Search Results (6,246)

Generic and consistent formulations for measurement of the backscattering cross section $\left({\sigma }_{bs}\right)$ and the volume backscattering coefficient $\left(s_v\right)$ using broadband pulse compression and narrowband echo integration are derived, for small- and finite-amplitude sound propagation. The theory applies to backscattering operation of echosounders and sonars in general, with focus on fisheries acoustics. Formally consistent mathematical relationships for broadband and narrowband operation of such instruments are established that ensure consistency with the underlying power budget equations on average-power form, bridging a gap in prior literature. The formulations give full flexibility in choice of transmit signals and reference signals for pulse compression. Generic and general criteria for quantitative consistency between broadband and narrowband operation are derived, establishing new knowledge and analysis tools. These criteria become identical for small- and finite-amplitude sound propagation. In addition to general criteria, two special cases are considered, relevant for actual operation scenarios. The criteria serve to test and evaluate the extent to which the methods used in broadband pulse compression and narrowband echo integration operating modes are correct and consistent, and to identify and reduce experienced discrepancies between such methods. These are topics of major concern for quantitative acoustic stock assessment, underlying national and international fisheries quota regulations. Full article

Forests play a crucial role in storing excess carbon released into the atmosphere. By mitigating climate change, forest carbon stocks play a vital role in achieving green transitions. However, limited information is available regarding the factors that affect forest carbon stocks. The primary objective of this analysis is to investigate the impact of green agricultural technologies and bioenergy on forest carbon stocks. The empirical investigation was conducted using the method of moments quantile regression (MMQR) technique. Results using the MMQR approach indicate that bioenergy is beneficial in augmenting forest carbon stores at all levels. A 1% increase in bioenergy is associated with an increase in forest carbon stocks ranging from 3.100 at the 10th quantile to 1.599 at the 90th quantile. In the context of developing economies, similar findings are observed; however, in developed economies, bioenergy only fosters forest carbon stocks at lower and middle quantiles. In contrast, green agricultural technologies have an adverse effect on forest carbon stocks. Green agricultural technologies have a significant negative impact on forest carbon stocks, particularly between the 10th and 80th quantiles, with their influence declining in magnitude from −2.398 to −0.619. This negative connection is observed in both developed and developing countries at most quantiles, except for higher quantiles in developed economies. Gross domestic product (GDP) has an adverse effect on forest carbon stores only in developing countries, whereas human capital diminishes forest carbon stocks in both developed and developing nations. Governments should provide support for the creators of bioenergy and agroforestry technologies so that forest carbon stocks can be increased. Full article

This study assesses the quality of financial reporting in ten Central and Eastern European countries using a methodology based on natural language processing (NLP) techniques. 570 annual reports of companies listed on the main index on the stock exchanges of 10 Central and Eastern European (CEE) countries, over the period 2019–2023, were evaluated to determine the degree of convergence of the following four measurable qualitative characteristics: relevance, exact representation, comparability and understandability. The main objective is to identify consistency in the quality of accounting information based on the application of an international financial reporting framework. The applied methodology eliminates subjective variability by implementing a standardized scoring system, aligned with the criteria developed by NiCE, using libraries such as spaCy and NLTK for term extraction, respective sentiment analysis and word frequency evaluation. The results reveal significant heterogeneity in all characteristics examined, with statistical tests confirming substantial differences between countries. The investigation of relevance revealed partial convergence, with three dimensions achieving complete uniformity, while the exact representation showed the highest variability. The assessment of comparability showed a significant difference between countries’ extreme values, and in terms of comprehensibility a formalistic approach was evident, with technical dimensions outweighing user-oriented aspects. The overall quality index varied significantly across countries, with a notable average deterioration in 2023, indicating structural vulnerabilities in financial reporting systems. These findings support initial hypotheses on the lack of homogeneity in the quality of financial reporting in the selected region, despite the implementation of international standards. Full article

This study investigates the predictive performance of financial indicators in forecasting stock prices within the automotive sector using an adaptive neuro-fuzzy inference system (ANFIS). In light of the growing complexity of global financial markets and the increasing demand for automated, data-driven forecasting models, this research aims to identify those financial ratios that most accurately reflect price dynamics in this specific industry. The model incorporates four widely used financial indicators, return on assets (ROA), return on equity (ROE), earnings per share (EPS), and profit margin (PM), as inputs. The analysis is based on real financial and market data from automotive companies, and model performance was assessed using RMSE, nRMSE, and confidence intervals. The results indicate that the full model, including all four indicators, achieved the highest accuracy and prediction stability, while the exclusion of ROA or ROE significantly deteriorated model performance. These findings challenge the weak-form efficiency hypothesis and underscore the relevance of firm-level fundamentals in stock price formation. This study’s sector-specific approach highlights the importance of tailoring predictive models to industry characteristics, offering implications for both financial modeling and investment strategies. Future research directions include expanding the indicator set, increasing the sample size, and testing the model across additional industry domains. Full article

