Search results for: linear density of reinforcement

Authors: A. Aljohani, D. Burke, D. Clarke, M. Gormally, M. Byrne, G. Fleming

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Introduction: House Dust Mites (HDMs) are a source of allergen particles embedded in textiles and furnishings. Vacuum sampling is commonly used to recover and determine the abundance of HDMs but the efficiency of this method is less than standardized. Here, the efficiency of recovery of HDMs was evaluated from home-associated textiles using vacuum sampling protocols.Methods/Approach: Living Mites (LMs) or dead Mites (DMs) House Dust Mites (Dermatophagoides pteronyssinus: FERA, UK) were separately seeded onto the surfaces of Smooth Cotton, Denim and Fleece (25 mites/10x10cm2 squares) and left for 10 minutes before vacuuming. Fabrics were vacuumed (SKC Flite 2 pump) at a flow rate of 14 L/min for 60, 90 or 120 seconds and the number of mites retained by the filter (0.4μm x 37mm) unit was determined. Vacuuming was carried out in a linear direction (Protocol 1) or in a multidirectional pattern (Protocol 2). Additional fabrics with LMs were also frozen and then thawed, thereby euthanizing live mites (now termed EMs). Results/Findings: While there was significantly greater (p=0.000) recovery of mites (76% greater) in fabrics seeded with DMs than LMs irrespective of vacuuming protocol or fabric type, the efficiency of recovery of DMs (72%-76%) did not vary significantly between fabrics. For fabrics containing EMs, recovery was greatest for Smooth Cotton and Denim (65-73% recovered) and least for Fleece (15% recovered). There was no significant difference (p=0.99) between the recovery of mites across all three mite categories from Smooth Cotton and Denim but significantly fewer (p=0.000) mites were recovered from Fleece. Scanning Electron Microscopy images of HMD-seeded fabrics showed that live mites burrowed deeply into the Fleece weave which reduced their efficiency of recovery by vacuuming. Research Implications: Results presented here have implications for the recovery of HDMs by vacuuming and the choice of fabric to ameliorate HDM-dust sensitization.

Keywords: allergy, asthma, dead, fabric, fleece, live mites, sampling

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Authors: A. C. Kumbharkhane

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Time domain dielectric relaxation microwave spectroscopy (TDRMS) is a term used to describe a technique of observing the time dependant response of a sample after application of time dependant electromagnetic field. A TDRMS probes the interaction of a macroscopic sample with a time dependent electrical field. The resulting complex permittivity spectrum, characterizes amplitude (voltage) and time scale of the charge-density fluctuations within the sample. These fluctuations may arise from the reorientation of the permanent dipole moments of individual molecules or from the rotation of dipolar moieties in flexible molecules, like polymers. The time scale of these fluctuations depends on the sample and its relative relaxation mechanism. Relaxation times range from some picoseconds in low viscosity liquids to hours in glasses, Therefore the TDRS technique covers an extensive dynamical process. The corresponding frequencies range from 10-4 Hz to 1012 Hz. This inherent ability to monitor the cooperative motion of molecular ensemble distinguishes dielectric relaxation from methods like NMR or Raman spectroscopy, which yield information on the motions of individual molecules. Recently, we have developed and established the TDR technique in laboratory that provides information regarding dielectric permittivity in the frequency range 10 MHz to 30 GHz. The TDR method involves the generation of step pulse with rise time of 20 pico-seconds in a coaxial line system and monitoring the change in pulse shape after reflection from the sample placed at the end of the coaxial line. There is a great interest to study the dielectric relaxation behaviour in liquid systems to understand the role of hydrogen bond in liquid system. The intermolecular interaction through hydrogen bonds in molecular liquids results in peculiar dynamical properties. The dynamics of hydrogen-bonded liquids have been studied. The theoretical model to explain the experimental results will be discussed.

Keywords: microwave, time domain reflectometry (TDR), dielectric measurement, relaxation time

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Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo

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Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.

Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution

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Authors: Claudia Schier, Arvid Biallas, Bernd Friedrich

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The demand for Li-ion-batteries owing to their benefits, such as; fast charging time, high energy density, low weight, large temperature range, and a long service life performance is increasing compared to other battery systems. These characteristics are substantial not only for battery-operated portable devices but also in the growing field of electromobility where high-performance energy storage systems in the form of batteries are highly requested. Due to the sharp rising production, there is a tremendous interest to recycle spent Li-Ion batteries in a closed-loop manner owed to the high content of valuable metals such as cobalt, manganese, and lithium as well as regarding the increasing demand for those scarce applied metals. Currently, there are just a few industrial processes using hydrometallurgical methods to recover valuable metals from Li-ion-battery waste. In this study, the extraction of valuable metals from spent Li-ion-batteries is investigated by pretreated and subsequently leached battery wastes using different precipitation methods in a comparative manner. For the extraction of lithium, cobalt, and other valuable metals, pelletized battery wastes with an initial Li content of 2.24 wt. % and cobalt of 22 wt. % is used. Hydrochloric acid with 4 mol/L is applied with 1:50 solid to liquid (s/l) ratio to generate pregnant leach solution for subsequent precipitation steps. In order to obtain pure precipitates, two different pathways (pathway 1 and pathway 2) are investigated, which differ from each other with regard to the precipitation steps carried out. While lithium carbonate recovery is the final process step in pathway 1, pathway 2 requires a preliminary removal of lithium from the process. The aim is to evaluate both processes in terms of purity and yield of the products obtained. ICP-OES is used to determine the chemical content of leach liquor as well as of the solid residue.

