Smart Urbanization – Key to Sustainable Cities

Urbanisation is a major change taking place globally. It is estimated that 500 million people will be urbanised by 2030 which is around 60% of the world’s population will be living in cities. Cities fuel economic development through mobilizing capital, work force, knowledge/information and technology and offer better chances of wealth generation, better health facilities, education and a good quality of life with better services and facilities. This has led to the increase in “megacities” (urban areas with a population of 10 million or more) and primate cities (leading cities in the region disproportionately larger than others in the urban hierarchy) across the globe. Urbanization propelled by economic reforms are putting cities under perpetual pressure of population concentration and energy intensive growth model. The cities are often confronted with a multitude of key problems like high urban densities, traffic congestion, energy inadequacy, unplanned development and lack of basic services. Due to high land values, migrants often have no choice but to settle in shantytowns and slums, where they lack access to decent housing and sanitation, health care and education thus adding to urban poverty. Urbanisation is also contributing significantly to climate change as 20 largest cities consume 80% of the world’s energy and urban areas generate 80% of greenhouse gas emissions worldwide. The challenges of rapid urbanisation are to deal with the social, economic and environment development through more effective and comprehensive land administration functions, supported by efficient per capita infrastructure supply , resolving issues such as climate change, disaster management, insecurity, energy scarcity, environmental pollution, and extreme poverty. Urbanization must be able to support urban planning to achieve sustainable development in order to meet the growing energy and housing demands, reliable public transportation systems and be able to meet essential urban services without putting pressure on resources. Therefore it needs to support innovative urban planning policies and strategies beyond traditional urban planning paradigms. Urbanisation on the positive side provides an unparalleled urban planning opportunity to pre-address social and environmental problems, including reduction of greenhouse gas emissions combined with the retrofitting and upgrading of facilities and networks in existing urban centres, as well as smart urban planning of cities can provide better education, healthcare and high-quality energy services more efficiently and with less emissions because of their advantages of scale, proximity and lower geographic footprints. Thus “Smart Urbanisation” is the key to safer cities of tomorrow. Building cities sustainably using smart growth principles, compact development planning form, using eco-city concepts, concept of low carbon electricity ecosystem etc, provides an opportunity to avoid future sources of greenhouse emissions, while developing more liveable and efficient urban centres. It could also alleviate population pressure on natural habitats and biodiversity thus reducing the risks to natural disasters. High-level integration of existing technologies to deliver a smart energy network, enhanced electricity transmission, energy efficient transportation, and low carbon building footprints, will make it easier to manage the unfolding urbanisation, and could have much positive impact on energy use and consumption. Policy interventions and government investments are important determining tools to its success. This paper attempts to discuss the principles of “smart urbanisation” in light of sustainable cities of tomorrow

Outbreak of Salmonella Typhi enteric fever in sub-urban area of North India: A public health perspective

AbstractOutbreaks of enteric fever are a major health concern not only due to significant human morbidity and mortality but also fear of spread of multidrug resistant strains. We report an outbreak of enteric fever caused by Salmonella enterica serotype Typhi in a suburban area, in city Chandigarh of North India. Twenty-seven strains of S. typhi were isolated from blood cultures over a period of two weeks with 18 of these 27 patients residing in the same area. Maximum cases were in the age group 5-14 years (10 patients, 55.5%) while 4 (22.2%) cases were children under 5 years. All the strains showed similar resistogram being resistant to ampicillin and nalidixic acid, intermediate to ciprofloxacin and sensitive to chloramphenicol, ceftriaxone, cefotaxime, cotrimoxazole and azithromycin on disc diffusion testing. Minimum inhibitory concentration of ciprofloxacin was determined by agar dilution method and was found to be raised (⩾ 2 μ g/mL). This nalidixic acid resistant S. typhi outbreak report warrants the necessity of implementing stringent sanitation practices in public health interest

Stability Analysis of Artificial Bee Colony Optimization Algorithm

Theoretical analysis of swarm intelligence and evolutionary algorithms is relatively less explored area of research. Stability and convergence analysis of swarm intelligence and evolutionary algorithms can help the researchers to fine tune the parameter values. This paper presents the stability analysis of a famous Artificial Bee Colony (ABC) optimization algorithm using von Neumann stability criterion for two-level finite difference scheme. Parameter selection for the ABC algorithm is recommended based on the obtained stability conditions. The findings are also validated through numerical experiments on test problems

Efficacy of premixed versus sequential administration of dexmedetomidine as an adjuvant to intrathecal hyperbaric bupivacaine in lower limb surgery

