migration model and a newly defined Seasonal Area Ratio (SAR) index. The results suggest that: (1) Near-infrared reflectance and NDVI were identified as the optimal spectral indices for spring and autumn, respectively. This approach led to a classification achieving an overall accuracy of 87.3 ± 1.4% and a Kappa coefficient of 0.84 ± 0.02. Notably, the mixed ecotone was mapped with producers’ and users’ accuracies of 85.2% and 83.6%. (2) The vegetation followed a distinct land-to-sea ecological sequence of “pure P. australis–mixed ecotone–pure S. alterniflora”, predominantly distributed as an east–west trending belt. This pattern was fragmented by tidal creeks and micro-topography in the northwest, contrasting with geometrically regular linear features in the central area, indicative of human engineering. (3) The ecotone showed continuous seaward expansion from 2016 to 2023. Spring exhibited a consistent annual area growth of 13.93% and a stable seaward centroid migration, whereas autumn exhibited significant intra-annual fluctuations in both area and centroid, likely influenced by extreme climate events. (4) Analysis using the Seasonal Area Ratio (SAR) index, defined as the ratio of autumn to spring ecotone area, revealed a clear transition in the seasonal competition pattern in 2017, initiating a seven-year spring-dominant phase after a single year of autumn dominance. This spring-dominated era exhibited a distinctive sawtooth fluctuation pattern, indicative of competitive dynamics arising from the phenological advancement of P. australis combined with the niche penetration of S. alterniflora. This study elucidates the multiscale competition mechanisms between S. alterniflora and P. australis, thereby providing a scientific basis for effective invasive species control and ecological restoration in coastal wetlands. Full article

The study analyzes the long-term development prospects of the Latvian dairy sector until 2032, using an integrated modeling approach that combines the AGMEMOD partial equilibrium model with the TOPSIS multi-criteria evaluation method. The study addresses the main challenge facing the sector—how to maintain productivity in the context of structural consolidation and increasing environmental requirements. The AGMEMOD model was recalibrated using updated data for Latvia for 2015–2023. Two scenarios were developed: A1 “Targeted and intensive farm modernization” and A2 “Limited farm modernization”. Scenario A1 is characterized by gradual technological adoption, leading to higher productivity while keeping total milk production almost unchanged relative to the Baseline scenario, whereas scenario A2 reflects slower modernization and reduced productivity growth. The TOPSIS evaluation identified scenario A1 as the most attractive alternative, as it combines productivity gains and greater adaptability to policy and environmental requirements. The results confirm that technological modernization and flexible policy mechanisms are essential to maintain the competitiveness and productivity performance of Latvia’s dairy sector. The integrated AGMEMOD–TOPSIS approach provides a methodological tool for evidence-based policy analysis and strategic planning in agricultural market management. Full article

Cultural tourism (CT) has emerged as a critical driver of destination competitiveness; however, stakeholders struggle to balance heritage preservation, sustainable growth, and visitor management. Current decision making often lacks the practical information required to assess the multi-dimensional impacts of CT and to align strategies with sustainability goals. This paper presents a user-centred digital decision support system (DSS) developed under the European project IMPACTOUR. The methodological contribution is a procedure that uncovers links among strategies, actions, and performance indicators, conditioned on destination characteristics, by leveraging hierarchical multi-criteria analysis to weight sustainability domains. Co-designed with stakeholders, it integrates social and technological components and uses triangulated data to prioritise strategies and evaluate impacts. The visual interface offers a smart dashboard that supports strategic decision making and displays related key performance indicators, enabling stakeholders to monitor outcomes against predefined sustainability objectives. Pilot implementations in several European regions demonstrate the tool’s efficacy in fostering data-driven planning to achieve a balanced approach between tourism and liveability. While the system is scalable, its current limits include regional specificity and data availability. Future work will incorporate AI-driven predictive analytics and adapt the DSS for application in non-European contexts, providing a replicable framework for advancing sustainable tourism policies in culturally rich destinations. Full article