Keywords: hydrochloric acid, hydrometallurgy, Li-ion-batteries, metal recovery

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Authors: O. Hakim, K. Hart, P. McCabe, J. Berry, L. E. Rhodes, N. Spyrou, A. Alfuraih, S. Lanham-New

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It is known that skin pigmentation reduces the penetration of ultraviolet radiation (UVR) and thus photosynthesis of 25(OH)D. However, the ethnic differences in 25(OH)D production remain to be fully elucidated. This study aimed to investigate the differences in vitamin D production between Asian and Caucasian postmenopausal women, in response to a defined, controlled UVB exposure. Seventeen women; nine white Caucasian (skin phototype II and III), eight South Asian women (skin phototype IV and V) participated in the study, acting as their controls. Three blood samples were taken for measurement of 25(OH)D during the run-in period (nine days, no sunbed exposure) after which all subjects underwent an identical UVR exposure protocol irrespective of skin colour (nine days, three sunbed sessions: 6, 8 and 8 minutes respectively with approximately 80% of body surface exposed). Skin tone was measured four times during the study. Both groups showed a gradual increase in 25(OH)D with final levels significantly higher than baseline (p<0.01). 25(OH)D concentration mean from a baseline of 43.58±19.65 to 57.80±17.11 nmol/l among Caucasian and from 27.03±23.92 to 44.73±17.74 nmol/l among Asian women. The baseline status of vitamin D was classified as deficient among the Asian women and insufficient among the Caucasian women. The percentage increase in vitamin D3 among Caucasians was 39.86% (21.02) and 207.78% (286.02) in Asian subjects respectively. This greater response to UVR exposure reflects the lower baseline levels of the Asian subjects. The mixed linear model analysis identified a significant effect of duration of UVR exposure on the production of 25(OH)D. However, the model shows no significant effect of ethnicity and skin tone on the production of 25(OH)D. These novel findings indicate that people of Asian ethnicity have the full capability to produce a similar amount of vitamin D compared to the Caucasian group; initial vitamin D concentration influences the amount of UVB needed to reach equal serum concentrations.

Keywords: ethnicity, Caucasian, South Asian, vitamin D, ultraviolet radiation, UVR

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Authors: Akriti Chandra, Gourav Dwivedi, Seema Sharma, Shivani

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This study investigates the adoption of green business (GB) models within a circular economy framework (CEBM) for Micro Small and Medium Enterprise (MSME), given the rising importance of sustainable practices. The research begins by exploring the shift from linear business models towards resource-efficient, sustainable models, emphasizing the benefits of the circular economy. The study's literature review identifies 60 influential factors impacting the shift to green businesses, grouped as internal and external drivers. However, there is a research gap in examining these factors' interrelationships and operationalizing them within MSMEs. To address this gap, the study employs Total Interpretive Structural Modelling (TISM) to establish a hierarchical structure of factors influencing GB and circular economy business model (CEBM) adoption. Findings reveal that factors like green innovation and market competitiveness are particularly impactful. Using Systems Theory, which views organizations as complex adaptive systems, the study contextualizes these drivers within MSMEs, proposing a framework for a sustainable business model adoption. The study concludes with significant implications for policymakers, suggesting that the identified factors and their hierarchical relationships can guide policy formulation for a broader transition to green business practices. This work also invites further research, recommending larger, quantitative studies to empirically validate these factors and explore practical challenges in implementing CEBMs.

Keywords: green business (GB), circular economy business model (CEBM), micro small and medium enterprise (MSME), total interpretive structural modelling (TISM), systems theory

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Authors: Praveen K. Khatri, Neha Karanwal, Savita Kaul, Suman L. Jain

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Conversion of biomass through green chemical routes is of great industrial importance as biomass is considered to be most widely available inexpensive renewable resource that can be used as a raw material for the production of bio fuel and value-added organic products. In this regard, acid catalyzed dehydration of biomass derived pentose sugar (mainly D-xylose) to furfural is a process of tremendous research interest in current scenario due to the wider industrial applications of furfural. Furfural is an excellent organic solvent for refinement of lubricants and separation of butadiene from butene mixture in synthetic rubber fabrication. In addition it also serve as a promising solvent for many organic materials, such as resins, polymers and also used as a building block for synthesis of various valuable chemicals such as furfuryl alcohol, furan, pharmaceutical, agrochemicals and THF. Here in a sulfonated polymer impregnated carbon composite solid acid catalyst (P-C-SO3H) was prepared by the pyrolysis of a polymer matrix impregnated with glucose followed by its sulfonation and used for the dehydration of xylose to furfural. The developed catalyst exhibited excellent activity and provided almost quantitative conversion of xylose with the selective synthesis of furfural. The higher catalytic activity of P-C-SO3H may be due to the more even distribution of polycyclic aromatic hydrocarbons generated from incomplete carbonization of glucose along the polymer matrix network, leading to more available sites for sulfonation which resulted in greater sulfonic acid density in P-C-SO3H as compared to sulfonated carbon catalyst (C-SO3H). In conclusion, we have demonstrated sulfonated polymer impregnated carbon composite (P-C-SO3H) as an efficient and selective solid acid catalyst for the dehydration of xylose to furfural. After completion of the reaction, the catalyst was easily recovered and reused for several runs without noticeable loss in its activity and selectivity.

