Exploration of the UAE Native Plants For sustainable Landscaping in Arid Region

In order to maintain sustainability for landscapes in the arid region, the use of native plants is of considerable importance, in the light of the fact that the exotic plants currently used do not resource efficient. The native plants adapted to the harsh environment of the desert ecosystem could play a critical role in this direction where the natural resources could be sustainably used. Research on evaluation and analyzes of native plant species of the UAE for potential application in landscapes have been considered. The present investigation reports the results of the exploration of native plants suited for sustainable landscape for resource efficiency. It also encompasses the study about the response of native grass species identified in the survey and the shrubs to varying levels of irrigation. Further, the germination responses of selected plant species, tissue culture propagation of endangered tree species and their long-term conservation strategies were also part of the study. During plant exploration, 61 plants were identified with potential for landscaping out of which, based on further evaluations with specific landscape qualities, 30 plant species of different forms were recommended for future landscape use. A native grass Digitaria spp. was identified, which was found to have the potential to be used as ground covers in arid landscapes, compared with four nonnative grass species. The analysis and confirmation of stabilized responses for drought tolerance were done based on morphological responses, elemental status and antioxidant enzyme mechanisms operating under wider frequency of irrigation. In 9 selected shrubs and one grass species, irrigation experiment was conducted with a constant irrigation volume under four different frequencies. The responses to induced drought were assessed based on the morphological parameters, macro and micronutrient status that can influence the growth and development. The seeds of fourteen plant species were subjected to germination responses after exogenous application of gibberellic acid at 400 mg/l and 200 mg/l to accelerate germination, where many of the desert species are recalcitrant. The mean germination time (MGT) was shorter, where higher germination is noticed. In vitro propagation protocols were standardized in 3 endangered tree species viz., Moringa peregrina, Haloxylon persicum and Acridocarpus orientalis by direct organogenesis as part of in vitro conservation and faster multiplication. Long-term storage employing cryopreservation by vitrification and desiccation method was accomplished in the above three species. Based on the findings of this study, it can be concluded that the use of native plants of the UAE for landscape applications could create resource efficient, sustainable landscaping

A Distributed SON-Based User-Centric Backhaul Provisioning Scheme

5G definition and standardization projects are well underway, and governing characteristics and major challenges have been identified. A critical network element impacting the potential performance of 5G networks is the backhaul, which is expected to expand in length and breadth to cater to the exponential growth of small cells while offering high throughput in the order of gigabit per second and less than 1 ms latency with high resilience and energy efficiency. Such performance may only be possible with direct optical fiber connections that are often not available country-wide and are cumbersome and expensive to deploy. On the other hand, a prime 5G characteristic is diversity, which describes the radio access network, the backhaul, and also the types of user applications and devices. Thus, we propose a novel, distributed, self-optimized, end-to-end user-cell-backhaul association scheme that intelligently associates users with candidate cells based on corresponding dynamic radio and backhaul conditions while abiding by users' requirements. Radio cells broadcast multiple bias factors, each reflecting a dynamic performance indicator (DPI) of the end-to-end network performance such as capacity, latency, resilience, energy consumption, and so on. A given user would employ these factors to derive a user-centric cell ranking that motivates it to select the cell with radio and backhaul performance that conforms to the user requirements. Reinforcement learning is used at the radio cells to optimise the bias factors for each DPI in a way that maximise the system throughput while minimising the gap between the users' achievable and required end-to-end quality of experience (QoE). Preliminary results show considerable improvement in users' QoE and cumulative system throughput when compared with the state-of-the-art user-cell association schemes

CONSIDERATIONS ON A THEORY OF DESCRIPTIVE ACTIVITY

From a working definition of description, the meaning of idealized representation is presented. I t is suggested that, as a universal means of depiction, idealized representation stands in a contradictory relationship with the concrete conditions of its production, generating descriptive irresponsibility. Features of descriptive activity are presented, which serve as a basis for redefining the moral character of idealized representation

Computational Discovery of Energy-Efficient Heat Treatment for Microstructure Design using Deep Reinforcement Learning

