PM10 Chemical Characteristics in a Background Site at the Universidad Libre Bogotá

One of the most important factors for air pollution is that the concentrations of PM10 maintain a constant trend, with the exception of some places where that frequently surpasses the allowed ranges established by Colombian legislation. The community that surrounds the Universidad Libre Bogotá is inhabited by a considerable number of students and workers, all of whom are possibly being exposed to PM10 for long periods of time while on campus. Thus, the chemical characterization of PM10 found in the ambient air at the Universidad Libre Bogotá was identified as a problem. A Hi-Vol sampler and EPA Test Method 5 were used to determine if the quality of air is adequate for the human respiratory system. Additionally, quartz fiber filters were utilized during sampling. Samples were taken three days a week during a dry period throughout the months of November and December 2015. The gravimetric analysis method was used to determine PM10 concentrations. The chemical characterization includes non-conventional carcinogenic pollutants. Atomic absorption spectrophotometry (AAS) was used for the determination of metals and VOCs were analyzed using the FTIR (Fourier transform infrared spectroscopy) method. In this way, concentrations of PM10, ranging from values of 13 µg/m3 to 66 µg/m3, were obtained; these values were below standard conditions. This evidence concludes that the PM10 concentrations during an exposure period of 24 hours are lower than the values established by Colombian law, Resolution 610 of 2010; however, when comparing these with the limits set by the World Health Organization (WHO), these concentrations could possibly exceed permissible levels.

Food Security Model and the Role of Community Empowerment: The Case of a Marginalized Village in Mexico, Tatoxcac, Puebla

Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Electromagnetic Assessment of Submarine Power Cable Degradation Using Finite Element Method and Sensitivity Analysis

Submarine power cables used for offshore wind farms electric energy distribution and transmission are subject to numerous threats. Some of the risks are associated with transport, installation and operating in harsh marine environment. This paper describes the feasibility of an electromagnetic low frequency sensing technique for submarine power cable failure prediction. The impact of a structural damage shape and material variability on the induced electric field is evaluated. The analysis is performed by modeling the cable using the finite element method, we use sensitivity analysis in order to identify the main damage characteristics affecting electric field variation. Lastly, we discuss the results obtained.

Adaptive Design of Large Prefabricated Concrete Panels Collective Housing

More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Compressed Suffix Arrays to Self-Indexes Based on Partitioned Elias-Fano

A practical and simple self-indexing data structure, Partitioned Elias-Fano (PEF) - Compressed Suffix Arrays (CSA), is built in linear time for the CSA based on PEF indexes. Moreover, the PEF-CSA is compared with two classical compressed indexing methods, Ferragina and Manzini implementation (FMI) and Sad-CSA on different type and size files in Pizza & Chili. The PEF-CSA performs better on the existing data in terms of the compression ratio, count, and locates time except for the evenly distributed data such as proteins data. The observations of the experiments are that the distribution of the φ is more important than the alphabet size on the compression ratio. Unevenly distributed data φ makes better compression effect, and the larger the size of the hit counts, the longer the count and locate time.

Transport of Analytes under Mixed Electroosmotic and Pressure Driven Flow of Power Law Fluid

In this study, we have analyzed the transport of analytes under a two dimensional steady incompressible flow of power-law fluids through rectangular nanochannel. A mathematical model based on the Cauchy momentum-Nernst-Planck-Poisson equations is considered to study the combined effect of mixed electroosmotic (EO) and pressure driven (PD) flow. The coupled governing equations are solved numerically by finite volume method. We have studied extensively the effect of key parameters, e.g., flow behavior index, concentration of the electrolyte, surface potential, imposed pressure gradient and imposed electric field strength on the net average flow across the channel. In addition to study the effect of mixed EOF and PD on the analyte distribution across the channel, we consider a nonlinear model based on general convective-diffusion-electromigration equation. We have also presented the retention factor for various values of electrolyte concentration and flow behavior index.

Moment Estimators of the Parameters of Zero-One Inflated Negative Binomial Distribution

In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.