Keywords: Solid acid , Biomass conversion, Xylose Dehydration, Heterogeneous catalyst

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Authors: Apostolos Kalatzis, Ashish Teotia, Vishnunarayan Girishan Prabhu, Laura Stanley

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Emotions are functional behaviors influenced by thoughts, stimuli, and other factors that induce neurophysiological changes in the human body. Understanding and classifying emotions are challenging as individuals have varying perceptions of their environments. Therefore, it is crucial that there are publicly available databases and virtual reality (VR) based environments that have been scientifically validated for assessing emotional classification. This study utilized two commercially available VR applications (Guided Meditation VR™ and Richie’s Plank Experience™) to induce acute stress and calm state among participants. Subjective and objective measures were collected to create a validated multimodal dataset and classification scheme for affective state classification. Participants’ subjective measures included the use of the Self-Assessment Manikin, emotional cards and 9 point Visual Analogue Scale for perceived stress, collected using a Virtual Reality Assessment Tool developed by our team. Participants’ objective measures included Electrocardiogram and Respiration data that were collected from 25 participants (15 M, 10 F, Mean = 22.28  4.92). The features extracted from these data included heart rate variability components and respiration rate, both of which were used to train two machine learning models. Subjective responses validated the efficacy of the VR applications in eliciting the two desired affective states; for classifying the affective states, a logistic regression (LR) and a support vector machine (SVM) with a linear kernel algorithm were developed. The LR outperformed the SVM and achieved 93.8%, 96.2%, 93.8% leave one subject out cross-validation accuracy, precision and recall, respectively. The VR assessment tool and data collected in this study are publicly available for other researchers.

Keywords: affective computing, biosignals, machine learning, stress database

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Authors: Shanawaz Patil, Mohamed Haneef, K. S. Narayanaswamy

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In the recent years, aluminum metal matrix composites were most widely used, which are finding wide applications in various field such as automobile, aerospace defense etc., due to their outstanding mechanical properties like low density, light weight, exceptional high levels of strength, stiffness, wear resistance, high temperature resistance, low coefficient of thermal expansion and good formability. In the present work, an effort is made to study the effect of heat treatment on mechanical properties of aluminum 7075 alloy reinforced with constant weight percentage of naturally occurring mineral beryl and varying weight percentage of graphene. The hybrid composites are developed with 0.5 wt. %, 1wt.%, 1.5 wt.% and 2 wt.% of graphene and 6 wt.% of beryl  by stir casting liquid metallurgy route. The cast specimens of unreinforced aluminum alloy and hybrid composite samples were prepared for heat treatment process and subjected to solutionizing treatment (T6) at a temperature of 490±5 ^oC for 8 hours in a muffle furnace followed by quenching in boiling water. The microstructure analysis of as cast and heat treated hybrid composite specimens are examined by scanning electron microscope (SEM). The tensile test and hardness test of unreinforced aluminum alloy and hybrid composites are examined. The wear behavior is examined by pin-on disc apparatus. The results of as cast specimens and heat treated specimens were compared. The heat treated Al7075-Beryl-Graphene hybrid composite had better properties and significantly improved the ultimate tensile strength, hardness and reduced wear loss when compared to aluminum alloy and  as cast hybrid composites.

Keywords: beryl, graphene, heat treatment, mechanical properties

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Authors: Ali Albadri

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The logistics equation has never been used or studied in scientific fields outside the field of ecology. It has never been used to understand the behavior of a dynamic system of mechanical machines, like an escalator. We have studied the compatibility of the logistic map against real measurements from an escalator. This study has proven that there is good compatibility between the logistics equation and the experimental measurements. It has discovered the potential of a relationship between the fractal dimension and the non-linearity parameter, R, in the logistics equation. The fractal dimension increases as the R parameter (non-linear parameter) increases. It implies that the fractal dimension increases as the phase of the life span of the machine move from the steady/stable phase to the periodic double phase to a chaotic phase. The fractal dimension and the parameter R can be used as a tool to verify and check the health of machines. We have come up with a theory that there are three areas of behaviors, which they can be classified during the life span of a machine, a steady/stable stage, a periodic double stage, and a chaotic stage. The level of attention to the machine differs depending on the stage that the machine is in. The rate of faults in a machine increases as the machine moves through these three stages. During the double period and the chaotic stages, the number of faults starts to increase and become less predictable. The rate of predictability improves as our monitoring of the changes in the fractal dimension and the parameter R improves. The principles and foundations of our theory in this work have and will have a profound impact on the design of systems, on the way of operation of systems, and on the maintenance schedules of the systems. The systems can be mechanical, electrical, or electronic. The discussed methodology in this paper will give businesses the chance to be more careful at the design stage and planning for maintenance to control costs. The findings in this paper can be implied and used to correlate the three stages of a mechanical system to more in-depth mechanical parameters like wear and fatigue life.

Keywords: logistcs map, bifurcation map, fractal dimension, logistics equation

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Authors: Camila Lozano-Vivas, Camila Quevedo-Villamil, Ingrid Munoz-Quijano, Diego Loaiza

