Search Results (33)

Amid rising climate concerns, understanding how renewable energy adoption, human capital, fossil fuel efficiency, and globalization collectively shape CO₂ emissions is crucial for unlocking pathways to a cleaner, resilient, and globally connected low-carbon future. Using China as a case study, this research investigates the drivers of CO₂ emissions, focusing on fossil fuel efficiency, renewable energy adoption, and globalization, utilizing quarterly data from 1984Q1 to 2023Q4. To ensure robust and nuanced insights, the study integrates advanced machine learning techniques alongside Quantile-on-Quantile Kernel Regularized Least Squares (QQ-KRLS) and a Modified Quantile Regression as robustness checks, capturing complex distributional dynamics often overlooked in conventional analyses. To the authors’ knowledge, this is the first empirical study examining such relationships for the case of China. The results reveal that globalization, fossil fuel efficiency, renewable energy, human capital, and financial risk all contribute to increasing CO₂ emissions. The study proposes precise policies based on the findings obtained. Full article

Starting from ${\psi }_k$-Raina’s fractional integrals (${\psi }_k$-RFIs), the study obtains a new generalization of the Hermite–Hadamard–Mercer (H-H-M) inequality. Several trapezoid-type inequalities are constructed for functions whose derivatives of orders 1 and 2, in absolute value, are convex and involve ${\psi }_k$-RFIs. The results of the research are refinements of the Hermite–Hadamard (H-H) and H-H-M-type inequalities. For several types of fractional integrals—Riemann–Liouville (R-L), k-Riemann–Liouville (k-R-L), $\psi$-Riemann–Liouville ($\psi$-R-L), ${\psi }_k$-Riemann–Liouville (${\psi }_k$-R-L), Raina’s, k-Raina’s, and $\psi$-Raina’s fractional integrals ($\psi$-RFIs)—new inequalities of H-H and H-H-M-type are established, respectively. This article presents special cases of the main results and provides numerous examples with graphical illustrations to confirm the validity of the results. This study shows the efficiency of the findings with a couple of applications, taking into account the modified Bessel function and the q-digamma function. Full article

In recent years, the integration of industrial robotics has emerged as a powerful tool in reshaping industries by enhancing production efficiency, reducing waste generation, and optimizing resource utilization. However, industrial robotics, particularly in manufacturing and production, require significant energy that can potentially impact on environmental quality. Despite the growing adoption of artificial intelligence (AI)-based industrial robotics, there is a paucity of literature on the impact of industrial robotics on the ecological footprint (EF), particularly in the context of advanced economies. In this context, this study aims to investigate the impact of industrial robotics, resource efficiency, energy transition, and geopolitical risk EF in G7 countries from 1993 to 2021. The study employed advanced econometric techniques, including Kernel-based Regularized Least Squares (KRLS) and Artificial Neural Network (ANN) machine learning methods. The results unveiled that industrial robotics significantly curtail environmental degradation by impeding the EF. Resource efficiency and energy transition posed a significant and negative impact on the EF. Geopolitical risks and economic growth exacerbate the EF. Based on the results, the study proposes important policy implications for achieving sustainable development. Full article

South Africa’s national development plan has outlined aspirations to achieve a sustainable environment. However, the country remains bound for an unsustainable trajectory. Despite this ecological issue, no studies have probed how biomass and coal energy impact ecological quality. In light of this gap, this study inspects the environmental effect of political risk, coal energy, and biomass energy in South Africa. Also, this study integrates economic growth and natural resources into its framework. This study uses the load capacity factor (LC), which is a more aggregate proxy of ecological quality due to its accounting for the demand and supply aspect of the environment. This study uses the dynamic autoregressive distributive lag estimator (ARDL), which is capable of not only providing details of the influence of each determinant on LC in the long and short term but also of capturing the counterfactual shock of positive or negative exogenous variables on the LC. The kernel regularized least squares (KRLS) method is used for a robustness analysis of the dynamic ARDL approach. Furthermore, the findings of the dynamic ARDL simulation estimator disclose the negative impact of economic growth on the LC, thereby contributing to environmental deterioration by 0.552%. Natural resources and coal energy have an adverse impact on the LC, indicating a reduction in environmental sustainability by 0.037% and 0.290%, respectively. Meanwhile, biomass contributes to the LC, thereby promoting ecological quality by 0.421%. Political risk contributes to the reduction in the LC. This research provides pertinent policy considerations for policymakers and governments in South Africa, suggesting that the government of South Africa should invest in biomass energy and sustainable extraction procedures since biomass energy has a vital role in increasing ecological quality. Full article