Closing the Loop between Building Sustainability and Stakeholder Engagement: Case Study of an Australian University

Rapid population growth and urbanization is creating pressure throughout the world. This has a dramatic effect on a lot of elements which include water, food, transportation, energy, infrastructure etc. as few of the key services. Built environment sector is growing concurrently to meet the needs of urbanization. Due to such large scale development of buildings, there is a need for them to be monitored and managed efficiently. Along with appropriate management, climate adaptation is highly crucial as well because buildings are one of the major sources of greenhouse gas emission in their operation phase. Buildings to be adaptive need to provide a triple bottom approach to sustainability i.e., being socially, environmentally and economically sustainable. Hence, in order to deliver these sustainability outcomes, there is a growing understanding and thrive towards switching to green buildings or renovating new ones as per green standards wherever possible. Academic institutions in particular have been following this trend globally. This is highly significant as universities usually have high occupancy rates because they manage a large building portfolio. Also, as universities accommodate the future generation of architects, policy makers etc., they have the potential of setting themselves as a best industry practice model for research and innovation for the rest to follow. Hence their climate adaptation, sustainable growth and performance management becomes highly crucial in order to provide the best services to users. With the objective of evaluating appropriate management mechanisms within academic institutions, a feasibility study was carried out in a recent 5-Star Green Star rated university building (housing the School of Construction) in Victoria (south-eastern state of Australia). The key aim was to understand the behavioral and social aspect of the building users, management and the impact of their relationship on overall building sustainability. A survey was used to understand the building occupant’s response and reactions in terms of their work environment and management. A report was generated based on the survey results complemented with utility and performance data which were then used to evaluate the management structure of the university. Followed by the report, interviews were scheduled with the facility and asset managers in order to understand the approach they use to manage the different buildings in their university campuses (old, new, refurbished), respective building and parameters incorporated in maintaining the Green Star performance. The results aimed at closing the communication and feedback loop within the respective institutions and assist the facility managers to deliver appropriate stakeholder engagement. For the wider design community, analysis of the data highlights the applicability and significance of prioritizing key stakeholders, integrating desired engagement policies within an institution’s management structures and frameworks and their effect on building performance

The Importance of Intellectual Property for Universities of Technology in South Africa: Challenges Faced and Proposed Way Forward

Intellectual property should be a day-to-day business decision due to its value, but increasingly, a number of institution are still not aware of the importance. Intellectual Property (IP) and its value are often not adequately appreciated. In the increasingly knowledge-driven economy, IP is a key consideration in day-to-day business decisions because new ideas and products appear almost daily in the market, which results in continuous innovation and research. Therefore, this paper will focus on the importance of IP for universities of technology and also further demonstrates how IP can become an economic tool and the challenges faced by these universities in implementing an IP system.

A Numerical Study on Electrophoresis of a Soft Particle with Charged Core Coated with Polyelectrolyte Layer

Migration of a core-shell soft particle under the influence of an external electric field in an electrolyte solution is studied numerically. The soft particle is coated with a positively charged polyelectrolyte layer (PEL) and the rigid core is having a uniform surface charge density. The Darcy-Brinkman extended Navier-Stokes equations are solved for the motion of the ionized fluid, the non-linear Nernst-Planck equations for the ion transport and the Poisson equation for the electric potential. A pressure correction based iterative algorithm is adopted for numerical computations. The effects of convection on double layer polarization (DLP) and diffusion dominated counter ions penetration are investigated for a wide range of Debye layer thickness, PEL fixed surface charge density, and permeability of the PEL. Our results show that when the Debye layer is in order of the particle size, the DLP effect is significant and produces a reduction in electrophoretic mobility. However, the double layer polarization effect is negligible for a thin Debye layer or low permeable cases. The point of zero mobility and the existence of mobility reversal depending on the electrolyte concentration are also presented.