The use of eco-organic ingredients as a source of protein in aquaculture diets needs important attention due to the growing demand for organic seafood products. The present study evaluated the effects of fish meal substitution by different organic ingredients on the growth, body composition, retention efficiency, enzyme activity, and nutrient digestibility of white shrimp Penaeus vannamei. The four dietary formulations tested were formulated with organic ingredients and the fish meal was replaced by the following organic protein meals: Iberian pig viscera meal (PIG), trout by-product meal (TRO), insect meal (FLY), and organic vegetable meal (WHT), in addition to a control diet (CON) that included 15% fish meal. A growth trial was carried out for 83 days, raising 1 g shrimp to commercial size (20 g). Shrimp were stocked at 167 shrimp/m³ (15 individuals per 90 L tank). The results showed that the growth obtained by shrimp fed with TRO (19.27 g) and PIG (19.35 g) were similar in weight gain to the control diet (20.76 g), while FLY (16.04 g) and WHT (16.73 g) meals resulted in a significant lower final weight. The FLY diet showed significantly lower protein digestibility (68.89%) compared to the CON, PIG, TRO, and WHT diets, and significantly higher trypsin activity (0.17 mU/g) compared to shrimp fed with the PIG, TRO, and WHT diets. Shrimp fed with WHT have a significantly lower body weight percentage of protein (19.69%) than shrimp fed with the WHT and TRO diets, and some significant differences in dietary aminoacidic levels affecting amino acid body composition. These results indicate that Iberian pig viscera and trout by-product meal can successfully replace fish meal in Pacific white shrimp aquaculture. Full article

This study proposes a novel Deep Reinforcement Learning (DRL) policy network structure for portfolio management called PortRSMs. PortRSMs employs stacked State-Space Models (SSMs) for the modeling of multi-scale continuous regime shifts in financial time series, striking a balance between exploring consistent distribution properties over short periods and maintaining sensitivity to sudden shocks in price sequences. PortRSMs also performs cross-asset regime fusion through hypergraph attention mechanisms, providing a more comprehensive state space for describing changes in asset correlations and co-integration. Experiments conducted on two different trading frequencies in the stock markets of the United States and Hong Kong show the superiority of PortRSMs compared to other approaches in terms of profitability, risk–return balancing, robustness, and the ability to handle sudden market shocks. Specifically, PortRSMs achieves up to a 0.03 improvement in the annual Sharpe ratio in the U.S. market, and up to a 0.12 improvement for the Hong Kong market compared to baseline methods. Full article

The ten-year fishing ban on the Yangtze River aims to restore aquatic biodiversity and rebuild fishery resources. Megalobrama skolkovii, a key species in the basin, was investigated using 2024 data to provide a preliminary assessment of its population structure, stock dynamics, and early recovery. Age analysis (n = 243) showed that 1–6-year-olds were dominated by fish aged 3 (35%), with few older than 4, indicating moderate structural truncation. Growth parameters modeled by the von Bertalanffy Growth Function yielded L_∞ = 61.89 cm and k = 0.25 year⁻¹, with a weight–growth inflection age of 4.4 years. Natural mortality (M = 0.48 year⁻¹) was estimated using Pauly’s empirical formula, and total mortality (Z = 0.55 year⁻¹) was estimated from the catch curve analysis. While fishing mortality (F) was statistically indistinguishable from zero, a plausible low-intensity fishing scenario was explored to assess potential impacts of residual activities. Length-based indicators (LBIs) showed P_mat = 46.05%, P_opt = 9.51%, and P_mega = 6.88%, suggesting reproductive recovery but incomplete structural restoration. These preliminary findings reveal an asymmetrical recovery trajectory, whereby physiological improvements and enhanced recruitment have occurred, yet full structural restoration remains incomplete. This underscores the need for continued, long-term conservation and monitoring to support population resilience. Full article

Broth cooking is a traditional pretreatment and ripening strategy for high-commercial-value dehydrated marine food, effectively enhancing its texture and rehydration properties. In this work, we characterized the structural information of Maillard reaction products (MRPs) derived from beef scrap stock and investigated their effects on the texture and rehydration performance of dehydrated abalone. The optical and structural properties of the MRPs were analyzed using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), transmission electron microscopy (TEM), and fluorescence spectroscopy. These MRPs showed osmosis in abalone processing including pretreatment and drying. Low-field nuclear magnetic resonance (LF-NMR) results revealed that MRP pretreatment improved the moisture migration and physicochemical properties of dehydrated abalone. These findings suggest that MRPs, owing to their high osmotic efficiency and nanoscale size, could serve as promising food additives and potential alternatives to traditional penetrating agents in the food industry, enhancing the rehydration performance of dried seafood and reducing quality deterioration. Full article