Deep Reinforcement Learning (DRL) is employed to develop autonomously optimized and custom-designed heat-treatment processes that are both, microstructure-sensitive and energy efficient. Different from conventional supervised machine learning, DRL does not rely on static neural network training from data alone, but a learning agent autonomously develops optimal solutions, based on reward and penalty elements, with reduced or no supervision. In our approach, a temperature-dependent Allen-Cahn model for phase transformation is used as the environment for the DRL agent, serving as the model world in which it gains experience and takes autonomous decisions. The agent of the DRL algorithm is controlling the temperature of the system, as a model furnace for heat-treatment of alloys. Microstructure goals are defined for the agent based on the desired microstructure of the phases. After training, the agent can generate temperature-time profiles for a variety of initial microstructure states to reach the final desired microstructure state. The agent's performance and the physical meaning of the heat-treatment profiles generated are investigated in detail. In particular, the agent is capable of controlling the temperature to reach the desired microstructure starting from a variety of initial conditions. This capability of the agent in handling a variety of conditions paves the way for using such an approach also for recycling-oriented heat treatment process design where the initial composition can vary from batch to batch, due to impurity intrusion, and also for the design of energy-efficient heat treatments. For testing this hypothesis, an agent without penalty on the total consumed energy is compared with one that considers energy costs. The energy cost penalty is imposed as an additional criterion on the agent for finding the optimal temperature-time profile

Shedding light on the formation of the pre-biotic molecule formamide with ASAI

Formamide (NH2CHO) has been proposed as a pre-biotic precursor with a key role in the emergence of life on Earth. While this molecule has been observed in space, most of its detections correspond to high-mass star-forming regions. Motivated by this lack of investigation in the low-mass regime, we searched for formamide, as well as isocyanic acid (HNCO), in 10 low- and intermediate-mass pre-stellar and protostellar objects. The present work is part of the IRAM Large Programme ASAI (Astrochemical Surveys At IRAM), which makes use of unbiased broadband spectral surveys at millimetre wavelengths. We detected HNCO in all the sources and NH2CHO in five of them. We derived their abundances and analysed them together with those reported in the literature for high-mass sources. For those sources with formamide detection, we found a tight and almost linear correlation between HNCO and NH2CHO abundances, with their ratio being roughly constant -between 3 and 10- across 6 orders of magnitude in luminosity. This suggests the two species are chemically related. The sources without formamide detection, which are also the coldest and devoid of hot corinos, fall well off the correlation, displaying a much larger amount of HNCO relative to NH2CHO. Our results suggest that, while HNCO can be formed in the gas phase during the cold stages of star formation, NH2CHO forms most efficiently on the mantles of dust grains at these temperatures, where it remains frozen until the temperature rises enough to sublimate the icy grain mantles. We propose hydrogenation of HNCO as a likely formation route leading to NH2CHO.Comment: 26 pages, 9 figures. Accepted by Monthly Notices of the Royal Astronomical Societ

‘Not the same person anymore’: groupwork, identity and social learning online

This paper argues that identity may be key to understanding why social presence has been considered so important to successful learning experiences. A qualitative case study of 10 students and 4 tutors in an online postgraduate education program was conducted. The research applied the work of Goffman to explain the relationship between social presence and support for the social production of identity online. Semi-structured individual and group interviews revealed the importance of trustworthy social interaction to support students’ performance of identity and identity shifts in fostering deeper social learning. Implications for the design of effective online learning experiences are provided

An efficient data Parallelization of the Radix-23 (Carbon) FFT on GPU/CPU

Solving Complex Problem that is coupled with intensive workloads; necessities the access to a massively parallel computational power. Up to date, Graphic Processing Units (GPUs) are the only architecture that could handle the most complex computationally intensive workloads. In the light of this rapid-growing advancement in computational technologies, this paper will propose a high-performance parallel radix-23 FFT suitable for such GPU and CPU systems. The proposed algorithm could reduce the computational complexity by a factor that tends to reach pr if implemented in parallel (pr is the number of cores/threads) plus the combination phase to complete the required FFT