Search results for: Quaternion offset linear canonical transform

Authors: G. T. Ramos-Escobedo, E. T. Pecina-Treviño, L. F. Camacho-Ortegon, E. Orrantia-Borunda

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The mineral bioflotation represents a viable alternative for the evaluation of new processes benefit alternative. The adsorption bacteria on minerals surfaces will depend mainly on the type of the microorganism as well as of the studied mineral surface. In the current study, adhesion of S. carnosus on coal was studied. Several methods were used as: DRX, Fourier Transform Infra Red (FTIR) adhesion isotherms and kinetic. The main goal is the recovery of organic matter by the microflotation process on coal particles with biological reagent (S. carnosus). Adhesion tests revealed that adhesion took place after 8 h at pH 9. The results suggest that the adhesion of bacteria to solid substrates can be considered an abiotic physicochemical process that is consequently governed by bacterial surface properties such as their specific surface area, hydrophobicity and surface functionalities. The greatest coal fine flotability was 75%, after 5 min of flotation.

Keywords: fine coal, bacteria, adhesion, recovery organic matter

Procedia PDF Downloads 293

Authors: Khalil H. Al-Bayati, G. Nasma, Hussein Ban H. Adel

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The purpose of the present work is to calculate the expectation value of potential energy for different spin states (ααα ≡ βββ, αβα ≡ βαβ) and compare it with spin states (αββ, ααβ ) for lithium excited state (1s2s3s) and Li-like ions (Be+, B+2) using Hartree-Fock wave function by partitioning technique. The result of inter particle expectation value shows linear behaviour with atomic number and for each atom and ion the shows the trend ααα < ααβ < αββ < αβα.

Keywords: lithium excited state, potential energy, 1s2s3s, mathematical physics

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Authors: Bandar A. Alkhayyal

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Modern supply chains are typically linear, transforming virgin raw materials into products for end consumers, who then discard them after use to landfills or incinerators. Nowadays, there are major efforts underway to create a circular economy to reduce non-renewable resource use and waste. One important aspect of these efforts is the development of Green Supply Chain (GSC) systems which enables a reverse flow of used products from consumers back to manufacturers, where they can be refurbished or remanufactured, to both economic and environmental benefit. This paper develops novel multi-objective optimization models to inform GSC system design at multiple levels: (1) strategic planning of facility location and transportation logistics; (2) tactical planning of optimal pricing; and (3) policy planning to account for potential valuation of GSC emissions. First, physical linear programming was applied to evaluate GSC facility placement by determining the quantities of end-of-life products for transport from candidate collection centers to remanufacturing facilities while satisfying cost and capacity criteria. Second, disassembly and remanufacturing processes have received little attention in industrial engineering and process cost modeling literature. The increasing scale of remanufacturing operations, worth nearly $50 billion annually in the United States alone, have made GSC pricing an important subject of research. A non-linear physical programming model for optimization of pricing policy for remanufactured products that maximizes total profit and minimizes product recovery costs were examined and solved. Finally, a deterministic equilibrium model was used to determine the effects of internalizing a cost of GSC greenhouse gas (GHG) emissions into optimization models. Changes in optimal facility use, transportation logistics, and pricing/profit margins were all investigated against a variable cost of carbon, using case study system created based on actual data from sites in the Boston area. As carbon costs increase, the optimal GSC system undergoes several distinct shifts in topology as it seeks new cost-minimal configurations. A comprehensive study of quantitative evaluation and performance of the model has been done using orthogonal arrays. Results were compared to top-down estimates from economic input-output life cycle assessment (EIO-LCA) models, to contrast remanufacturing GHG emission quantities with those from original equipment manufacturing operations. Introducing a carbon cost of $40/t CO2e increases modeled remanufacturing costs by 2.7% but also increases original equipment costs by 2.3%. The assembled work advances the theoretical modeling of optimal GSC systems and presents a rare case study of remanufactured appliances.