The auxin indole-3-acetic acid (IAA) is essential for plant growth and stress adaptation. Its biosynthesis via the indole-3-acetaldoxime (IAOx) pathway has recently undergone a paradigm shift. Recent genetic and metabolomic studies have fundamentally revised the indole-3-acetaldoxime (IAOx) pathway from a linear route (IAOx→IAN→IAM→IAA) to a dynamic network. This review synthesizes this paradigm shift by integrating evidence from key Arabidopsis studies. Crucially, mutants disrupting multiple downstream enzyme families fail to block IAA overproduction in the IAOx-accumulating superroot 2 (sur2) background. Functioning as a central branching point between auxin and defense metabolism, the tryptophan-derived metabolite IAOx, along with indole-3-acetonitrile (IAN) and indole-3-acetamide (IAM), elicits auxin responses via independent, tissue-specific pathways, with no metabolic requirement for IAM as a universal intermediate. Furthermore, IAN and IAM levels do not increase with massive IAOx accumulation, indicating a bypass route from IAOx to IAA. We conclude that IAOx acts as a central metabolic hub, partitioning flux competitively between growth and defense. Resolving the unknown IAOx-converting enzyme, the signaling roles of IAN/IAM, and the logic of metabolic channeling is vital to understanding how plants integrate hormonal and stress responses. Full article

Water scarcity in arid/semi-arid regions restricts agricultural sustainability systems and hinders the achievement of regional sustainable development goals, especially in northwest China’s extremely arid areas, where acute water supply–demand conflicts and inefficient traditional practices intensify competition for water between agricultural and ecological sectors. This study aims to verify the effectiveness of an intelligent automatic irrigation system in mitigating water scarcity pressures and enhancing agricultural sustainability in the Shule River Basin of northwestern China, a region where traditional irrigation methods not only yield suboptimal crop outputs but also undermine long-term water resource sustainability. A smart irrigation module, integrating “sensing–decision–execution” processes, was embedded within a digital twin platform to enable precise, resource-efficient water management that aligns with sustainable development principles. Sunflower (Helianthus annuus L.), the most popular cash crop in the area, was used as the test crop, with three soil moisture-based irrigation levels compared against traditional farmer practices. Key indicators including leaf area index (LAI), dry biomass, grain yield, and irrigation water use efficiency (IWUE) were systematically evaluated. The results showed that (1) LAI increased from the seedling to flowering stage, with smart irrigation treatments significantly outperforming farmer practices in both crop growth and water-saving effects, laying a foundation for sustainable yield improvement; (2) total dry biomass at maturity was positively correlated with irrigation amount but smart irrigation optimized the allocation of water resources to avoid waste, balancing productivity and sustainability; (3) grain yield peaked within 70–89% field capacity (fc), with further increases leading to diminishing returns and unnecessary water consumption that impairs sustainable water use; (4) IWUE followed a parabolic trend, reaching its maximum under the same optimal irrigation range, indicating that smart irrigation can maximize water productivity while preserving water resources for ecological and future agricultural needs. The digital twin-driven smart irrigation system enhances both crop yield and water productivity in arid regions, providing a scalable model for precision water management in water-stressed agricultural zones. The results provide a key empirical basis and technical approach for sustainably using irrigation water, optimizing water–energy–food–ecology synergy, and advancing sustainable agriculture in arid regions of Northwest China, which is crucial for achieving regional sustainable development objectives amid worsening water scarcity. Full article

This study investigates the nonlinear dynamics that emerge from the interactions between cancer cells and immune cells within a predator–prey model, wherein cancer cell growth obeys the Gompertz law. A bifurcation analysis allows for the identification of states of dormancy, uncontrolled growth, and multistability with and without chemotherapy. In the absence of chemotherapy, a Gompertz model predicts bistability with low (dormant) and high (active) tumor levels. However, unlike models based on the logistic equation, it shows that a stable tumor-free solution does not exist, consistent with the medical understanding about the risk of remaining disease even with successful treatment. Under chemotherapy, the model demonstrates highly complex dynamics with up to four coexisting stable steady states, stable tumor levels, and chemotherapy-induced oscillations. Parameter continuation studies show that the potency of immune recruitment, rate of cell inactivation, and drug saturation are essential in characterizing transitions among these dynamical regions. The analysis indicates that the choice of growth rate plays a significant role in determining the physiological implications for therapy, suggesting a cure for a model with a logistic growth rate, but merely tumor control for a Gompertzian scenario. Moreover, these results provide insights into optimal chemotherapy dosage to prevent problems associated with bistability and to capitalize on stable dormancy. Full article

