Proposing a Popular Method for Meteorological Drought Monitoring in the Kabul River Basin, Afghanistan

This paper investigates meteorological drought in one of Afghanistan's most important socio-economic river basins called Kabul River Basin (KRB) using a 38 years monthly precipitation data. Several drought indices such as Standardized Precipitation Index (SPI), Percent of Normal Precipitation Index (PNPI), Deciles Index (DI), and China-Z Index (CZI) were applied for the first time on the basin in order to observe the correlation among the indices in the basin for drought, and to see which method is suitable for drought monitoring in KRB. Due to the concerns that climate is changing and especially the rapid snowmelt that accounts for 80% of the precipitation in Afghanistan, it was essential to carry such a study in order to warn the responsible bodies in the country for a better drought management. Moreover, the rapid population increase and USAge of more water for both drinking and agricultural purposes in the basin with a possible decrease in the annual precipitation make it necessary to undertake such a study. The results of the investigation show that KRB area experienced drought conditions continuously from 2000 to 2004 with a peak extreme drought in 2001 which confirm to the reported worst drought in the region. It is noted that log-SPI, gamma-SPI, and Deciles captured the historical extreme and severe drought periods successfully, therefore, these methods are recommended to be applied to this region as drought assessment tools

Solving Ambiguities with Perspective Taking

Humans constantly generate and solve ambiguities while interacting with each other in their every day activities. Hence, having a robot that is able to solve ambiguous situations is essential if we aim at achieving a fluent and acceptable human-robot interaction. We propose a strategy that combines three mechanisms to clarify ambiguous situations generated by the human partner. We implemented our approach and successfully performed validation tests in several different situations both, in simulation and with the HRP-2 robot.Psycholog

Understanding the integration of artificial intelligence in healthcare organisations and systems through the NASSS framework: a qualitative study in a leading Canadian academic centre

Background: Artificial intelligence (AI) technologies are expected to “revolutionise” healthcare. However, despite their promises, their integration within healthcare organisations and systems remains limited. The objective of this study is to explore and understand the systemic challenges and implications of their integration in a leading Canadian academic hospital. Methods: Semi-structured interviews were conducted with 29 stakeholders concerned by the integration of a large set of AI technologies within the organisation (e.g., managers, clinicians, researchers, patients, technology providers). Data were collected and analysed using the Non-Adoption, Abandonment, Scale-up, Spread, Sustainability (NASSS) framework. Results: Among enabling factors and conditions, our findings highlight: a supportive organisational culture and leadership leading to a coherent organisational innovation narrative; mutual trust and transparent communication between senior management and frontline teams; the presence of champions, translators, and boundary spanners for AI able to build bridges and trust; and the capacity to attract technical and clinical talents and expertise. Constraints and barriers include: contrasting definitions of the value of AI technologies and ways to measure such value; lack of real-life and context-based evidence; varying patients’ digital and health literacy capacities; misalignments between organisational dynamics, clinical and administrative processes, infrastructures, and AI technologies; lack of funding mechanisms covering the implementation, adaptation, and expertise required; challenges arising from practice change, new expertise development, and professional identities; lack of official professional, reimbursement, and insurance guidelines; lack of pre- and post-market approval legal and governance frameworks; diversity of the business and financing models for AI technologies; and misalignments between investors’ priorities and the needs and expectations of healthcare organisations and systems. Conclusion: Thanks to the multidimensional NASSS framework, this study provides original insights and a detailed learning base for analysing AI technologies in healthcare from a thorough socio-technical perspective. Our findings highlight the importance of considering the complexity characterising healthcare organisations and systems in current efforts to introduce AI technologies within clinical routines. This study adds to the existing literature and can inform decision-making towards a judicious, responsible, and sustainable integration of these technologies in healthcare organisations and systems

Which One? Grounding the Referent Based on Efficient Human-Robot Interaction

In human-robot interaction, a robot must be prepared to handle possible ambiguities generated by a human partner. In this work we propose a set of strategies that allow a robot to identify the referent when the human partner refers to an object giving incomplete information, i.e. an ambiguous description. Moreover, we propose the use of an ontology to store and reason on the robot's knowledge to ease clarification, and therefore, improve interaction. We validate our work through both simulation and two real robotic platforms performing two tasks: a daily-life situation and a game.Psycholog

Numerical Study of the Bond Strength Evolution of Corroded Reinforcement in Concrete in Pull‐Out Tests