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Colombia's limited oil reserves make the finding of new fields of extraction or the potentiate of the existing ones a more important task to do every day; the exploration projects that allow to have a better knowledge of the oil basins are essential. The upper Magdalena Valley basin - VSM, whose reserves are limited, has been one of the first basins for the exploration and production of hydrocarbons in Colombia. The Hondita and Lomagorda formations were deposited in the Late Cretaceous Middle Albian to the Coniacian and are characterized by being the hydrocarbon-generating rocks in the VSM basin oil system along with the Shale de Bambucá; therefore multiple studies have been made. In the oil industry, geochemical properties are used to understand the origin, migration, accumulation, and alteration of hydrocarbons and, in general, the evolution of the basin containing them. One of the most important parameters to understand this evolution is the formation temperature of the oil system. For this reason, a microthermometric study of fluid inclusions was carried out to recognize formation temperatures and to determine certain basic physicochemical variables, homogenization temperature, pressure, density and salinity of the fluid at the time of entrapment, providing evidence on the history of different events in different geological environments in the evolution of a sedimentary basin. Prior to this study, macroscopic and microscopic petrographic analyses of the samples collected in the field were performed. The results of the mentioned properties of the fluid inclusions in the different samples analyzed have salinities ranging from 20.22% to 26.37% eq. by weight NaCl, similar densities found in the ranges of 1.05 to 1.16 g/cc and an average homogenization temperature at 142.92°C, indicating that, at the time of their entanglement, the rock was in the window of generation of medium hydrocarbons –light with fragile characteristics of the rock that would make it useful to treat them as naturally fractured reservoirs.

Keywords: homogenization temperature, fluid inclusions, microthermometry, salinity

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Keyvan Ramin

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The geometric nonlinearity of Off-Diagonal Bracing System (ODBS) could be a complementary system to covering and extending the nonlinearity of reinforced concrete material. Finite element modeling is performed for flexural frame, x-braced frame and the ODBS braced frame system at the initial phase. Then the different models are investigated along various analyses. According to the experimental results of flexural and x-braced frame, the verification is done. Analytical assessments are performed in according to three-dimensional finite element modeling. Non-linear static analysis is considered to obtain performance level and seismic behavior, and then the response modification factors calculated from each model’s pushover curve. In the next phase, the evaluation of cracks observed in the finite element models, especially for RC members of all three systems is performed. The finite element assessment is performed on engendered cracks in ODBS braced frame for various time steps. The nonlinear dynamic time history analysis accomplished in different stories models for three records of Elcentro, Naghan, and Tabas earthquake accelerograms. Dynamic analysis is performed after scaling accelerogram on each type of flexural frame, x-braced frame and ODBS braced frame one by one. The base-point on RC frame is considered to investigate proportional displacement under each record. Hysteresis curves are assessed along continuing this study. The equivalent viscous damping for ODBS system is estimated in according to references. Results in each section show the ODBS system has an acceptable seismic behavior and their conclusions have been converged when the ODBS system is utilized in reinforced concrete frame.

Keywords: FEM, seismic behaviour, pushover analysis, geometric nonlinearity, time history analysis, equivalent viscous damping, passive control, crack investigation, hysteresis curve

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Authors: Naz Najma, Grace T. M. Dal Sasso, Maria de Lourdes de Souza

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The development of information and communication technologies and the accessibility of mobile devices has increased the possibilities of the teaching and learning process anywhere and anytime. Mobile and web application allows the production of constructive teaching and learning models in various educational settings, showing the potential for active learning in nursing. The objective of this study was to present the development of an educational technology (Savinglife®, an app) for learning cardiopulmonary resuscitation and advanced cardiovascular life support training. Savinglife® is a technological production, based on the concept of virtual learning and problem-based learning approach. The study was developed from January 2016 to November 2016, using five phases (analyze, design, develop, implement, evaluate) of the instructional systems development process. The technology presented 10 scenarios and 12 simulations, covering different aspects of basic and advanced cardiac life support. The contents can be accessed in a non-linear way leaving the students free to build their knowledge based on their previous experience. Each scenario is presented through interactive tools such as scenario description, assessment, diagnose, intervention and reevaluation. Animated ECG rhythms, text documents, images and videos are provided to support procedural and active learning considering real life situation. Accessible equally on small to large devices with or without an internet connection, Savinglife® offers a dynamic, interactive and flexible tool, placing students at the center of the learning process. Savinglife® can contribute to the student’s learning in the assessment and management of basic and advanced cardiac life support in a safe and ethical way.

Keywords: problem-based learning, cardiopulmonary resuscitation, nursing education, advanced cardiac life support, educational technology

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Authors: Meera A. Albloushi, Adel B. Gougam

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The development in the field of piezoelectrics has led to a renewed interest in ZnO nanowires (NWs) as a promising material in the nanogenerator devices category. It can be used as a power source for self-powered electronic systems with higher density, higher efficiency, longer lifetime, as well as lower cost of fabrication. Highly aligned ZnO nanowires seem to exhibit a higher performance compared with nonaligned ones. The purpose of this study was to develop ZnO nanowires and to investigate their electrical and chemical properties for various applications. They were grown on silicon (100) and glass substrates. We have used a low temperature and non-hazardous method: aqueous chemical growth (ACG). ZnO (non-doped) and AZO (Aluminum doped) seed layers were deposited using RF magnetron sputteringunder Argon pressure of 3 mTorr and deposition power of 180 W, the times of growth were selected to obtain thicknesses in the range of 30 to 125 nm. Some of the films were subsequently annealed. The substrates were immersed tilted in an equimolar solution composed of zinc nitrate and hexamine (HMTA) of 0.02 M and 0.05 M in the temperature range of 80 to 90 ᵒC for 1.5 to 2 hours. The X-ray diffractometer shows strong peaks at 2Ө = 34.2ᵒ of ZnO films which indicates that the films have a preferred c-axis wurtzite hexagonal (002) orientation. The surface morphology of the films is investigated by atomic force microscope (AFM) which proved the uniformity of the film since the roughness is within 5 nm range. The scanning electron microscopes(SEM) (Quanta FEG 250, Quanta 3D FEG, Nova NanoSEM 650) are used to characterize both ZnO film and NWs. SEM images show forest of ZnO NWs grown vertically and have a range of length up to 2000 nm and diameter of 20-300 nm. The SEM images prove that the role of the seed layer is to enhance the vertical alignment of ZnO NWs at the pH solution of 5-6. Also electrical and optical properties of the NWs are carried out using Electrical Force Microscopy (EFM). After growing the ZnO NWs, developing the nano-generator is the second step of this study in order to determine the energy conversion efficiency and the power output.