Climate change reshapes crop–weed interactions and challenges the cultivation of oilseed rape (Brassica napus L.). Common ragweed (Ambrosia artemisiifolia L.) strongly suppresses early crop development, increases stress sensitivity and leads to yield loss. The stress–physiological responses of oilseed rape to ragweed competition were investigated using a combination of conventional and non-invasive methods. A pot experiment was conducted with increasing ragweed densities (0, 1, 3, 5 and 10 plants). Plant height and biomass were evaluated via non-destructive indicators (SPAD, NDVI) and different stages (1–15 and 16–30 min) of delayed fluorescence (DF) alongside ferric reducing antioxidant power (FRAP). Increasing ragweed density caused changes in growth, altered DF magnitude and decay kinetics, indicating photosynthetic imbalance. Moderate weed competition (1–5) induced an adaptive, eustress-like response characterised by enhanced non-enzymatic antioxidant capacity, whereas higher ragweed densities overwhelmed this compensatory mechanism, resulting in oxidative stress-like responses. Among all measured traits, DF₁–₁₅ proved to be the earliest and most sensitive indicator of the transition from adaptive to disruptive stress: T1: 0 ragweed: 213.07 ± 10.36 cps/mm² and 92.66 ± 6.67 cps/mm². These results demonstrate that delayed fluorescence, combined with conventional physiological and antioxidant-based parameters, enables the early detection of competitive stress in oilseed rape well before visible symptoms appear. Full article

The present study examined the impact of agricultural exports on economic growth in Lambayeque, Peru, during the period 2010–2023. An ordinary least squares (OLS) econometric model was employed to analyze the relationship between gross value added (GVA) and key macroeconomic variables, including agricultural exports, private investment, real wages, terms of trade, and the real multilateral exchange rate. The findings indicate that the model possesses considerable explanatory power (R² = 0.973) and that agricultural exports exert a positive and significant influence on regional GVA. In addition, private investment and real wages demonstrate positive elasticities, while terms of trade exhibit a negative relationship with regional economic growth. This highlights Lambayeque’s vulnerability to external price shocks. The study thus underscores the pivotal role of the Olmos Project, which has been instrumental in transforming arid land into fruitful agricultural zones through the implementation of an irrigation system encompassing over 22,000 hectares. This initiative has not only augmented agricultural exports, accounting for an impressive 90% of Lambayeque’s supply, but also contributed significantly to regional economic development by supporting employment generation and poverty reduction. Nevertheless, the presence of negative terms of trade indicates that the regional economy exhibits structural vulnerability in the face of external shocks. Notwithstanding the intrinsic limitations of regional, trade, and macroeconomic statistics, an understanding of the correlation between agro-exports and economic growth in a paradigmatic region of northern Peru provides substantial evidence for formulating policies to enhance the competitiveness and sustainability of the agro-export model. Full article