Keywords: circular economy, extended producer responsibility, greenhouse gas emissions, industrial ecology, low carbon logistics, green supply chains

Procedia PDF Downloads 162

Authors: Charlotte K. Lee, Henrique R. N. Aguiar, Ralph Smith, James Baldock, Sam Botchey

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Background: Femoral neck stress fractures (FNSF) are uncommon, making up 1 to 7.2% of stress fractures in healthy subjects. FNSFs are prevalent in young women, military recruits, endurance athletes, and individuals with energy deficiency syndrome or female athlete triad. Presentation is often non-specific and is often misdiagnosed following the initial examination. There is limited research addressing the return–to–activity time after FNSF. Previous studies have demonstrated prognostic time predictions based on various imaging techniques. Here, (1) OxSport clinic FNSF practice standards are retrospectively reviewed, (2) FNSF cohort demographics are examined, (3) Regression models were used to predict return–to–activity prognosis and consequently determine bone stress risk factors. Methods: Patients with a diagnosis of FNSF attending Oxsport clinic between 01/06/2020 and 01/01/2020 were selected from the Rheumatology Assessment Database Innovation in Oxford (RhADiOn) and OxSport Stress Fracture Database (n = 14). (1) Clinical practice was audited against five criteria based on local and National Institute for Health Care Excellence guidance, with a 100% standard. (2) Demographics of the FNSF cohort were examined with Student’s T-Test. (3) Lastly, linear regression and Random Forest regression models were used on this patient cohort to predict return–to–activity time. Consequently, an analysis of feature importance was conducted after fitting each model. Results: OxSport clinical practice met standard (100%) in 3/5 criteria. The criteria not met were patient waiting times and documentation of all bone stress risk factors. Importantly, analysis of patient demographics showed that of the population with complete bone stress risk factor assessments, 53% were positive for modifiable bone stress risk factors. Lastly, linear regression analysis was utilized to identify demographic factors that predicted return–to–activity time [R2 = 79.172%; average error 0.226]. This analysis identified four key variables that predicted return-to-activity time: vitamin D level, total hip DEXA T value, femoral neck DEXA T value, and history of an eating disorder/disordered eating. Furthermore, random forest regression models were employed for this task [R2 = 97.805%; average error 0.024]. Analysis of the importance of each feature again identified a set of 4 variables, 3 of which matched with the linear regression analysis (vitamin D level, total hip DEXA T value, and femoral neck DEXA T value) and the fourth: age. Conclusion: OxSport clinical practice could be improved by more comprehensively evaluating bone stress risk factors. The importance of this evaluation is demonstrated by the population found positive for these risk factors. Using this cohort, potential bone stress risk factors that significantly impacted return-to-activity prognosis were predicted using regression models.

Keywords: eating disorder, bone stress risk factor, femoral neck stress fracture, vitamin D

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Authors: Essam Al Daoud

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Genome rearrangement is an important area in computational biology and bioinformatics. The basic problem in genome rearrangements is to compute the edit distance, i.e., the minimum number of operations needed to transform one genome into another. Unfortunately, unsigned genome rearrangement problem is NP-hard. In this study an improved ant colony optimization algorithm to approximate the edit distance is proposed. The main idea is to convert the unsigned permutation to signed permutation and evaluate the ants by using Kaplan algorithm. Two new operations are added to the standard ant colony algorithm: Replacing the worst ants by re-sampling the ants from a new probability distribution and applying the crossover operations on the best ants. The proposed algorithm is tested and compared with the improved breakpoint reversal sort algorithm by using three datasets. The results indicate that the proposed algorithm achieves better accuracy ratio than the previous methods.

Keywords: ant colony algorithm, edit distance, genome breakpoint, genome rearrangement, reversal sort

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Authors: Leila Samiee, Amir Yadegari, Saeedeh Tasharrofi

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In the work presented here, nitrogen-doped graphene materials were synthesized and used as metal-free electrocatalysts for oxygen reduction reaction (ORR) under alkaline conditions. Paraphenylenediamine was used as N precursor. The N-doped graphene was synthesized under hydrothermal treatment at 200°C. All the materials have been characterized by X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), Transmission electron microscopy (TEM) and X-ray photo-electron spectroscopy (XPS). Moreover, for electrochemical evaluation of samples, Rotating Disk electrode (RDE) and Cyclic Voltammetry techniques (CV) were employed. The resulting material exhibits an outstanding catalytic activity for the oxygen reduction reaction (ORR) as well as excellent resistance towards methanol crossover effects, indicating their promising potential as ORR electrocatalysts for alkaline fuel cells.