Keywords: ZnO nanowires(NWs), aqueous chemical growth (ACG), piezoelectric NWs, harvesting enery

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Authors: Aurelija Burinskienė, Dalė Dzemydienė, Arūnas Miliauskas

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This research aims at developing the approach for more effective freight delivery and transportation process management. The road congestions and the identification of causes are important, as well as the context information recognition and management. The measure of many parameters during the transportation period and proper control of driver work became the problem. The number of vehicles per time unit passing at a given time and point for drivers can be evaluated in some situations. The collection of data is mainly used to establish new trips. The flow of the data is more complex in urban areas. Herein, the movement of freight is reported in detail, including the information on street level. When traffic density is extremely high in congestion cases, and the traffic speed is incredibly low, data transmission reaches the peak. Different data sets are generated, which depend on the type of freight delivery network. There are three types of networks: long-distance delivery networks, last-mile delivery networks and mode-based delivery networks; the last one includes different modes, in particular, railways and other networks. When freight delivery is switched from one type of the above-stated network to another, more data could be included for reporting purposes and vice versa. In this case, a significant amount of these data is used for control operations, and the problem requires an integrated methodological approach. The paper presents an approach for providing e-services for drivers by including the assessment of the multi-component infrastructure needed for delivery of freights following the network type. The construction of such a methodology is required to evaluate data flow conditions and overloads, and to minimize the time gaps in data reporting. The results obtained show the possibilities of the proposing methodological approach to support the management and decision-making processes with functionality of incorporating networking specifics, by helping to minimize the overloads in data reporting.

Keywords: transportation networks, freight delivery, data flow, monitoring, e-services

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Authors: Fuyuan Ma, Yuhan Wang, Junhe Zhang, Ying Wang

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Identifying the sources of information dissemination is a pivotal task in the study of collective behaviors in networks, enabling us to discern and intercept the critical pathways through which information propagates from its origins. This allows for the control of the information’s dissemination impact in its early stages. Numerous methods for source detection rely on pre-existing, underlying propagation models as prior knowledge. Current models that eschew prior knowledge attempt to harness label propagation algorithms to model the statistical characteristics of propagation states or employ Graph Neural Networks (GNNs) for deep reverse modeling of the diffusion process. These approaches are either deficient in modeling the propagation patterns of information or are constrained by the over-smoothing problem inherent in GNNs, which limits the stacking of sufficient model depth to excavate global propagation patterns. Consequently, we introduce the ODESI model. Initially, the model employs a label propagation algorithm to delineate the distribution density of infected states within a graph structure and extends the representation of infected states from integers to state vectors, which serve as the initial states of nodes. Subsequently, the model constructs a deep architecture based on GNNs-coupled Ordinary Differential Equations (ODEs) to model the global propagation patterns of continuous propagation processes. Addressing the challenges associated with solving ODEs on graphs, we approximate the analytical solutions to reduce computational costs. Finally, we conduct simulation experiments on two real-world social network datasets, and the results affirm the efficacy of our proposed ODESI model in source identification tasks.

Keywords: source identification, ordinary differential equations, label propagation, complex networks

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Authors: Olufunmilayo Folaranmi

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This research was carried out to examine the impact of socio-cultural factors on the management and utilization of solid waste in Ibadan Metropolis. A descriptive survey research design was adopted for the study while a systematic and stratified random sampling technique was used to select 300 respondents which were categorized into high, middle and low-density areas. Four hypothesis were tested using chi-square test on variables of unavailability of waste disposal facilities and waste management, negligence of contractors to liaise with community members, lack of adequate environmental education and waste management and utilization, low level of motivation of sanitation workers with solid wastes management, lack of community full participation with solid waste management and utilization. Results showed that significant effect of waste disposal facilities on solid waste management and utilization (X2 +16.6, P < .05). Also, there is a significant relationship between negligence of the contractors to liaise with community elites with improper disposal (X2 = 87.5, P < .05). The motivation of sanitation workers is significantly related to solid waste management (X2 = 70.4, P < .05). Adequate environmental education and awareness influenced solid waste management. There was also a significant relationship between lack of community participation with waste management disposal and improper waste disposal. Based on the findings from the study it was recommended that the quality of life in urban centers should be improved, social welfare of the populace enhanced and environment should be adequately attended to. Poverty alleviation programmes should be intensified and made to live beyond the life of a particular administration, micro-credit facilities should be available to community members to promote their welfare. Lastly, sustained environmental education programmes for citizens at all levels of education, formal and informal through the use of agencies like Ethical and Attitudinal Reorientation Commission (EARCOM) and the National Orientation Agency (NOA).