Licorice is an important specialty crop that links agricultural production, processing and trade, and rural livelihoods in the arid and semi-arid regions of China. Using UN Comtrade data for HS 130212 from 1990 to 2024, this study evaluates the international Trade Competitiveness of China’s licorice exports and identifies the sources of export growth. A multi-indicator static framework is constructed, combining International Market Share (IMS), the Trade Competitiveness Index (TC), the Revealed Symmetric Comparative Advantage index (RSCA) and the Revealed Competitive Advantage index (CA). The results show that China maintains a relatively large and stable global market share and a persistent net export position, but its comparative and net Competitive Advantages are weaker than those of high-end suppliers such as France and Israel, revealing a pattern of “large scale but weak competitiveness”. To capture dynamic drivers, an extended Constant Market Share (CMS) model is applied to decompose China’s licorice exports into world demand, structural and competitiveness effects. The decomposition indicates that export growth has gradually shifted from being mainly driven by global demand expansion to relying more on improvements in product competitiveness and market reconfiguration, particularly in emerging markets. These findings suggest that upgrading product quality and processing, strengthening standards and branding, and promoting more inclusive value-chain development are essential for transforming China’s licorice exports from scale expansion to high-quality growth and for enhancing rural incomes in producing regions. Full article

We study a hybrid stochastic SIS co-infection model for two primary strains and a co-infected class with Crowley–Martin incidence, Markovian regime switching, and Lévy jumps. The model is a four-dimensional regime-switching Lévy-driven SDE system with state-dependent diffusion and jump coefficients. Under natural integrability conditions on the jumps and a mild structural assumption on removal rates, we prove uniform high-order moment bounds for the total population, establish pathwise sublinear growth, and derive strong laws of large numbers for all Brownian and Lévy martingales, reducing the long-time analysis to deterministic time averages. Using logarithmic Lyapunov functionals for the infective classes, we introduce four noise-corrected effective growth parameters ${\lambda }_1,\dots ,{\lambda }_4$ and two interaction matrices $A,B$ that encode the combined impact of Crowley–Martin saturation, regime switching, and jump noise. In terms of explicit inequalities involving ${\lambda }_k$ and the entries of $A,B$, we obtain sharp almost-sure criteria for extinction of all infectives, persistence with competitive exclusion, and coexistence in mean of both primary strains, together with the induced long-term behaviour of the co-infected class. Numerical simulations with regime switching and compensated Poisson jumps illustrate and support these thresholds. This provides, to our knowledge, the first rigorous extinction-exclusion-coexistence theory for a multi-strain SIS co-infection model under the joint influence of Crowley–Martin incidence, Markov switching, and Lévy perturbations. Full article

Against the backdrop of global energy transition and sustainable development, advancing the new energy industry has become a critical pathway for optimizing energy structures and achieving the dual carbon goals. However, while China’s new energy sector has experienced rapid growth, it has also exposed a series of challenges, including insufficient innovation momentum, irrational resource allocation, and low conversion rates of R&D outcomes. To delve into the root causes and propose improvement pathways, this study selected 76 listed new energy enterprises from 2021 to 2023 as samples. It comprehensively employed the DEA-BCC model, Malmquist productivity index, and Tobit regression model to conduct empirical analysis across three dimensions: static, dynamic, and influencing factors. The findings revealed: firstly, during the study period, overall static efficiency remained low, with only about 32.90% of enterprises operating efficiently. Efficiency decomposition indicated that low and unstable pure technical efficiency constrained overall efficiency gains. In contrast, while scale efficiency was relatively high, its growth was sluggish, and some enterprises exhibited significant scale irrelevance. Secondly, dynamic total factor productivity exhibited fluctuating growth primarily driven by technological progress. However, declining technical efficiency—particularly the deterioration of scale efficiency—indicated that while the new energy industry advanced technologically and expanded in scale, its management capabilities had not kept pace. This mismatch among the three factors trapped the industry in a “high investment, low efficiency” dilemma. Thirdly, regression analysis of influencing factors indicated that corporate governance and market competitiveness were pivotal to innovation efficiency: the proportion of independent directors and revenue growth rate exerted significant positive impacts, while equity concentration showed a significant negative effect. Firm size had a weaker influence, and government support did not demonstrate a significant positive impact. Accordingly, this paper proposes pathways to enhance innovation efficiency in new energy enterprises, including optimizing corporate governance structures, formulating differentiated subsidy policies, and improving the innovation ecosystem. The findings of this study not only provide empirical references for the innovative development of the new energy industry but also offer theoretical support for relevant policy formulation. Full article