Irrigation water pricing between governmental policies and farmers’ perception: Implications for green-houses horticultural production in Teboulba (Tunisia)

A positive mathematical programming model was constructed in this study to assess the effect of three water pricing scenarios on Teboulba’s agricultural production systems. The effects of these scenarios were estimated for three groups of farmers from three irrigated districts. Results show that water demand in group 1 remains inelastic until achieving the price of 0.20 TD. A price above this level decreases water consumption, farmer’s incomes as well as seasonal labor demand. For groups 2 and 3, the water demand curves remain highly inelastic even with a full cost recovery price. However, once reaching this last price, the model shows important income reductions reaching 20% of the current observed income. Moreover, a pricing policy aiming to recover operational and maintenance costs and which will be implemented independently from other economic, social and environmental measures can threaten the sustainability of the production systems in the region.Water pricing, positive mathematical programming, greenhouses, economic impact, Teboulba, Environmental Economics and Policy, Farm Management, Resource /Energy Economics and Policy, Q15, Q18,

The Effect of E-Learning Approach on Studentsa Achievement in Fraction Math Course Level 5 at Yemens Public Primary School

E-learning (EL) is widely used in school and other organizations all over the world, because of difficulties in math skills (Remembering , understanding , application). There have not been any major surveys in the Yemen Public Primary School (YPPS) in that regard. This is the driving question behind this research: What is the effectiveness and usefulness of using e-learning approach in teaching the fraction math course for students of level 5 in the republic of Yemen on (Remembering , understanding , application) skills ? In this study, an experimental group of (30) students studying a course using e-learning approach. The control group (30) students they studying a course traditional learning, experimental design approach were used. The students2019; achievement was examined between two groups. The research results proved that there is a significant increase in gain in achievement, The EL has achieved efficiency greater than traditional learning in (Remembering, understanding, application) skills

High Glucose, High Fatty Acid-Induced Toxicity, Oxidative and Metabolic Stress and Alterations in Cell Signalling In Pancreatic Rin-5f Cells: Attenuation by N-Acetylcysteine

Hyperglycaemia and hyperlipidaemia are the main causes of diabetes and obesity-associated complications. Increased oxidative stress, inflammatory responses and altered energy metabolism have been associated with hyperglycaemia and hyperlipidaemia. The concept of ‘glucolipotoxicity’ has arisen from the combination of the deleterious effects of the chronic elevation of levels of glucose and fatty acids on pancreatic β-cells’ function and/or survival. The synergistic effect of both nutrients exacerbates β-cells’ dysfunction over time and creates a vicious cycle of impaired insulin secretion and metabolic disturbances. Though numerous studies have been conducted in this field, the exact molecular mechanisms and causative factors still need to be established. The aim of the present work is to elucidate the molecular mechanisms of altered cell signalling, oxidative and metabolic stress, and inflammatory/antioxidant responses in the presence of high concentrations of glucose/fatty acids in a cell-culture system using an insulin-secreting pancreatic β- cell line (Rin-5F) and to study the effect of the antioxidant N-acetylcysteine (NAC) on β-cell toxicity. In our study, we investigated the molecular mechanism of cytotoxicity due to high glucose concentration (up to 25mM) and high saturated fatty acid concentration (up to 0.3mM palmitic acid) on Rin-5F cells. In this regard, initially, we investigated the effects of streptozotocin (STZ), a known β-cell toxin that is structurally related to glucose, to identify specific molecular and metabolic targets affected in pancreatic β-cells. Furthermore, we aim to elucidate the cytoprotective effects of NAC on β-cell toxicity induced by STZ/high glucose/high palmitic acid. Our results show that the cellular and molecular mechanisms of β-cell toxicity are mediated by increased oxidative stress, imbalance of redox homeostasis, disruption of mitochondrial bioenergetics and alterations in cell signalling. On the other hand, NAC treatment attenuates β-cell cytotoxicity, apoptosis and mitochondrial damage associated with oxidative stress. The use of an in-vitro cell-culture model in this study suggests the cellular and molecular mechanism(s) of β-cell toxicity without the involvement of multiple physiological factors that would be seen in vivo, which might contribute to the disease progression

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds

Deep neural networks are vulnerable to adversarial attacks, in which imperceptible perturbations to their input lead to erroneous network predictions. This phenomenon has been extensively studied in the image domain, and has only recently been extended to 3D point clouds. In this work, we present novel data-driven adversarial attacks against 3D point cloud networks. We aim to address the following problems in current 3D point cloud adversarial attacks: they do not transfer well between different networks, and they are easy to defend against via simple statistical methods. To this extent, we develop a new point cloud attack (dubbed AdvPC) that exploits the input data distribution by adding an adversarial loss, after Auto-Encoder reconstruction, to the objective it optimizes. AdvPC leads to perturbations that are resilient against current defenses, while remaining highly transferable compared to state-of-the-art attacks. We test AdvPC using four popular point cloud networks: PointNet, PointNet++ (MSG and SSG), and DGCNN. Our proposed attack increases the attack success rate by up to 40% for those transferred to unseen networks (transferability), while maintaining a high success rate on the attacked network. AdvPC also increases the ability to break defenses by up to 38% as compared to other baselines on the ModelNet40 dataset.Comment: Presented at European conference on computer vision (ECCV), 2020. The code is available at https://github.com/ajhamdi/AdvP