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

Gênero, religião e cultura organizacional: uma perspectiva comparativa entre Brasil e França

SANTOS, Naira Pinheiro dos. Gênero, religião e cultura organizacional: uma perspectiva comparativa entre Brasil e França. São Paulo: Terceira Via, 2018

As novas guerras sexuais: diferença, poder religioso e identidade LGBT no Brasil.

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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

Ideologia de gênero: os porquês e suas consequências no contexto do Plano Nacional de Educação Brasileiro 2014-2024

Nos debates que envolveram o Plano Nacional de Educação 2014-2024, no Brasil, foram derrubadas as explicitações diretivas, dentre as quais constavam gênero e orientação sexual. Analisando este contexto, o presente artigo defende a necessidade da educação com base em gênero e orientação sexual no Brasil, tal como já havia sido indicado no Documento Final da CONAE 2010. Além disso, o texto explana por que gênero se tornou um grande foco de atuação política de políticos religiosos e lideranças católicas e evangélicas, de forma que sua articulação política e suas falas que apontam gênero como ideologia foram capazes de produzir fobia de gênero na população brasileira

Religião e Política: medos sociais, extremismo religioso e as eleições 2014

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Development of a machine learning model and a user interface to detect illegal swimming pools

Portuguese legislation states the compulsory reporting of the addition of amenities, such as swimming pools, to the Portuguese tax authority. The purpose is to update the property tax value, to be charged annually to the owner of each real estate. According to MarketWatch, this decade will bring a global rise to the number of swimming pools due to certain factors such as: cost reduction, increasing health consciousness, and others. The need for inspections to ensure that all new constructions are communicated to the competent authorities is therefore rapidly increasing and new solutions are needed to address this problem. Typically, supervision is done by sending human resources to the field, involving huge time and resource consumption, and preventing the catalogue from updating at a rate close to the speed of construction. Automation is rapidly becoming an absolute requirement to improve task efficiency and affordability. Recently, Deep Learn- ing algorithms have shown incredible performance results when used for object detection tasks. Based on the above, this work presents a study on the various existing object detec- tion algorithms and the implementation of a Deep Learning model capable of recognizing swimming pools from satellite images. To achieve the best results for this specific task, the RetinaNet algorithm was chosen. To provide a smooth user experience with the developed model, a simple graphical user interface was also created

Monocytes as Endothelial Progenitor Cells (EPCs), Another Brick in the Wall to Disentangle Tumor Angiogenesis

The project was funded by IPOLFG, EPE, by iNOVA4Health (UID/Multi/04462/2019) a program financially supported by Fundação para a Ciência e Tecnologia/Ministério da Educação e Ciência, through national funds and co-funded by FEDER under the PT2020 Partnership Agreement and by Fundação para a Ciência eTecnologia (PhD student fellowship: PD/BD/128337/2017).Bone marrow contains endothelial progenitor cells (EPCs) that, upon pro-angiogenic stimuli, migrate and differentiate into endothelial cells (ECs) and contribute to re-endothelialization and neo-vascularization. There are currently no reliable markers to characterize EPCs, leading to their inaccurate identification. In the past, we showed that, in a panel of tumors, some cells on the vessel wall co-expressed CD14 (monocytic marker) and CD31 (EC marker), indicating a putative differentiation route of monocytes into ECs. Herein, we disclosed monocytes as potential EPCs, using in vitro and in vivo models, and also addressed the cancer context. Monocytes acquired the capacity to express ECs markers and were able to be incorporated into blood vessels, contributing to cancer progression, by being incorporated in tumor neo-vasculature. Reactive oxygen species (ROS) push monocytes to EC differentiation, and this phenotype is reverted by cysteine (a scavenger and precursor of glutathione), which indicates that angiogenesis is controlled by the interplay between the oxidative stress and the scavenging capacity of the tumor microenvironment.publishersversionpublishe

Moderate exercise training promotes adaptations in coronary blood flow and adenosine production in normotensive rats

OBJECTIVES: Aerobic exercise training prevents cardiovascular risks. Regular exercise promotes functional and structural adaptations that are associated with several cardiovascular benefits. The aim of this study is to investigate the effects of swimming training on coronary blood flow, adenosine production and cardiac capillaries in normotensive rats. METHODS: Wistar rats were randomly divided into two groups: control (C) and trained (T). An exercise protocol was performed for 10 weeks and 60 min/day with a tail overload of 5% bodyweight. Coronary blood flow was quantified with a color microsphere technique, and cardiac capillaries were quantified using light microscopy. Adenine nucleotide hydrolysis was evaluated by enzymatic activity, and protein expression was evaluated by western blot. The results are presented as the means ± SEMs (p<0.05). RESULTS: Exercise training increased the coronary blood flow and the myocardial capillary-to-fiber ratio. Moreover, the circulating and cardiac extracellular adenine nucleotide hydrolysis was higher in the trained rats than in the sedentary rats due to the increased activity and protein expression of enzymes, such as E-NTPDase and 59- nucleotidase. CONCLUSIONS: Swimming training increases coronary blood flow, number of cardiac capillaries, and adenine nucleotide hydrolysis. Increased adenosine production may be an important contributor to the enhanced coronary blood flow and angiogenesis that were observed in the exercise-trained rats; collectively, these results suggest improved myocardial perfusion