Search Results (19,035)

Controlling dry matter intake (DMI) is one strategy to reduce feed costs and increase efficiency. Including fat at a high concentrate level can increase the energy density of diets fed to ruminants, thus reducing DMI further. Therefore, the objective of this study was to evaluate the effects on fermentation and nutrient digestion of including different fat sources when high-concentrate diets with high-fat inclusion are used under simulating precision feeding in continuous culture. We hypothesized that incorporating different fat sources into the aforementioned program can improve nutrient utilization without affecting rumen fermentation. Four treatments were randomly assigned to eight continuous cultures in a randomized complete block design and ran for two periods of 10 d. Diets included a high concentrate level (HC; 65% DM) with high-fat inclusion starting with a 3% basal level of fat in the diet as the control (0% added fat; CON) and 9% fat in the diet (6% added poultry fat, PF; 6% added coconut oil, CO; and (6% added soybean oil, SO). Data were analyzed using the MIXED procedure of SAS with repeated measures. The DM, OM, NDF, and ADF digestibility coefficients (dCs) were higher for PF and CO, followed by SO and then CON. Starch and FA dCs were higher for different fat sources than for the CON. The total VFA concentration was higher for CON. There was a reduction in acetate and propionate with different fat sources. The mean culture pH and NH₃N were the highest for CO, followed by PF, then SO, and CON. The protozoa population was higher for CON than for the other fat treatments, followed by CO, PF, and SO. These results suggest that simulated precision feeding using continuous culture fermenters with high-concentrate diets up to 65% and high fat up to 6% can improve nutrient digestion approximately to 15% with changes in fermentation rate and profiles. Full article

Cocoa represents a crucial source of income in coastal regions of Ecuador, where the product is exported for the production of high-value chocolates. However, elevated levels of cadmium (Cd) in cocoa beans, attributable to volcanic soils, have the potential to impede international trade, particularly in accordance with European Union regulations. The main objective of this study was to reduce Cd concentrations in cocoa beans of two genotypes, Nacional and CCN-51, by applying different doses of pectin trans-eliminase (PTE) enzyme during the fermentation process in conjunction with mucilage washing techniques, pre-drying resting periods, and various drying methods. To this end, a Taguchi orthogonal design (L9) was employed to evaluate nine treatments per genotype, complemented with two controls. The most efficacious treatment for Nacional was identified as T7, involving a 0.30 mL·kg⁻¹ PTE dose, the absence of mucilage washing, a 48 h resting period, and drying in a marquee. This treatment resulted in a 68.6% reduction in Cd concentration (from 0.28 to 0.09 mg·kg⁻¹). For CCN-51, T3 (0.10 mL·kg⁻¹ PTE, complete washing, 48 h resting, and splint drying) yielded a 26.4% reduction in Cd (from 0.42 to 0.31 mg·kg⁻¹). It is noteworthy that none of the treatments exceeded the EU regulatory threshold of 0.8 mg·kg⁻¹. A physico-chemical analysis was conducted, which revealed significant treatment effects on pH (ranging from 5.63 to 6.85) and acidity (0.02% to 0.03%). Sensory evaluation indicated enhancements in cocoa and nutty flavors, along with a reduction in undesirable astringency and bitterness, particularly in Nacional samples. The findings of this study demonstrate that the combination of enzyme-assisted fermentation and optimized postharvest techniques represents a pragmatic approach to the mitigation of cadmium in cocoa, while simultaneously preserving or enhancing product quality. Full article

