Displacements of Slopes Under Earthquake Loading

The displacements and rates of displacement of slopes post-rupture are influenced by the dynamic response of soils. Pre-existing shear surfaces at or close to residual strength are frequently present in slopes of clay and weak mudstone, due to previous slope movement or tectonic disturbance. Knowledge of the strength of such surfaces under rapid loading is necessary of stability during and after an earthquake is to be examined. To obtain such data, high speed displacement controlled ring shear tests have been performed, on samples after being pre-sheared to residual conditions. With the results from those tests, suitable constitutive laws were derived for the soils and numerical analysis were made of an old landslide submitted to dynamic earthquake loading. Analysis were also performed for first landslides, on plastic clays, in order to calculate the maximum velocity, displacement and duration of sliding. The calculation is based on the assumption that the whole moving mass is displaced as a single rigid body with resistance mobilised along the sliding surface. Newmark\u27s sJjding block was used, sliding on a nonlinear surface involving a resistance dependent on factors such as displacement and rate of slip

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

Spectral libraries and their uncertainties

Libraries of stellar spectra are fundamental tools in the study of stellar populations and in automatic determination of atmospheric parameters for large samples of observed stars. In the context of the present volume, here I give an overview of the current status of stellar spectral libraries from the perspective of stellar population modeling: what we have currently available, how good they are, and where we need further improvement

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

Nano-hydroxyapatite in oral care cosmetics: characterization and cytotoxicity assessment

Nano-hydroxyapatite has been used as an oral care ingredient, being incorporated in several products for the treatment of dental hypersensitivity and enamel remineralisation. Despite its promising results, regulatory and safety concerns have been discussed and questioned by the European Scientific Committee on Consumer Safety (SCCS) regarding the usage of hydroxyapatite nanoparticles in oral care products. In this work, a commercially available nano-hydroxyapatite was characterized and its cytocompatibility towards human gingival fibroblasts was evaluated, as well as its irritation potential using the in vitro HET-CAM assay. All the conditions chosen in this study tried to simulate the tooth brushing procedure and the hydroxyapatite nanoparticles levels normally incorporated in oral care products. The commercial hydroxyapatite nanoparticles used in this study exhibited a rod-like morphology and the expected chemical and phase composition. The set of in vitro cytotoxicity parameters accessed showed that these nanoparticles are highly cytocompatible towards human gingival fibroblasts. Additionally, these nanoparticles did not possess any irritation potential on HET-CAM assay. This study clarifies the issues raised by SCCS and it concludes that this specific nano-hydroxyapatite is cytocompatible, as these nanoparticles did not alter the normal behaviour of the cells. Therefore, they are safe to be used in oral care products.The authors acknowledge the support of the Biointerfaces and Nanotechnology i3S Scientific Platform, as well as Luís Teixeira and Marta Ferro from University of Aveiro for the characterization of the HA-NP with TEM. Financial support from the European Union (FEDER funds POCI/01/0145/FEDER/007265) and National Funds (FCT/MEC, Fundação para a Ciência e Tecnologia and Ministério da Educação e Ciência) under the Partnership Agreement PT2020 UID/QUI/50006/2019 is acknowledged

Biological control of Prays Oleae (BERN.) By chrysopids in tras-os-Montes region (Northeastern Portugal)

A study was carried out in an olive grove in the Tras-os-Montes region, in the period 1993 to 1996 to establish the rate of predation of chrysopids on Prays oleae (Bern.) eggs. Data on a trial conducted in 1996 to evaluate the effectiveness of field releases of Chrysoperla carnea (Steph.) in controlling eggs of the carpophagous generation of the pest are also reported. Six species of Chrysopidae have been collected. The most abundant were C. carnea and Mallada flavifrons (Brauer) which together represented about 74% of total captures. The main period of adult catches occurred between July and October. The rate of predation by chrysopids on P. oleae eggs varied among different generations of the pest and in different years, reaching 34% for the carpophagous generation in 1996. The potential damage that might be expected from the studied population of P. oleae was almost halved by releasing 360 larvae of C. carnea per tree.PAMAF lED no 611