Keywords: alkaline fuel cell, graphene, metal-free catalyst, paraphenylen diamine

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Authors: Preshanthan Moodley

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This study compares two different pretreatments for sugarcane leaf waste (SLW): steam salt-alkali (SSA) and microwave salt-alkali (MSA). The two pretreatment types were modelled, optimized, and validated with R² > 0.97. Reducing sugar yields of 1.21g/g were obtained with optimized SSA pretreatment using 1.73M ZnCl₂, 1.36M NaOH and 9.69% solid loading, and 1.17g/g with optimized MSA pretreatment using 1.67M ZnCl₂, 1.52M NaOH at 400W for 10min. A lower pretreatment time (10min) was required for the MSA model (83% lower). The structure of pretreated SLW was assessed using scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR). The optimized SSA and MSA models showed lignin removal of 80.5 and 73% respectively. The MSA pretreatment was further examined on sorghum leaves and Napier grass and showed yield improvements of 1.9- and 2.8-fold compared to recent reports. The developed pretreatment methods demonstrated high efficiency at enhancing enzymatic hydrolysis on various lignocellulosic substrates.

Keywords: lignocellulosic biomass, pretreatment, salt, sugarcane leaves

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Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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Authors: Vijay Shankar

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In the era of water scarcity, effective use of water via irrigation requires good methods for determining crop water needs. Implementation of irrigation scheduling programs requires an accurate estimate of water use by the crop. Moisture depletion from the root zone represents the consequent crop evapotranspiration (ET). A numerical model for simulating soil water depletion in the root zone has been developed by taking into consideration soil physical properties, crop and climatic parameters. The governing differential equation for unsaturated flow of water in the soil is solved numerically using the fully implicit finite difference technique. The water uptake by plants is simulated by using three different sink functions. The non-linear model predictions are in good agreement with field data and thus it is possible to schedule irrigations more effectively. The present paper describes irrigation scheduling based on moisture depletion from the different layers of the root zone, obtained using different sink functions for three cash, oil and forage crops: cotton, safflower and barley, respectively. The soil is considered at a moisture level equal to field capacity prior to planting. Two soil moisture regimes are then imposed for irrigated treatment, one wherein irrigation is applied whenever soil moisture content is reduced to 50% of available soil water; and other wherein irrigation is applied whenever soil moisture content is reduced to 75% of available soil water. For both the soil moisture regimes it has been found that the model incorporating a non-linear sink function which provides best agreement of computed root zone moisture depletion with field data, is most effective in scheduling irrigations. Simulation runs with this moisture uptake function result in saving 27.3 to 45.5% & 18.7 to 37.5%, 12.5 to 25% % &16.7 to 33.3% and 16.7 to 33.3% & 20 to 40% irrigation water for cotton, safflower and barley respectively, under 50 & 75% moisture depletion regimes over other moisture uptake functions considered in the study. Simulation developed can be used for an optimized irrigation planning for different crops, choosing a suitable soil moisture regime depending upon the irrigation water availability and crop requirements.

Keywords: irrigation water, evapotranspiration, root uptake models, water scarcity

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Authors: Sujani B. Y. Abeywardena, Srimala Perera, K. M. Nalin De Silva, S. Walpalage

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Surface modifications are vital to accomplish the moisture management property in highly demanded synthetic fabrics. Biomimetic and bio-inspired surface modifications are identified as one of the fascinating areas of research. In this study, nature’s way of cooling elephants’ body temperature using mud bathing was mimicked to create a superior wettable nylon fabric with improved comfortability. For that, bentonite nanoclay was covalently grafted on nylon fabric using silane as a coupling agent. Fourier transform infrared spectra and Scanning electron microscopy images confirmed the successful grafting of nanoclay on nylon. The superior wettability of surface modified nylon was proved by standard protocols. This fabric coating strongly withstands more than 50 cycles of laundry. It is expected that this bio-inspired wettable nylon fabric may break the barrier of using nylon in various hydrophilic textile applications.

