Search Results (1,528)

Rice (Oryza sativa L.) grain quality is a critical determinant of market value, consumer acceptance, and nutritional security. This multifaceted trait is governed by the dynamic interaction of genotype (G), environment (E), and management practices (M). In this review, we synthesize recent advances in understanding these multifaceted determinants. We first delineate the genetic architecture, emphasizing key genes and quantitative trait loci (QTLs) such as Wx, ALK, Chalk5, and the GS3/GW families, which control starch composition, gelatinization temperature, chalkiness, and grain dimensions, forming the foundational blueprint for quality potential. We examine how this genetic potential is influenced by environmental factors, focusing on the detrimental impacts of abiotic stresses, particularly high temperatures during grain filling and drought, which impair milling yield, increase chalkiness, and modify starch and protein profiles. Furthermore, we discuss how optimized agronomic strategies—including precision water management (e.g., alternate wetting and drying), balanced nitrogen fertilization, and targeted micronutrient (e.g., silicon) application—can mitigate these adverse effects and potentially improve specific quality parameters. Post-harvest handling is identified as the final determinant of product quality. We conclude that achieving high and stable rice quality under climate variability requires an integrated G × E × M approach. Prospects include next-generation breeding for climate-resilient quality, precision agronomy guided by real-time sensing, synergistic soil health management, and the integration of systems biology with digital agriculture to design sustainable, high-quality rice production systems. Full article

The upscaling of turbines in the offshore wind industry has been unprecedented, as compared to 5–6 MW rated turbines 10 years ago. A typical 20–26 MW rated turbine in modern commercial applications (MingYang MySE 18.X-20 MW installed in 2025 and 26 MW prototype by Dongfang Electric tested in 2025) has been demonstrated. This scaling has been made possible by increasing rotor diameters (>250 m) and hub heights (>150–180 m) to achieve capacity factors of up to 55–65%, annual energy generation of more than 80 GWh/turbine, and significant decreases in levelised cost of energy (LCOE) to current values of up to 63–65 USD 2023/MWh globally averaged in 2023 (with minor variability in 2024 due to market changes and new regional areas). The paper analyses turbine upscaling over three levels of hierarchy, including turbine scale—rated capacity and physical aspect, project scale—multi-gigawatts of farms, and market scale—the global pipeline > 1500 GW level, and combines techno-economic evaluation, structural evaluation of loads, and infrastructure needs assessment. The upscaling has the advantage of reducing the number of turbines dramatically (e.g., 500 to 67 turbines in a 1 GW farm, as turbine size is increased to 15 MW) and balancing-of-plant (BoP) CAPEX (turbine-to-turbine foundations and cables) by some 20 to 30 percent per unit of capacity, and serial production learning rates of between 15 and 18% per doubling of capacity. But the problems that come with the increase in ultra-large designs are nonlinear increments in mass and load (i.e., blade-root and tower-bending moments), logistical constraints (blades > 120 m, nacelle up to 800–1000 tonnes demanding special vessels and ports), supply-chain issues (rare-earth materials, vessel shortages increase day rates by 30–50%), and technology limitations (aeroelastic compounded by numerical differences between reference 5 MW, 10 MW, and 15 MW models), it becomes evident that there is a significant increase in deflections of the tower and blades and platform surge/pitch responses with continued increases in power levels, but without a correspondingly mature infrastructure. The regional differences (mature ports of Europe vs. U.S. Jones Act restrictions vs. scale-up of vessels/manufacturing in China) lead to the necessity of optimisation depending on the context. The analysis concludes that, to the extent of mature markets with adapted logistics, continuous upscaling is an effective business strategy and can result in 5 to 12 percent further reductions in LCOE, but beyond that point, gains become marginal or even negative, as risks and costs increase. The competitiveness of the future depends on multi-scale/multi-market-based approaches—modular-based families of turbines, programmatic standardisation, vibration control innovations, and industry coordination towards supply-chain alignment and standards. Its major strength is that it transcends mere size–cost relationships and shows how nonlinear structural processes, aero-hydro-servo-elastic interactions, and bottlenecks in logistical systems are becoming more determinant of the efficiency of ultra-large turbines. The study demonstrates that upscaling turbines has LCOE benefits through the support of associated improvements in installation facility, supply-chain preparedness, and structural vibration control potential, based on the comparisons of quantitative loads, techno-economic scaling trends, and regional market differentiation. Full article