Quantification of E-Waste: A Case Study in Federal University of Espírito Santo, Brazil

The segregation of waste of electrical and electronic equipment (WEEE) in the generating source, its characterization (quali-quantitative) and identification of origin, besides being integral parts of classification reports, are crucial steps to the success of its integrated management. The aim of this paper was to count WEEE generation at the Federal University of Espírito Santo (UFES), Brazil, as well as to define sources, temporary storage sites, main transportations routes and destinations, the most generated WEEE and its recycling potential. Quantification of WEEE generated at the University in the years between 2010 and 2015 was performed using data analysis provided by UFES’s sector of assets management. EEE and WEEE flow in the campuses information were obtained through questionnaires applied to the University workers. It was recorded 6028 WEEEs units of data processing equipment disposed by the university between 2010 and 2015. Among these waste, the most generated were CRT screens, desktops, keyboards and printers. Furthermore, it was observed that these WEEEs are temporarily stored in inappropriate places at the University campuses. In general, these WEEE units are donated to NGOs of the city, or sold through auctions (2010 and 2013). As for recycling potential, from the primary processing and further sale of printed circuit boards (PCB) from the computers, the amount collected could reach U$ 27,839.23. The results highlight the importance of a WEEE management policy at the University.

Collision Detection Algorithm Based on Data Parallelism

Modern computing technology enters the era of parallel computing with the trend of sustainable and scalable parallelism. Single Instruction Multiple Data (SIMD) is an important way to go along with the trend. It is able to gather more and more computing ability by increasing the number of processor cores without the need of modifying the program. Meanwhile, in the field of scientific computing and engineering design, many computation intensive applications are facing the challenge of increasingly large amount of data. Data parallel computing will be an important way to further improve the performance of these applications. In this paper, we take the accurate collision detection in building information modeling as an example. We demonstrate a model for constructing a data parallel algorithm. According to the model, a complex object is decomposed into the sets of simple objects; collision detection among complex objects is converted into those among simple objects. The resulting algorithm is a typical SIMD algorithm, and its advantages in parallelism and scalability is unparalleled in respect to the traditional algorithms.

Simulation of the Large Hadrons Collisions Using Monte Carlo Tools

In many cases, theoretical treatments are available for models for which there is no perfect physical realization. In this situation, the only possible test for an approximate theoretical solution is to compare with data generated from a computer simulation. In this paper, Monte Carlo tools are used to study and compare the elementary particles models. All the experiments are implemented using 10000 events, and the simulated energy is 13 TeV. The mean and the curves of several variables are calculated for each model using MadAnalysis 5. Anomalies in the results can be seen in the muons masses of the minimal supersymmetric standard model and the two Higgs doublet model.

Effect of Cavities on the Behaviour of Strip Footing Subjected to Inclined Load

One of the important concerns within the field of geotechnical engineering is the presence of cavities in soils. This present work is an attempt to understand the behaviour of strip footing subjected to inclined load and constructed on cavitied soil. The failure mechanism of strip footing located above such soils was studied analytically. The capability of analytical model to correctly expect the system behaviour is assessed by carrying out verification analysis on available studies. The study was prepared by finite element software (PLAXIS) in which an elastic-perfectly plastic soil model was used. It was indicated, from the results of the study, that the load carrying capacity of foundation constructed on cavity can be analysed well using such analysis. The research covered many foundation cases, and in each foundation case, there occurs a critical depth under which the presence of cavities has shown minimum impact on the foundation performance. When cavities are found above this critical depth, the load carrying capacity of the foundation differs with many influences, such as the location and size of the cavity and footing depth. Figures involving the load carrying capacity with the affecting factors studied are presented. These figures offer information beneficial for the design of strip footings rested on underground cavities. Moreover, the results might be used to design a shallow foundation constructed on cavitied soil, whereas the obtained failure mechanisms may be employed to improve numerical solutions for this kind of problems.

Thermal Fracture Analysis of Fibrous Composites with Variable Fiber Spacing Using Jk-Integral

In this study, fracture analysis of a fibrous composite laminate with variable fiber spacing is carried out using Jk-integral method. The laminate is assumed to be under thermal loading. Jk-integral is formulated by using the constitutive relations of plane orthotropic thermoelasticity. Developed domain independent form of the Jk-integral is then integrated into the general purpose finite element analysis software ANSYS. Numerical results are generated so as to assess the influence of variable fiber spacing on mode I and II stress intensity factors, energy release rate, and T-stress. For verification, some of the results are compared to those obtained using displacement correlation technique (DCT).