The goal of this study is to develop numerous Hermite–Hadamard–Mercer (H–H–M)-type inequalities involving various fractional integral operators, including classical, Riemann–Liouville (R.L), k-Riemann–Liouville (k-R.L), and their generalized fractional integral operators. In addition, we establish a number of corresponding fractional integral inequalities for three-times differentiable convex functions that are connected to the right side of the H–H–M-type inequality. For these results, further remarks and observations are provided. Following that, a couple of graphical representations are shown to highlight the key findings of our study. Finally, some applications on special means are shown to demonstrate the effectiveness of our inequalities. Full article

While there is a vast body of literature on environmental sustainability, the disaggregated impact of major non-renewable energy (NRE) consumption on the environmental sustainability of the United States (U.S.) is understudied, particularly in terms of using a load capacity factor (LCF) perspective. In this study, the above research gap is addressed using a dynamic autoregressive distributed lag (DYNARDL) model to analyze the heterogeneous impact of NRE consumption on the environmental sustainability of the U.S. from 1961 to 2022. Given the U.S.’s heavy reliance on energy consumption from NRE sources, this analysis provides an in-depth examination of the long-term effects of this energy consumption on the environment. Based on the analysis of the DYNARDL model, it is found that an increase of one unit of coal, natural gas, and petroleum energy consumption reduces environmental sustainability by 0.007, 0.006, and 0.008 units in the short-run and 0.006, 0.004, and 0.005 units in the long-run, respectively. However, one unit of nuclear energy consumption increases environmental sustainability by 0.007 units in the long-run. The kernel-based regularized system (KRLS) result reveals that coal and petroleum energy consumption have a significantly negative causal link with environmental sustainability, while nuclear energy consumption demonstrates a significant positive causal relationship. The research suggests the expansion of the use of nuclear energy by gradually reducing the utilization of coal and petroleum-based forms of energy, then natural gas, to improve environmental sustainability in the U.S., while considering the social and economic implications of efforts aimed at shifting away from the use of fossil fuels. Full article

This study aimed to assess the effect of dietary supplementation of a mixture of botanical compounds and essential oil (Phyto AquaMeric, PAM) on the growth, immune and antioxidant parameters and environmental benefits in Nile tilapia. Two diets including a control and a PAM-supplemented diet at 0.5 g kg⁻¹ were prepared for the trial. The diets were isonitrogenous (30% crude protein) and isoenergetic (17 MJ kg⁻¹) extruded diets. Nile tilapia weighing initially 74.22 ± 1.96 g fish⁻¹ were stocked in 2 m³ hapas at a density of 20 fish per m³ (40 fish per hapa). Each group was tested in triplicates over 80 days. The antioxidant potential of PAM was compared to vitamin C through KRL test, showing a higher value from 35 to 100 mg. The in vivo trial did not exhibit any significant growth performance improvement. However, the PAM group had a significantly improved feed conversion ratio (FCR) and protein efficiency ratio (PER). Moreover, the antioxidant enzymes superoxide dismutase (SOD) and glutathione peroxidase (GPx), Malondialdehyde (MDA), immune parameters (ACH50, lysozyme, phagocytic and phenoloxidase activities), digestive enzymes and hepatic enzymes were significantly improved in the PAM-fed group. An evaluation of eutrophication potential of PAM supplementation revealed a low input in the system. In conclusion, this mixture of botanicals and essential oil exhibited in vitro and in vivo antioxidant potential, improved health and digestive parameters and contributed to a reduced eutrophication risk in the tilapia production system. Full article