The European Union aims to cut greenhouse gas emissions by 55% by 2030 and reach climate neutrality by 2050, targets that depend on expanding renewable generation in the European energy system. While photovoltaic (PV) capacity has grown quickly in several member states, others remain far behind. This paper frames that divergence as a systems planning problem: installed MW expands through diffusion-like dynamics, but the conversion of investment into energizable capacity is filtered by grid-integration constraints and institutional throughput. The study develops a macro-level framework for systems-level assessment and decision support to guide PV capacity planning and budget allocation using official 2012–2022 data for 22 EU countries. We combine (i) unsupervised clustering of standardized national deployment trajectories, (ii) bounded logistic fits interpreted as an operational diffusion-with-saturation representation that yield comparable growth parameters and maturity years (80–90% of the estimated ceiling), and (iii) a proportional reallocation scenario for countries below 5 GW in 2022. Three clusters emerge—steady growth, early plateau, and atypical paths—and an analytically tractable maturity indicator integrates capacity, rate, and timing in a single measure. In a 10 GW reallocation scenario, average progress toward the 5 GW benchmark rises from 9.8% to 23.1%, closing about 14.8% of the aggregate shortfall. The allocation experiment reveals a clear asymmetry: systems with an existing installed base convert additional MW into benchmark progress more efficiently than very low-baseline systems, where binding constraints are more likely to sit in permitting, interconnection queues, and hosting capacity rather than in finance alone. Turning these allocations into usable capacity depends on timely interconnection and power-electronics integration and on grid-enablement constraints such as interconnection readiness, inverter compliance, and local hosting capacity in high-penetration areas. The contribution is a transparent, updateable decision-support pipeline that links observed trajectory regimes to a maturity “clock” and an auditable allocation baseline, making the trade-off between closing capacity gaps and respecting feasibility filters explicit in an EU system with heterogeneous national subsystems. The proposed approach links macro-level maturity clusters to operational feasibility signals in the grid integration layer, showing that modeling-based allocation can improve system progress but cannot substitute grid-enablement measures, highlighting the importance of regional coordination in the EU energy system under heterogeneous national trajectories. Full article

The possibility of realizing Higgs inflation in a model with a small non-minimal coupling constant, which was demonstrated recently, provides grounds for further development of the model. Incorporating the electroweak SM into the Two-Measure theory (TMT) in a way that fully accounts for the TMT structure leads to a theory we call the Two-Measure Standard Model (TMSM). The TMSM is realized in the context of cosmology as a set of cosmologically modified copies of the Glashow–Weinberg–Salam (GWS) theory, such that each of the copies exists as a local quantum field theory defined on the classical cosmological background at the appropriate stage of its evolution. This basic idea is studied in detail for two stages of the cosmological background evolution: for slow-roll inflation and for the stage of approaching the vacuum. Mainly due to the presence of the ratio of two volume measures in all equations of motion, all TMSM coupling constants turn into a kind of “running” (classical) TMT-effective parameters. During the evolution of the cosmological background, changing these parameters yields new results: (1) the classical “running” TMT-effective Higgs self-coupling parameter increases from $\lambda \sim {10}^{-11}$ (which provides Higgs inflation consistent with the Planck CMB data at $\xi ={\displaystyle \frac{1}{6}}$) to $\lambda \sim 0.1$ at the stage close to the vacuum; (2) the mass term in the TMT-effective Higgs potential changes sign from positive to negative, which provides SSB in the standard way of GWS theory; (3) the classical “running” parameters of the gauge and Yukawa couplings change by several orders of magnitude; (4) the GWS theory is reproduced when the Yukawa constant in the original action is chosen to be universal for three generations of fermions. We show that, due to these classical-level results, taking into account quantum corrections in the one-loop approximation preserves the slow-roll inflation regime and does not violate the vacuum stability during inflation. Full article