Keywords: bentonite nanoclay, biomimetic, covalent modification, nylon fabric, surface, wettability

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Authors: Yang Zhou, Kaijian Li, Guiwen Liu

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Offsite construction is an innovative alternative to conventional site-based construction, with wide-ranging benefits. It requires building components, elements or modules were prefabricated and pre-assembly before installed into their final locations. To improve efficiency and achieve synergies, in recent years, construction companies were clustered into construction industrial parks (CIPs) in China. A CIP is a community of construction manufacturing and service businesses located together on a common property. Companies involved in industrial clusters can obtain environment and economic benefits by sharing resources and information in a given region. Therefore, the concept of industrial symbiosis (IS) can be applied to the traditional CIP to achieve sustainable industrial development or redevelopment through the implementation of eco-industrial parks (EIP). However, before designing a symbiosis network between companies in a CIP, candidate support tenants need to be selected to complement the existing construction companies. In this study, an access indicator system and a linear programming model are established to select candidate tenants in a CIP while satisfying the degree of connectivity among the enterprises in the CIP, minimizing the environmental impact, and maximizing the annualized profit of the CIP. The access indicator system comprises three primary indicators and fifteen secondary indicators, is proposed from the perspective of park-based level. The fifteen indicators are classified as three primary indicators including industrial symbiosis, environment performance and economic benefit, according to the three dimensions of sustainability (environment, economic and social dimensions) and the three R's of the environment (reduce, reuse and recycle). The linear programming model is a method to assess the satisfactoriness of all the indicators and to make an optimal multi-objective selection among candidate tenants. This method provides a practical tool for planners of a CIP in evaluating which among the candidate tenants would best complement existing anchor construction tenants. The reasonability and validity of the indicator system and the method is worth further study in the future.

Keywords: construction industrial park, China, industrial symbiosis, offsite construction, selection of support tenants

Procedia PDF Downloads 281

Authors: Rihab Ben Lamine, Raoudha Ben Jemaa, Ikram Amous Ben Amor

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This paper proposes a graph planning technique for semantic adaptable Web Services composition. First, we use an ontology based context model for extending Web Services descriptions with information about the most suitable context for its use. Then, we transform the composition problem into a semantic context aware graph planning problem to build the optimal service composition based on user's context. The construction of the planning graph is based on semantic context aware Web Service discovery that allows for each step to add most suitable Web Services in terms of semantic compatibility between the services parameters and their context similarity with the user's context. In the backward search step, semantic and contextual similarity scores are used to find best composed Web Services list. Finally, in the ranking step, a score is calculated for each best solution and a set of ranked solutions is returned to the user.

Keywords: semantic web service, web service composition, adaptation, context, graph planning

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Authors: Pooja Seth, Shruti Aggarwal

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Thermoluminescence dosimetry (TLD) is one of the most effective methods for the assessment of dose during diagnostic radiology and radiotherapy applications. In these applications monitoring of absorbed dose is essential to prevent patient from undue exposure and to evaluate the risks that may arise due to exposure. LiF based thermoluminescence (TL) dosimeters are promising materials for the estimation, calibration and monitoring of dose due to their favourable dosimetric characteristics like tissue-equivalence, high sensitivity, energy independence and dose linearity. As the TL efficiency of a phosphor strongly depends on the preparation route, it is interesting to investigate the TL properties of LiF based phosphor in nanocrystalline form. LiF doped with magnesium (Mg), copper (Cu), sodium (Na) and silicon (Si) in nanocrystalline form has been prepared using chemical co-precipitation method. Cubical shape LiF nanostructures are formed. TL dosimetry properties have been investigated by exposing it to gamma rays. TL glow curve structure of nanocrystalline form consists of a single peak at 419 K as compared to the multiple peaks observed in microcrystalline form. A consistent glow curve structure with maximum TL intensity at annealing temperature of 573 K and linear dose response from 0.1 to 1000 Gy is observed which is advantageous for radiotherapy application. Good reusability, low fading (5 % over a month) and negligible residual signal (0.0019%) are observed. As per photoluminescence measurements, wide emission band at 360 nm - 550 nm is observed in an undoped LiF. However, an intense peak at 488 nm is observed in doped LiF nanophosphor. The phosphor also exhibits the intense optically stimulated luminescence. Nanocrystalline LiF: Mg, Cu, Na, Si phosphor prepared by co-precipitation method showed simple glow curve structure, linear dose response, reproducibility, negligible residual signal, good thermal stability and low fading. The LiF: Mg, Cu, Na, Si phosphor in nanocrystalline form has tremendous potential in diagnostic radiology, radiotherapy and high energy radiation application.

