Search results for: Minimum Spanning tree

Authors: D. Kokt, T. F. Dreyer

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The main objective of the study was to design a mentoring programme aimed at developing the soft skills of mentors. The mentors are all employed by a multinational corporation. The company had a mentoring plan in place that did not yield the required results, especially related to the development of soft skills. This prompted the researchers to conduct an extensive literature review followed by a mixed methods approach to ascertain the best practices in developing the soft skills of mentors. The outcomes of the study led to the development of a structured mentoring programme using 25 modules to be completed by mentors. The design incorporated a blended modular approach using both face-to-face teaching and teaching supported by Information Communication Technology (ICT). Blended learning was ideal as the ICT component helped to minimise instructor-mentor physical contact as part of the health measures during the Covid-19 pandemic. The blended learning approach also allowed instructors and mentors an online or offline mode, so that mentors could have more time for creative and cooperative exercises. A range of delivery methodologies were spread out across the different modules to ensure mentor engagement and accelerate mentor development. This included concept development through in-person instructor-led training sessions, concept development through virtual instructor-led training sessions, simulations, case studies, e-learning, role plays, interactive learning using mentoring toolkits, and experiential learning through application. The mentor development journey included formal modular competency assessments. All modules contained post-competency assessment consisting of 10 questions (comprising of a combination of explanatory questions and multiple-choice questions) to ensure understanding and deal with identified competency gaps. The minimum pass mark for all modular competency assessments was 80%. Mentors were allowed to retake the assessment if they scored less than 80% until they demonstrated understanding at the required level.

Keywords: mentor, mentee, soft skills, mentor development, blended learning, modular approach

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Authors: Abu Yousuf, Maksudur Rahman Khan, Ahasanul Karim, Amirul Islam, Minhaj Uddin Monir, Sharmin Sultana, Domenico Pirozzi

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Traditional biodiesel feedstock like edible oils or plant oils, animal fats and cooking waste oil have been replaced by microbial oil in recent research of biodiesel synthesis. The well-known community of microbial oil producers includes microalgae, oleaginous yeast and seaweeds. Conventional transesterification of microbial oil to produce biodiesel is lethargic, energy consuming, cost-ineffective and environmentally unhealthy. This process follows several steps such as microbial biomass drying, cell disruption, oil extraction, solvent recovery, oil separation and transesterification. Therefore, direct transesterification of biodiesel synthesis has been studying for last few years. It combines all the steps in a single reactor and it eliminates the steps of biomass drying, oil extraction and separation from solvent. Apparently, it seems to be cost-effective and faster process but number of difficulties need to be solved to make it large scale applicable. The main challenges are microbial cell disruption in bulk volume and make faster the esterification reaction, because water contents of the medium sluggish the reaction rate. Several methods have been proposed but none of them is up to the level to implement in large scale. It is still a great challenge to extract maximum lipid from microbial cells (yeast, fungi, algae) investing minimum energy. Electroporation technique results a significant increase in cell conductivity and permeability caused due to the application of an external electric field. Electroporation is required to alter the size and structure of the cells to increase their porosity as well as to disrupt the microbial cell walls within few seconds to leak out the intracellular lipid to the solution. Therefore, incorporation of electroporation techniques contributed in direct transesterification of microbial lipids by increasing the efficiency of biodiesel production rate.

Keywords: biodiesel, electroporation, microbial lipids, transesterification

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Authors: Noreen Noreen, Aamir Ijaz, Hamza Akhtar

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Background: Screening plays a major role to detect chromosomal abnormalities, Down syndrome, neural tube defects and other inborn diseases of the newborn. Serum biomarkers in the second trimester are useful in determining risk of most common chromosomal anomalies; these test include Alpha-fetoprotein (AFP), Human chorionic gonadotropin (hCG), Unconjugated Oestriol (UEȝ)and inhibin-A. Quadruple biomarkers are worth test in diagnosing the congenital pathology during pregnancy, these procedures does not form a part of routine health care of pregnant women in Pakistan, so the median value is lacking for population in Pakistan. Objective: To determine median values of biochemical maternal serum markers in local population during second trimester maternal screening. Study settings: Department of Chemical Pathology and Endocrinology, Armed Forces Institute of Pathology (AFIP) Rawalpindi. Methods: Cross-Sectional study for estimation of reference values. Non-probability consecutive sampling, 155 healthy pregnant women, of 30-40 years of age, will be included. As non-parametric statistics will be used, the minimum sample size is 120. Result: Total 155 women were enrolled into this study. The age of all women enrolled ranged from 30 to39 yrs. Among them, 39 per cent of women were less than 34 years. Mean maternal age 33.46±2.35 SD and maternal body weight were 54.98±2.88. Median value of quadruple markers calculated from 15-18th week of gestation that will be used for calculation of MOM for screening of trisomy21 in this gestational age. Median value at 15 week of gestation were observed hCG 36650 mIU/ml, AFP 23.3 IU/ml, UEȝ 3.5 nmol/L, InhibinA 198 ng/L, at 16 week of gestation hCG 29050 mIU/ml, AFP 35.4 IU/ml, UEȝ 4.1 nmol/L, InhibinA 179 ng/L, at 17 week of gestation hCG 28450 mIU/ml, AFP 36.0 IU/ml, UEȝ 6.7 nmol/L, InhibinA 176 ng/L and at 18 week of gestation hCG 25200 mIU/ml, AFP 38.2 IU/ml, UEȝ 8.2 nmol/L, InhibinA 190 ng/L respectively.All the comparisons were significant (p-Value <0.005) with 95% confidence Interval (CI) and level of significance of study set by going through literature and set at 5%. Conclusion: The median values for these four biomarkers in Pakistani pregnant women can be used to calculate MoM.

