Search results for: industrial scale nano-CaCO3

Authors: Meshari Al-Harbi

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A comparative area-season-elemental-wise time series analysis by Dust Track monitor (2012-2013) revealed high PM10 dispersion in the outdoor environment in the sequence of industrial> express highways>residential>open areas. Time series analysis from 7AM-6AM (until next day), 30d (monthly), 3600sec. (for any given period of a month), and 12 months (yearly) showed peak PM10 dispersion during 1AM-7AM, 1d-4d and 25d-31d of every month, 1500-3600 with the exception in PM10 dispersion in residential areas, and in the months-March to June, respectively. This time-bound PM10 dispersion suggests the primary influence of human activities (peak mobility and productivity period for a given time frame) besides the secondary influence of meteorological parameters (high temperature and wind action) and, occasional dust storms. Whereas, gravimetric analysis reveals the influence of precipitation, low temperature and low volatility resulting high trace metals in PM10 during winter than in summer and primarily attributes to the influence of nature besides, the secondary attributes of smoke stack emission from various industries and automobiles. Furthermore, our study recommends residents to limit outdoor air pollution exposures and take precautionary measures to inhale PM10 pollutants from the atmosphere.

Keywords: aerosol, pollution, respirable particulates, trace-metals

Procedia PDF Downloads 307

Authors: Hussien Ali, Mesfin Menza, Fitsum Hagos, Amare Haileslassie

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Climate change has perverse effects on agricultural productivity and natural resource base, negatively affecting the well-being of the households and communities. The government and NGOs promote climate smart agricultural (CSA) practices to help farmers adapt to and mitigate the negative effects of climate change. This study aims to identify widely available CSA practices and examine their impacts on food security and multi-dimensional poverty of rural farm households in the Central Rift Valley, Ethiopia. Using three-stage proportional to size sampling procedure, the study randomly selected 278 households from two kebeles from four districts each. A cross-sectional data of 2020/21 cropping season was collected using structured and pretested survey questionnaire. Food consumption score, dietary diversity score, food insecurity experience scale, and multidimensional poverty index were calculated to measure households’ welfare indicators. Multinomial endogenous switching regression model was used to assess average treatment effects of CSA on these outcome indicators on adopter and non-adopter households. The results indicate that the widely adopted CSA practices in the area are conservation agriculture, soil fertility management, crop diversification, and small-scale irrigation. Adopter households have, on average, statistically higher food consumption score, dietary diversity score and lower food insecurity access scale than non-adopters. Moreover, adopter households, on average, have lower deprivation score in multidimensional poverty compared to non-adopter households. Up scaling the adoption of CSA practices through the improvement of households’ implementation capacity and better information, technical advice, and innovative financing mechanisms is advised. Up scaling CSA practices can further promote achieving global goals such as SDG 1, SDG 2, and SDG 13 targets, aimed to end poverty and hunger and mitigate the adverse impacts of climate change, respectively.

Keywords: climate-smart agriculture, food security, multidimensional poverty, upscaling CSA, Ethiopia

