21436 research outputs found
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Development of a pH-Responsive Delivery System Suitable for Naringenin and Other Hydrophobic Flavonoids Using the Interactions Between Basil Seed Gum and Milk Protein Complexes
No full textIncorporating hydrophobic flavonoids such as naringenin into food systems is challenging due to their poor water solubility and instability. Effective delivery systems are essential to improve solubility, dispersibility, and controlled release during digestion. This study developed a food-grade encapsulation system using basil seed gum water-soluble extract (BSG-WSE) combined with proteins, sodium caseinate (NaCas) and whey protein isolate (WPI), via pH-driven and mild heat treatments in aqueous media, without the use of organic solvents, to ensure safety and sustainability. BSG-WSE and NaCas were tested at mass ratios of 1:1, 1:3, and 1:5 under pH conditions of 4, 5, and 7, followed by heat treatments at 60 °C or 80 °C for 30 min. The total biopolymer concentrations were 0.15%, 0.3%, and 0.45% (w/v). The most stable colloidal system was obtained at a 1:1 ratio, pH 4, and 60 °C, which was further evaluated for two additional flavonoids (rutin and quercetin) and with WPI as an alternative protein source. The highest loading capacity (11.18 ± 0.17%) and encapsulation efficiency (72.50 ± 0.85%) were achieved for naringenin under these conditions. Quercetin exhibited superior performance, with a loading capacity of 14.1 ± 3.12% and an encapsulation efficiency of 94.36 ± 5.81%, indicating a stronger affinity for the delivery system. WPI showed lower encapsulation efficiency than NaCas. Ternary systems (BSG-WSE, NaCas, and naringenin) formed under different pH and heat treatments displayed distinct morphologies and interactions. The pH 4 system demonstrated good dispersion and pH-responsive release of naringenin, highlighting its potential as a delivery vehicle for hydrophobic flavonoids. BSG-WSE significantly improved the stability of protein-based complexes formed via pH-driven assembly. Physicochemical characterization, rheological analysis, and release studies suggest that this system is particularly suitable for semi-solid food products such as yogurt or emulsions, supporting its application in functional food development.fals
Using prediction markets and forecasting surveys to predict 28 replication outcomes of classic articles in social psychology and judgement and decision making
No full textCan researchers predict if classic findings published in the field of social psychology and judgement and decision making replicate? We set up prediction markets and a forecasting survey for predicting replications of 28 experiments of classic well-cited articles. Forecasters predicted if the original results would replicate, where a successful replication was defined as an effect in the same direction as the original and a signal (p-value lower than 0.05). Of the 28 original studies, 16 (57%) met the replication success criteria, compared to a predicted replication rate of 70% in the prediction markets and 65% replication rate in the survey. We concluded only suggestive evidence for associations of replication outcomes with prediction market prices (r = 0.43, 95% CI [0.07, 0.69]) and average survey beliefs (r = 0.26, 95% CI [-0.12, 0.58]). The prediction market effects were similar to observed effects in previous prediction market studies and suggest that prediction markets can to some extent predict replication outcomes, yet predictions are far from perfect and conducting replications is much more informative about the credibility of published findings. Data and code are available at https://doi.org/10.17605/OSF.IO/2KMH7.fals
Tax authority independence and earnings management
No full textThis study investigates how tax authority independence affects corporate earnings management. We employ a difference-in-differences approach and find that increased tax authority independence significantly reduces earnings management, particularly for firms engaging in downward earnings management. Additionally, we observe that this negative correlation is influenced by factors such as ownership structure, political connections, audit quality, and legal environment. Furthermore, we demonstrate that enhanced tax enforcement and corporate governance serve as channels through which the independence of tax authorities mitigates earnings manipulation.fals
Collaborative optimization operation method of electrical-thermal‑hydrogen multi-energy storage system based on variable mode decomposition