Hydropower capacity in the United States currently stands at approximately 103 GW, and there are remaining water resources that could help meet the rapidly increasing demand for electricity and ancillary grid services. Existing dams that do not generate power, known as non-powered dams, are a near-term solution to enhance the contribution of hydropower to the US power grid. However, there are thousands of such sites, and the lack of detailed information about their specific characteristics and associated costs presents significant challenges for stakeholders. This study addresses these challenges by developing a reference site model to evaluate the potential costs of hydropower at non-powered dams using currently available technologies. An application of the model reveals a wide range of estimates for capacity, capital costs, levelized cost of electricity, and cost components. While many sites are competitive with current technologies, the majority would need cost-reducing innovations to be viable. Despite the limited available information, the model offers valuable insights into the relative competitiveness of hydropower projects at non-powered dams. The simulation results highlight the need for continued technological advancements in hydropower and provide a basis for evaluating the benefits of new innovations. Full article

China’s power sector is undergoing a complicated transformation characterized by intricate dependence on the dominant coal infrastructure and abundant renewable energy resources. This study assesses China’s carbon-neutral transition pathways for the period of 2024–2060 by using the “Establish Before Breaking” principle within a policy-informed, high-resolution energy system modeling framework. To examine the technological, economic, and environmental trade-offs of various carbon-neutral strategies, four scenarios (Reference (REF), Carbon Capture and Storage (CCS), Renewable-Based (REB), and Integrated (ING)) were developed, and their impacts were assessed through the application of the Low Emission Analysis Platform and the Next Energy Modeling (LEAP–NEMO) model. The results reveal that the ING scenario represents the most feasible and policy-consistent pathway, achieving an 88% renewable electricity share and a total installed capacity of approximately 8000 gigawatts (GW) by 2060. This pathway relies on a dual-track strategy that combines accelerated renewable deployment—supported by geographical complementarity and multi-regional Power-to-X (PtX) systems—with the strategic stabilization of conventional generation assets. The findings further demonstrate that retaining a small but critical share of flexible coal-CCS (0.2–0.5%) and nuclear capacity is necessary to address sub-daily variability, mitigate duck-curve effects, and ensure power system reliability under high renewable penetration. This integrated approach offers a systematic pathway for deep decarbonization within China’s unique energy context, ensuring a just, equitable, and sustainable transition. Full article

The orbital dynamics of compact-object binaries composed of neutron stars (NSs) and white dwarfs (WDs) can be influenced by the gravitational interaction with the gas of dark matter (DM) particles, generating dynamical friction. We discuss the orbital dynamics of detached binaries, quantifying the effect of dynamical friction from DM relative to that driven solely by gravitational-wave emission in vacuum. We focus on fermionic DM within the Ruffini–Arguelles–Rueda (RAR) model, for a fermion of rest-mass in the range 56–300 keV. We find that, for NS-NS, NS-WD, and WD-WD with parameters similar to those of J0737-3039, J0348+0432, and J0651+2844, the DM dynamical friction becomes detectable by space-based GW interferometers such as LISA and TianQin for binaries within a few milliparsec from the Galactic center, and could even dominate the orbital dynamics. Full article

Core-collapse supernovae (CCSNe) remain a critical focus in the search for gravitational waves in modern astronomy. Their detection and subsequent analysis will enhance our understanding of the explosion mechanisms in massive stars. This paper investigates the use of convolutional neural networks (CNN) to enhance the detection of gravitational waves originating from CCSNe. We employ two time–frequency analysis techniques to generate spectrograms (training data): short-time Fourier transform (STFT) and Q-transform (QT). Two CNNs were trained independently on sets of spectrogram images of simulated CCSNe signals and advanced LIGO noise. The CNNs detect CCSNe signals based on their time–frequency representation. Both CNNs achieve a near 100% true positive rate for CCSNe GW events with a signal-to-noise ratio greater than 0.5 in our test set. Nevertheless, the CNN trained on the STFT spectrograms outperforms the one based on the Q-transform for SNRs below 0.5. Full article