Keywords: screening, down syndrome, quadruple test, second trimester, serum biomarkers

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Authors: Komal Saini, S. K. Sahoo, B. S. Bajwa

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The Laser Fluorimetery Technique has been used for the microanalysis of uranium content in water samples collected from different sources like the hand pumps, tube wells in the drinking water samples of SW & NE Punjab, India. The geographic location of the study region in NE Punjab is between latitude 31.21º- 32.05º N and longitude 75.60º-76.14º E and for SW Punjab is between latitude 29.66º-30.48º N and longitude 74.69º-75.54º E. The purpose of this study was mainly to investigate the uranium concentration levels of ground water being used for drinking purposes and to determine its health effects, if any, to the local population of these regions. In the present study 131 samples of drinking water collected from different villages of SW and 95 samples from NE, Punjab state, India have been analyzed for chemical and radiological toxicity. In the present investigation, uranium content in water samples of SW Punjab ranges from 0.13 to 908 μgL−1 with an average of 82.1 μgL−1 whereas in samples collected from NE- Punjab, it ranges from 0 to 28.2 μgL−1 with an average of 4.84 μgL−1. Thus, revealing that in the SW- Punjab 54 % of drinking water samples have uranium concentration higher than international recommended limit of 30 µgl-1 (WHO, 2011) while 35 % of samples exceeds the threshold of 60 µgl-1 recommended by our national regulatory authority of Atomic Energy Regulatory Board (AERB), Department of Atomic Energy, India, 2004. On the other hand in the NE-Punjab region, none of the observed water sample has uranium content above the national/international recommendations. The observed radiological risk in terms of excess cancer risk ranges from 3.64x10-7 to 2.54x10-3 for SW-Punjab, whereas for NE region it ranges from 0 to 7.89x10-5. The chemical toxic effect in terms of Life-time average Daily Dose (LDD) and Hazard Quotient (HQ) have also been calculated. The LDD for SW-Punjab varies from 0.0098 to 68.46 with an average of 6.18 µg/ kg/day whereas for NE region it varies from 0 to 2.13 with average 0.365 µg/ kg/day, thus indicating presence of chemical toxicity in SW Punjab as 35% of the observed samples in the SW Punjab are above the recommendation limit of 4.53 µg/ kg/day given by AERB for 60 µgl-1 of uranium. Maximum & Minimum values for hazard quotient for SW Punjab is 0.002 & 15.11 with average 1.36 which is considerably high as compared to safe limit i.e. 1. But for NE Punjab HQ varies from 0 to 0.47. The possible sources of high uranium observed in the SW- Punjab will also be discussed.

Keywords: uranium, groundwater, radiological and chemical toxicity, Punjab, India

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Authors: Fumihiro Imai, Shinichi Watanabe, Shingo Maeda, Haruna Imai, Hiroki Niimi

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It is important to know the growth rate of brain tumors before surgery because it influences treatment planning, including not only surgical resection strategy but also adjuvant therapy after surgery. Amide proton transfer (APT) imaging is an emerging molecular magnetic resonance imaging (MRI) technique based on chemical exchange saturation transfer without the administration of a contrast medium. The underlying assumption in APT imaging of tumors is that there is a close relationship between the proliferative activity of the tumor and mobile protein synthesis. We aimed to evaluate the diagnostic performance of APT imaging of pre-and post-treatment brain tumors. Ten patients with brain tumor underwent conventional and APT-weighted sequences on a 3.0 Tesla MRI before clinical intervention. The maximum and the minimum APT-weighted signals (APTWmax and APTWmin) in each solid tumor region were obtained and compared before and after a clinical intervention. All surgical specimens were examined for histopathological diagnosis. Eight of ten patients underwent adjuvant therapy after surgery. Histopathological diagnosis was glioma in 7 patients (WHO grade 2 in 2 patients, WHO grade 3 in 3 patients, and WHO grade 4 in 2 patients), meningioma WHO grade 1 in 2 patients, and primary lymphoma of the brain in 1 patient. High-grade gliomas showed significantly higher APTW signals than that low-grade gliomas. APTWmax in one huge parasagittal meningioma infiltrating into the skull bone was higher than that in glioma WHO grade 4. On the other hand, APTWmax in another convexity meningioma was the same as that in glioma WHO grade 3. Diagnosis of primary lymphoma of the brain was possible with APT imaging before pathological confirmation. APTW signals in residual tumors decreased dramatically within one year after adjuvant therapy in all patients. APT imaging demonstrated excellent diagnostic performance for the planning of surgery and adjuvant therapy of brain tumors.

Keywords: amides, magnetic resonance imaging, brain tumors, cell proliferation

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Authors: B. Rakjarit, S. Athichanagorn

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Double displacement process is a method in which gas is injected at an updip well to displace the oil bypassed by waterflooding operation from downdip water injector. As gas injection is costly and a large amount of gas is needed, gas dump-flood from multiple gas reservoirs is an attractive alternative. The objective of this paper is to demonstrate the benefits of the novel approach of double displacement process via gas dump-flood from multiple gas reservoirs. A reservoir simulation model consisting of a dipping oil reservoir and several underlying layered gas reservoirs was constructed in order to investigate the performance of the proposed method. Initially, water was injected via the downdip well to displace oil towards the producer located updip. When the water cut at the producer became high, the updip well was shut in and perforated in the gas zones in order to dump gas into the oil reservoir. At this point, the downdip well was open for production. In order to optimize oil recovery, oil production and water injection rates and perforation strategy on the gas reservoirs were investigated for different numbers of gas reservoirs having various depths and thicknesses. Gas dump-flood from multiple gas reservoirs can help increase the oil recovery after implementation of waterflooding upto 10%. Although the amount of additional oil recovery is slightly lower than the one obtained in conventional double displacement process, the proposed process requires a small completion cost of the gas zones and no operating cost while the conventional method incurs high capital investment in gas compression facility and high-pressure gas pipeline and additional operating cost. From the simulation study, oil recovery can be optimized by producing oil at a suitable rate and perforating the gas zones with the right strategy which depends on depths, thicknesses and number of the gas reservoirs. Conventional double displacement process has been studied and successfully implemented in many fields around the world. However, the method of dumping gas into the oil reservoir instead of injecting it from surface during the second displacement process has never been studied. The study of this novel approach will help a practicing engineer to understand the benefits of such method and can implement it with minimum cost.

Keywords: gas dump-flood, multi-gas layers, double displacement process, reservoir simulation

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Authors: Lina Wu, Jia Liu, Ye Li

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The goal of this project is to investigate constant properties (called the Liouville-type Problem) for a p-stable map as a local or global minimum of a p-energy functional where the domain is a Euclidean space and the target space is a closed half-ellipsoid. The First and Second Variation Formulas for a p-energy functional has been applied in the Calculus Variation Method as computation techniques. Stokes’ Theorem, Cauchy-Schwarz Inequality, Hardy-Sobolev type Inequalities, and the Bochner Formula as estimation techniques have been used to estimate the lower bound and the upper bound of the derived p-Harmonic Stability Inequality. One challenging point in this project is to construct a family of variation maps such that the images of variation maps must be guaranteed in a closed half-ellipsoid. The other challenging point is to find a contradiction between the lower bound and the upper bound in an analysis of p-Harmonic Stability Inequality when a p-energy minimizing map is not constant. Therefore, the possibility of a non-constant p-energy minimizing map has been ruled out and the constant property for a p-energy minimizing map has been obtained. Our research finding is to explore the constant property for a p-stable map from a Euclidean space into a closed half-ellipsoid in a certain range of p. The certain range of p is determined by the dimension values of a Euclidean space (the domain) and an ellipsoid (the target space). The certain range of p is also bounded by the curvature values on an ellipsoid (that is, the ratio of the longest axis to the shortest axis). Regarding Liouville-type results for a p-stable map, our research finding on an ellipsoid is a generalization of mathematicians’ results on a sphere. Our result is also an extension of mathematicians’ Liouville-type results from a special ellipsoid with only one parameter to any ellipsoid with (n+1) parameters in the general setting.