Keywords: management, social welfare, socio-cultural factors, solid waste

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Authors: Adamu S. Salawu, Ibrahim O. Isah

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Direct solution to several forms of fourth-order ordinary differential equations is not easily obtained without first reducing them to a system of first-order equations. Thus, numerical methods are being developed with the underlying techniques in the literature, which seeks to approximate some classes of fourth-order initial value problems with admissible error bounds. Multistep methods present a great advantage of the ease of implementation but with a setback of several functions evaluation for every stage of implementation. However, hybrid methods conventionally show a slightly higher order of truncation for any k-step linear multistep method, with the possibility of obtaining solutions at off mesh points within the interval of solution. In the light of the foregoing, we propose the continuous form of a hybrid multistep method with Chebyshev polynomial as a basis function for the numerical integration of fourth-order initial value problems of ordinary differential equations. The basis function is interpolated and collocated at some points on the interval [0, 2] to yield a system of equations, which is solved to obtain the unknowns of the approximating polynomial. The continuous form obtained, its first and second derivatives are evaluated at carefully chosen points to obtain the proposed block method needed to directly approximate fourth-order initial value problems. The method is analyzed for convergence. Implementation of the method is done by conducting numerical experiments on some test problems. The outcome of the implementation of the method suggests that the method performs well on problems with oscillatory or trigonometric terms since the approximations at several points on the solution domain did not deviate too far from the theoretical solutions. The method also shows better performance compared with an existing hybrid method when implemented on a larger interval of solution.

Keywords: Chebyshev polynomial, collocation, hybrid multistep method, initial value problems, interpolation

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Authors: Xuan Zhao, Wen Jiang

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In this study, a web crawler was used to collect POI sample data from 38 districts and counties of Chongqing in 2022, and ArcGIS was combined to coordinate and projection conversion and realize data visualization. Nuclear density analysis and spatial correlation analysis were used to explore the spatial distribution characteristics of elderly care facilities in Chongqing, and K mean cluster analysis was carried out with GeoDa to study the spatial concentration degree of elderly care resources in 38 districts and counties. Finally, the driving force of spatial differentiation of elderly care facilities in various districts and counties of Chongqing is studied by using the method of geographic detector. The results show that: (1) in terms of spatial distribution structure, the distribution of elderly care facilities in Chongqing is unbalanced, showing a distribution pattern of ‘large dispersion and small agglomeration’ and the asymmetric pattern of ‘west dense and east sparse, north dense and south sparse’ is prominent. (2) In terms of the spatial matching between elderly care resources and the elderly population, there is a weak coordination between the input of elderly care resources and the distribution of the elderly population at the county level in Chongqing. (3) The analysis of the results of the geographical detector shows that the single factor influence is mainly the number of elderly population, public financial revenue and district and county GDP. The high single factor influence is mainly caused by the elderly population, public financial income, and district and county GDP. The influence of each influence factor on the spatial distribution of elderly care facilities is not simply superimposed but has a nonlinear enhancement effect or double factor enhancement. It is necessary to strengthen the synergistic effect of two factors and promote the synergistic effect of multiple factors.

Keywords: aging, elderly care facilities, spatial differentiation, geographical detector, driving force analysis, Mountain city

Procedia PDF Downloads 42

Authors: Maurício N. Kleinberg, Ana P. R. N. Barroso, Frederico R. Silva, Natasha l. Gomes, Rodrigo F. Guimarães, Marcelo M. V. Parente, Jackson Q. Malveira

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Increased production of biofuels, especially biodiesel, as an option to replace the diesel derived from oil is already a reality in countries seeking a renewable and environmentally friendly fuel, as is the case in Brazil. However, it is known that the use of fuels, renewable or not, implies that it is in contact with various metallic materials which may cause corrosion. In the search for more corrosion resistant materials has been experimentally observed that the addition of molybdenum in ferritic steels increases their protective character without significantly burdening the cost of production. In order to evaluate the effect of adding molybdenum, samples of commercial steel (austenitic, ferritic and carbon steel) and the experimental ferritic alloy with a high molybdenum content (5.3%) were immersed separately into biodiesel derived from transesterification of soy oil to monitor the corrosion process of these metal samples, and in parallel to analyze the oxidative degradation of biodiesel itself. During the immersion time of 258 days, biodiesel samples were taken for analysis of acidity, kinematic viscosity, density and refraction. Likewise, the metal samples were taken from the biodiesel to be weighed and microstructurally analyzed by light microscopy. The results obtained at the end of 258 days shown that biodiesel presented a considerable increase on the values of the studied parameters for all the samples. However, this increase was not able to produce significant mass loss in metallic samples. As regards the microstructural analysis, it showed the onset of surface oxidation on the carbon steel sample. As for the other samples, no significant surface changes were shown. These results are consistent with literature for short immersion times. It is concluded that the increase in the values of the studied parameters is not significant yet, probably due to the low time of immersion and exposure of the samples. Thus, it is necessary to continue the tests so that the objectives of this work are achieved.

Keywords: biodiesel, corrosion, immersion, experimental alloy

Procedia PDF Downloads 440

Authors: Henok Marie Shiferaw, Barbara Schneider-Muntau

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Test repeatability and data reproducibility are a concern in many geotechnical laboratory tests due to inherent soil variability, inhomogeneous sample preparation and measurement inaccuracy. Test results on comparable test specimens vary to a considerable extent. Thus, also the derived shear strength parameters from triaxial tests are affected. In this contribution, we present the reproducibility of effective shear strength parameters from consolidated undrained triaxial tests on plain soil and cement-treated soil specimens. Six remolded test specimens were prepared for the plain soil and for the cement-treated soil. Conventional three levels of consolidation pressure testing were considered with an effective consolidation pressure of 100 kPa, 200 kPa and 300 kPa, respectively. At each effective consolidation pressure, two tests were done on comparable test specimens. Focus was laid on the same mean dry density and same water content during sample preparation for the two specimens. The cement-treated specimens were tested after 28 days of curing. Shearing of test specimens was carried out at a deformation rate of 0.4 mm/min after sample saturation at a back pressure of 900 kPa, followed by consolidation. The effective peak and residual shear strength parameters were then estimated from regression analysis of 21 different combinations of the failure stresses from the six tests conducted for both the plain soil and cement-treated soil samples. The 21 different stress combinations were constructed by picking three, four, five and six failure tresses at once at different combinations. Results indicate that the effective shear strength parameters estimated from the regression of different combinations of the failure stresses vary. Effective critical friction angle was found to be more consistent than effective peak friction angle with a smaller standard deviation. The reproducibility of the shear strength parameters for the cement-treated specimens was even lower than that of the untreated specimens.