With the global population predicted to reach 10 billion by 2050, pesticides are essential for agricultural production. However, they can introduce chemical stressors into aquatic ecosystems. Chlorpyrifos (CPF) is a widely used organophosphate insecticide that can enter aquatic environments and poses potential risks to early-life-stage fish. Because the retina is an extension of the central nervous system and vision-guided behaviors are highly sensitive to neural dysfunction, we hypothesized that CPF exposure disrupts neurobehavioral and visual function via oxidative stress and PPARα-related signaling. Zebrafish larvae were exposed to CPF (0.01, 0.1, 1, 10, and 100 μg/L) with a vehicle control (VC). During the photomotor response assay, exposure to 100 μg/L CPF reduced overall swimming activity by 48.90% and dark-period activity by 57.71%, whereas 1 μg/L CPF modestly increased total distance by 6.96% (p = 0.003) and dark-period distance by 5.40% (p = 0.011). Transcriptomic profiling highlighted nervous- and vision-related functional categories, and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment implicated pathways including gonadotropin-releasing hormone (GnRH), mitogen-activated protein kinase (MAPK), and peroxisome proliferator-activated receptor (PPAR) signaling. Targeted neurotransmitter metabolomics showed significant increases in dopamine, γ-aminobutyric acid (GABA), and acetylcholine across treatment groups, indicating broad neurotransmitter dysregulation. Consistent with these findings, neuronal fluorescence in Tg (elavl3: EGFP) larvae decreased by 12.1% and 32.5% in the 1 and 100 μg/L groups, respectively (p < 0.001), and glial fibrillary acidic protein (GFAP) immunofluorescence increased in the eye/brain/olfactory bulb at 1 μg/L (p = 0.037) and 100 μg/L (p = 0.002). Histology further showed retinal injury, with a 14.3% reduction in photoreceptor layer thickness at 100 μg/L (p = 0.034). Mechanistically, coexposure to a PPARα antagonist (GW6471) alleviated CPF-induced behavioral deficits (1.80-fold increase in dark locomotion) and reduced elevated GABA and dopamine levels by 36.8% and 47.3%, respectively. Together, these results indicate that CPF can impair neuro-visual development and that oxidative stress and PPARα-related signaling are closely associated with these effects. Full article

Bio-CO₂ is part of the natural carbon cycle and represents a sustainable carbon source for the production of Renewable Fuels of Non-Biological Origin (RFNBOs), such as synthetic methanol. This study addresses the critical knowledge gap in aligning diverse biogenic CO₂ sources with e-methanol requirements in the EU by providing harmonized mapping, based on datasets, literature sources, and reported industrial statistics at the sectoral and country level. Bio-CO₂ streams from biogas and biogas upgrading, biomass combustion, pulp and paper, bioethanol production, and the food and beverage sector are evaluated for total emissions, CO₂ concentrations and purity, the geographical distribution, seasonality, and impurity profiles. Results show that approximately 350 Mtpa of bio-CO₂ are emitted across the EU, with highly heterogeneous characteristics. Biogas upgrading and fermentation-based processes generate highly pure CO₂ streams (>98–99%), yet their small and dispersed nature complicates logistics. In contrast, biomass-combustion and pulp and paper sectors provide large volumes (around 214.6–298.2 Mtpa and 73.9 Mtpa CO₂, respectively), but in diluted streams (typically 3–15% and 10–20%). Replacing just 10% of the EU maritime fuel demand with e-methanol would require 53.6 Mtpa of bio-CO₂ and 58 GW of electrolyzer capacity, a stark contrast to the current operational 385 MW. The findings highlight the need for infrastructure planning and aggregation hubs to enable the large-scale deployment of RFNBO methanol in the maritime sector. Full article