Keywords: Bochner formula, Calculus Stokes' Theorem, Cauchy-Schwarz Inequality, first and second variation formulas, Liouville-type problem, p-harmonic map

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

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Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Alinka Molnár-Tóth, Tímea Tánczos, Regina Barna, Katalin Jakab, Péter Klivényi

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Supported by neuroscientific findings, the so-called Hub-and-Spoke model of the human semantic system is based on two subcomponents of semantic cognition, namely the semantic control process and semantic representation. Our semantic knowledge is multimodal in nature, as the knowledge system stored in relation to a conception is extensive and broad, while different aspects of the conception may be relevant depending on the purpose. The motivation of our research is to develop a new diagnostic measurement procedure based on the preservation of semantic representation, which is appropriate to the specificities of the Hungarian language and which can be used to compare the non-verbal semantic knowledge of healthy and aphasic persons. The development of the test will broaden the Hungarian clinical diagnostic toolkit, which will allow for more specific therapy planning. The sample of healthy persons (n=480) was determined by the last census data for the representativeness of the sample. Based on the concept of the Pyramids and Palm Tree Test, and according to the characteristics of the Hungarian language, we have elaborated a test based on different types of semantic information, in which the subjects are presented with three pictures: they have to choose the one that best fits the target word above from the two lower options, based on the semantic relation defined. We have measured 5 types of semantic knowledge representations: associative relations, taxonomy, motional representations, concrete as well as abstract verbs. As the first step in our data analysis, we examined the normal distribution of our results, and since it was not normally distributed (p < 0.05), we used nonparametric statistics further into the analysis. Using descriptive statistics, we could determine the frequency of the correct and incorrect responses, and with this knowledge, we could later adjust and remove the items of questionable reliability. The reliability was tested using Cronbach’s α, and it can be safely said that all the results were in an acceptable range of reliability (α = 0.6-0.8). We then tested for the potential gender differences using the Mann Whitney-U test, however, we found no difference between the two (p < 0.05). Likewise, we didn’t see that the age had any effect on the results using one-way ANOVA (p < 0.05), however, the level of education did influence the results (p > 0.05). The relationships between the subtests were observed by the nonparametric Spearman’s rho correlation matrix, showing statistically significant correlation between the subtests (p > 0.05), signifying a linear relationship between the measured semantic functions. A margin of error of 5% was used in all cases. The research will contribute to the expansion of the clinical diagnostic toolkit and will be relevant for the individualised therapeutic design of treatment procedures. The use of a non-verbal test procedure will allow an early assessment of the most severe language conditions, which is a priority in the differential diagnosis. The measurement of reaction time is expected to advance prodrome research, as the tests can be easily conducted in the subclinical phase.

Keywords: communication disorders, diagnostic toolkit, neurorehabilitation, semantic knowlegde

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Authors: Hasan Ziari, Hassan Fazaeli, Seyed Javad Vaziri Kang Olyaei, Asma Sadat Dabiri

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The presence of cracks in concrete pavements is a place for the ingression of corrosive substances, acids, oils, and water into the pavement and reduces its long-term durability and level of service. One of the causes of early cracks in concrete pavements is the plastic shrinkage. This shrinkage occurs due to the formation of negative capillary pressures after the equilibrium of the bleeding and evaporation rates at the pavement surface. These cracks form if the tensile stresses caused by the restrained shrinkage exceed the tensile strength of the concrete. Different climate conditions change the rate of evaporation and thus change the balance time of the bleeding and evaporation, which changes the severity of cracking in concrete. The present study examined the relationship between the balance time of bleeding and evaporation and the area of cracking in the concrete slabs using the standard method ASTM C1579 in 27 different environmental conditions by using continuous video recording and digital image analyzing. The results showed that as the evaporation rate increased and the balance time decreased, the crack severity significantly increased so that by reducing the balance time from the maximum value to its minimum value, the cracking area increased more than four times. It was also observed that the cracking area- balance time curve could be interpreted in three sections. An examination of these three parts showed that the combination of climate conditions has a significant effect on increasing or decreasing these two variables. The criticality of a single factor cannot cause the critical conditions of plastic cracking. By combining two mild environmental factors with a severe climate factor (in terms of surface evaporation rate), a considerable reduction in balance time and a sharp increase in cracking severity can be prevented. The results of this study showed that balance time could be an essential factor in controlling and predicting plastic shrinkage cracking in concrete pavements. It is necessary to control this factor in the case of constructing concrete pavements in different climate conditions.

Keywords: bleeding and cracking severity, concrete pavements, climate conditions, plastic shrinkage

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Authors: J. Das, T. S. Mahule, V. V. Srinivasu

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Electron spin resonance (ESR) study at 9.45 GHz and a field modulation frequency of 100Hz was performed on bulk polycrystalline samples of Mn:TM (Fe/Ni) and Mn:RE (Gd/Sm) co doped ZnO samples with composition Zn1-xMn:TM/RE)xO synthesised by solid state reaction route and sintered at 500 0C temperature. The room temperature microwave absorption data collected by sweeping the DC magnetic field from -500 to 9500 G for the Mn:Fe and Mn:Ni co doped ZnO samples exhibit a rarely reported non resonant low field absorption (NRLFA) in addition to a strong absorption at around 3350G, usually associated with ferromagnetic resonance (FMR) satisfying Larmor’s relation due to absorption in the full saturation state. Observed low field absorption is distinct to ferromagnetic resonance even at low temperature and shows hysteresis. Interestingly, it shows a phase opposite with respect to the main ESR signal of the samples, which indicates that the low field absorption has a minimum value at zero magnetic field whereas the ESR signal has a maximum value. The major resonance peak as well as the peak corresponding to low field absorption exhibit asymmetric nature indicating magnetic anisotropy in the sample normally associated with intrinsic ferromagnetism. Anisotropy parameter for Mn:Ni codoped ZnO sample is noticed to be quite higher. The g values also support the presence of oxygen vacancies and clusters in the samples. These samples have shown room temperature ferromagnetism in the SQUID measurement. However, in rare earth (RE) co doped samples (Zn1-x (Mn: Gd/Sm)xO), which show paramagnetic behavior at room temperature, the low field microwave signals are not observed. As microwave currents due to itinerary electrons can lead to ohmic losses inside the sample, we speculate that more delocalized 3d electrons contributed from the TM dopants facilitate such microwave currents leading to the loss and hence absorption at the low field which is also supported by the increase in current with increased micro wave power. Besides, since Fe and Ni has intrinsic spin polarization with polarisability of around 45%, doping of Fe and Ni is expected to enhance the spin polarization related effect in ZnO. We emphasize that in this case Fe and Ni doping contribute to polarized current which interacts with the magnetization (spin) vector and get scattered giving rise to the absorption loss.