Procedia PDF Downloads 90

Authors: Cristina Costescu, Carmen David, Adrian Roșan

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Executive functions (EF) and emotion regulation strategies are processes that allow individuals to function in an adaptative way and to be goal-oriented, which is essential for success in daily living activities, at school, or in social contexts. The Emotion Regulation and Executive Functioning Scale for Children and Adolescents (REMEX) represents an empirically based tool (based on the model of EF developed by Diamond) for evaluating significant dimensions of child and adolescent EFs and emotion regulation strategies, mainly in school contexts. The instrument measures the following dimensions: working memory, inhibition, cognitive flexibility, executive attention, planning, emotional control, and emotion regulation strategies. Building the instrument involved not only a top-down process, as we selected the content in accordance with prominent models of FE, but also a bottom-up one, as we were able to identify valid contexts in which FE and ER are put to use. For the construction of the instrument, we implemented three focus groups with teachers and other professionals since the aim was to develop an accurate, objective, and ecological instrument. We used the focus group method in order to address each dimension and to yield a bank of items to be further tested. Each dimension is addressed through a task that the examiner will apply and through several items derived from the main task. For the validation of the instrument, we plan to use item response theory (IRT), also known as the latent response theory, that attempts to explain the relationship between latent traits (unobservable cognitive processes) and their manifestations (i.e., observed outcomes, responses, or performance). REMEX represents an ecological scale that integrates a current scientific understanding of emotion regulation and EF and is directly applicable to school contexts, and it can be very useful for developing intervention protocols. We plan to test his convergent validity with the Childhood Executive Functioning Inventory (CHEXI) and Emotion Dysregulation Inventory (EDI) and divergent validity between a group of typically developing children and children with neurodevelopmental disorders, aged between 6 and 9 years old. In a previous pilot study, we enrolled a sample of 40 children with autism spectrum disorders and attention-deficit/hyperactivity disorder aged 6 to 12 years old, and we applied the above-mentioned scales (CHEXI and EDI). Our results showed that deficits in planning, bebavior regulation, inhibition, and working memory predict high levels of emotional reactivity, leading to emotional and behavioural problems. Considering previous results, we expect our findings to provide support for the validity and reliability of the REMEX version as an ecological instrument for assessing emotion regulation and EF in children and for key features of its uses in intervention protocols.

Keywords: executive functions, emotion regulation, children, item response theory, focus group

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Authors: Nour El Houda Bensiradj, Nafila Zouaghi, Taha Bensiradj

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The pollution of water resources is characterized by the presence of microorganisms, chemicals, or industrial waste. Generally, this waste generates effluents containing large quantities of heavy metals, making the water unsuitable for consumption and causing the death of aquatic life and associated biodiversity. Currently, it is very important to assess the impact of heavy metals in water pollution as well as the processes for treating and reducing them. Among the methods of water treatment and disinfection, we mention the complexation of metal ions using ligands which serve to precipitate and subsequently eliminate these ions. In this context, we are interested in the study of complexes containing heavy metals such as zinc, nickel, and cadmium, which are present in several industrial discharges and are discharged into water sources. We will use the ligands of triethanolamine (TEA) and nitrilotriacetic acid (NTA). The theoretical study is based on molecular modeling, using the density functional theory (DFT) implemented in the Gaussian 09 program. The geometric and energetic properties of the above complexes will be calculated. Spectral properties such as infrared, as well as reactivity descriptors, and thermodynamic properties such as enthalpy and free enthalpy will also be determined.

Keywords: heavy metals, NTA, TEA, DFT, IR, reactivity descriptors

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Authors: Nutcha Thianbut

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In the petroleum drilling industry, besides oil and gas, water is also produced from petroleum production. which will have oil droplets dispersed in the water as an emulsion. Commonly referred to as produced water, most industrial water-based produced water methods use the method of pumping water back into wells or catchment areas. because it cannot be utilized further, but in the compression of water each time, the cost is quite high. And the survey found that the amount of water from the petroleum production process has increased every year. In this research, we would like to study the removal of oil in produced water by the Coalescer device using fibers from agricultural waste as an intermediary. As an alternative to reduce the cost of water management in the petroleum drilling industry. The objectives of this research are 1. To study the fiber pretreatment by chemical process for the efficiency of oil-water separation 2. To study and design the fiber-packed coalescer device to destroy the emulsion of crude oil in water. 3. To study the working conditions of coalescer devices in emulsion destruction. using a fiber medium. In this research, the experiment was divided into two parts. The first part will study the absorbency of fibers. It compares untreated fibers with chemically treated alkaline fibers that change over time as well as adjusting the amount of fiber on the absorbency of the fiber and the second part will study the separation of oil from produced water by Coalescer equipment using fiber as medium to study the optimum condition of coalescer equipment for further development and industrial application.