Understanding the changes in the root system architecture of bread wheat under phosphorus (P)-limited conditions is critical for identifying specific traits contributing to improved P uptake. Phenotypic variability in root, biomass, and P index-related traits among 204 diverse wheat genotypes at the seedling stage was examined under low and optimum P treatments. Strong genotypic and phenotypic associations between P utilization efficiency (PUtE) and total root volume, dry weight of root and shoot, total P uptake, and total plant biomass were observed under optimum P. Under low P, strong positive correlations between PUtE and total root length, total root volume, total surface area, and total biomass were observed, while it was negatively correlated with average diameter. These traits exhibited medium to high heritability. Under low P, average root diameter, primary root length, root mass ratio, total root tips, and surface area showed high Shannon–Weaver diversity index (H’) values (>0.79). The agglomerative hierarchical clustering analysis grouped the genotypes into four distinct clusters. The best performing genotypes in Clusters I and II indicated their strong relationship with P use efficiency due to higher percent increases in total root length, total surface area, total root volume, total root tips, total biomass, P efficiency ratio, specific root length, and PUtE under low P as compared to optimum P conditions. The present study identified specific root system architectural traits and P use-efficient genotypes (SHANGHAI, Pavon F76, BWL 5233, SONALIKA, KHARCHIA LOCAL, WH 102, BWL 4425, HD 2888.2, CBW 12, MN75136/PGO, KRL 19, and WH 1022) associated with efficient P uptake and utilization. These identified genotypes and traits may be useful in wheat breeding programs to develop P-efficient varieties with better adaptations for sustainable agriculture. Full article

Crops grown on salt-affected soils may experience physiological drought stress, ion toxicity, and mineral shortage, resulting in lower growth and output. Salinity is the most important abiotic factor limiting crop development and output globally. Improving agri-food production in salt-prone locations is critical for meeting rising food demands in the near future. A pot experiment was conducted to study the impact of saline irrigation water on the chemical properties of sandy loam soil and their influence on growth, yield, and other biometric parameters of wheat (Triticum aestivum L.), Cv KRL 213 in the farmer’s field at Karnal. Three irrigation water treatments, i.e., Tube well water (TW), saline water (SW1, EC_iw 10.0 dS m⁻¹, SAR 5.0 mmol^1/2 L^−1/2), and concentrated saline water (SW2, EC_iw 10.0 dS m⁻¹, SAR 5.0 mmol^1/2L^−1/2), were applied in reclaimed normal soil (pHs 7.5 and ECe 1.0 dS m⁻¹). The results showed that, when low-quality water was applied to normal soil, salt increased, increasing the likelihood of normal soil deterioration. Continuous irrigation with concentrated salt water (SW2) raised the ECe of the root zone soil, which had a negative impact on wheat crop mortality (approximately 70%). In post-wheat samples, soil organic carbon, calcium carbonate, and cation exchange capacity (CEC) remained constant across all water treatments. Concentrated salty water (SW2) is not advised on its own, but it can be used in conjunction with other management practices (by mixing with rain, pond, or canal water) to reduce the negative impacts on soil chemical characteristics and crop development. Full article

Vitamin E is an essential nutrient usually recommended in post-weaning piglets, when a decline in the serum vitamin E concentration is observed. Selected polyphenols have the potential to partially replace vitamin E in animal feed. The aim of this study was to investigate the effect of the dietary inclusion of some commercial polyphenol products (PPs) on the growth performance, antioxidant status and immunity of post-weaning piglets. A total of 300 piglets (BW 7.18 kg ± 1.18) were randomly assigned to six dietary groups: CON⁻ (40 mg/kg vitamin E); CON⁺(175.8 mg/kg vitamin E); and PP1, PP2, PP3 and PP4, in which 50% vitamin E of CON⁺ was replaced with PP with equivalent vitamin E activity. The PP1 group exhibited lower performance (p < 0.05) than the other dietary groups, but a similar performance to that commonly registered in pig farms. Dietary polyphenols did not influence the IgG concentration or the IL-6, IL-10, IFN-γ and TNF-α cytokine concentrations. A lower IL-8 level was found in the PP4 group than in the other groups. The diets that affected the vitamin A content showed the highest value (p < 0.05) in the PP1 group, and a trend was noted for vitamin E with a higher content in PP4 and CON⁺. The polyphenols-enriched diets, especially the PP3 diet, maintained an antioxidant capacity (whole blood KRL) similar to the CON⁺ diet. In conclusion, the replacement of vitamin E with all PPs enables partial vitamin E substitution in post-weaning piglets. Full article