No full textThe integration and utilization of renewable energy into the grid is key to building a clean and low-carbon energy system, but its intermittency and volatility cause significant wind and solar curtailment. To address this, this paper proposes a multi-energy storage system integrating electrical, thermal, and hydrogen storage. The system firstly uses Variational Mode Decomposition (VMD) to decompose and reconstruct the power difference between the source and the load. The power allocation based on the dynamic response characteristics of supercapacitors, hydrogen storage, and thermal storage tanks. Three progressive operating strategies are designed: baseline power allocation based on VMD (Strategy 1), adaptive VMD adjustment considering the state of charge (SOC) of energy storage (Strategy 2), and coordinated optimization introducing grid regulation (Strategy 3). An experimental platform focused on lithium batteries and supercapacitors was built to verify the feasibility of the power allocation and real-time adjustment strategies. Furthermore, the experimentally validated control strategies were applied to a simulation case of a Beijing community to conduct system modeling based on a physical model. Results show that Strategy 3 achieves zero SOC violation in energy storage, significantly outperforming Strategy 1 (which had a 47.5% violation rate) and Strategy 2 (37%), with operational costs reduced by 13.3% and 17.7% compared to Strategies 1 and 2, respectively, and a system excess capacity ratio of 0%. The conclusions indicate that the proposed VMD-based multi-energy storage coordinated optimization method, especially Strategy 3 combined with grid regulation, can effectively enhance system stability and economy, providing an effective solution for multi-energy system management in scenarios with a high proportion of renewable energy.fals
Modelling the cost of ewe mortality in New Zealand sheep flocks
No full textCONTEXT
Reported ewe mortality rates in extensively farmed sheep flocks range from 2.9–12.8%. Most deaths occur over the lambing period, and many are potentially preventable or treatable. An understanding of the costs of ewe mortality would allow farmers to determine which interventions are most cost-effective.
OBJECTIVE
Use a dynamic bioeconomic model to investigate the impacts of ewe mortality on cash operating surplus for New Zealand sheep flocks.
METHODS
An existing dataset of 23 flocks was used which comprised data on ewe numbers throughout the year, ewe deaths, reproductive data and farm demographic data (location, size, topography and stock numbers). Each flock was modelled using economic data for the 2023 financial year. Cash operating surplus per ewe (COS/ewe) was generated for each flock using their actual death rates. For flocks with death rates >4%, the effects on COS/ewe were also modelled based on a reduction in ewe deaths by 20% or 50%.
RESULTS AND CONCLUSIONS
Flocks with higher ewe death rates had lower COS/ewe, with an overall correlation of 0.58. Reducing deaths by 20% and 50% resulted in an increased COS/ewe of NZ2.66/ewe and NZ6.67/ewe, respectively. Multiplying these numbers by the total number of ewes in their flock provides guidance to producers on how much they could spend to reduce the death rate of their ewes.
SIGNIFICANCE
Producers can use the results, along with their flock-specific ewe mortality data, to determine cost-effective strategies to reduce ewe mortality.fals
Data-driven virtual sensor systems for dynamic temperature monitoring along food supply chains
No full textContinuous monitoring of perishable food temperatures along supply chains is crucial for quality assurance and reducing food loss and waste. However, cost and installation constraints restrict sensor deployment, compromising the reliability of temperature monitoring. This study proposes a data-driven virtual sensor system that leverages deep learning to integrate multi-source data, enabling temperature estimation at sensor-inaccessible locations and thus reducing dependence on extensive physical sensor deployment. The system was evaluated across postharvest processing, storage, and transport. Results indicate that, with a fixed number of physical sensors, increasing the virtual-to-physical sensor ratio from 16 to 32 maintains the root mean square error below 0.3 °C. Further analysis shows that sensor placement within pallets has minimal impact on performance, whereas the choice of data sources and model architecture exerts a significant influence. Notably, a configuration of one sensor per pallet with a BiLSTM + attention model outperforms shallow networks, demonstrating the potential of data-driven virtual sensor system to enhance temperature monitoring and efficiency along food supply chains.fals
Unlocking antimicrobial potential of microalgae on food-borne bacteria: A standardized framework and future directions
No full textFoodborne infections are a global challenge, costing billions annually through food losses, trade restrictions, and healthcare expenses. Growing concerns over chemical antimicrobials such as antibiotics, sanitizers, and disinfectants, have driven interest in sustainable bio-control strategies for food systems. Microalgae, which produce a plethora of biomolecules including carbohydrates, lipids, proteins, and various secondary metabolites, represent a promising source of antimicrobial compounds. Despite numerous reports demonstrating antimicrobial activity in microalgal extracts, no microalgae-derived antimicrobials have yet reached commercialization.