Keywords: co-doping, electron spin resonance, hysteresis, non-resonant microwave absorption

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Authors: Majid Amidpour, Parisa Karimi, Marzieh Joda

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For the last few years, release of burned undesirable by-products has become a challenging issue in oil industries. Flaring, as one of the main sources of air contamination, involves detrimental and long-lasting effects on human health and is considered a substantial reason for energy losses worldwide. This research involves studying the implications of two main flare gas recovery methods at three oil refineries, all in Iran as the case I, case II, and case III in which the production capacities are increasing respectively. In the proposed methods, flare gases are converted into more valuable products, before combustion by the flare networks. The first approach involves collecting, compressing and converting the flare gas to smokeless fuel which can be used in the fuel gas system of the refineries. The other scenario includes utilizing the flare gas as a feed into liquefied petroleum gas (LPG) production unit already established in the refineries. The processes of these scenarios are simulated, and the capital investment is calculated for each procedure. The cumulative profits of the scenarios are evaluated using Net Present Value method. Furthermore, the sensitivity analysis based on total propane and butane mole fraction is carried out to make a rational comparison for LPG production approach, and the results are illustrated for different mole fractions of propane and butane. As the mole fraction of propane and butane contained in LPG differs in summer and winter seasons, the results corresponding to LPG scenario are demonstrated for each season. The results of the simulations show that cumulative profit in fuel gas production scenario and LPG production rate increase with the capacity of the refineries. Moreover, the investment return time in LPG production method experiences a decline, followed by a rising trend with an increase in C₃ and C₄ content. The minimum value of time return occurs at propane and butane sum concentration values of 0.7, 0.6, and 0.7 in case I, II, and III, respectively. Based on comparison of the time of investment return and cumulative profit, fuel gas production is the superior scenario for three case studies.

Keywords: flare gas reduction, liquefied petroleum gas, fuel gas, net present value method, sensitivity analysis

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Authors: Pranjal Srivastava, Piyali Sengupta

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The performance of marine drilling risers is crucial in the offshore oil and gas industry to ensure safe drilling operation with minimum downtime. Experimental investigations on marine drilling risers are limited in the literature owing to the expensive and exhaustive test setup required to replicate the realistic riser model and ocean environment in the laboratory. Therefore, this study presents an analytical model of marine drilling riser for determining its fragility under ocean environmental loading. In this study, the marine drilling riser is idealized as a continuous beam having a concentric circular cross-section. Hydrodynamic loading acting on the marine drilling riser is determined by Morison’s equations. By considering the equilibrium of forces on the marine drilling riser for the connected and normal drilling conditions, the governing partial differential equations in terms of independent variables z (depth) and t (time) are derived. Subsequently, the Runge Kutta method and Finite Difference Method are employed for solving the partial differential equations arising from the analytical model. The proposed analytical approach is successfully validated with respect to the experimental results from the literature. From the dynamic analysis results of the proposed analytical approach, the critical design parameters peak displacements, upper and lower flex joint rotations and von Mises stresses of marine drilling risers are determined. An extensive parametric study is conducted to explore the effects of top tension, drilling depth, ocean current speed and platform drift on the critical design parameters of the marine drilling riser. Thereafter, incremental dynamic analysis is performed to derive the fragility functions of shallow water and deep-water marine drilling risers under ocean environmental loading. The proposed methodology can also be adopted for downtime estimation of marine drilling risers incorporating the ranges of uncertainties associated with the ocean environment, especially at deep and ultra-deepwater.

Keywords: drilling riser, marine, analytical model, fragility

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Authors: Anna Curtin, Matthew Thibodeau, Heather Buckley

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Water scarcity is characterized by a lack of access to clean and affordable drinking water, as well as water for hygienic and economic needs. The amount of people effected by water scarcity is expected to increase in the coming years due to climate change, population growth, and pollution, amongst other things. In response, scientists are pursuing cost effective drinking water treatment methods, often with a focus on alternative water sources. Desalination of seawater via reverse osmosis is one promising alternative method. Desalination of seawater via reverse osmosis, however, is limited significantly by biofouling of the filtration membrane. Biofouling is the buildup of microorganisms in a biofilm at the water-membrane interface. It clogs the membrane, decreasing the efficiency of filtration, consequently increasing operational and maintenance costs. Although effective, existing chemical treatment methods can damage the membrane, decreasing the lifespan of the membrane; create antibiotic resistance; and cause harm to humans and the environment if they pass through the membrane into the permeate. The current project focuses on applying safer preservatives used in home and personal care products to RO membranes to investigate the biofouling treatment efficacy. Currently, many of these safer preservatives have only been tested on cells in planktonic phase in suspension cultures, not on cells in biofilms. The results of suspension culture tests are not applicable to biofouling scenarios because organisms in planktonic phase in suspension cultures exhibit different morphological, chemical, and metabolic characteristics than those in a biofilm. Testing antifoulant efficacy of safer preservatives on biofilms will provide more applicable results to biofouling on RO membranes. To do this, biofilms will be grown on 96-well-plates and minimum inhibitory concentrations (MIC90) and log-reductions will be calculated for various safer preservatives. Results from these tests will be used to guide doses for tests of safer preservatives in a bench-scale RO system.

Keywords: reverse osmosis, biofouling, preservatives, antimicrobial, safer alternative, green chemistry

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Authors: Nikhil Kumar, Asish Bandyopadhyay

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Laser welding process is a capable technology for forming the automobile, microelectronics, marine and aerospace parts etc. In the present work, a mathematical and statistical approach is adopted to study the laser welding of AISI 304 stainless steel. A robotic control 500 W pulsed Nd:YAG laser source with 1064 nm wavelength has been used for welding purpose. Butt joints are made. The effects of welding parameters, namely; laser power, scanning speed and pulse width on the seam width and depth of penetration has been investigated using the empirical models developed by response surface methodology (RSM). Weld quality is directly correlated with the weld geometry. Twenty sets of experiments have been conducted as per central composite design (CCD) design matrix. The second order mathematical model has been developed for predicting the desired responses. The results of ANOVA indicate that the laser power has the most significant effect on responses. Microstructural analysis as well as hardness of the selected weld specimens has been carried out to understand the metallurgical and mechanical behaviour of the weld. Average micro-hardness of the weld is observed to be higher than the base metal. Higher hardness of the weld is the resultant of grain refinement and δ-ferrite formation in the weld structure. The result suggests that the lower line energy generally produce fine grain structure and improved mechanical properties than the high line energy. The combined effects of input parameters on responses have been analyzed with the help of developed 3-D response surface and contour plots. Finally, multi-objective optimization has been conducted for producing weld joint with complete penetration, minimum seam width and acceptable welding profile. Confirmatory tests have been conducted at optimum parametric conditions to validate the applied optimization technique.