Keywords: produced water, fiber, surface modification, coalescer

Procedia PDF Downloads 166

Authors: Negin Bayat, Nahid HasanZadeh

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Effluents of different industries such as metalworking, battery industry, mining, including heavy metal are considered problematic issues for both humans and the environment. These heavy metals include cadmium, copper, zinc, nickel, chromium, cyanide, lead, etc. Different physicochemical and biological methods are used to remove heavy metals, such as sedimentation, coagulation, flotation, chemical precipitation, filtration, membrane processes (reverse osmosis and nanofiltration), ion exchange, biological methods, adsorption with activated carbon, etc. These methods are generally either expensive or ineffective. In recent years, considerable attention has been given to the removal of heavy metal ions from solution by absorption using discarded and low-cost materials. In this study, nickel removal using an adsorption process by eucalyptus powdered leaves and poplar ash was investigated. This is an applied study. The effect of various parameters on metal removal, such as pH, amount of adsorbent, contact time, and stirring speed, was studied using a discontinuous method. This research was conducted in aqueous solutions on the laboratory scale. Then, optimum absorption conditions were obtained. Then, the study was conducted on real wastewater samples. In addition, the nickel concentration in the wastewater before and after the absorption process was measured. In all experiments, the remaining nickel was measured using an atomic absorption spectrometry device at 382 nm wavelength after an appropriate time and filtration. The results showed that increasing both adsorbent and pH parameters increase the metal removal rate. Nickel removal increased at the first 60 minutes. Then, the absorption rate remained constant and reached equilibrium. A desired removal rate with 40 mg in 100 ml adsorbent solution at pH = 9.5 was observed. According to the obtained results, the best absorption rate was observed at 40 mg dose using a combination of eucalyptus leaves and poplar ash in this study, which was equal to 99.76%. Thus, this combined method can be used as an inexpensive and effective absorbent for the removal of nickel from aqueous solutions.

Keywords: absorption, wastewater, nickel, poplar ash, eucalyptus leaf, treatment

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Authors: Alberto Fina, Samuele Colonna, Maria del Mar Bernal, Orietta Monticelli, Mauro Tortello, Renato Gonnelli, Julio Gomez, Chiara Novara, Guido Saracco

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Thermally conductive polymer nanocomposites are of high interest for several applications including low-temperature heat recovery, heat exchangers in a corrosive environment and heat management in electronics and flexible electronics. In this paper, the preparation of thermally conductive nanocomposites exploiting graphene-related materials is addressed, along with their thermal characterization. In particular, correlations between 1- chemical and physical features of the nanoflakes and 2- processing conditions with the heat conduction properties of nanocomposites is studied. Polymers are heat insulators; therefore, the inclusion of conductive particles is the typical solution to obtain a sufficient thermal conductivity. In addition to traditional microparticles such as graphite and ceramics, several nanoparticles have been proposed, including carbon nanotubes and graphene, for the use in polymer nanocomposites. Indeed, thermal conductivities for both carbon nanotubes and graphenes were reported in the wide range of about 1500 to 6000 W/mK, despite such property may decrease dramatically as a function of the size, number of layers, the density of topological defects, re-hybridization defects as well as on the presence of impurities. Different synthetic techniques have been developed, including mechanical cleavage of graphite, epitaxial growth on SiC, chemical vapor deposition, and liquid phase exfoliation. However, the industrial scale-up of graphene, defined as an individual, single-atom-thick sheet of hexagonally arranged sp2-bonded carbons still remains very challenging. For large scale bulk applications in polymer nanocomposites, some graphene-related materials such as multilayer graphenes (MLG), reduced graphene oxide (rGO) or graphite nanoplatelets (GNP) are currently the most interesting graphene-based materials. In this paper, different types of graphene-related materials were characterized for their chemical/physical as well as for thermal properties of individual flakes. Two selected rGOs were annealed at 1700°C in vacuum for 1 h to reduce defectiveness of the carbon structure. Thermal conductivity increase of individual GNP with annealing was assessed via scanning thermal microscopy. Graphene nano papers were prepared from both conventional RGO and annealed RGO flakes. Characterization of the nanopapers evidenced a five-fold increase in the thermal diffusivity on the nano paper plane for annealed nanoflakes, compared to pristine ones, demonstrating the importance of structural defectiveness reduction to maximize the heat dissipation performance. Both pristine and annealed RGO were used to prepare polymer nanocomposites, by melt reactive extrusion. Thermal conductivity showed two- to three-fold increase in the thermal conductivity of the nanocomposite was observed for high temperature treated RGO compared to untreated RGO, evidencing the importance of using low defectivity nanoflakes. Furthermore, the study of different processing paremeters (time, temperature, shear rate) during the preparation of poly (butylene terephthalate) nanocomposites evidenced a clear correlation with the dispersion and fragmentation of the GNP nanoflakes; which in turn affected the thermal conductivity performance. Thermal conductivity of about 1.7 W/mK, i.e. one order of magnitude higher than for pristine polymer, was obtained with 10%wt of annealed GNPs, which is in line with state of the art nanocomposites prepared by more complex and less upscalable in situ polymerization processes.