This review focuses on some microalgal species already produced at commercial scale, including those with GRAS status (e.g., Chlorella vulgaris and Chlamydomonas reinhardtii). As for other microalgae-based products (e.g., biofuel oil), successful antimicrobial production depends on identifying key species and strains, optimizing growth conditions, and refining harvesting, cell disruption, and extraction protocols. Although research in this area is expanding, further studies are needed to improve our understanding of antimicrobials synthesis and to assess how these factors influence antimicrobial activity. Commonly used antibacterial assays such as disc diffusion and microdilution have limitations that must be considered when evaluating the antimicrobial activity of microalgal extracts. Overall, inconsistencies in testing and reporting have hindered the clear identification of microalgae as sources of effective antimicrobials. This review proposes a framework for future extract preparation and antimicrobial assessment and discusses future prospects to enhance the discovery and yield of microalgal antimicrobials.fals
Application of image analysis combined with regression models to estimate the reduction of Escherichia coli and Salmonella spp. on vegetable surfaces after washing
No full textEscherichia coli, a bacterium indicating improper hygiene practices during food production, is commonly found in the intestines of humans and animals, while Salmonella spp. are dangerous bacteria that cause typhoid fever and severe diarrhea. These pathogens have been found in fresh vegetables. This study investigated how the vegetable surface characteristics influenced bacterial adhesion. The reduction of bacteria during the washing process was assessed using different concentrations and types of chemicals. The relationships between variables obtained from image analysis techniques and bacterial adhesion on vegetable surfaces were also evaluated. The most effective way to inhibit bacteria was by washing with 2.0% lactic acid, with bacterial reduction from an initial concentration of 8.74 to 2.92 log CFU/m<sup>2</sup>. Pearson’s correlation with the highest r value was surface area (A) with values ranging from 0.764 to 0.993, followed by surface roughness (R) with values between 0.019 and 0.986, and Fractal dimension (FD) with values between − 0.510 and − 0.992. The correlation between A and the number of bacteria (E. coli and Salmonella) was the highest, with surface area influencing bacterial adhesion to the vegetable surface. Greater surface roughness was associated with a higher initial bacterial load, making the A value a good predictor of changes in bacteria during washing with organic acids at various concentrations.fals
Application of landmark analysis and piecewise Cox regression to identify features associated with prognosis: A national retrospective cohort study of New Zealand women
No full textBackground
Breast cancer prognosis changes over time in complex ways depending on individual risk factors. This study aimed to analyze how breast cancer outcomes in New Zealand women change over time and identify features associated with breast cancer specific survival and locoregional recurrence across different receptor subtypes.
Methods
A retrospective cohort study was conducted using data from Te Rēhita Mate Ūtaetae (Breast Cancer Foundation National Register) on 21,574 women diagnosed with invasive breast cancer between 2000–2019. We applied k-medians survival clustering, landmark analysis, and piecewise Cox regression to identify time-specific risk patterns and prognostic features.
Results
Survival improved significantly for women diagnosed more recently. Triple-negative breast cancer had the poorest 5-year breast cancer specific survival but demonstrated better outcomes for women surviving beyond this period. In contrast, ER+/HER2- tumors, associated with favorable short-term outcomes, showed the highest risk of late recurrence and breast cancer mortality beyond 10 years. Younger age at diagnosis (≤44 years) was associated with increased recurrence risks, especially for ER-/HER2+ tumors. Radiation therapy reduced early LRR across subtypes. Tumor grade was inversely associated with late recurrence, while stage 2 disease in ER+ tumors markedly elevated late recurrence odds compared to stage 1.
Conclusions
This study demonstrates the dynamic nature of breast cancer prognosis, with key findings emphasizing the time-dependent shifts in risk across receptor subtypes. These findings underscore the importance of personalized, receptor-specific follow-up strategies, including extended monitoring for subgroups at heightened long-term risk.fals
The Relative Impact of Different News on Stock Returns: Evidence From New Zealand
No full textWe estimate the effects of different news events on New Zealand stock returns. Our results indicate that local news, such as announcements from the New Zealand Central Bank interest rate changes (official cash rate) and company earnings reports, generally has a greater impact than international news. However, U.S. Federal Open Market Committee interest rate announcements also exert an important impact. There are no consistent differences in the impact of news on stocks with different cross-sectional characteristics, such as small and large, value and growth, and low- and high-leverage stocks.fals