Renewable energy sources (RES) will be the main source of energy in the future. The main goal of this study was to analyze and elaborate a prognosis for the development of renewable energy sources in Poland. Specific objectives included: evaluation of the prognosis developed as part of Poland’s energy policy (PEP), development of our own forecast of the share of renewable energy sources, and comparison of the forecast developed for Poland’s energy policy with our own forecast. We have also elaborated a hypothesis that the prognosis for the development of renewable energy sources for Poland prepared by PEP, and our own prognosis based on Autoregressive Moving Average (ARIMA) models, are both promising and confirm the development of the renewable energy sector in the future. We used the Augmented Dickey–Fuller (ADF) test as well as ARIMA models. Moreover, we compared own RES prognosis with prognoses proposed by the European Union. Cumulative capital expenditures from 2021 to 2040, including financing costs, will amount to PLN 300 billion, of which PLN 195 billion go towards renewable energy sources alone. Photovoltaics (PV) will account for the largest share of energy production, reaching 16 GW of achievable capacity, followed by onshore wind farms with 9.7 GW. Solid biomass accounts for the largest share of renewable energy consumption in heating and cooling, although its share is gradually decreasing from 98.6% in 2005 to a projected 75% in 2040. Heat pumps, which had no share in 2005, are expected to increase their share to a projected 11.8% in 2040. Solar technology has also increased from 0% in 2005 to a projected 5.6% in 2040. The share of renewable energy in this energy sector is increasing from 22.1% in 2020 to 31.8% in 2030 and 39.7% in 2040. The prognosis elaborated by PEP for 2025–2040 are very optimistic and the prognosis elaborated based on ARIMA models is also promising. Both prognoses predict the development of RES in the future and the transformation of the energy sector in Poland. Full article

Marine renewable energy could support Costa Rica’s decarbonization pathway, but its offshore resource base and enabling conditions remain poorly characterized in the body of knowledge. This study provides the first integrated assessment of marine energy resources, grid integration opportunities, and governance challenges in Costa Rica. A meta-analysis of 76 technical, legal, and policy sources is combined with qualitative doctrinal analysis, GIS-based multi-criteria evaluation for Ocean Thermal Energy Conversion (OTEC), and satellite and reanalysis data for winds, waves, currents, and sea surface temperature to estimate power densities and extractable energy. Results show a contrast between the Pacific and Caribbean coasts. For instance, on the Northern Pacific coast, there are strong Papagayo winds, and persistent swells yield high offshore wind and wave energy potentials, with technical offshore wind resources of around 14.4 GW and Pacific wave power frequently exceeding 20–25 kW/m with relatively low seasonal variability. Furthermore, twelve OTEC-suitable zones are identified with two priority areas in the southern Pacific that combine steep bathymetry and strong thermal gradients with limited environmental conflicts, but they overlap with sensitive conservation and Indigenous territories. Current energy potential is more localized and modest in the Caribbean coast. The analysis highlights major infrastructural, legal, and social barriers but concludes that marine energy can play a pivotal role in diversifying Costa Rica’s renewable-dominated electricity market. Full article

This study examined the geopolymerization behavior of granite waste powder and reactive silica powder (GWS), utilizing granite waste powder as a sustainable precursor material, to develop an environmentally friendly substitute for Ordinary Portland cement. To obtain this objective, a total of three different mixes of calcined granite waste with reactive silica (1:1, 3:2, 7:3) were cast to evaluate the aim of this study. Due to low inherent reactivity of granite waste powder, the alkali activation was achieved using a combined solution of alkali activators consisting of 8 mol/L concentration of NaOH and Na₂SiO₃ solution at mass ratio of 1:1.2 prepared 24 h in advance to ensure complete dissolution and stabilization prior to pouring it into the GWS paste. The finest particle size distribution for optimal reactivity performance was achieved by choosing lowest median particles size from 4.0 μm–4.2 μm among all mixtures. ICP-MS analysis of granite waste and reactive silica showed the presence of silica (0.11% and 0.26% respectively) and calcium (49.61% and 38.92% respectively) content adequate for effective geopolymerization of the paste. The elemental composition, new phase formation and microstructural analysis were examined using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR) techniques and Scanning Electron Microscopy (SEM) analysis. XRD analysis revealed that all GWS mixes were predominantly amorphous, with crystalline quartz, feldspar and minor α-cristobalite peaks diminishing from GWS50 to GWS70 confirming increased reactivity due to enormous reactive silica content. FTIR spectra of GWS mixes displayed characteristics of O-H (3375 cm⁻¹), H-O-H (1645 cm⁻¹), and Si-O-T (982–1000 cm⁻¹) bands, with the main Si-O-T peak shifting to higher wavenumbers from GWS50 to GWS70 due to increased GW content, indicating reduced geopolymerization effect in GWS50. SEM analysis revealed that among all mixes, GWS70 exhibited the most ideal dense matrix with increasing content of granite waste along with strong N-A-S-H gel formation. Compressive strength at 28 days increased from 11.2 MPa for GWS50 to 14.2 MPa for GWS60 and 13.8 MPa for GWS70, demonstrating that higher reactive silica powder content significantly enhanced the mechanical performance of the alkali-activated paste. These findings demonstrated that alkali-activated geopolymers of GSW offer a viable alternative to Ordinary Portland cement with optimized mixes by valorizing industrial waste and reducing reliance on high-carbon cement production. Full article