Keywords: graphene, graphene-related materials, scanning thermal microscopy, thermally conductive polymer nanocomposites

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Authors: Ivone R. Oliveira, Isabela S. Gonçalves, Tiago M. B. Campos, Leandro J. Raniero, Luana M. R. Vasconcellos, João H. Lopes

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Originally, the principles of guided tissue/bone regeneration (GTR/GBR) were followed to restore the architecture and functionality of the periodontal system. In essence, a biocompatible polymer-based occlusive membrane is used as a barrier to prevent migration of epithelial and connective tissue to the regenerating site. In this way, progenitor cells located in the remaining periodontal ligament can recolonize the root area and differentiate into new periodontal tissues, alveolar bone, and new connective attachment. The use of synthetic or collagen-derived membranes with or without calcium phosphate-based bone graft materials has been the treatment used. Ideally, these membranes need to exhibit sufficient initial mechanical strength to allow handling and implantation, withstand the various mechanical stresses suffered during surgery while maintaining their integrity, and support the process of bone tissue regeneration and repair by resisting cellular traction forces and wound contraction forces during tissue healing in vivo. Although different RTG/ROG products are available on the market, they have serious deficiencies in terms of mechanical strength. Aiming to improve the mechanical strength and osteogenic properties of the membrane, this work evaluated the production of membranes that integrate the biocompatibility of the natural polymer (silk fibroin - FS) and the synthetic polymer poly(vinyl pyrrolidone - PVP) with graphene nanoplates (NPG) and gold nanoparticles (AuNPs), using the electrospinning equipment (AeroSpinner L1.0 from Areka) which allows the execution of high voltage spinning and/or solution blowing and with a high production rate, enabling development on an industrial scale. Silk fibroin uniquely solved many of the problems presented by collagen and was used in this work because it has unique combined merits, such as programmable biodegradability, biocompatibility and sustainable large-scale production. Graphene has attracted considerable attention in recent years as a potential biomaterial for mechanical reinforcement because of its unique physicochemical properties and was added to improve the mechanical properties of the membranes associated or not with the presence of AuNPs, which have shown great potential in regulating osteoblast activity. The preparation of FS from silkworm cocoons involved cleaning, degumming, dissolution in lithium bromide, dialysis, lyophilization and dissolution in hexafluoroisopropanol (HFIP) to prepare the solution for electrospinning, and crosslinking tests were performed in methanol. The NPGs were characterized and underwent treatment in nitric acid for functionalization to improve the adhesion of the nanoplates to the PVP fibers. PVP-NPG membranes were produced with 0.5, 1.0 and 1.5 wt% functionalized or not and evaluated by SEM/FEG, FTIR, mechanical strength and cell culture assays. Functionalized GNP particles showed stronger binding, remaining adhered to the fibers. Increasing the graphene content resulted in higher mechanical strength of the membrane and greater biocompatibility. The production of FS-PVP-NPG-AuNPs hybrid membranes was performed by electrospinning in separate syringes and simultaneously the FS solution and the solution containing PVP-NPG 1.5 wt% in the presence or absence of AuNPs. After cross-linking, they were characterized by SEM/FEG, FTIR and behavior in cell culture. The presence of NPG-AuNPs increased the viability and the presence of mineralization nodules.