Keywords: shear strength parameters, test repeatability, data reproducibility, triaxial soil testing, cement improvement of soils

Procedia PDF Downloads 35

Authors: Victor Ananth Paramananth, Rashid Muniginin, Mahaya Abd Rahman, Siti Afifah Ismail

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Safety issues, scene protection, and appropriate evidence collection must be handled in any bio crime scene. There will be a scene or multi-scene to be cordoned for investigation in any bio-incident or bio crime event. Evidence collection is critical in determining the type of microbial or toxin, its lethality, and its source. As a consequence, from the start of the investigation, a proper sampling method is required. The most significant challenges for the crime scene officer would be deciding where to obtain samples, the best sampling method, and the sample sizes needed. Since there could be evidence in liquid, viscous, or powder shape at a crime scene, crime scene officers have difficulty determining which tools to use for sampling. To maximize sample collection, the appropriate tools for sampling methods are necessary. This study aims to assist the crime scene officer in collecting liquid, viscous, and powder biological samples in sufficient quantity while preserving sample quality. Observational tests on sample collection using liquid, viscous, and powder samples for adequate quantity and sample quality were performed using UV light in this research. The density of the light emission varies upon the method of collection and sample types. The best tools for collecting sufficient amounts of liquid, viscous, and powdered samples can be identified by observing UV light. Instead of active microorganisms, the invisible powder is used to assess sufficient sample collection during a crime scene investigation using various collection tools. The liquid, powdered and viscous samples collected using different tools were analyzed using Fourier transform infrared - attenuate total reflection (FTIR-ATR). FTIR spectroscopy is commonly used for rapid discrimination, classification, and identification of intact microbial cells. The liquid, viscous and powdered samples collected using various tools have been successfully observed using UV light. Furthermore, FTIR-ATR analysis showed that collected samples are sufficient in quantity while preserving their quality.

Keywords: biological sample, crime scene, collection tool, UV light, forensic

Procedia PDF Downloads 196

Authors: O. Delage, H. Bencherif, T. Portafaix, A. Bourdier

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The main purpose of time series analysis is to learn about the dynamics behind some time ordered measurement data. Two approaches are used in the literature to get a better knowledge of the dynamics contained in observation data sequences. The first of these approaches concerns time series decomposition, which is an important analysis step allowing patterns and behaviors to be extracted as components providing insight into the mechanisms producing the time series. As in many cases, time series are short, noisy, and non-stationary. To provide components which are physically meaningful, methods such as Empirical Mode Decomposition (EMD), Empirical Wavelet Transform (EWT) or, more recently, Empirical Adaptive Wavelet Decomposition (EAWD) have been proposed. The second approach is to reconstruct the dynamics underlying the time series as a trajectory in state space by mapping a time series into a set of Rᵐ lag vectors by using the method of delays (MOD). Takens has proved that the trajectory obtained with the MOD technic is equivalent to the trajectory representing the dynamics behind the original time series. This work introduces the singular spectrum decomposition (SSD), which is a new adaptive method for decomposing non-linear and non-stationary time series in narrow-banded components. This method takes its origin from singular spectrum analysis (SSA), a nonparametric spectral estimation method used for the analysis and prediction of time series. As the first step of SSD is to constitute a trajectory matrix by embedding a one-dimensional time series into a set of lagged vectors, SSD can also be seen as a reconstruction method like MOD. We will first give a brief overview of the existing decomposition methods (EMD-EWT-EAWD). The SSD method will then be described in detail and applied to experimental time series of observations resulting from total columns of ozone measurements. The results obtained will be compared with those provided by the previously mentioned decomposition methods. We will also compare the reconstruction qualities of the observed dynamics obtained from the SSD and MOD methods.

Keywords: time series analysis, adaptive time series decomposition, wavelet, phase space reconstruction, singular spectrum analysis

Procedia PDF Downloads 106

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 504

Authors: Madhalasa Iyer

Abstract:

The increase in sustainable practices have encouraged the research and production of alternative fuels. New techniques of bio flocculation with the addition of yeast and bacteria strains have increased the efficiency of biofuel production. Fatty acid methyl ester (FAME) analysis in previous research has indicated that yeast can serve as a plausible enhancer for microalgal lipid production. The research hopes to identify the yeast and microalgae treatment group that produces the largest algae biomass. The mass of the dried algae is used as a proxy for TAG production correlating to the cultivation of biofuels. The study uses a model bioreactor created and built using PVC pipes, 8-port sprinkler system manifold, CO2 aquarium tank, and disposable water bottles to grow the microalgae. Nannochloropsis sp., and Isochrysis galbanawere inoculated separately in experimental group 1 and 2 with no treatments and in experimental groups 3 and 4 with each algaeco-cultured with Saccharomyces cerevisiae in the medium of standard garden stone fertilizer. S. cerevisiae was grown in a petri dish with nutrient agar medium before inoculation. A Secchi stick was used before extraction to collect data for the optical density of the microalgae. The biomass estimator was then used to measure the approximate production of biomass. The microalgae were grown and extracted with a french press to analyze secondary measurements using the dried biomass. The experimental units of Isochrysis galbana treated with the baker’s yeast strains showed an increase in the overall mass of the dried algae. S. cerevisiae proved to be an accurate and helpful addition to the solution to provide for the growth of algae. The increase in productivity of this fuel source legitimizes the possible replacement of non-renewable sources with more promising renewable alternatives. This research furthers the notion that yeast and mutants can be engineered to be employed in efficient biofuel creation.