Mid-infrared (MIR) femtosecond lasers, resonant with the absorption bands of amide-related molecular groups in the range of 6.1 to 6.5 μm, have been demonstrated to be effective for tissue ablation. However, the flexible and stable delivery of such pulses to micrometer-scale tissue regions for controlled ablation remains challenging. Here, we utilize a silica-based anti-resonant hollow-core fiber (AR-HCF) to deliver high-power MIR femtosecond pulses with high temporal and spectral fidelity, featuring pulse durations of approximately 340 fs and peak power densities exceeding 1 GW/cm², for selective tissue ablation. Benefiting from the small numerical aperture of the AR-HCF, a relatively stable and consistent beam spot size can be maintained over a millimeter-scale propagation distance. Precise control of the ablation depth can be achieved by appropriately selecting the scanning parameters, with penetration depths reaching the sub-millimeter scale. Furthermore, for the first time, we systematically compare the tissue ablation performance of MIR femtosecond lasers at resonant wavelengths (6.4 and 6.1 μm) and a non-resonant wavelength (5.5 μm) under identical scanning conditions. An ablation depth ratio of more than 8:1 is observed, demonstrating the high efficiency and selectivity of the resonance-based ablation mechanism. These results establish flexible delivery of high-power MIR femtosecond pulses in tissue-resonant bands via silica-based AR-HCF as a powerful platform for selective, precise, and efficient tissue ablation, providing a promising approach for interventional and minimally invasive surgery. Full article

The policymakers of Bangladesh have been mapping the energy mix to shift its high dependency on fossil fuels to sustainable energy; wind energy is addressed as a highly potential option. A feasible site selection process is essential for wind power plant establishment; thus, this study aims to identify potential areas for the sustainable development of large-scale wind plants by considering socio-economic, safety and environmental factors. In this study, two techniques of multi-criteria analysis (MCA), analytical hierarchy process (AHP) and ratio scale weighting (RSW), were incorporated with geographic information system (GIS) to select the optimal area in Bangladesh. This study considers fifteen sub-criteria under four main criteria, namely, socio-economy, geology, ecology, and climatology. AHP and RSW assign suitable weights to the sub-criteria based on their significant impact on the plant. GIS analyzes spatial data layers and produces suitability maps with the following categories: 5—most suitable, 4—suitable, 3—moderately suitable, 2—unsuitable, 1—completely unsuitable, and 0—excluded area. The final suitability map was generated using suitability maps of AHP and RSW. Finally, a combination of the final suitability map and the wind speed suitability map provide a total suitable area of 1595.8293 km². This could produce 2.96 GW power with 1418 wind turbines and be able to reduce 4,992,346.42 tons of CO₂ emissions annually (calculated using a reference turbine). The study was uniquely carried out at a 150 m hub height, and integration of AHP and RSW for weight cross-validation was performed for the first time in large-scale wind plant siting in Bangladesh. The findings of the study can be helpful for decision-makers in developing large-scale wind power plants. Full article