Food Chemistry: Food quality and new analytical approaches

Peer Reviewe

The Influence of Neural Networks on Hydropower Plant Management in Agriculture: Addressing Challenges and Exploring Untapped Opportunities

Hydropower plants are crucial for stable renewable energy and serve as vital water sources for sustainable agriculture. However, it is essential to assess the current water management practices associated with hydropower plant management software. A key concern is the potential conflict between electricity generation and agricultural water needs. Prioritising water for electricity generation can reduce irrigation availability in agriculture during crucial periods like droughts, impacting crop yields and regional food security. Coordination between electricity and agricultural water allocation is necessary to ensure optimal and environmentally sound practices. Neural networks have become valuable tools for hydropower plant management, but their black-box nature raises concerns about transparency in decision making. Additionally, current approaches often do not take advantage of their potential to create a system that effectively balances water allocation. This work is a call for attention and highlights the potential risks of deploying neural network-based hydropower plant management software without proper scrutiny and control. To address these concerns, we propose the adoption of the Agriculture Conscious Hydropower Plant Management framework, aiming to maximise electricity production while prioritising stable irrigation for agriculture. We also advocate reevaluating government-imposed minimum water guidelines for irrigation to ensure flexibility and effective water allocation. Additionally, we suggest a set of regulatory measures to promote model transparency and robustness, certifying software that makes conscious and intelligent water allocation decisions, ultimately safeguarding agriculture from undue strain during droughts

A Self-Adaptive Penalty Method for Integrating Prior Knowledge Constraints into Neural ODEs

The continuous dynamics of natural systems has been effectively modelled using Neural Ordinary Differential Equations (Neural ODEs). However, for accurate and meaningful predictions, it is crucial that the models follow the underlying rules or laws that govern these systems. In this work, we propose a self-adaptive penalty algorithm for Neural ODEs to enable modelling of constrained natural systems. The proposed self-adaptive penalty function can dynamically adjust the penalty parameters. The explicit introduction of prior knowledge helps to increase the interpretability of Neural ODE -based models. We validate the proposed approach by modelling three natural systems with prior knowledge constraints: population growth, chemical reaction evolution, and damped harmonic oscillator motion. The numerical experiments and a comparison with other penalty Neural ODE approaches and \emph{vanilla} Neural ODE, demonstrate the effectiveness of the proposed self-adaptive penalty algorithm for Neural ODEs in modelling constrained natural systems. Moreover, the self-adaptive penalty approach provides more accurate and robust models with reliable and meaningful predictions

The fracturation influence on the exploitation of ornamental rocks: the case of the Pedras Salgadas granite (Vila Real, North of Portugal)

[Abstract] The exploitation of ornamental granite in Pedras Salgadas region is limited by the regional fault pattern, which is formed by three sets of principal faults. Based upon the joint spacings measurements, the medium was computed for each quarry and for the massif. The medium exploitaion yield of the quarries was also estimated

Linfangioleiomiomatose pulmonar inicial provável e linfangioleiomioma mediastinal

A 68 year old woman was submitted to a mediastinal lymphangioleiomyoma resection found in a follow-up study of lower left lung resection due to bronchiectasis complicated by chylothorax. This led to a revaluation of the pulmonary specimen that revealed, in addition to inflammatory bronchiectasis, small spindle cell nodules in the lung parenchyma, similar to minute pulmonary meningothelial-like nodules, but with smooth muscle actin immunohistochemical positivity. The possibility of initial pulmonary development of lymphangioleiomyomatosis is discussed

Water use efficiency in bananas pome type cropsusing empirical coefficient based on leaf area.

The aim of this work was to evaluate the yield and water use efficiency (WUE) of banana ?Prata-Anã? (AAB) and ?BRS Platina? (AAAB) during two cycles of production in a semi-arid climate of Brazil (classified as Aw according Köppen)

The role of Dark Matter interaction in galaxy clusters

We consider a toy model to analyze the consequences of dark matter interaction with a dark energy background on the overall rotation of galaxy clusters and the misalignment between their dark matter and baryon distributions when compared to {\Lambda}CDM predictions. The interaction parameters are found via a genetic algorithm search. The results obtained suggest that interaction is a basic phenomenon whose effects are detectable even in simple models of galactic dynamics.Comment: RevTeX 4.1, 5 pages, 3 figure

Magnetic reconfiguration of MnAs/GaAs(001) observed by Magnetic Force Microscopy and Resonant Soft X-ray Scattering

We investigated the thermal evolution of the magnetic properties of MnAs epitaxial films grown on GaAs(001) during the coexistence of hexagonal/orthorhombic phases using polarized resonant (magnetic) soft X-ray scattering and magnetic force microscopy. The results of the diffuse satellite X-ray peaks were compared to those obtained by magnetic force microscopy and suggest a reorientation of ferromagnetic terraces as temperature rises. By measuring hysteresis loops at these peaks we show that this reorientation is common to all ferromagnetic terraces. The reorientation is explained by a simple model based on the shape anisotropy energy. Demagnetizing factors were calculated for different configurations suggested by the magnetic images. We noted that the magnetic moments flip from an in-plane mono-domain orientation at lower temperatures to a three-domain out-of-plane configuration at higher temperatures. The transition was observed when the ferromagnetic stripe width L is equal to 2.9 times the film thickness d. This is in good agreement with the expected theoretical value of L = 2.6d.Comment: 16 pages in PD

Metabolic engineering of fatty acids from soybean seeds.

Edição do Congress of the Brazilian Biotechnology Society, Florianópolis, 2013