Keywords: biofuel, co-culture, S. cerevisiae, microalgae, yeast

Procedia PDF Downloads 109

Authors: Auwal Garba, Rabiu Maijama’a, Abdullahi Muhammad Jalam

Abstract:

Variability in climate has affected the agricultural production all over the globe. This concern has motivated important changes in the field of research during the last decade. Climate variability is believed to have declining effects towards rice production in Nigeria. This study examined climate variability and its impact on rice productivity in Dass Local Government Area, Bauchi State, by employing Linear Trend Model (LTM), analysis of variance (ANOVA) and regression analysis. Annual seasonal data of the climatic variables for temperature (min. and max), rainfall, and solar radiation from 1990 to 2015 were used. Results confirmed that 74.4% of the total variation in rice yield in the study area was explained by the changes in the independent variables. That is to say, temperature (minimum and maximum), rainfall, and solar radiation explained rice yield with 74.4% in the study area. Rising mean maximum temperature would lead to reduction in rice production while moderate increase in mean minimum temperature would be advantageous towards rice production, and the persistent rise in the mean maximum temperature, in the long run, will have more negatively affect rice production in the future. It is, therefore, important to promote agro-meteorological advisory services, which will be useful in farm planning and yield sustainability. Closer collaboration among the meteorologist and agricultural scientist is needed to increase the awareness about the existing database, crop weather models among others, with a view to reaping the full benefits of research on specific problems and sustainable yield management and also there should be a special initiative by the ADPs (State Agricultural Development Programme) towards promoting best agricultural practices that are resilient to climate variability in rice production and yield sustainability.

Keywords: climate variability, impact, productivity, rice

Procedia PDF Downloads 103

Authors: Fatemeh Najafi

Abstract:

The major stress factor limiting crop growth and development of sesame (Sesamum indicum L.) is drought stress in arid and semiarid regions of the world. For this study the effects of water stress on some qualitative and quantitative traits in sesame germplasm was conducted in the Research Farm of Seed and Plant Improvement Institute, Karaj, in the crop year. Genotypes in a randomized complete block design with three replications in two environments (moisture stress and normal) were studied in regard of the seed weight, capsule weight, grain yield, biomass, plant height, number of capsules per plant, etc. The characteristics were evaluated based on the combined analysis. Irrigation was based on first class evaporation basin. After flowering stage drought stress was applied. The water deficit reduced growth period. Days to reach full ripening decreased so that the reduction was significant at the five percent level. Drought stress reduces yield and plant biomass. Genotypes based on combined analysis of these two traits were significant at the one percent level. Genotypes differ in terms of yield stress in terms of density plots, grain yield, days to first flowering and days to the half of the cap on the confidence level of five percent and traits of days to emergence of the first capsule and days to reach full ripening at the one percent level were significant. Other traits were not significant. The correlation of traits in circumstances of stress the number of seeds per capsule has the greatest impact on performance. The sensitivity and stress tolerance index was calculated. Based on the indicators, (Fars variety) and variety Karaj were identified as the most tolerant genotypes among the studied genotypes to drought stress. The highest sensitivity indicator of stress was related to genotype (FARS).

Keywords: sesamum, drought, stress, germplasm, resistance

Procedia PDF Downloads 73

Authors: Y. P. Wang, J. K. Chen, C. H. Lee, G. H. Huang, M. C. Wang, S. W. Chen, Y. T. Kuan, H. C. Lin, C. Y. Huang, W. H. Liang, W. C. Lin, H. C. Yu

Abstract:

The hi-tech industries in the Science Park at southern Taiwan were heavily damaged by a strong earthquake early 2016. The financial loss in this event was attributed primarily to the automated stocker system handling fully processed products, and recovery of the automated stocker system from the aftermath proved to contribute major lead time. Therefore, development of effective means for protection of stockers against earthquakes has become the highest priority for risk minimization and business continuity. This study proposes to mitigate the seismic response of the stockers by introducing viscous fluid dampers in between the ceiling and the top of the stockers. The stocker is expected to vibrate less violently with a passive control force on top. Linear damper is considered in this application with an optimal damping coefficient determined from a preliminary parametric study. The damper is small in size in comparison with those adopted for building or bridge applications. Component test of the dampers has been carried out to make sure they meet the design requirement. Shake table tests have been further conducted to verify the proposed scheme under realistic earthquake conditions. Encouraging results have been achieved by effectively reducing the seismic responses of up to 60% and preventing the FOUPs from falling off the shelves that would otherwise be the case if left unprotected. Effectiveness of adopting a viscous fluid damper for seismic control of the stocker on top against the ceiling has been confirmed. This technique has been adopted by Macronix International Co., LTD for seismic retrofit of existing stockers. Demonstrative projects on the application of the proposed technique are planned underway for other companies in the display industry as well.

Keywords: hi-tech industries, seismic protection, automated stocker system, viscous fluid damper

Procedia PDF Downloads 357

Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

Abstract:

This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

Procedia PDF Downloads 504