The corrosion of rebars in reinforced concrete structures impacts their geometry (diameter and ribs) and mass, damages the concrete at the interface between the two materials, deteriorates the bond strength, and causes the cracking of the concrete cover. In the following study, a 2D numerical model of the pull‐out test is presented in order to study the impact of corrosion on the bond strength. Several parameters are investigated: the embedment depth, the rebar’s diameter, and the width of the concrete cover. The model reproduces the slip of the rebar and the failure through the splitting of concrete. It integrates an interface between the two materials and a concrete damage model that simulate the deterioration of concrete in compression and tension. The results obtained are validated with experimental data from the literature. Moreover, a parametric study is carried out to determine the impact of the embedment depth, the diameter of the rebar, and the concrete cover on the bond strength. The present study confirms that a greater embedment depth increases the pulling load. The study also confirms that the rebar’s diameter impacts highly the loss of bond between the rebar and the concrete cover. Lastly, the final main result of this paper is that the width of the concrete cover slows the loss of bond strength between the two materials

International Journal of Smart Grid and Clean Energy Maximum power tracking control wind turbine based on permanent magnet synchronous generator with complete converter

Abstract This paper discusses the problem of maximum power point tracking (MPPT) of Wind Turbine based on a permanent magnet synchronous generator (PMSG) connected to power grid trough complete static converter. To achieve this, we propose a control scheme of synchronous generator, consisting of a DC/AC device followed by a second DC/AC device. The idea behind MPPT principle is turbine speed variation depending on wind speed in case of generator indirect connection to power grid. Simulations on Matlab-Simulink can be found at the end of the paper, confirming a good consistency with study objectives of control scheme, selection of setting parameters and complete converter architecture

Seismic risk in the city of Al Hoceima (north of Morocco) using the vulnerability index method, applied in Risk-UE project

The final publication is available at Springer via http://dx.doi.org/10.1007/s11069-016-2566-8Al Hoceima is one of the most seismic active regions in north of Morocco. It is demonstrated by the large seismic episodes reported in seismic catalogs and research studies. However, seismic risk is relatively high due to vulnerable buildings that are either old or don’t respect seismic standards. Our aim is to present a study about seismic risk and seismic scenarios for the city of Al Hoceima. The seismic vulnerability of the existing residential buildings was evaluated using the vulnerability index method (Risk-UE). It was chosen to be adapted and applied to the Moroccan constructions for its practicality and simple methodology. A visual inspection of 1102 buildings was carried out to assess the vulnerability factors. As for seismic hazard, it was evaluated in terms of macroseismic intensity for two scenarios (a deterministic and probabilistic scenario). The maps of seismic risk are represented by direct damage on buildings, damage to population and economic cost. According to the results, the main vulnerability index of the city is equal to 0.49 and the seismic risk is estimated as Slight (main damage grade equal to 0.9 for the deterministic scenario and 0.7 for the probabilistic scenario). However, Moderate to heavy damage is expected in areas located in the newer extensions, in both the east and west of the city. Important economic losses and damage to the population are expected in these areas as well. The maps elaborated can be a potential guide to the decision making in the field of seismic risk prevention and mitigation strategies in Al Hoceima.Peer ReviewedPostprint (author's final draft

Transient up- and down-regulation of expression of myosin light chain 2 and myostatin mRNA mark the changes from stratified hyperplasia to muscle fiber hypertrophy in larvae of gilthead sea bream (Sparus aurata L.)

Hyperplasia and hypertrophy are the two mechanisms by which muscle develops and grows. We study these two mechanisms, during the early development of white muscle in Sparus aurata, by means of histology and the expression of structural and regulatory genes. A clear stage of stratified hyperplasia was identified early in the development of gilthead sea bream but ceased by 35 dph when hypertrophy took over. Mosaic recruitment of new white fibers began as soon as 60 dph. The genes mlc2a and mlc2b were expressed at various levels during the main phases of hyperplasia and hypertrophy. The genes myog and mlc2a were significantly up-regulated during the intensive stratified formation of new fibers and their expression was significantly correlated. Expression of mstn1 and igf1 increased at 35 dph, appeared to regulate the hyperplasia-to-hypertrophy transition, and may have stimulated the expression of mlc2a, mlc2b and col1a1 at the onset of mosaic hyperplasia. The up-regulation of mstn1 at transitional phases in muscle development indicates a dual regulatory role of myostatin in fish larval muscle growth