Keywords: ANOVA, laser welding, modeling and optimization, response surface methodology

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Authors: Inyeol Paik, Ah-Ryang Kim

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In this research, a statistical analysis is carried out to examine the statistical properties of the formula given in the design code for concrete structures. The design formulas of the Korea highway bridge design code - the limit state design method (KHBDC) which is the current national bridge design code and the design code for concrete structures by Korea Concrete Institute (KCI) are applied for the analysis. The safety levels provided by the strength formulas of the design codes are defined based on the probabilistic and statistical theory.KHBDC is a reliability-based design code. The load and resistance factors of this code were calibrated to attain the target reliability index. It is essential to define the statistical properties for the design formulas in this calibration process. In general, the statistical characteristics of a member strength are due to the following three factors. The first is due to the difference between the material strength of the actual construction and that used in the design calculation. The second is the difference between the actual dimensions of the constructed sections and those used in design calculation. The third is the difference between the strength of the actual member and the formula simplified for the design calculation. In this paper, the statistical study is focused on the third difference. The formulas for calculating the shear strength of concrete members are presented in different ways in KHBDC and KCI. In this study, the statistical properties of design formulas were obtained through comparison with the database which comprises the experimental results from the reference publications. The test specimen was either reinforced with the shear stirrup or not. For an applied database, the bias factor was about 1.12 and the coefficient of variation was about 0.18. By applying the statistical properties of the design formula to the reliability analysis, it is shown that the resistance factors of the current design codes satisfy the target reliability indexes of both codes. Also, the minimum resistance factors of the KHBDC which is written in the material resistance factor format and KCE which is in the member resistance format are obtained and the results are presented. A further research is underway to calibrate the resistance factors of the high strength and high-performance concrete design guide.

Keywords: concrete design code, reliability analysis, resistance factor, shear strength, statistical property

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Authors: Fariborz Shekari, Abdollah Javanmard, Amin Abbasi

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A pot experiment conducted to evaluate the response of two red bean cultivars, Sayad and Derakhshan, to water deficit stress during post-flowering growth stage and recovery potential of plants after stress. Treatments were included regular irrigation or control, water deficit during flowering stage, water deficit during pod formation and water deficit during pod filling period. Results showed that plant height had positive effects on yield of cultivars so that, the tall cultivar, ‘Sayad’, had higher yields. Stress application during flowering stage showed the highest negative impact on plant height and subsequently yield. The longest and the higher number of pods as well as the greatest number of seeds in pods were recorded in control treatment in ‘Sayad’. Stress application during pod formation resulted in the minimum amount of all studied traits in both cultivars. Stress encountered during seed filling period had the least effect on number and length of pods and seed/pod. However, 100 seeds weight significantly decreased. The highest amount for 100 seeds weight was record in control plants in ‘Derakhshan’. Under all treatments, ‘Sayad’ had higher biologic and seed yield compared to ‘Derakhshan’. The least amount of yield was recorded during stress application in pod formation and flowering period for ‘Sayad’ and ‘Derakhshan’ respectively. Harvest index of ‘Sayad’ was more affect by stress application. Data related to photosynthetic rate showed that during stress application, ‘Derakhshan’ owned rapid decline in photosynthesis. Beyond stress alleviation and onset of irrigation, recovery potential of ‘Sayad’ was higher than ‘Derakhshan’ and this cultivar was able to rapidly restore the photosynthesis rate of stress faced plants near control ones. In total, stress had lower impacts on photosynthetic rate of ‘Sayad’ cultivar.

Keywords: common bean, water stress, yield, yield components, photosynthetic rate

Procedia PDF Downloads 293

Authors: Ghassan Kbar, Shady Aly, Ibrahim Alsharawy, Akshay Bhatia, Nur Alhasan, Ronaldo Enriquez

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The Smart Help for persons with disability (PWD) is a part of the project SMARTDISABLE which aims to develop relevant solution for PWD that target to provide an adequate workplace environment for them. It would support PWD needs smartly through smart help to allow them access to relevant information and communicate with other effectively and flexibly, and smart editor that assist them in their daily work. It will assist PWD in knowledge processing and creation as well as being able to be productive at the work place. The technical work of the project involves design of a technological scenario for the Ambient Intelligence (AmI) - based assistive technologies at the workplace consisting of an integrated universal smart solution that suits many different impairment conditions and will be designed to empower the Physically disabled persons (PDP) with the capability to access and effectively utilize the ICTs in order to execute knowledge rich working tasks with minimum efforts and with sufficient comfort level. The proposed technology solution for PWD will support voice recognition along with normal keyboard and mouse to control the smart help and smart editor with dynamic auto display interface that satisfies the requirements for different PWD group. In addition, a smart help will provide intelligent intervention based on the behavior of PWD to guide them and warn them about possible misbehavior. PWD can communicate with others using Voice over IP controlled by voice recognition. Moreover, Auto Emergency Help Response would be supported to assist PWD in case of emergency. This proposed technology solution intended to make PWD very effective at the work environment and flexible using voice to conduct their tasks at the work environment. The proposed solution aims to provide favorable outcomes that assist PWD at the work place, with the opportunity to participate in PWD assistive technology innovation market which is still small and rapidly growing as well as upgrading their quality of life to become similar to the normal people at the workplace. Finally, the proposed smart help solution is applicable in all workplace setting, including offices, manufacturing, hospital, etc.