Keywords: barrier membranes, silk fibroin, nanoparticles, tissue regeneration.

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Authors: Mostafa Shahriari, Sergio Rojas, David Pardo, Angel Rodriguez- Rozas, Shaaban A. Bakr, Victor M. Calo, Ignacio Muga

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Logging-While Drilling (LWD) is a technique to record down-hole logging measurements while drilling the well. Nowadays, LWD devices (e.g., nuclear, sonic, resistivity) are mostly used commercially for geo-steering applications. Modern borehole resistivity tools are able to measure all components of the magnetic field by incorporating tilted coils. The depth of investigation of LWD tools is limited compared to the thickness of the geological layers. Thus, it is a common practice to approximate the Earth’s subsurface with a sequence of 1D models. For a 1D model, we can reduce the dimensionality of the problem using a Hankel transform. We can solve the resulting system of ordinary differential equations (ODEs) either (a) analytically, which results in a so-called semi-analytic method after performing a numerical inverse Hankel transform, or (b) numerically. Semi-analytic methods are used by the industry due to their high performance. However, they have major limitations, namely: -The analytical solution of the aforementioned system of ODEs exists only for piecewise constant resistivity distributions. For arbitrary resistivity distributions, the solution of the system of ODEs is unknown by today’s knowledge. -In geo-steering, we need to solve inverse problems with respect to the inversion variables (e.g., the constant resistivity value of each layer and bed boundary positions) using a gradient-based inversion method. Thus, we need to compute the corresponding derivatives. However, the analytical derivatives of cross-bedded formation and the analytical derivatives with respect to the bed boundary positions have not been published to the best of our knowledge. The main contribution of this work is to overcome the aforementioned limitations of semi-analytic methods by solving each 1D model (associated with each Hankel mode) using an efficient multi-scale finite element method. The main idea is to divide our computations into two parts: (a) offline computations, which are independent of the tool positions and we precompute only once and use them for all logging positions, and (b) online computations, which depend upon the logging position. With the above method, (a) we can consider arbitrary resistivity distributions along the 1D model, and (b) we can easily and rapidly compute the derivatives with respect to any inversion variable at a negligible additional cost by using an adjoint state formulation. Although the proposed method is slower than semi-analytic methods, its computational efficiency is still high. In the presentation, we shall derive the mathematical variational formulation, describe the proposed multi-scale finite element method, and verify the accuracy and efficiency of our method by performing a wide range of numerical experiments and comparing the numerical solutions to semi-analytic ones when the latest are available.

Keywords: logging-While-Drilling, resistivity measurements, multi-scale finite elements, Hankel transform