Large language models (LLMs) now match or exceed human performance on many open-ended language tasks, yet they continue to produce fluent but incorrect statements, which is a failure mode widely referred to as hallucination. In low-stakes settings this may be tolerable; in regulated or safety-critical domains such as financial services, compliance review, and client decision support, it is not. Motivated by these realities, we develop an integrated mitigation framework that layers complementary controls rather than relying on any single technique. The framework combines structured prompt design, retrieval-augmented generation (RAG) with verifiable evidence sources, and targeted fine-tuning aligned with domain truth constraints. Our interest in this problem is practical. Individual mitigation techniques have matured quickly, yet teams deploying LLMs in production routinely report difficulty stitching them together in a coherent, maintainable pipeline. Decisions about when to ground a response in retrieved data, when to escalate uncertainty, how to capture provenance, and how to evaluate fidelity are often made ad hoc. Drawing on experience from financial technology implementations, where even rare hallucinations can carry material cost, regulatory exposure, or loss of customer trust, we aim to provide clearer guidance in the form of an easy-to-follow tutorial. This paper makes four contributions. First, we introduce a three-layer reference architecture that organizes mitigation activities across input governance, evidence-grounded generation, and post-response verification. Second, we describe a lightweight supervisory agent that manages uncertainty signals and triggers escalation (to humans, alternate models, or constrained workflows) when confidence falls below policy thresholds. Third, we analyze common but under-addressed security surfaces relevant to hallucination mitigation, including prompt injection, retrieval poisoning, and policy evasion attacks. Finally, we outline an implementation playbook for production deployment, including evaluation metrics, operational trade-offs, and lessons learned from early financial-services pilots. Full article

Understanding watershed-scale interactions among landscape patterns, river morphology, and water quality is essential for effective water management. However, quantitative assessment of their coupled effects remains challenging. Utilizing water quality observation data, this study analyzed the independent and interactive influences of landscape pattern and river structure on the water quality of inlet rivers in the Chaohu Lake Basin (CLB) using correlation analysis and partial least squares structural equation modelling (PLS-SEM). The main conclusions are as follows: (1) The river water quality showed significant spatial distribution characteristics, and the northwestern part of the CLB formed a pollution aggregation area. (2) Ammonia nitrogen correlated positively with impervious surfaces but negatively with forest cover and patch cohesion, permanganate index linked positively to water surface but negatively to forest cover, and water temperature exhibited a significant negative correlation with network connectivity. (3) PLS-SEM results showed that both river structure (path coefficient = 0.877, p < 0.001) and landscape pattern (path coefficient = 0.177, p < 0.05) significantly influenced CLB water quality, with river structure having a stronger effect. This study supports source-based water quality control for Chaohu Lake Basin. Full article

Polycyclic aromatic hydrocarbon (PAH) derivatives, specifically azaarenes and nitrated and oxygenated PAHs, are emerging contaminants of concern due to their increased toxicity and persistence compared to the parent PAHs. Despite their toxicity, their simultaneous analysis in complex matrices, such as in fumes emitted from bituminous mixtures, remains challenging due to limitations of conventional analytical techniques. To address this, an advanced methodology was developed using Ultra-High-Performance Liquid Chromatography coupled with High-Resolution Mass Spectrometry (UHPLC-HRMS Orbitrap Eclipse) equipped with an APCI source for the simultaneous identification and quantification of 14 PAH derivatives. Chromatographic and ionization parameters were optimized to ensure maximum sensitivity and selectivity. Following ICH Q2(R2) guidelines, the method was validated, demonstrating excellent linearity (R² > 0.99), high mass accuracy (≤5 ppm), strong precision (<15%), and excellent sensitivity. Limits of detection (LODs) ranged from 0.1 µg L⁻¹ to 0.6 µg L⁻¹ and limits of quantification (LOQs) ranged from 0.26 µg L⁻¹ to 1.87 µg L⁻¹. The validated method was successfully applied to emissions from asphalt pavement materials collected on quartz filters under controlled conditions, enabling the identification and quantification of all 14 targeted compounds. These results confirm the method’s robustness and suitability for trace-level analysis of PAH derivatives in complex environmental matrices. Full article

Natural tyrosinase inhibitors are currently a hot research topic due to their potential application in cosmetic and medicinal products. For the plant Lycopodiastrum casuarinoides, the chemical constituents with a tyrosinase inhibitory effect have not been investigated yet. Bioassay-guided isolation was conducted on the aboveground parts, resulting in the isolation of 10 compounds (1–10). Their chemical structures were confirmed by their spectral data and comparison with literature data. It might be worth pointing out that compounds 3–9 were isolated from the genus Lycopodiastrum for the first time. The bioassay revealed that compounds 6 and 7 displayed moderate mushroom tyrosinase inhibitory activity (IC₅₀ = 1.90 and 2.43 mM, respectively), which was close to the positive control kojic acid (IC₅₀ = 0.17 mM). Moreover, the in silico experiments disclosed that Lys180, His178 and other amino residues played key roles in the binding modes between compounds 6 and 7 and mushroom tyrosinase (PDB: 2Y9X). These findings suggested potential for further investigation on this species as a source of cosmetic ingredients. Full article