Keywords: thermoluminescence, nanophosphor, optically stimulated luminescence, co-precipitation method

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Authors: Jesus Ruano, Francesc Xavier Trias, Asensi Oliva

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A three-dimensional incompressible Large Eddy Simulation (LES) is performed to compute the hydrodynamic field around a pair of tandem cylinders. Symmetry-preserving schemes will be used during this simulation in conjunction with Finite Volume Method (FVM) to obtain the hydrodynamic field around the selected geometry. A set of results consisting of pressure and velocity and the combination of them will be stored at different surfaces near the cylinders as the initial input for the second part of the study. A post-processing of the obtained results based on Ffowcs-Williams and Hawkings (FWH) equation with a Fourier Transform of the acoustic sources will be used to compute noise at several probes located far away from the region where the hydrodynamics are computed. Directivities as well as spectral profile of the obtained acoustic field will be analyzed.

Keywords: far-field noise, Ffowcs-Williams and Hawkings, finite volume method, large eddy simulation, long-span bodies

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Amien Rahardjo, Faiz Husnayain, Iwa Garniwa

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PLN used the kWh meter to determine the amount of energy consumed by the household customers. High precision of kWh meter is needed in order to give accuracy results as the accuracy can be decreased due to the presence of harmonic. In this study, an estimation of active power consumed was developed. Based on the first year study results, the largest deviation due to harmonics can reach up to 9.8% in 2200VA and 12.29% in 3500VA with kWh meter analog. In the second year of study, deviation of digital customer meter reaches 2.01% and analog meter up to 9.45% for 3500VA household customers. The aim of this research is to produce an estimation system to calculate the total energy consumed by household customer using analog meter so the losses due to irregularities PLN recording of energy consumption based on the measurement used Analog kWh-meter installed is avoided.

Keywords: harmonics estimation, harmonic distortion, kWh meters analog and digital, THD, household customers

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Authors: M. P. Joshi, F. Deganello, L. F. Liotta, V. La Parola, G. Pantaleo

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For the first time, commercial iron nitrate was replaced by rust wastes, as a source of Iron for the preparation of LaFeO₃ powders by solution combustion synthesis (SCS). A detailed comparison with a reference powder obtained by SCS, starting from a commercial iron nitrate, was also performed. Several techniques such as X-ray diffraction combined with Rietveld refinement, mass plasma atomic emission spectroscopy, nitrogen adsorption measurements, temperature programmed reduction, X-ray photoelectron spectroscopy, Fourier transform analysis and scanning electron microscopy were used for the characterization of the rust wastes as well as of the perovskite powders. The performance of this ecofriendly material was evaluated by testing the activity and selectivity in the propylene oxidation, in order to use it for the benefit of the environment. Characterization and performance results clearly evidenced limitations and peculiarities of this new approach.

Keywords: perovskite type catalysts, solution combustion synthesis, X-ray diffraction, rust wastes

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Authors: Ibrahim Dauda Muhammad, Mokhtar Awang

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To synthesize a specific phase of zirconia (ZrO₂) nanotubes, zirconium (Zr) foil was subjected to the anodization process in a fluorine-containing electrochemical bath for a fixed duration. The resulting zirconia nanotubes (ZNTs) were then characterized using various techniques, including UV-vis spectroscopy, Fourier-transform infrared spectroscopy (FTIR), transmission electron microscopy (TEM), energy-dispersive X-ray spectroscopy (EDX), and X-ray diffraction (XRD). The XRD diffraction pattern confirmed that the ZNTs were crystalline, with a predominant texture along the [111] direction, indicating that the majority of the phase was cubic. TEM images revealed that most of the nanotubes were vertically aligned and self-organized, with diameters ranging from 32.9 to 38.8 nm and wall thicknesses between 3.0 and 7.3 nm. Additionally, the synthesized ZNTs had a length-to-width ratio of 235, which closely matches the ratio of 240 observed in another study where anodization was not used. This study demonstrates that a specific phase of zirconia nanotube can be successfully synthesized, with promising potential applications in catalysis and other areas.