In the context of worsening climate change and biodiversity loss, forest carbon offset projects are viewed as important nature-based solutions to mitigate these trends. However, there is limited evidence on whether these projects provide net benefits for biodiversity conservation. This study uses a staggered difference-in-differences model with balanced panel data from 128 counties in Sichuan Province, China, spanning from 2000 to 2020, to examine whether these projects bring biodiversity conservation co-benefits. The results show that the implementation of forest carbon offset projects leads to a 55.1% decrease in the ecosystem service value of forest biodiversity, with the negative impact particularly pronounced in areas facing agricultural land use and livestock pressures. The dynamic effect tests indicate that the benefits of biodiversity conservation generally begin to decline significantly 5 years after project implementation. Additional analyses show that although projects certified under biodiversity conservation standards also exhibit negative effects, the magnitude of decline is substantially smaller compared to uncertified projects, and certified projects achieve greater carbon stock gains. Heterogeneity analysis demonstrates that projects employing native tree species show significant positive effects. Moreover, spatial econometric results demonstrate significant negative spillover effects within an 80 km radius surrounding the project sites, with the effect attenuating over distance. To maximize the potential of forest carbon offset projects in addressing both climate change and biodiversity loss, it is important to mitigate the negative impacts on biodiversity within and beyond project boundaries and to enhance the continuous monitoring of projects that have been certified for biodiversity conservation. Full article

Quantum finance, as a key application scenario of quantum computing, showcases multiple significant advantages of quantum machine learning over traditional machine learning methods. This paper first aims to overcome the limitations of the hidden quantum Markov model (HQMM) in handling continuous data and proposes an innovative method to convert continuous data into discrete-time sequence data. Second, a hybrid quantum computing model is developed to forecast stock market trends. The model was used to predict 15 stock indices from the Shanghai and Shenzhen Stock Exchanges between June 2018 and June 2021. Experimental results demonstrate that the proposed quantum model outperforms classical algorithmic models in handling higher complexity, achieving improved efficiency, reduced computation time, and superior predictive performance. This validation of quantum advantage in financial forecasting enables the practical deployment of quantum-inspired prediction models by investors and institutions in trading environments. This quantum-enhanced model empowers investors to predict market regimes (bullish/bearish/range-bound) using real-time data, enabling dynamic portfolio adjustments, optimized risk controls, and data-driven allocation shifts. Full article

Vaccination is the most effective method to counteract infectious diseases in farmed fish. It secures aquaculture production and safeguards the wild stock and aquatic ecosystem from catastrophic contagious diseases. In vaccine development, recombinant subunit vaccines are favorable candidates since they can be economically produced in large quantities without growing many pathogens, as in inactivated or attenuated vaccine production. However, recombinant subunit vaccines are often weak or deficient in immunogenicity, resulting in inadequate defenses against infections. Technologies that can increase the immunogenicity of recombinant subunit vaccines are in desperate need. Enhanced green fluorescence protein (EGFP) has a low antigenicity and is susceptible to folding changes and losing fluorescence after fusing with other proteins. Using these valuable features of EGFP, we comprehend two amphipathic alpha-helical peptides, AH1 and AH3, derived from Hepatitis C virus and Influenza A virus, respectively, that can induce high immune responses of their fused EGFP in fish without affecting their folding. AH3-EGFP has the most elevated cell binding, significantly 62% and 36% higher than EGFP and AH1-EGFP, respectively. Immunizations with AH1-EGFP or AH3-EGFP significantly induced higher anti-EGFP antibody levels 300–500-fold higher than EGFP immunization after the boost injection in rainbow trout. Our results suggest that AH1 and AH3 effectively increase the immunogenicity of EGFP without influencing its structure. Further validation of their value in other recombinant proteins is necessary to demonstrate their broader utility in enhancing the immunogenicity of subunit vaccines. We also suggest that EGFP and its variants are promising candidates for initially screening proper immunogenicity-enhancing peptides or proteins to advance recombinant subunit vaccine development. Full article