Behavior of Current in a Semiconductor Nanostructure under Influence of Embedded Quantum Dots

Motivated by recent experimental and theoretical developments, we investigate the influence of embedded quantum dot (EQD) of different geometries (lens, ring and pyramidal) in a double barrier heterostructure (DBH). We work with a general theory of quantum transport that accounts the tight-binding model for the spin dependent resonant tunneling in a semiconductor nanostructure, and Rashba spin orbital to study the spin orbit coupling. In this context, we use the second quantization theory for Rashba effect and the standard Green functions method. We calculate the current density as a function of the voltage without and in the presence of quantum dots. In the second case, we considered the size and shape of the quantum dot, and in the two cases, we worked considering the spin polarization affected by external electric fields. We found that the EQD generates significant changes in current when we consider different morphologies of EQD, as those described above. The first thing shown is that the current decreases significantly, such as the geometry of EQD is changed, prevailing the geometrical confinement. Likewise, we see that the current density decreases when the voltage is increased, showing that the quantum system studied here is more efficient when the morphology of the quantum dot changes.

Optimization of Samarium Extraction via Nanofluid-Based Emulsion Liquid Membrane Using Cyanex 272 as Mobile Carrier

Samarium as a rare-earth element is playing a growing important role in high technology. Traditional methods for extraction of rare earth metals such as ion exchange and solvent extraction have disadvantages of high investment and high energy consumption. Emulsion liquid membrane (ELM) as an improved solvent extraction technique is an effective transport method for separation of various compounds from aqueous solutions. In this work, the extraction of samarium from aqueous solutions by ELM was investigated using response surface methodology (RSM). The organic membrane phase of the ELM was a nanofluid consisted of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as mobile carrier, and kerosene as base fluid. 1 M nitric acid solution was used as internal aqueous phase. The effects of the important process parameters on samarium extraction were investigated, and the values of these parameters were optimized using the Central Composition Design (CCD) of RSM. These parameters were the concentration of MWCNT in nanofluid, the carrier concentration, and the volume ratio of organic membrane phase to internal phase (Roi). The three-dimensional (3D) response surfaces of samarium extraction efficiency were obtained to visualize the individual and interactive effects of the process variables. A regression model for % extraction was developed, and its adequacy was evaluated. The result shows that % extraction improves by using MWCNT nanofluid in organic membrane phase and extraction efficiency of 98.92% can be achieved under the optimum conditions. In addition, demulsification was successfully performed and the recycled membrane phase was proved to be effective in the optimum condition.

Performance Study of Neodymium Extraction by Carbon Nanotubes Assisted Emulsion Liquid Membrane Using Response Surface Methodology

The high purity rare earth elements (REEs) have been vastly used in the field of chemical engineering, metallurgy, nuclear energy, optical, magnetic, luminescence and laser materials, superconductors, ceramics, alloys, catalysts, and etc. Neodymium is one of the most abundant rare earths. By development of a neodymium–iron–boron (Nd–Fe–B) permanent magnet, the importance of neodymium has dramatically increased. Solvent extraction processes have many operational limitations such as large inventory of extractants, loss of solvent due to the organic solubility in aqueous solutions, volatilization of diluents, etc. One of the promising methods of liquid membrane processes is emulsion liquid membrane (ELM) which offers an alternative method to the solvent extraction processes. In this work, a study on Nd extraction through multi-walled carbon nanotubes (MWCNTs) assisted ELM using response surface methodology (RSM) has been performed. The ELM composed of diisooctylphosphinic acid (CYANEX 272) as carrier, MWCNTs as nanoparticles, Span-85 (sorbitan triooleate) as surfactant, kerosene as organic diluent and nitric acid as internal phase. The effects of important operating variables namely, surfactant concentration, MWCNTs concentration, and treatment ratio were investigated. Results were optimized using a central composite design (CCD) and a regression model for extraction percentage was developed. The 3D response surfaces of Nd(III) extraction efficiency were achieved and significance of three important variables and their interactions on the Nd extraction efficiency were found out. Results indicated that introducing the MWCNTs to the ELM process led to increasing the Nd extraction due to higher stability of membrane and mass transfer enhancement. MWCNTs concentration of 407 ppm, Span-85 concentration of 2.1 (%v/v) and treatment ratio of 10 were achieved as the optimum conditions. At the optimum condition, the extraction of Nd(III) reached the maximum of 99.03%.