Keywords: zirconia nanotubes, anodization, characterization, cubic phase

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Authors: Paul Okonkwo, Howard Smith

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A study to estimate the size of the cabin and major aircraft components as well as detect and avoid interference between internally placed components and the external surface, during the conceptual design synthesis and optimisation to explore the design space of a BWB, was conducted. Sizing of components follows the Bradley cabin sizing and rubber engine scaling procedures to size the cabin and engine respectively. The interference detection and avoidance algorithm relies on the ability of the Class Shape Transform parameterisation technique to generate polynomial functions of the surfaces of a BWB aircraft configuration from the sizes of the cabin and internal objects using few variables. Interference detection is essential in packaging of non-conventional configuration like the BWB because of the non-uniform airfoil-shaped sections and resultant varying internal space. The unique configuration increases the need for a methodology to prevent objects from being placed in locations that do not sufficiently enclose them within the geometry.

Keywords: packaging, optimisation, BWB, parameterisation, aircraft conceptual design

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Authors: Gabriel A. Juma, Adiel M. Magana, Githaiga N. Michael, James G. Kairo

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Seagrass meadows are important carbon sinks, thus understanding this role and their conservation provides opportunities for their applications in climate change mitigation and adaptation. This study aimed at understanding seagrass contribution to ecosystem carbon at Gazi Bay; by comparing carbon stocks in seagrass beds of two mangroves fringed creeks of the bay. Specifically, the objectives included assessing the distribution and abundance of seagrass in the fringed creeks, and estimating above and below-ground biomass. Results obtained would be added to the mangrove and open bay carbon in estimating total ecosystem carbon of Gazi bay. The stratified random sampling strategy was applied in this study. Transects were laid perpendicular to the waterline at intervals of 50 meters from the upper region near the mangroves to the deeper end of the creek across seagrass meadows. Along these transects, 0.25m2 square quadrats were laid at 10 m to assess distribution and composition of seagrasses in the creeks. A total of 80 plots were sampled. Above-ground biomass was sampled by harvesting all the seagrass materials within the quadrat while four sediment cores were obtained from each quarter of the quadrat and then sorted into necromass, rhizomes and roots to determine below ground biomass. Samples were cleaned and dried in the oven for 72 hours at 60˚C in the laboratory. Total biomass was determined by multiplying biomass with carbon conversion factor of 0.34. In all the statistical tests, a significant level was set at α = 0.05. Eight species of seagrass were encountered in Western creek (WC) while seven in the Eastern creek (EC). Based on importance value, the dominant species in WC were Cymodocea rotundata and Halodule uninervis while Thalassodendron ciliatum and Enhalus acoroides dominated the eastern creek. The cover of seagrass in EC was 67.97% compared to 56.45% in WC. There was a significance difference in abundance of seagrass species between the two creeks (t = 1.97, D.F = 35, p < 0.05). Similarly, there was significance differences between total seagrass biomass (t= -8.44, D.F. = 53, p < 0.05) and species composition (F(7,79) = 14.6, p < 0.05) in the two creeks. Mean seagrass in the creeks was 7.25 ± 4.2 Mg C ha-1, (range: 4.1 - 12.9 Mg C ha-1). The findings of the current study reveal variations in biomass stocks of the two creeks of Gazi bay that have varying biophysical features. It is established that habitat heterogeneity between the creeks contributes to the variation in seagrass abundance and biomass stocking. This enhances understanding of these ecosystems hence the establishment of carbon offset project in seagrass for livelihood improvement and increased conservation.

Keywords: seagrass, above-ground, below-ground, creeks, Gazi bay

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Tondani Mudau, Sherine B. Van Wyk, Zuhayr Kafaar, Janan Dietrich

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Female adolescents residing in a patriarchal society such as South Africa are more inclined to embrace feminine ideologies. Internalizing these ideologies may expose female adolescents to mental health challenges such as depression and anxiety. This study explored whether the internalisation of adolescent femininity ideologies namely, objectified relationship with own body (ORB) and inauthentic self in relationships (ISR) predicted anxiety and depression in late female adolescents at Stellenbosch University. The sample of the study consisted of 1451 (18-24) female undergraduate and postgraduate students enrolled at Stellenbosch University. The mean age of the participants was 20 (SD=1.46), and most participants (39.7%) were first-year students. The study employed a cross-sectional quantitative research design. Data was collected through an online self-completion survey, the survey consisted of three sections, the first section asked biographical questions regarding age, gender, race and family background. The second section measured the internalisation of feminine ideologies by using the adolescent femininity ideology scale which has two subscales namely inauthentic self in relationship with others (ISR) and objectified relationship with one’s own body (ORB). The ISR scale had the Cronbach Alpha of 0.76, and the ORB scale had the Cronbach Alpha of 0.83. The third section measured mental health (depression and anxiety) by using the Hopkins Symptoms 25-checklist which had the Cronbach Alpha of 0.93. Data were analysed through multiple linear regression from IBM SPSS (Statistical Package for the Social Sciences Version 24). The overall results of the multiple linear regression showed that The AFIS combination accounted for 14% for anxiety as measured by the Hopkins Symptoms Checklist R² = .142, F (2, 682) = 56.431, p < .001. The combination also accounted for 24% for depression as measured by the Hopkins Symptoms Checklist R² = .239, F (2, 682) = 106.971, p < .0. The findings in this study affirm the objectification and feminist theory contentions that internalising femininity ideologies (ISR and ORB) predict negative mental health in female adolescents.

