Bamboo reinforced concrete: a critical review

© 2018, The Author(s). The use of small diameter whole-culm (bars) and/or split bamboo (a.k.a. splints or round strips) has often been proposed as an alternative to relatively expensive reinforcing steel in reinforced concrete. The motivation for such replacement is typically cost—bamboo is readily available in many tropical and sub-tropical locations, whereas steel reinforcement is relatively more expensive—and more recently, the drive to find more sustainable alternatives in the construction industry. This review addresses such ‘bamboo-reinforced concrete’ and assesses its structural and environmental performance as an alternative to steel reinforced concrete. A prototype three bay portal frame, that would not be uncommon in regions of the world where bamboo-reinforced concrete may be considered, is used to illustrate bamboo reinforced concrete design and as a basis for a life cycle assessment of the same. The authors conclude that, although bamboo is a material with extraordinary mechanical properties, its use in bamboo-reinforced concrete is an ill-considered concept, having significant durability, strength and stiffness issues, and does not meet the environmentally friendly credentials often attributed to it

A historical overview of the classification, evolution, and dispersion of Leishmania parasites and sandflies

Background The aim of this study is to describe the major evolutionary historical events among Leishmania, sandflies, and the associated animal reservoirs in detail, in accordance with the geographical evolution of the Earth, which has not been previously discussed on a large scale. Methodology and Principal Findings Leishmania and sandfly classification has always been a controversial matter, and the increasing number of species currently described further complicates this issue. Despite several hypotheses on the origin, evolution, and distribution of Leishmania and sandflies in the Old and New World, no consistent agreement exists regarding dissemination of the actors that play roles in leishmaniasis. For this purpose, we present here three centuries of research on sandflies and Leishmania descriptions, as well as a complete description of Leishmania and sandfly fossils and the emergence date of each Leishmania and sandfly group during different geographical periods, from 550 million years ago until now. We discuss critically the different approaches that were used for Leishmana and sandfly classification and their synonymies, proposing an updated classification for each species of Leishmania and sandfly. We update information on the current distribution and dispersion of different species of Leishmania (53), sandflies (more than 800 at genus or subgenus level), and animal reservoirs in each of the following geographical ecozones: Palearctic, Nearctic, Neotropic, Afrotropical, Oriental, Malagasy, and Australian. We propose an updated list of the potential and proven sandfly vectors for each Leishmania species in the Old and New World. Finally, we address a classical question about digenetic Leishmania evolution: which was the first host, a vertebrate or an invertebrate? Conclusions and Significance We propose an updated view of events that have played important roles in the geographical dispersion of sandflies, in relation to both the Leishmania species they transmit and the animal reservoirs of the parasites

Towards learning travelers’ preferences in a context-aware fashion

Providing personalized offers, and services in general, for the users of a system requires perceiving the context in which the users’ preferences are rooted. Accordingly, context modeling is becoming a relevant issue and an expanding research field. Moreover, the frequent changes of context may induce a change in the current preferences; thus, appropriate learning methods should be employed for the system to adapt automatically. In this work, we introduce a methodology based on the so-called Context Dimension Tree—a model for representing the possible contexts in the very first stages of Application Design—as well as an appropriate conceptual architecture to build a recommender system for travelers

Context Awareness in the Travel Companion of the Shift2Rail Initiative

Providing personalized offers, and services in general, for the users of a system requires perceiving the context in which the users' preferences are rooted. In this work, we introduce the use of an already known model and methodology-based on the so-called Context Dimen-sion Tree- A long with a conceptual architecture to build a recommender system that offers personalized services for travelers. The research is per-formed in the frame of the Shift2Rail initiative as part of the Innovation Programme 4 of EU Horizon 2020

Thermography captures the differential sensitivity of dryland functional types to changes in rainfall event timing and magnitude

Drylands of the southwestern United States are rapidly warming, and rainfall is becoming less frequent and more intense, with major yet poorly understood implications for ecosystem structure and function. Thermography-based estimates of plant temperature can be integrated with air temperature to infer changes in plant physiology and response to climate change. However, very few studies have evaluated plant temperature dynamics at high spatiotemporal resolution in rainfall pulse-driven dryland ecosystems. We address this gap by incorporating high-frequency thermal imaging into a field-based precipitation manipulation experiment in a semi-arid grassland to investigate the impacts of rainfall temporal repackaging. All other factors held constant, we found that fewer/larger precipitation events led to cooler plant temperatures (1.4°C) compared to that of many/smaller precipitation events. Perennials, in particular, were 2.5°C cooler than annuals under the fewest/largest treatment. We show these patterns were driven by: increased and consistent soil moisture availability in the deeper soil layers in the fewest/largest treatment; and deeper roots of perennials providing access to deeper plant available water. Our findings highlight the potential for high spatiotemporal resolution thermography to quantify the differential sensitivity of plant functional groups to soil water availability. Detecting these sensitivities is vital to understanding the ecohydrological implications of hydroclimate change.U.S. Department of Agriculture12 month embargo; first published 11 July 2023This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

2019–2020 Australia Fire and Its Relationship to Hydroclimatological and Vegetation Variabilities

Wildfire is a major concern worldwide and particularly in Australia. The 2019–2020 wildfires in Australia became historically significant as they were widespread and extremely severe. Linking climate and vegetation settings to wildfires can provide insightful information for wildfire prediction, and help better understand wildfires behavior in the future. The goal of this research was to examine the relationship between the recent wildfires, various hydroclimatological variables, and satellite-retrieved vegetation indices. The analyses performed here show the uniqueness of the 2019–2020 wildfires. The near-surface air temperature from December 2019 to February 2020 was about 1 °C higher than the 20-year mean, which increased the evaporative demand. The lack of precipitation before the wildfires, due to an enhanced high-pressure system over southeast Australia, prevented the soil from having enough moisture to supply the demand, and set the stage for a large amount of dry fuel that highly favored the spread of the fires

A Multi-objective Mathematical Model Considering Economic and Social Criteria in Dynamic Cell Formation

Part 1: Knowledge-Based SustainabilityInternational audienceThis paper addresses a Dynamic Cellular Manufacturing Systems (DCMS) problem considering both economic and social criteria, that is, the problem deals with the minimization of the total costs and maximization of social issues. We develop a bi-objective mathematical model of this problem in order to capture the trade-off between these two objectives. The strategic decisions considered in the model define the configuration of cells and part-families in each period. In order to solve our model, we design a new Non-dominated Sorting Genetic Algorithm (NSGA-II) as a meta-heuristic method. Our approach is illustrated on two samples of problems randomly generated