Objective: To evaluate the efficacy of intrathecal hyperbaric bupivacaine premixed with dexmeditomidine compared with sequential administration in separate syringes on block characteristics, haemodynamic parameters, side effect profile and postoperative analgesic requirement.Trial design: This was a prospective, randomised clinical studyMethod: Sixty orthopaedic patients scheduled for elective lower limb surgery under spinal anaesthesia were divided into two groups to receive either intrathecal hyperbaric bupivacaine 12.5 mg premixed (Group P) with dexmeditomidine 10 μg (diluted to 0.5 ml with normal saline) or by sequential administration in separate syringes (Group S). Outcome: Block characteristics, haemodynamic parameters, side effect profile and postoperative analgesic requirement were compared in both groups.Results: Time to achieve T10 spinal level was significantly less in group S (4.467 + 0.973 min) compared with group P (5.5 + 1.167 min). Similarly, patients in group S achieved Modified Bromage III earlier (6.1 + 1.296 min) than group P (7.5 + 1.333 min), p-value 0.0001.Conclusion: Dexmeditomidine given sequentially in a separate syringe as adjuvant to intrathecal hyperbaric bupivacaine can result in faster onset of both sensory and motor block and prolongs the duration of spinal anaesthesia, minimises clinically significant side effects and reduces the postoperative analgesic requirement.Keywords: dexmedetomidine, hyperbaric bupivacaine, intrathecal bloc

Design of wind farm layout with non-uniform turbines using fitness difference based BBO

Biogeography-based optimization (BBO) is an emerging meta-heuristic algorithm. BBO is inspired from the migration of species from one island to another. This study presents the solution of the wind farm layout optimization problem with wind turbines having non-uniform hub heights and rotor radii using BBO and an improved version of BBO. This study proposes an improved version of BBO, Fitness Difference Based BBO (FD-BBO). FD-BBO is obtained by incorporating the concept of fitness differences in original BBO. First, in order to justify the superiority of FD-BBO over BBO, it is tested over $15$ standard test problems of optimization. The numerical results of FD-BBO are compared with the original version of BBO and an advanced version of BBO, Blended BBO (BBBO). Through graphical and statistical analyses, FD-BBO is established to be an efficient and accurate algorithm. The BBO, BBBO and FD-BBO are than applied to solve the wind farm layout optimization problem. In the considered problem, not only the location of the wind turbines but hub heights and rotor radii are also taken as decision variables. Two cases of the problems are dealt: $26$ turbines in the farm size of $2000m$ $\times$ $2000m$ and $30$ turbines in the farm size of $2000m$ $\times$ $2000m$. Numerical results are compared with earlier published results and that of original BBO and Blended BBO. It is found that FD-BBO is the better approach to solving the problem under consideration

Analysing convergence, consistency and trajectory of Artificial Bee Colony Algorithm

Recently, swarm intelligence based algorithms gained attention of the researchers due to their wide applicability and ease of implementation. However, much research has been made on the development of swarm intelligence algorithms but theoretical analysis of these algorithms is still a less explored area of the research. Theoretical analyses of trajectory and convergence of potential solutions towards the equilibrium point in the search space can help the researchers to understand the iteration-wise behaviour of the algorithms which can further help in making them efficient. Artificial Bee Colony (ABC) optimization algorithm is swarm intelligence based algorithm. This paper presents the convergence analysis of ABC algorithm by using results from the theory of dynamical system and convergent boundaries for the parameters $\phi$ and $\psi$ is proposed. Also the trajectory of potential solutions in the search space is analysed by obtaining a partial differential equation corresponding to the position update equation of ABC algorithm. The analysis reveals that the ABC algorithm performs better/efficiently when parameters $\phi$ and $\psi$ are in the convergent region and potential solutions movement follows 1-Dimensional advection equation

Evaluation of peripheral arterial occlusive disease by computed tomography angiography

Background: Characterization of peripheral arterial occlusive disease (PAOD) can be performed with non-invasive angiography using computed tomography (CT). The present study was conducted to evaluate the CT angiographic spectrum of aortoiliac and the lower limb arterial disease in symptomatic patients of peripheral arterial occlusive disease (PAOD) and to classify the lesions according to the Trans-Atlantic Inter-Society Consensus II (TASC II).Methods: The study was carried out in the department of radio-diagnosis in collaboration with departments of cardiothoracic surgery, cardiology and surgery, Safdarjung Hospital and Vardhman Mahavir Medical College, New Delhi. 50 patients aged above 40 years presenting with symptoms and (or) signs of lower limb peripheral arterial disease were recruited into the study after evaluating the renal function. Patient’s clinical history, ABI index and categories of PAOD according to the classification of Fontaine was noted. CT angiography of aortoiliac and lower limb arteries was performed with Philips Brilliance 40 CT unit. The findings in each CT angiography were analysed in respect to site, number, nature and distribution of the lesions and classified individually according to the TASC II.Results: The patients included in the study were all more than 40 years of age. The age range in the study group was 42 years to 75 years. The majority (86%) were male patients. Smoking and dyslipidemia were found to be the main risk factors in our patients. 24% of patients had documentary evidence of ischemic heart disease. On grading with ABI majority of patients (58%) presented in the end stage of the disease (stage IV). On CT angiography, number of lesions detected was 157. 97.4% of lesions were either stenotic or occlusive and 2.54% are with aneurysm. Maximum number of patients had femoropopliteal lesions followed by aortailiac lesions. 14 Winslow pathways were found in 10 patients. Maximum numbers of femoropopliteal lesions (47.29%) belong to type D, type B lesions account for 50% of total aortoiliac lesions based on TASC II classification. Out of 50, 40 were made follow up. Among them 8 were managed with conservative treatment and remaining 32 managed with treatment based TASC II classification.Conclusions: CT angiography is a reliable noninvasive imaging method for the comprehensive and multi parameter evaluation of patients with PAOD. CT angiographic findings are a highly accurate basis for treatment decisions and planning