Intensified human activities in recent years, such as wastewater discharge and agricultural non-point source pollution have led to a decline in lake water quality, especially in the middle and lower reaches of the Yangtze River Basin, which threaten the stability of lake water ecosystems. Therefore, it is necessary to conduct a scientific assessment of the water eco-environmental quality of shallow lakes and implement targeted management measures. Considering the characteristics of shallow lakes, major ecological and environmental issues, and current standards and guidelines, an indicator system method was employed to establish a water eco-environmental quality evaluation system tailored for typical shallow lakes in the middle and lower reaches of the Yangtze River Basin. This evaluation system comprises three criteria layers (aquatic organism, habitat quality, and water quality) and 10 indicator layers. Using survey data from 2022 to 2024 for evaluation, the results showed that the water eco-environmental quality of Lake Gehu was rated as poor, with the lowest score for macrophyte coverage and the highest score for riparian vegetation coverage. This indicates that the shoreline restoration project in Lake Gehu was effective, while the lake water quality still needs improvement. Remedial measures include increasing aquatic vegetation coverage, reducing nitrogen and phosphorus pollution loads, and controlling the occurrence of algal blooms. This evaluation system combines field surveys with remote sensing monitoring data, fully considering historical and current conditions, and can guide local authorities in evaluating lake water environmental quality. The constructed evaluation system is applicable for the assessment of shallow lakes in the middle and lower reaches of Yangtze River Basin. It provides a scientific basis for the continuous improvement of eco-environmental quality and the construction of Beautiful Lakes Initiative, contributing to the management and protection of lake ecosystems. Full article

The Fenwei Plain (FWP), one of China’s most polluted regions, has experienced severe ozone (O₃) pollution in recent years. Volatile organic compounds (VOCs), key O₃ precursors, undergo significant photochemical degradation, yet their loss and the implications for source apportionment and ozone formation potential (OFP) in this region remain unclear. This study conducted summertime VOC measurements in two industrial cities in the FWP, Hancheng (HC) and Xingping (XP), to quantify photochemical losses of VOCs and assessed their impact on source attribution and OFP with photochemical age-based parameterization methods. Significant VOC photochemical losses were observed, averaging 3.6 ppbv (7.1% of initial concentrations) in HC and 1.9 ppbv (5.6%) in XP, with alkenes experiencing the highest depletion (22–30%). Source apportionment based on both initial (corrected) and observed concentrations revealed that industrial sources (e.g., coking, coal washing, and rubber manufacturing) dominated ambient VOCs. Ignoring photochemical losses underestimated contributions from natural gas combustion and biogenic sources, while it overestimated the secondary source. OFP calculated with lost VOCs (OFP_loss) reached 34 ppbv in HC and 15 ppbv in XP, representing 20% and 25% of OFP based on observed concentrations, respectively, with reactive alkenes accounting for over 90% of OFPloss. The results highlight the importance of accounting for VOC photochemical losses for accurate source identification and developing effective O₃ control strategies in the FWP. Full article

Nitrogen dioxide (NO₂) plays a crucial role in environmental processes and public health. In recent years, NO₂ pollution has been monitored using a combination of in situ measurements and satellite remote sensing, supported by the development of advanced retrieval algorithms. With advancements in satellite technology, large-scale NO₂ monitoring is now feasible through instruments such as GOME-2C and TROPOMI. However, the fixed local overpass times of polar-orbiting satellites limit their ability to capture the complete diurnal cycle of NO₂, introducing uncertainties in emission estimation and pollution trend analysis. In this study, we evaluated differences in NO₂ observations between GOME-2C (morning overpass at ~09:30 LT) and TROPOMI (afternoon overpass at ~13:30 LT) across three representative regions—East Asia, Central Africa, and Europe—that exhibit distinct emission sources and atmospheric conditions. By comparing satellite-derived tropospheric NO₂ column densities with ground-based measurements from the Pandora network, we analyzed spatial distribution patterns and seasonal variability in NO₂ concentrations. Our results show that East Asia experiences the highest NO₂ concentrations in densely populated urban and industrial areas. During winter, lower boundary layer heights and weakened photolysis processes lead to stronger accumulation of NO₂ in the morning. In Central Africa, where biomass burning is the dominant emission source, afternoon fire activity is significantly higher, resulting in a substantial difference (1.01 × 10¹⁶ molecules/cm²) between GOME-2C and TROPOMI observations. Over Europe, NO₂ pollution is primarily concentrated in Western Europe and along the Mediterranean coast, with seasonal peaks in winter. In high-latitude regions, weaker solar radiation limits the photochemical removal of NO₂, causing concentrations to continue rising into the afternoon. These findings demonstrate that differences in polar-orbiting satellite overpass times can significantly affect the interpretation of daily NO₂ variability, especially in regions with strong diurnal emissions or meteorological patterns. This study highlights the observational limitations of fixed-time satellites and offers an important reference for the future development of geostationary satellite missions, contributing to improved strategies for NO₂ pollution monitoring and control. Full article