Keywords: adolescents, anxiety, depression, feminine ideologies, inauthentic self, mental health, self-objectification, South Africa

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Authors: C. L Popa, C.S. Ciobanu, S. L. Iconaru, P. Chapon, A. Costescu, P. Le Coustumer, D. Predoi

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In this paper, the preparation and characterization of silver doped hydroxyapatite thin films and their antimicrobial activity characterized is reported. The resultant Ag: HAp films coated on commercially pure Si disks substrates were systematically characterized by Scanning Electron Microscopy (SEM) coupled with X-ray Energy Dispersive Spectroscopy detector (X-EDS), Glow Discharge Optical Emission Spectroscopy (GDOES) and Fourier Transform Infrared spectroscopy (FT-IR). GDOES measurements show that a substantial Ag content has been deposited in the films. The X-EDS and GDOES spectra revealed the presence of a material composed mainly of phosphate, calcium, oxygen, hydrogen and silver. The antimicrobial efficiency of Ag:HAp thin films against Escherichia coli and Staphylococcus aureus bacteria was demonstrated. Ag:HAp thin films could lead to a decrease of infections especially in the case of bone and dental implants by surface modification of implantable medical devices.

Keywords: silver, hydroxyapatite, thin films, GDOES, SEM, FTIR, antimicrobial effect

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Authors: Yeshona Sewsynker

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This study presents three microwave-assisted alkalic salt pretreatments to enhance delignification and enzymatic saccharification of corn cobs. The effects of process parameters of salt concentration (0-15%), microwave power intensity (0-800 W) and pretreatment time (2-8 min) on reducing sugar yield from corn cobs were investigated. Pretreatment models were developed with the high coefficient of determination values (R2>0.85). Optimization gave a maximum reducing sugar yield of 0.76 g/g. Scanning electron microscopy (SEM) and Fourier Transform Infrared analysis (FTIR) showed major changes in the lignocellulosic structure after pretreatment. A 7-fold increase in the sugar yield was observed compared to previous reports on the same substrate. The developed pretreatment strategy was effective for enhancing enzymatic saccharification from lignocellulosic wastes for microbial biofuel production processes and value-added products.

Keywords: pretreatment, lignocellulosic biomass, enzymatic hydrolysis, delignification

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Authors: Mohammed Husein Mohammad Rashid

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For a bounded linear operator T acting on a complex infinite dimensional Hilbert space ℋ, we say that T is ∗-class A operator (abbreviation T∈A*) if |T²|≥ |T*|². In this article, we prove the following assertions:(i) we establish some conditions which imply the normality of ∗-class A; (ii) we consider ∗-class A operator T ∈ ℬ(ℋ) with reducing kernel such that TX = XS for some X ∈ ℬ(K, ℋ) and prove the Fuglede-Putnam type theorem when adjoint of S ∈ ℬ(K) is dominant operators; (iii) furthermore, we extend the asymmetric Putnam-Fuglede theorem the class of ∗-class A operators.

Keywords: fuglede-putnam theorem, normal operators, ∗-class a operators, dominant operators

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Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur

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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.