Sine Cosine Algorithm for Optimization

This open access book serves as a compact source of information on sine cosine algorithm (SCA) and a foundation for developing and advancing SCA and its applications. SCA is an easy, user-friendly, and strong candidate in the field of metaheuristics algorithms. Despite being a relatively new metaheuristic algorithm, it has achieved widespread acceptance among researchers due to its easy implementation and robust optimization capabilities. Its effectiveness and advantages have been demonstrated in various applications ranging from machine learning, engineering design, and wireless sensor network to environmental modeling. The book provides a comprehensive account of the SCA, including details of the underlying ideas, the modified versions, various applications, and a working MATLAB code for the basic SCA

Oxide_Oxide Ceramic Matrix Composite (CMC) Exhaust Mixer Development in the NASA Environmentally Responsible Aviation (ERA) Project

LibertyWorks, a subsidiary of Rolls-Royce Corporation, first studied CMC (ceramic matrix composite) exhaust mixers for potential weight benefits in 2008. Oxide CMC potentially offered weight reduction, higher temperature capability, and the ability to fabricate complex-shapes for increased mixing and noise suppression. In 2010, NASA was pursuing the reduction of NOx emissions, fuel burn, and noise from turbine engines in Phase I of the Environmentally Responsible Aviation (ERA) Project (within the Integrated Systems Research Program). ERA subtasks, including those focused on CMC components, were being formulated with the goal of maturing technology from Proof of Concept Validation (Technology Readiness Level 3 (TRL 3)) to System/Subsystem or Prototype Demonstration in a Relevant Environment (TRL 6). LibertyWorks, a subsidiary of Rolls-Royce Corporation, first studied CMC (ceramic matrix composite) exhaust mixers for potential weight benefits in 2008. Oxide CMC potentially offered weight reduction, higher temperature capability, and the ability to fabricate complex-shapes for increased mixing and noise suppression. In 2010, NASA was pursuing the reduction of NOx emissions, fuel burn, and noise from turbine engines in Phase I of the Environmentally Responsible Aviation (ERA) Project (within the Integrated Systems Research Program). ERA subtasks, including those focused on CMC components, were being formulated with the goal of maturing technology from Proof of Concept Validation (Technology Readiness Level 3 (TRL 3)) to System/Subsystem or Prototype Demonstration in a Relevant Environment (TRL 6). Oxide CMC component at both room and elevated temperatures. A TRL5 (Component Validation in a Relevant Environment) was attained and the CMC mixer was cleared for ground testing on a Rolls-Royce AE3007 engine for performance evaluation to achieve TRL 6

Fitness Varying Gravitational Constant in GSA

Gravitational Search Algorithm (GSA) is a recent metaheuristic algorithm inspired by Newton's law of gravity and law of motion. In this search process, position change is based on the calculation of step size which depends upon a constant namely, Gravitational Constant (G). G is an exponentially decreasing function throughout the search process. Further, inspite of having different masses, the value of G remains same for each agent, which may cause inappropriate step size of agents for the next move, and thus leads the swarm towards stagnation or sometimes skipping the true optima. To overcome stagnation, we first propose a gravitational constant having different scaling characteristics for different phase of the search process. Secondly, a dynamic behavior is introduced in this proposed gravitational constant which varies according to the fitness of the agents. Due to this behavior, the gravitational constant will be different for every agent based on its fitness and thus will help in controlling the acceleration and step sizes of the agents which further improve exploration and exploitation of the solution search space. The proposed strategy is tested over 23 well-known classical benchmark functions and 11 shifted and biased benchmark functions. Various statistical analyses and a comparative study with original GSA, Chaos-based GSA (CGSA), Bio-geography Based Optimization (BBO) and DBBO has been carried out