Simulations of an impulsive model for the growth of fruit trees

Mediterranean agricultural systems have been severely affected because of the decrease in rainfall and more frequent and severe droughts due to the global warming phenomenon. The current and future scenario of water deficit could have a negative effect on the growth and development rates of the fruit trees, reflected in the drop of production. To help to face this problem, this work presents a mathematical simulation model of fruit growth with two-time scales: a continuous scale that governs the dynamics of fruit growth and a discrete scale representing the period of time in which the system is intervened with irrigation supply. The results obtained in the simulations allow us to describe and understand the physical phenomena involved in the growth dynamics of fruit trees. In addition, show the importance of the water resource for the growth and development of fruit trees; therefore, a scenario of water deficit would compromise the production and existence of fruit trees.

Complexity, interdisciplinarity and design literacy

In today’s complex world, a variety of perspectives are needed to better understand and solve challenges. For decades, global organisations and researchers have pointed to interdisciplinarity as a way forward for educational systems. Educational research offers great possibilities and gains for students involved in interdisciplinary teaching and learning processes, and the interdisciplinary nature of design thinking and practice can play a vital role in interdisciplinary general education. This paper explores how future scenario-building, as part of general design education, can serve as a framework for inter-disciplinarity in general education and contribute to a better understanding of complex problems, challenges and design literacy.

The Concept of Understanding the Social Phenomenon in Its Theoretical Images: From Reconstruction to Scenario Design

This article is devoted to solving the problem of epistemological and ontological insufficiency of traditional scientific approaches applied to the comprehension of social phenomena presented in their disordered, chaotic multidisciplinary theoretical images (interpretations). A comprehensive and in-depth analysis of disciplinary strategies / programs for comprehending social phenomena that serve as the object of scientific views of a number of scientific fields has shown that they demonstrate a pronounced methodological approach, lack of clarity of which description language describes / is able to fully describe their object of scientific knowledge. The key specificity of the problematization of the article is determined by the fact that the focus is on the process / result of reconstructing / constructing theoretical interpretations of a social phenomenon taken in the coordinates of space and time. It is proposed to correlate the following processes with the process of understanding the theoretical interpretations of the studied social phenomenon: reconstruction (past, present) and scenario construction (present, future). The author's analytical position is determined by the fact that theoretical interpretations of the perceived social phenomenon will always belong exclusively to the past and future of its plans, but not to the present. This implicit, but very important facet, unfortunately, escapes in the dominant and well-established theoretical reflection of social phenomena today. The main purpose of this publication is to overcome the above-mentioned difficulties, relying on the proposed universal concept of comprehension of multidisciplinary social phenomena. The author's approach proposed in the publication, based on the idea of understanding the theoretical interpretations of the social phenomenon under study belonging to the world of the past (reconstruction - for understanding the theorizations of its past events) and the future (scenario construction - for reflection on the theoretical pictures of its future events), is designed to overcome the discovered problem. Summarizing, the paper formulated the principles for determining the optimal way to comprehend social phenomena and the key prohibitions dictated by the author's concept of comprehending social phenomena revealed to the researcher in their multidisciplinary interpretations /theorizations.

Multi-criteria prioritization of the renewable power plants in Australia using the fuzzy logic in decision-making method (FMCDM)

The presented study focused on developing an innovative decision-making framework to select the best renewable-power-plant technologies, considering comprehensive techno-economic and environmental variables. Due to the favourable conditions, Australia was selected as the case study. A fuzzy-logic method and analytical hierarchy process were applied to prioritize different renewable-energy power plants. The techno-economic factors included levelized cost of energy, initial cost, simple payback time, and operation and maintenance costs along with environmental factors including carbon payback time, energy payback time and greenhouse-gas emissions were used to rank the power plants. The results showed that the capital cost and simple payback time had the highest priority from an economic point of view. In comparison, greenhouse-gas emissions and carbon payback time were the dominant environmental factors. The analysis results provided economic and environmental priority tables for developing different power plants in the current state and a future scenario by 2030. The fuzzy results and pairwise composite matrix of alternatives indicated that the onshore wind, offshore wind, single-axis tracker polycrystalline photovoltaic, single-axis tracker monocrystalline photovoltaic, fix-tilted polycrystalline photovoltaic and fix-tilted monocrystalline photovoltaic scored the highest in the current state. In contrast, by 2030, the single-axis tracker photovoltaic power plants will be the best choice in the future scenario in Australia. Finally, the results were used and analysed to recommend and suggest several policy implementations and future research studies.

Impact of climate change on agriculture in eastern Uttar Pradesh and Bihar states (India)

Production of crops is greatly influenced by weather phenomena and therefore any change in climate will have major effects on crop yield and productivity. Using NYD analysis for prediction of crop yield on seasonal basis, it has been observed that maximum temperature may cause the reduction in yield of rice in Eastern Uttar Pradesh by 1.0 to 1.1% per ha by 2020. Similarly, minimum temperature may decrease the yield of rice by 1.5 to 1.9% per ha in Eastern Uttar Pradesh. From future scenario of rainfall it was observed that south-west monsoonal rainfall would be the major factor for controlling the yield of rice. The role of maximum temperature for wheat production in Bihar state is more significant as compared to Eastern Uttar Pradesh. The model predicts that wheat yield may decrease by 5-6% in Bihar state due to increase in maximum temperature by the end of 2080 whereas this decrement in Eastern Uttar Pradesh may be 1.5-2.0%.