The accuracy of X-ray fluorescence spectrometry in quantitative element analysis depends on the particular sample composition (so-called matrix effects). Counteracting these effects requires a large number of calibration samples similar in composition to those under analysis. Application of the model constructed for a particular type of samples is not possible for the analysis of samples having a different matrix composition. A possible solution for this problem can be found in the construction of universal calibration models. We propose the development of these universal models using chemometric tools: influence coefficients—partial least squares regression (IC-PLS) and nonlinear kernel regularized least squares regression. We hypothesize that the application of these methods for constructing calibration models would allow embracing the samples of different types in the framework of a single model. We explored this approach for the case of two substantially different types of samples: ores and steels. The performance of these methods was compared with the fundamental parameters (FP) method, which takes into account matrix effects using theoretical equations and allows handling samples of different elemental composition. IC-PLS significantly outperforms traditional FP in terms of accuracy for predicting the content of Al (root mean squared error of prediction 0.96% vs. 3.87%) and Ti (0.05% vs. 0.09%) and yields comparable results for Si and Mn quantification in ores and steels. Full article

In the frame of fractional calculus, the term convexity is primarily utilized to address several challenges in both pure and applied research. The main focus and objective of this review paper is to present Hermite–Hadamard (H-H)-type inequalities involving a variety of classes of convexities pertaining to fractional integral operators. Included in the various classes of convexities are classical convex functions, m-convex functions, r-convex functions, $(\alpha ,m)$-convex functions, $(\alpha ,m)$-geometrically convex functions, harmonically convex functions, harmonically symmetric functions, harmonically $(\theta ,m)$-convex functions, m-harmonic harmonically convex functions, $(s,r)$-convex functions, arithmetic–geometric convex functions, logarithmically convex functions, $(\alpha ,m)$-logarithmically convex functions, geometric–arithmetically s-convex functions, s-convex functions, Godunova–Levin-convex functions, differentiable $\varphi$-convex functions, $MT$-convex functions, $(s,m)$-convex functions, p-convex functions, h-convex functions, $\sigma$-convex functions, exponential-convex functions, exponential-type convex functions, refined exponential-type convex functions, n-polynomial convex functions, $\sigma ,s$-convex functions, modified $(p,h)$-convex functions, co-ordinated-convex functions, relative-convex functions, quasi-convex functions, $(\alpha ,h-m)-p$-convex functions, and preinvex functions. Included in the fractional integral operators are Riemann–Liouville (R-L) fractional integral, Katugampola fractional integral, k-R-L fractional integral, $(k,s)$-R-L fractional integral, Caputo-Fabrizio (C-F) fractional integral, R-L fractional integrals of a function with respect to another function, Hadamard fractional integral, and Raina fractional integral operator. Full article