Keywords: multiscale, bidimensional, wavelets, backscattering, multilayer, SPM, air pockets

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Authors: Humaira Khan, Mohsin Javed, Sammia Shahid

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The reinforced photocatalytic activity of graphene oxide (GO) along with composites of ZnO nanoparticles and copper-doped ZnO nanoparticles were studied by synthesizing ZnO and copper- doped ZnO nanoparticles by co-precipitation method. Zinc acetate and copper acetate were used as precursors, whereas graphene oxide was prepared from pre-oxidized graphite in the presence of H2O2.The supernatant was collected carefully and showed high-quality single-layer characterized by FTIR (Fourier Transform Infrared Spectroscopy), TEM (Transmission Electron Microscopy), SEM (Scanning Electron Microscopy), XRD (X-ray Diffraction Analysis), EDS (Energy Dispersive Spectrometry). The degradation of methylene blue as standard pollutant under UV-Visible irradiation gave results for photocatalytic activity of dopants. It could be concluded that shrinking of optical band caused by composites of Cu-dopped nanoparticles with GO enhances the photocatalytic activity.

Keywords: degradation, graphene oxide, photocatalysis, ZnO nanoparticles and copper-doped ZnO nanoparticles

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Authors: Prateek Singh, Dilshad Ahmad

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Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.

Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish

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Authors: Gracious Tendai Matayaya

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The world is facing problems in finding alternative resources to offset the decline in global petroleum reserves. The use of fossil fuels has prompted biofuel development, particularly in the transportation sector. In these circumstances, looking for alternative renewable energy sources makes sense. Petroleum-based fuels also result in a lot of carbon dioxide being released into the environment causing global warming. Replacing petroleum and fossil fuel-based fuels with biofuels has the advantage of reducing undesirable aspects of these fuels, which are mostly the production of greenhouse gas and dependence on unstable foreign suppliers. Algae refer to a group of aquatic microorganisms that produce a lot of lipids up to 60% of their total weight. This project aims to exploit the large amounts of oil produced by these microorganisms in the Soxhlet extraction to make biodiesel. Experiments were conducted to establish the cultivability of algae, harvesting methods, the oil extraction process, and the transesterification process. Although there are various methods for producing algal oil, the Soxhlet extraction method was employed for this particular research. After extraction, the oil was characterized before being used in the transesterification process that used methanol and hydrochloric acid as the process reactants. The properties of the resulting biodiesel were then determined. Because there is a requirement to dry wet algae, the experimental findings showed that Soxhlet extraction was the optimum way to produce a higher yield of microalgal oil. Upon cultivating algae, Compound D fertilizer was added as a source of nutrients (Phosphorous and Nitrogen), and the highest growth of algae was observed at 6 days (using 2 g of fertilizer), after which it started to decrease. Butanol, hexane, heptane and acetone have been experimented with as solvents, and heptane gave the highest amount of oil (89ml of oil) when 300 ml of solvent was used. This was compared to 73.21ml produced by butanol, 81.90 produced by hexane and 69.57ml produced by acetone, and as a result, heptane was used for the rest of the experiments, which included a variation of the mass of dried algae and time of extraction. This meant that the oil composition of algae was higher than other oil sources like peanuts, soybean etc. Algal oil was heated at 150℃ for 150 minutes in the presence of methanol (reactant) and hydrochloric acid (HCl), which was used as a catalyst. A temperature of 200℃ produced 93.64%, and a temperature of 250℃ produced 92.13 of biodiesel at 150 minutes.

Keywords: microalgae, algal oil, biodiesel, soxhlet extraction

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Authors: Samira Gharehkhani, Seyed Farid Seyed Shirazi, Abdolreza Gharehkhani, Hooman Yarmand, Ahmad Badarudin, Rushdan Ibrahim, Salim Newaz Kazi

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Nanocrystalline cellulose (NCC) were prepared by acid hydrolysis and ultrasound treatment of bleached Acacia mangium fibers. The obtained rod-shaped nanocrystals showed a uniform size. The results showed that NCC with high crystallinity can be obtained using 64 wt% sulfuric acid. The effect of synthesis condition was investigated. Different reaction times were examined to produce the NCC and the results revealed that an optimum reaction time has to be used for preparing the NCC. Morphological investigation was performed using the transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy and thermogravimetric analysis (TGA) were performed. X-ray diffraction (XRD) analysis revealed that the crystallinity increased with successive treatments. The NCC suspension was homogeneous and stable and no sedimentation was observed for a long time.

Keywords: acid hydrolysis, nanocrystalline cellulose, nano material, reaction time

Procedia PDF Downloads 509