Mobile Learning in Developing Countries: A Synthesis of the Past to Define the Future

Mobile learning (m-learning) is a novel approach to knowledge acquisition and dissemination and is gaining global attention. Steady progress in wireless technologies and the portability of communication devices continue to broaden the scope and use of mobiles. With the convergence of Web functionality onto mobile platforms and the affordability and availability of mobile technology, m-learning has the potential of being the next prevalent channel of education in both formal and informal settings. There is substantive literature on developed countries but the state in developing countries (DCs) however appears vague. This paper is a synthesis of extant literature on mobile learning in DCs. The research interest is based on the fact that in DCs, mobile communication and internet connectivity are popular. However, its use in education is under explored. There are some reviews on the state, conceptualizations, trends and teacher education, but to the authors’ knowledge, no study has focused on mobile learning adoption and integration issues. This study examines issues and gaps associated with its adoption and integration in DCs higher education institutions. A qualitative build-up of literature was conducted using articles pooled from electronic databases (Google Scholar and ERIC). To enable criteria for inclusion and incorporate diverse study perspectives, search terms used were m-learning, DCs, higher education institutions, challenges, benefits, impact, gaps and issues. The synthesis revealed that though mobile technology has diffused globally, its pedagogical pursuit in DCs remains quite low. The absence of a mobile Web and the difficulty of resource conversion into mobile format due to lack of funding and technical competence is a stumbling block. Again, the lack of established design and implementation rules to guide the development of m-learning platforms in DCs is a hindrance. The absence of access restrictions on devices poses security threats to institutional systems. Negative perceptions that devices are taking over faculty roles lead to resistance in some situations. Resistance to change can be a hindrance to the acceptance and success of new systems. Lack of interest for m-learning is also attributed to lower technological literacy levels of the underprivileged masses. Scholarly works on m-learning in DCs is yet to mature. Most technological innovations are handed down from developed countries, and this constantly creates a lag for DCs. Lack of theoretical grounding was also identified which reduces the objectivity of study reports. The socio-cultural terrain of DCs results in societies with different views and needs that have been identified as a hindrance to research. Institutional commitment decisions, adequate funding for the necessary infrastructural development as well as multiple stakeholder participation is important for project success. Evidence suggests that while adoption decisions are readily made, successful integration of the concept for its full benefits to be realized is often neglected. Recommendations to findings were made to provide possible remedies to identified issues.

E-Learning Recommender System Based on Collaborative Filtering and Ontology

In recent years, e-learning recommender systems has attracted great attention as a solution towards addressing the problem of information overload in e-learning environments and providing relevant recommendations to online learners. E-learning recommenders continue to play an increasing educational role in aiding learners to find appropriate learning materials to support the achievement of their learning goals. Although general recommender systems have recorded significant success in solving the problem of information overload in e-commerce domains and providing accurate recommendations, e-learning recommender systems on the other hand still face some issues arising from differences in learner characteristics such as learning style, skill level and study level. Conventional recommendation techniques such as collaborative filtering and content-based deal with only two types of entities namely users and items with their ratings. These conventional recommender systems do not take into account the learner characteristics in their recommendation process. Therefore, conventional recommendation techniques cannot make accurate and personalized recommendations in e-learning environment. In this paper, we propose a recommendation technique combining collaborative filtering and ontology to recommend personalized learning materials to online learners. Ontology is used to incorporate the learner characteristics into the recommendation process alongside the ratings while collaborate filtering predicts ratings and generate recommendations. Furthermore, ontological knowledge is used by the recommender system at the initial stages in the absence of ratings to alleviate the cold-start problem. Evaluation results show that our proposed recommendation technique outperforms collaborative filtering on its own in terms of personalization and recommendation accuracy.