This study was conducted at two farmers’ fields to assess the production potential and quality of summer fodder sorghum intervened between the rice-wheat cropping sequences (RWCS) on high residual alkalinity, i.e., residual sodium carbonate (RSC) water irrigation-induced sodic soil. The treatments were comprised of two field sites having different residual alkalinity [RSC ~5 me L⁻¹ (RSC-1) and ~7 me L⁻¹ (RSC-2) water irrigation in main plots, four neutralization strategies, i.e., control/unamended condition (N₀), gypsum @ 7.5 t ha⁻¹ (N₁), pressmud @ 10 t ha⁻¹ (N₂) and gypsum @ 3.75 t ha⁻¹ + pressmud @ 5 t ha⁻¹ (N₃) in sub plots and two varietal sequences of RWCS, i.e., salt tolerant varieties (CSR 30 basmati fb KRL 210) and traditionally grown varieties (PB 1121 fb HD 2967) of rice and wheat as sub–sub plots. Sorghum cv. Sugargraze (Advanta Company) was grown after the harvesting of wheat and cut for green fodder before transplanting rice during both years. Sorghum physiological and biochemical traits [relative water content (RWC), total chlorophyll content, photosynthetic rate (Pn), stomatal conductance (gS), transpiration rate (E), chlorophyll fluorescence (Fv/Fm), photon quantum yield [Y (II)] and K/Na ratio]; fodder quality traits [Crude protein (CP), and ether extract (EE)] and productivity [green fodder yield (GFY), dry matter yield, CP yield, EE yield and ash yield) and profitability (gross returns, net returns, benefit–cost ratio) significantly decreased with the increase in irrigation water RSC from 5 to 7 me L⁻¹. Proline, total soluble sugar (TSS), total soluble protein (TSP), dry matter (DM), ash, neutral detergent fibre (NDF), acid detergent fibre (ADF), acid detergent lignin (ADL), neutral detergent insoluble CP (NDICP) and acid detergent insoluble CP (ADICP) decreased with increasing RSC of irrigation water. Sodicity neutralization considerably improved sorghum physiological adaptation mechanisms, fodder quality, productivity and profitability. The introduction of summer fodder sorghum between RWCS resulted in additional net returns (NR) (INR 13.64 to 20.79 × 10³ ha⁻¹). Our results indicate that pressmud proved a feasible alternative to replace and/or reduce the quantity of gypsum required for neutralization of RSC water irrigation. Growing summer fodder sorghum between RWCS along with neutralization of RSC water irrigation can increase the availability of quality green fodder during lean period and also increase the profitability of the rice-wheat cropping system in high residual alkalinity water irrigation conditions. Full article

Different wellbeing measures have been used among cancer patients. This study aimed to first investigate the sensitivity of health state utility (HSU), capability, and subjective wellbeing (SWB) instruments in cancer. A cancer-specific instrument (QLQ-C30) was included and transferred onto the cancer-specific HSU scores. Furthermore, it examined the relative importance of key life domains explaining overall life satisfaction. Data were drawn from the Multi-instrument Comparison survey. Linear regression was used to explore the extent to which the QLQ-C30 sub-scales explain HSU and SWB. Kernel-based Regularized Least Squares (KRLS), a machine learning method, was used to explore the life domain importance of cancer patients. As expected, the QLQ-C30 sub-scales explained the vast majority of the variance in its derived cancer-specific HSU (R² = 0.96), followed by generic HSU instruments (R² of 0.65–0.73) and SWB and capability instruments (R² of 0.33–0.48). The cancer-specific measure was more closely correlated with generic HSU than SWB measures, owing to the construction of these instruments. In addition to health, life achievements, relationships, the standard of living, and future security all play an important role in explaining the overall life satisfaction of cancer patients. Full article

Knowledge Graphs (KGs), a structural way to model human knowledge, have been a critical component of many artificial intelligence applications. Many KG-based tasks are built using knowledge representation learning, which embeds KG entities and relations into a low-dimensional semantic space. However, the quality of representation learning is often limited by the heterogeneity and sparsity of real-world KGs. Multi-KG representation learning, which utilizes KGs from different sources collaboratively, presents one promising solution. In this paper, we propose a simple, but effective iterative method that post-processes pre-trained knowledge graph embedding (IPPT4KRL) on individual KGs to maximize the knowledge transfer from another KG when a small portion of alignment information is introduced. Specifically, additional triples are iteratively included in the post-processing based on their adjacencies to the cross-KG alignments to refine the pre-trained embedding space of individual KGs. We also provide the benchmarking results of existing multi-KG representation learning methods on several generated and well-known datasets. The empirical results of the link prediction task on these datasets show that the proposed IPPT4KRL method achieved comparable and even superior results when compared against more complex methods in multi-KG representation learning. Full article