Seismo-stratigraphic data of the Gulf of Pozzuoli have been revised with the aim of identifying the tectonic structures controlling the area in more detail and to highlight the possible relationships of the morpho-structures with the new bradyseismic crisis, still in course. In particular, the relationships between the tectonic structures, consisting of both normal faults and folds, and the possible rising of fluids have been analyzed based on seismic interpretation. We hypothesize that the normal faults occurring in this area have possibly controlled the rising of fluids in these extensional structures. The fluid uprising could possibly be related to the increasing gas activity of the Solfatara–Pisciarelli area onshore during the active bradyseismic crisis (2024–2025). The proposed mechanism is controlled by the occurrence of a heat source, possibly a magmatic reservoir, in the continental crust and/or the mantle, genetically related to the presence of submerged hydrothermal discharges in the coastal areas of the Campania region. To achieve this objective, detailed seismo-stratigraphic sections of the Gulf of Pozzuoli have been constructed, focusing on the areas characterized by tectonic activity. Fluid uprising is mainly controlled by the tectonic setting of the Gulf of Pozzuoli, characterized by anticlines and synclines, representing important structural and stratigraphic traps. Full article

To address the issue of key component degradation in hybrid electric commercial vehicles under complex driving cycles negatively impacting system economy and durability, this paper proposes a model predictive control (MPC)-based energy management co-optimization strategy. Firstly, dynamic degradation models for the key components are established, enabling high-fidelity characterization of component health status. Secondly, a system-level model incorporating vehicle dynamics, power battery, and electric drive motor is developed, with the degradation feedback mechanism deeply integrated. Building on this foundation, an MPC-based energy management strategy for multi-objective optimization is designed. Its core functionality lies in the cooperative allocation of power sources within a rolling horizon framework: by integrating component degradation status as critical feedback into the control loop, the strategy proactively coordinates the optimization objectives between operational economy (minimization of equivalent energy consumption) and key component durability (degradation mitigation). Simulation results demonstrate that, compared to traditional energy management strategies, the proposed strategy significantly enhances system performance while ensuring vehicle drivability: equivalent energy efficiency improves by approximately 3.5%, component degradation is reduced by up to 87%, and superior state of charge (SOC) regulation capability for the battery is achieved. This strategy provides an effective control method for achieving intelligent, long-life, and high-efficiency operation of hybrid electric commercial vehicles. Full article

This work presents the design and implementation of an automated, digital, and modular system to address a real-world industrial challenge: the automation and optimization of production schedules for Computer Numerical Control (CNC) machines in a factory in Portugal. The goal is to replicate and enhance the existing manual scheduling process by integrating multiple data sources and formulating a general Mixed-Integer Linear Programming (MILP) model with constraints. This model can be solved using MILP optimization methods to produce efficient scheduling solutions that minimize machine downtime, reduce tool change frequency, and lower operator workload. The proposed system is implemented using open-source Python abstraction interfaces (Python-MIP), employing state-of-the-art of MILP optimization solvers such as CBC and HiGHS for solution validation. The system is designed to accommodate a wide range of constraints and operational factors, which can be switched on or off as needed, thereby enhancing its flexibility and decision-support capabilities. Additionally, a user-friendly graphical application is developed to facilitate the input of specific scheduling data and constraints, enabling flexible and efficient formulation of diverse scheduling scenarios. The proposed system is validated through multiple case studies, demonstrating its effectiveness in optimizing industrial CNC scheduling tasks and providing a scalable, practical tool for real-world factory operations. Full article