Keywords: ambient intelligence, ICT, persons with disability PWD, smart application, SHW

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Authors: Z. Kolacinski, L. Szymanski. G. Raniszewski, D. Koza, L. Pietrzak

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Magnetic Bio-Nano-Fluid (BNF) can be composed of a buffer fluid such as plasma and magnetic nanoparticles such as iron, nickel, cobalt and their oxides. However iron is one of the best elements for magnetization by electromagnetic radiation. It can be used as a tool for medical diagnosis and treatment. Radio frequency (RF) radiation is able to heat iron nanoparticles due to magnetic hysteresis. Electromagnetic heating of iron nanoparticles and ferro-fluids BNF can be successfully used for non-invasive thermal ablation of cancer cells. Moreover iron atoms can be carried by carbon nanotubes (CNTs) if iron is used as catalyst for CNTs synthesis. Then CNTs became the iron containers and they screen the iron content against oxidation. We will present a method of CNTs addressing to the required cells. For thermal ablation of cancer cells we use radio frequencies for which the interaction with human body should be limited to minimum. Generally, the application of RF energy fields for medical treatment is justified by deep tissue penetration. The highly iron doped CNTs as the carriers creating magnetic fluid will be presented. An excessive catalyst injection method using electrical furnace and microwave plasma reactor will be presented. This way it is possible to grow the Fe filled CNTs on a moving surface in continuous synthesis process. This also allows producing uniform carpet of the Fe filled CNTs carriers. For the experimental work targeted to cell ablation we used RF generator to measure the increase in temperature for some samples like: solution of Fe2O3 in BNF which can be plasma-like buffer, solutions of pure iron of different concentrations in plasma-like buffer and in buffer used for a cell culture, solutions of carbon nanotubes (MWCNTs) of different concentrations in plasma-like buffer and in buffer used for a cell culture. Then the targeted therapies which can be effective if the carriers are able to distinguish the difference between cancerous and healthy cell’s physiology are considered. We have developed an approach based on ligand-receptor or antibody-antigen interactions for the case of colon cancer.

Keywords: cancer treatment, carbon nano tubes, drag delivery, hyperthermia, iron

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Authors: Ahmed E. Hodaib, Muhammed A. Hashem

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High-speed transportation has become a growing concern. To increase high-speed efficiencies and minimize power consumption of a vehicle, we need to eliminate the friction with the ground and minimize the aerodynamic drag acting on the vehicle. Due to the complexity and high power requirements of electromagnetic levitation, we make use of the air in front of the capsule, that produces the majority of the drag, to compress it in two phases and inject a proportion of it through small nozzles to make a high-pressure air cushion to levitate the capsule. The tube is partially-evacuated so that the air pressure is optimized for maximum compressor effectiveness, optimum tube size, and minimum vacuum pump power consumption. The total relative mass flow rate of the tube air is divided into two fractions. One is by-passed to flow over the capsule body, ensuring that no chocked flow takes place. The other fraction is sucked by the compressor where it is diffused to decrease the Mach number (around 0.8) to be suitable for the compressor inlet. The air is then compressed and intercooled, then split. One fraction is expanded through a tail nozzle to contribute to generating thrust. The other is compressed again. Bleed from the two compressors is used to maintain a constant air pressure in an air tank. The air tank is used to supply air for levitation. Dividing the total mass flow rate increases the achievable speed (Kantrowitz limit), and compressing it decreases the blockage of the capsule. As a result, the aerodynamic drag on the capsule decreases. As the tube pressure decreases, the drag decreases and the capsule power requirements decrease, however, the vacuum pump consumes more power. That’s why Design optimization techniques are to be used to get the optimum values for all the design variables given specific design inputs. Aerodynamic shape optimization, Capsule and tube sizing, compressor design, diffuser and nozzle expander design and the effect of the air bearing on the aerodynamics of the capsule are to be considered. The variations of the variables are to be studied for the change of the capsule velocity and air pressure.

Keywords: tube-capsule, hyperloop, aerodynamic design optimization, air compressor, air bearing

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Authors: N. Tochukwu, M. Mukhopadhyay, A. Mohamed

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It is no new that Nigeria faces a continual power shortage problem due to its vast population power demand and heavy reliance on nonrenewable forms of energy such as thermal power or fossil fuel. Many researchers have recommended using geothermal energy as an alternative; however, Past studies focus on the geophysical & geochemical investigation of this energy in the sedimentary and basement complex; only a few studies incorporated the remote sensing methods. Therefore, in this study, the preliminary examination of geothermal resources in the Middle Benue was carried out using satellite imagery in ArcMap. Landsat 8 scene (TIR, NIR, Red spectral bands) was used to estimate the Land Surface Temperature (LST). The Maximum Likelihood Classification (MLC) technique was used to classify sites with very low, low, moderate, and high LST. The intermediate and high classification happens to be possible geothermal zones, and they occupy 49% of the study area (38077km2). Riverline were superimposed on the LST layer, and the identification tool was used to locate high temperate sites. Streams that overlap on the selected sites were regarded as geothermal springs as. Surprisingly, the LST results show lower temperatures (<36°C) at the famous thermal springs (Awe & Wukari) than some unknown rivers/streams found in Kwande (38°C), Ussa, (38°C), Gwer East (37°C), Yola Cross & Ogoja (36°C). Studies have revealed that temperature increases with depth. However, this result shows excellent geothermal resources potential as it is expected to exceed the minimum geothermal gradient of 25.47 with an increase in depth. Therefore, further investigation is required to estimate the depth of the causative body, geothermal gradients, and the sustainability of the reservoirs by geophysical and field exploration. This method has proven to be cost-effective in locating geothermal resources in the study area. Consequently, the same procedure is recommended to be applied in other regions of the Precambrian basement complex and the sedimentary basins in Nigeria to save a preliminary field survey cost.

Keywords: ArcMap, geothermal resources, Landsat 8, LST, thermal springs, MLC

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Authors: Kevin Syam, Devendra K. Chauhan, Mandeep Singh Dhillon

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Background: The posterior horn of medial meniscus (PHMM) is a secondary stabilizer against anterior translation of tibia. Cadaveric studies have revealed increased strain on the ACL graft and greater instrumented laxity in Posterior horn deficient knees. Clinical studies have shown higher prevalence of radiological OA after ACL reconstruction combined with menisectomy. However, functional outcomes in ACL reconstructed knee in the absence of Posterior horn is less discussed, and specific role of posterior horn is ill-documented. This study evaluated functional and radiological outcomes in posterior horn preserved and posterior horn sacrificed ACL reconstructed knees. Materials: Of the 457 patients who had ACL reconstruction done over a 6 year period, 77 cases with minimum follow up of 18 months were included in the study after strict exclusion criteria (associated lateral meniscus injury, other ligamentous injuries, significant cartilage degeneration, repeat injury and contralateral knee injuries were excluded). 41 patients with intact menisci were compared with 36 patients with absent posterior horn of medial meniscus. Radiological and clinical tests for instability were conducted, and knees were evaluated using subjective International Knee Documentation Committee (IKDC) score and the Orthopadische Arbeitsgruppe Knie score (OAK). Results: We found a trend towards significantly better overall outcome (OAK) in cases with intact PHMM at average follow-up of 43.03 months (p value 0.082). Cases with intact PHMM had significantly better objective stability (p value 0.004). No significant differences were noted in the subjective IKDC score (p value 0.526) and the functional OAK outcome (category D) (p value 0.363). More cases with absent posterior horn had evidence of radiological OA (p value 0.022) even at mid-term follow-up. Conclusion: Even though the overall OAK and subjective IKDC scores did not show significant difference between the two subsets, the poorer outcomes in terms of objective stability and radiological OA noted in the absence of PHMM, indicates the importance of preserving this important part of the meniscus.