This review explores sexual aggression in broiler breeder males, aiming to synthesize existing scientific evidence regarding its causes, behavioral manifestations, and consequences, while addressing the genetic, neuroendocrine, and environmental mechanisms involved. Through an extensive analysis of scientific literature, the paper highlights that intensive genetic selection aimed at enhancing growth and productivity has resulted in unintended behavioral dysfunctions. These include the reduction or absence of courtship behavior, the occurrence of forced copulations, and a notable increase in injury rates among hens. Reproductive challenges observed in meat-type breeder flocks, in contrast to those in layer lines, appear to stem from selection practices that have overlooked traits related to mating behavior. Environmental and managerial conditions, including photoperiod manipulation, stocking density, nutritional imbalances, and the use of mixed-sex rearing systems, are also identified as contributing factors to the expression of sexual aggression. Furthermore, recent genetic findings indicate a potential link between inherited neurobehavioral factors and aggressive behavior, with the SORCS2 gene emerging as a relevant candidate. Based on these insights, the review emphasizes the importance of considering behavioral parameters in breeding programs in order to reconcile productivity objectives with animal welfare standards. Future research may benefit from a more integrative approach that combines behavioral, physiological, and genomic data to better understand and address the multifactorial nature of sexual aggression in poultry systems. Full article

This study investigates the spatial heterogeneity of carbon pools in young Betula sp. stands on former arable lands in the southern Moscow region, Russia. The findings could be useful for the current estimates and predictions of the carbon balance in such forest ecosystems. The research focuses on understanding the interactions between plant cover and the environment, i.e., how environmental factors such as stand density, tree diameter and height, light conditions, and soil properties affect ecosystem carbon pools. We also studied how heterogeneity in edaphic conditions affects the formation of plant cover, particularly tree regeneration and the development of ground layer vegetation. Field measurements were conducted on a permanent 50 × 50 m sampling plot divided into 5 × 5 m subplots, in order to capture variability in vegetation and soil characteristics. Key findings reveal significant differences in carbon stocks across subplots with varying stand densities and light conditions. This highlights the role of the spatial heterogeneity of soil properties and vegetation cover in carbon sequestration. The study demonstrates the feasibility of indirect estimation of carbon stocks using stand parameters (density, height, and diameter), with results that closely match direct measurements. The total ecosystem carbon stock was estimated at 80.47 t ha⁻¹, with the soil contribution exceeding that of living biomass and dead organic matter. This research emphasizes the importance of accounting for spatial heterogeneity in carbon assessments of post-agricultural ecosystems, providing a methodological framework for future studies. Full article

This study sought to quantify and characterize diverse rootstock scion interactions in cacao around graft compatibility, disease resistance, nutrient use efficiency, vigor traits, and translocation of nonstructural carbohydrates. In total, 106 grafts were performed with three scion cultivars (Matina 1/6, Criollo 22, Pound 7) and nine diverse open-pollinated seedling populations (BYNC, EQX 3348, GNV 360, IMC 14, PA 107, SCA 6, T 294, T 384, T 484). We found evidence for both local and translocated graft incompatibility. Cross sections and Micro-XCT imaging revealed anatomical anomalies, including necrosis and cavitation at the junction and accumulation of starch in the rootstock directly below the graft junction. Scion genetics were a significant factor in explaining differences in graft take, and graft take varied from 47% (Criollo 22) to 72% (Pound 7). Rootstock and scion identity both accounted for differences in survival over the course of the 30-month greenhouse study, with a low of 28.5% survival of Criollo 22 scions and a high of 72% for Pound 7 scions. Survival by rootstocks varied from 14.3% on GNV 360 to 100% survival on T 294 rootstock. A positive correlation of 0.34 (p = 0.098) was found between the graft success of different rootstock–scion combinations and their kinship coefficient, suggesting that relatedness of stock and scion could be a driver of incompatibility. Significant rootstock–scion effects were also observed for nutrient use efficiency, plant vigor, and resistance to Phytophthora palmivora. These findings, while preliminary in nature, highlight the potential of rootstock breeding to improve plant nutrition, resilience, and disease resistance in cacao. Full article

Accurate above-ground biomass (AGB) quantification is confounded by signal saturation and data fusion challenges, particularly in structurally complex ecosystems like bamboo forests. To address these gaps, this study developed a two-stage framework to map the AGB of Dendrocalamus giganteus in a subtropical mountain environment. This study first employed Empirical Bayesian Kriging Regression Prediction (EBKRP) to spatialize sparse GEDI and ICESat-2 LiDAR metrics using Sentinel-2 and topographic covariates. Subsequently, a stacked ensemble model, integrating four machine learning algorithms, predicted AGB from the full suite of continuous variables. The stacking model achieved high predictive accuracy (R² = 0.84, RMSE = 11.07 Mg ha⁻¹) and substantially mitigated the common bias of underestimating high AGB, improving the predicted observed regression slope from a base model average of 0.63 to 0.81. Furthermore, SHAP analysis provided mechanistic insights, identifying the canopy photon rate as the dominant predictor and quantifying the ecological thresholds governing AGB distribution. The mean AGB density was 71.8 ± 21.9 Mg ha⁻¹, with its spatial pattern influenced by elevation and human settlements. This research provides a robust framework for synergizing multi-source remote sensing data to improve AGB estimation, offering a refined methodological pathway for large-scale carbon stock assessments. Full article