Northern Hemisphere drought risk in a warming climate

Drought frequency and severity are projected to increase in the future, but the changes are expected to be unevenly distributed across the globe. Based on multi-model simulations under three different future emissions and shared socioeconomic pathways, we show that a significant drought intensification is expected in dry regions, whereby the severity depends on greenhouse gas emissions and development pathways. The drought hotspots are located in the sub-tropical regions where a moderate to extreme summer drought in today’s climate is expected to become a new normal by the end of the 21st century under the warmest scenario. On average, under the warmest future scenario, the drought occurrence rate is projected to be 100% higher than that of the low emission scenario. Further, for the regions which are currently less affected by long-lasting droughts, such as the European continent, climate models indicate a significant increase in drought occurrence probability under the warmest future scenario.

Risk of infestations by Dendroctonus mexicanus Hopkins and Dendroctonus frontalis Zimmermann bark beetles in forests of Michoacán

Introduction: Severe Dendroctonus spp. infestations are reported in North and Central America. Dendroctonus mexicanus Hopkins and Dendroctonus frontalis Zimmermann are recognized as forest pests and are common in the state of Michoacán, Mexico.Objective: To model current and future (2015-2039) spatial distribution of risk D. mexicanus and D. frontalis infestation in forests of Michoacán, Mexico.Materials and methods: Multicriteria evaluation techniques, including the analytic hierarchy process and fuzzy membership functions, were combined with climate and biophysical variables to obtain forest infestation risk maps for D. mexicanus and D. frontalis under current and future climate scenarios.Results and discussion: Climate, fire, tree density and topography were identified as relevant criteria influencing bark beetle outbreaks. The maximum risk value estimated for D. mexicanus was 0.78 and 0.83 for the current and future scenarios, respectively; for D. frontalis these values correspond to 0.84 and 0.85, respectively. In terms of area, high risk of infestation by D. mexicanus increased from 3.9 % (current scenario) to 5.0 % (future scenario); for D. frontalis it decreased from 10.8 % to 9.6 %. The very high-risk value remained constant (0.35 %) for both species and scenarios.Conclusions: Forests of the Transversal Volcanic Belt (in the northeastern part of Michoacán) have the highest risk of bark beetle infestation in the two modeled scenarios.

Adaptive Structures and Biomimetic Robots – A Perspective

This paper gives an overview of some recent full-scale demonstrations of morphing devices capable of providing innovative capabilities to general systems in changing shape and improving performance significantly during operations. In aeronautics, large progress has been observed over the last few years, meaning that this technology is rapidly transitioning from laboratory scale to high TRL demonstrators. The most advanced concepts already proved to withstand loads with minimal deformation while having the capability to change their geometry to attain additional benefits with respect to their original mission. In the same way, robotics has become one of the most prominent technological trends of the current century. The rapid increase in their use and development has significantly changed our society by gradually replacing a large share of human jobs. Such an evolution is also rapidly accelerating, as technological advances in automation, engineering, artificial intelligence, and machine learning converge. Since both domains involve the integration of actuators, sensors and controllers and face integrity challenges in harsh environments, they may be seen somehow related and probably share a common future. In this article, the authors propose an original view of a possible future scenario that is likely to consider a unique development path for research on adaptive structures and robotics.

Electrification of Road Transport and the Impacts on Air Quality and Health in the UK

Currently, many cities in Europe are affected by concentrations of PM2.5 and NO2 above the WHO guidelines on the protection of human health. This is a global problem in which the growth of road transport constitutes a major factor. Looking to the future, electric vehicles (EVs) are considered to be the choice technology for reducing road transport greenhouse gas emissions, but their impact on air quality needs to be considered. Taking the UK as a case study, this paper begins by understanding the trajectory of a future scenario without the introduction of EVs, reflecting on the latest emission control improvements in internal combustion engine vehicles (ICEVs). This is then compared to a 2050 scenario in which the introduction of EVs, based on the UK government’s Transport Decarbonisation Plan, is reviewed. This plan includes a ban on the sale of ICEV cars and LGVs, beginning in 2030, with the subsequent electrification of heavier vehicles. By 2030, population exposure to NOx was found to be significantly reduced in the ICEV scenario, with a marginal further reduction found for the EV scenario. The EV scenario further reduced NOx exposure by 2050, with most of the benefits being realized before 2040. For the ICEV and EV scenario, PM2.5 emissions were largely unchanged due to the primary contribution of non-exhaust emissions, suggesting that EVs are likely to yield relatively smaller changes in exposure to PM2.5 than for NOx.