The oscillations induced by voltage source converters (VSCs) in DC voltage timescale dynamics pose significant challenges to the safe and stable operation of VSC-dominated power systems. However, previous studies have conducted simplified analyses without fully understanding the fundamental roles of different timescale control loops in converter-interfaced systems. In light of this, this study first identifies the key state variables and operating points that directly characterize the energy storage levels of devices and networks in AC systems. A model for the converter-interfaced system is then established in the specified DC voltage timescale. The key contribution of this work is the proposal of an analytical framework that decomposes system stability into self-stabilizing (Self-stable) and externally coupled stabilizing (En-stable) paths based on internal voltage amplitude and frequency, aiming to reveal the physical mechanisms behind internal voltage amplitude and frequency oscillations in DC voltage timescale dynamics. Based on this framework, the Self-stable path and En-stable path of the internal voltage amplitude/frequency of converter-interfaced systems are derived. This novel analytical method mathematically decouples the stability of a single variable into a direct self-influence path and an indirect path coupled through other system variables. Subsequently, the causes of internal voltage amplitude/frequency oscillations in the specified voltage timescale are explained using the Self-stability and En-stability analysis method. A key finding of this study is that the stability of the internal voltage amplitude and frequency exhibits a dual relationship: for amplitude stability, the Self-stable path is stabilizing, whereas the coupled path is destabilizing; for frequency stability, the roles are reversed. Finally, the results are verified through simulations. Full article

Background/Objectives: The complexity of diseases such as cancer and auto-immune disorders drives the need for unique, target-driven therapeutics. A broader arsenal to generate better biologics-based therapeutics is needed to provide more efficient and effective antibody generation technologies. The critical parameter for antibody generation is to generate as much candidate diversity to each target as possible. Method/Results: We present guidelines for having an efficient process using a fully synthetic human single-domain antibody (sdAb) phage display library. Critical milestones for success focused on library quality control (QC) assessments, evaluation of specific biopanning outputs, and construct designs that enabled efficient transition to mammalian expression. The synthetic VHO libraries produced epitope diversity better than an immunized sourced library with candidates possessing nM potencies and monodispersity > 90% via SEC. Conclusions: Synthetic human scaffold sdAb phage display libraries was constructed, biopanned, and selected candidates that could be directly transitioned for mammalian expression. The diverse VHO sets of candidates produced from many targets easily provided opportunities to make a multi-specific biological compound. Both synthetic and immunized phage selection campaign results suggested that these technologies complemented each other to generate therapeutic candidates. Finally, we demonstrated how diverse data produced from a process that used VHO synthetic libraries could accelerate drug discovery. Full article

The construction industry is a major source of environmental degradation as it is responsible for a significant share of global CO₂ emissions, especially from cement and aggregate consumption. This study fills the need for sustainable construction materials by developing and evaluating a low-carbon fiber-reinforced concrete (FRC) made of steel slag powder (SSP), processed recycled concrete aggregates (PRCAs), and waste steel rivet fibers (WSRFs) derived from industrial waste. The research seeks to reduce dependency on virgin materials while maintaining high values of mechanical performance and durability in structural applications. Sixteen concrete mixes were used in the experimental investigations with control, SSP, SSP+RCA, and RCA, reinforced with various fiber dosages (0%, 0.2%, 0.8%, 1.4%) by concrete volume. Workability, density, compressive strength, tensile strength, and water absorption were measured according to the appropriate standards. Compressive and tensile strength increased in all mixes and the 1.4% WSRF mix had the best performance. However, it was found that a fiber content of 0.8% was optimal, which balanced the improvement in strength, durability, and workability by sustainable reuse of recycled materials and demolition waste. It was found by failure mode analysis that the transition was from brittle to ductile behavior as the fiber content increased. The relationship between compressive, tensile strength, and fiber content was visualized as a 3D response surface in order to support these mechanical trends. It is concluded in this study that 15% SSP, 40% PRCA, and 0.8% WSRF are feasible, specific solutions to improve concrete performance and advance the circular economy. Full article