Keywords: ACL, functional outcome, knee, posterior of medial meniscus

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Authors: Rana Tabassum, Ravi Kant, Banshi D. Gupta

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Malic acid is an extensively distributed organic acid in numerous horticultural products in minute amounts which significantly contributes towards taste determination by balancing sugar and acid fractions. An enhanced concentration of malic acid is utilized as an indicator of fruit maturity. In addition, malic acid is also a crucial constituent of several cosmetics and pharmaceutical products. An efficient detection and quantification protocol for malic acid is thus highly demanded. In this study, we report a novel detection scheme for malic acid by synergistically collaborating fiber optic surface plasmon resonance (FOSPR) and distinctive features of nanomaterials favorable for sensing applications. The design blueprint involves the deposition of an assembly of malate dehydrogenase enzyme entrapped in ZnO nanowires forming the sensing route over silver coated central unclad core region of an optical fiber. The formation and subsequent decomposition of the enzyme-analyte complex on exposure of the sensing layer to malic acid solutions of diverse concentration results in modification of the dielectric function of the sensing layer which is manifested in terms of shift in resonance wavelength. Optimization of experimental variables such as enzyme concentration entrapped in ZnO nanowires, dip time of probe for deposition of sensing layer and working pH range of the sensing probe have been accomplished through SPR measurements. The optimized sensing probe displays high sensitivity, broad working range and a minimum limit of detection value and has been successfully tested for malic acid determination in real samples of fruit juices. The current work presents a novel perspective towards malic acid determination as the unique and cooperative combination of FOSPR and nanomaterials provides myriad advantages such as enhanced sensitivity, specificity, compactness together with the possibility of online monitoring and remote sensing.

Keywords: surface plasmon resonance, optical fiber, sensor, malic acid

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Authors: Adeiza Matthew, Oluwadamilola Abubakar

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Wood energy, also known as wood fuel, is a renewable energy source that is derived from woody biomass, which is organic matter that is harvested from forests, woodlands, and other lands. Woody biomass includes trees, branches, twigs, and other woody debris that can be used as fuel. Wood energy can be classified based on its sources, such as trees outside forests, residues from wood harvesting and conversion, and energy plantations. There are several policy frameworks that support the use of wood energy, including participatory forest management and agroforestry. These policies aim to promote the sustainable use of woody biomass as a source of energy while also protecting forests and wildlife habitats. There are several options for using wood as a fuel, including central heating systems, pellet-based systems, wood chip-based systems, log boilers, fireplaces, and stoves. Each of these options has its own benefits and drawbacks, and the most appropriate option will depend on factors such as the availability of woody biomass, the heating needs of the household or facility, and the local climate. In order to use wood as a fuel, it must be harvested and stored properly. Hardwood or softwood can be used as fuel, and the heating value of firewood depends on the species of tree and the degree of moisture content. Proper harvesting and storage of wood can help to minimize environmental impacts and improve wildlife habitats. The use of wood energy has several environmental impacts, including the release of greenhouse gases during combustion and the potential for air pollution from combustion by-products. However, wood energy can also have positive environmental impacts, such as the sequestration of carbon in trees and the reduction of reliance on fossil fuels. The regulation and legislation of wood energy vary by country and region, and there is an ongoing debate about the potential use of wood energy in renewable energy technologies. Wood energy is a renewable energy source that can be used to generate electricity, heat, and transportation fuels. Woody biomass is abundant and widely available, making it a potentially significant source of energy for many countries. The use of wood energy can create local economic and employment opportunities, particularly in rural areas. Wood energy can be used to reduce reliance on fossil fuels and reduce greenhouse gas emissions. Properly managed forests can provide a sustained supply of woody biomass for energy, helping to reduce the risk of deforestation and habitat loss. Wood energy can be produced using a variety of technologies, including direct combustion, co-firing with fossil fuels, and the production of biofuels. The environmental impacts of wood energy can be minimized through the use of best practices in harvesting, transportation, and processing. Wood energy is regulated and legislated at the national and international levels, and there are various standards and certification systems in place to promote sustainable practices. Wood energy has the potential to play a significant role in the transition to a low-carbon economy and the achievement of climate change mitigation goals.

Keywords: biomass, timber, charcoal, firewood

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Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

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Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

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Authors: Aysen Caliskan, Hanzade Haykiri-Acma, Serdar Yaman

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Co-firing of coal and biomass blends is an effective method to reduce carbon dioxide emissions released by burning coals, thanks to the carbon-neutral nature of biomass. Besides, usage of biomass that is renewable and sustainable energy resource mitigates the dependency on fossil fuels for power generation. However, most of the biomass species has negative aspects such as low calorific value, high moisture and volatile matter contents compared to coal. Torrefaction is a promising technique in order to upgrade the fuel properties of biomass through thermal treatment. That is, this technique improves the calorific value of biomass along with serious reductions in the moisture and volatile matter contents. In this context, several woody biomass materials including Rhododendron, hybrid poplar, and ash-tree were subjected to torrefaction process in a horizontal tube furnace at 200°C under nitrogen flow. In this way, the solid residue obtained from torrefaction that is also called as 'biochar' was obtained and analyzed to monitor the variations taking place in biomass properties. On the other hand, some Turkish lignites from Elbistan, Adıyaman-Gölbaşı and Çorum-Dodurga deposits were chosen as coal samples since these lignites are of great importance in lignite-fired power stations in Turkey. These lignites were blended with the obtained biochars for which the blending ratio of biochars was kept at 10 wt% and the lignites were the dominant constituents in the fuel blends. Burning tests of the lignites, biomasses, biochars, and blends were performed using a thermogravimetric analyzer up to 900°C with a heating rate of 40°C/min under dry air atmosphere. Based on these burning tests, properties relevant to burning characteristics such as the burning reactivity and burnout yields etc. could be compared to justify the effects of torrefaction and blending. Besides, some characterization techniques including X-Ray Diffraction (XRD), Fourier Transform Infrared (FTIR) spectroscopy and Scanning Electron Microscopy (SEM) were also conducted for the untreated biomass and torrefied biomass (biochar) samples, lignites and their blends to examine the co-combustion characteristics elaborately. Results of this study revealed the fact that blending of lignite with 10 wt% biochar created synergistic behaviors during co-combustion in comparison to the individual burning of the ingredient fuels in the blends. Burnout and ignition performances of each blend were compared by taking into account the lignite and biomass structures and characteristics. The blend that has the best co-combustion profile and ignition properties was selected. Even though final burnouts of the lignites were decreased due to the addition of biomass, co-combustion process acts as a reasonable and sustainable solution due to its environmentally friendly benefits such as reductions in net carbon dioxide (CO2), SOx and hazardous organic chemicals derived from volatiles.

Keywords: burnout performance, co-combustion, thermal analysis, torrefaction pretreatment

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Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

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Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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Authors: Lai Peng, Cristina Pintucci, Dries Seuntjens, José Carvajal-Arroyo, Siegfried Vlaeminck

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Economic incentives drive the implementation of short-cut nitrogen removal processes such as nitritation/denitritation (Nit/DNit) to manage nitrogen in waste streams devoid of biodegradable organic carbon. However, as any biological nitrogen removal process, the potent greenhouse gas nitrous oxide (N2O) could be emitted from Nit/DNit. Challenges remain in understanding the fundamental mechanisms and development of engineered mitigation strategies for N2O production. To provide answers, this work focuses on manure as a model, the biggest wasted nitrogen mass flow through our economies. A sequencing batch reactor (SBR; 4.5 L) was used treating the centrate (centrifuge supernatant; 2.0 ± 0.11 g N/L of ammonium) from an anaerobic digester processing mainly pig manure, supplemented with a co-substrate. Glycerin was used as external carbon source, a by-product of vegetable oil. Out-selection of nitrite oxidizing bacteria (NOB) was targeted using a combination of low dissolved oxygen (DO) levels (down to 0.5 mg O2/L), high temperature (35ºC) and relatively high free ammonia (FA) (initially 10 mg NH3-N/L). After reaching steady state, the process was able to remove 100% of ammonium with minimum nitrite and nitrate in the effluent, at a reasonably high nitrogen loading rate (0.4 g N/L/d). Substantial N2O emissions (over 15% of the nitrogen loading) were observed at the baseline operational condition, which were even increased under nitrite accumulation and a low organic carbon to nitrogen ratio. Yet, higher DO (~2.2 mg O2/L) lowered aerobic N2O emissions and weakened the dependency of N2O on nitrite concentration, suggesting a shift of N2O production pathway at elevated DO levels. Limiting the greenhouse gas emissions (environmental protection) from such a system could be substantially minimized by increasing the external carbon dosage (a cost factor), but also through the implementation of an intermittent aeration and feeding strategy. Promising steps forward have been presented in this abstract, yet at the conference the insights of ongoing experiments will also be shared.

Keywords: mitigation, nitrous oxide, nitritation/denitritation, pig manure

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Authors: Shaun G. Abbott, Rebecca C. Reynolds, James B. Etter, John B. F. de Wit

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The benefits of physical activity (PA) on health are well documented. Low socioeconomic status (SES) is associated with poor health, with PA a suggested mediator. Pedometers and accelerometers offer an effective behavior change tool to increase PA levels. While the role of pedometer and accelerometer use in increasing PA is recognized in many populations, little is known in low-SES groups. We are aiming to assess the effectiveness of pedometer- and accelerometer-based interventions for increasing PA step count and improving subsequent health outcomes among low-SES groups of high-income countries. Medline, Embase, PsycINFO, CENTRAL and SportDiscus databases were searched to identify articles published before 10th July, 2015; using search terms developed from previous systematic reviews. Inclusion criteria are: low-SES participants classified by income, geography, education, occupation or ethnicity; study duration minimum 4 weeks; an intervention and control group; wearing of an unsealed pedometer or accelerometer to objectively measure PA as step counts per day for the duration of the study. We retrieved 2,142 articles from our database searches, after removal of duplicates. Two investigators independently reviewed titles and abstracts of these articles (50% each) and a combined 20% sample were reviewed to account for inter-assessor variation. We are currently verifying the full texts of 430 articles. Included studies will be critically appraised for risk of bias using guidelines suggested by the Cochrane Public Health Group. Two investigators will extract data concerning the intervention; study design; comparators; steps per day; participants; context and presence or absence of obesity and/or chronic disease. Heterogeneity amongst studies is anticipated, thus a narrative synthesis of data will be conducted with the simplification of selected results into percentage increases from baseline to allow for between-study comparison. Results will be presented at the conference in December if selected.

Keywords: accelerometer, pedometer, physical activity, socioeconomic, step count

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Authors: Sandra Young

Abstract:

The biodiversity literature is vast and heterogeneous. In today’s data age, numbers of data integration and standardisation initiatives aim to facilitate simultaneous access to all the literature across biodiversity domains for research and forecasting purposes. Ontologies are being used increasingly to organise this information, but the rationalisation intrinsic to ontologies can hit obstacles when faced with the intrinsic fluidity and inconsistency found in the domains comprising biodiversity. Essentially the problem is a conceptual one: biological taxonomies are formed on the basis of specific, physical specimens yet nomenclatural rules are used to provide labels to describe these physical objects. These labels are ambiguous representations of the physical specimen. An example of this is with the genus Melpomene, the scientific nomenclatural representation of a genus of ferns, but also for a genus of spiders. The physical specimens for each of these are vastly different, but they have been assigned the same nomenclatural reference. While there is much research into the conceptual stability of the taxonomic concept versus the nomenclature used, to the best of our knowledge as yet no research has looked empirically at the literature to see the conceptual plurality or singularity of the use of these species’ names, the linguistic representation of a physical entity. Language itself uses words as symbols to represent real world concepts, whether physical entities or otherwise, and as such lexicography has a well-founded history in the conceptual mapping of words in context for dictionary making. This makes it an ideal candidate to explore this problem. The lexicographic approach uses corpus-based analysis to look at word use in context, with a specific focus on collocated word frequencies (the frequencies of words used in specific grammatical and collocational contexts). It allows for inconsistencies and contradictions in the source data and in fact includes these in the word characterisation so that 100% of the available evidence is counted. Corpus analysis is indeed suggested as one of the ways to identify concepts for ontology building, because of its ability to look empirically at data and show patterns in language usage, which can indicate conceptual ideas which go beyond words themselves. In this sense it could potentially be used to identify if the hierarchical structures present within the empirical body of literature match those which have been identified in ontologies created to represent them. The first stages of this research have revealed a hierarchical structure that becomes apparent in the biodiversity literature when annotating scientific species’ names, common names and more general names as classes, which will be the focus of this paper. The next step in the research is focusing on a larger corpus in which specific words can be analysed and then compared with existing ontological structures looking at the same material, to evaluate the methods by means of an alternative perspective. This research aims to provide evidence as to the validity of the current methods in knowledge representation for biological entities, and also shed light on the way that scientific nomenclature is used within the literature.

Keywords: ontology, biodiversity, lexicography, knowledge representation, corpus linguistics

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