Procedia PDF Downloads 386

Authors: Navven Desai, Veena Soraganvi

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Heavy metals such as lead, cadmium and mercury do not have biological significance hence they are known to be extremely toxic heavy metals. Water contains various heavy metals like Cadmium (Cd), Chromium (Cr), Copper (Cu), Nickel (Ni), Arsenic (As), Lead (Pb), and Zinc (Zn) etc., when it gets polluted with industrial waste water. These heavy metals cause various health effects even at low concentration when consumed by humans. Most of the heavy metals are poisonous to living organisms. Heavy metals are non-degradable and are preserved in the environment through bioaccumulation. Therefore removal of heavy metals from water is necessary. In recent years, a great deal of attentions has been focused on to the application of nanosized metal oxides to treat heavy metals, especially titanium oxides, ferric oxides, manganese oxides, aluminium oxides and magnesium oxides as adsorbent and photocatalyst. TiO2 based photocatalysts have attracted continuously increasing attention because of the excellent properties such as high light -conversion efficiency, chemical stability, nontoxic nature, low cost. The catalyst displays high photocatalytic activity because of its large surface area. In this study, the photocatalytic degradation of Lead (Pb) from aqueous solution was investigated in natural sunlight by using TiO2 as Nanomaterial. This study was performed at laboratory scale. All the experiments were carried out in the batch process. The concentration of lead was constant (25mg/lit) in the experiment and effect of titanium dioxide dose and pH were varied to study the removal efficiency of the lead by adsorption. Further study was performed on the dependence of photocatalytic reaction on the reaction temperature. The aqueous solution was prepared by Lead metal powder. TiO2 photo catalyst nanopowder used was Sisco-74629 grade. The heavy metal is analyzed with VARIAN AA 240 atomic adsorption spectrophotometer. The study shows, with increasing TiO2 dose and pH the lead removal increases. According to study, it can be concluded that the utilization of titanium dioxide accounted for higher efficiency in the removal of lead from aqueous solution.

Keywords: adsorption, heavy metals, nanomaterial, photocatalysis

Procedia PDF Downloads 298

Authors: Lama Bendak

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Parents and teachers face major problems dealing with attention deficit hyperactivity students. One solution is by changing the school to a less restrictive one or leaving school for good. The purpose of this study is to highlight the importance and role of individual educational plans (IEP) in helping cycle one ages six to nine attention deficit hyperactivity disorder (ADHD) students on the behavioral level. We have adopted the qualitative approach experimental where the total number of the students in our field of study was 66 from four schools. We have limited our study to cycle one students; that is grades 1, 2 and 3, whose ages range from 5.5 to 8.5. We divided the students into two groups where the controlled group was 36 students, and the experimental group was 30 students. The measuring instrument or tool that we used in our study is The SNAP-IV Teacher and Parents Rating Scale and was filled by class teachers. We did the pretest during the first trimester of the school year. Then we applied the Individual Educational Plans IEP's for two trimesters. Then we did the posttest and submitted the results for analysis, where we used the ANCOVA. The results of this study showed that the IEP's efficacy in helping ADHD students on the behavioral aspect showed statistical differences and varied depending on the initial level of difficulty of the student.

Keywords: attention deficit hyperactivity disorder, individual educational plans, behavioral charts, SNAP-IV teacher and parents rating scale

Procedia PDF Downloads 287

Authors: Wan-Ting Liao, Angela K. Tzeng

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Empathy has been an important issue in psychology, education, as well as cognitive neuroscience. Empathy has two major components: cognitive and emotional. Cognitive component refers to the ability to understand others’ perspectives, thoughts, and actions, whereas emotional component refers to understand how others feel. Empathy can be induced, attitude can then be changed, and with enough attitude change, helping behavior can occur. This finding leads us to two questions: is attitude change really necessary for prosocial behavior? And, what roles cognitive and affective empathy play? For the second question, participants with different psychopathic personality (PP) traits are critical because high PP people were found to suffer only affective empathy deficit. Their cognitive empathy shows no significant difference from the control group. 132 college students voluntarily participated in the current three-stage study. Stage 1 was to collect basic information including Interpersonal Reactivity Index (IRI), Psychopathic Personality Inventory-Revised (PPI-R), Attitude Scale, Visual Analogue Scale (VAS), and demographic data. Stage two was for empathy induction with three controversial scenarios, namely domestic violence, depression with a suicide attempt, and an ex-offender. Participants read all three stories and then rewrite the stories by one of two perspectives (empathetic vs. objective). They would then complete the VAS and Attitude Scale one more time for their post-attitude and emotional status. Three IVs were introduced for data analysis: PP (High vs. Low), Responsibility (whether or not the character is responsible for what happened), and Perspective-taking (Empathic vs. Objective). Stage 3 was for the action. Participants were instructed to freely use the 17 tokens they received as donations. They were debriefed and interviewed at the end of the experiment. The major findings were people with higher empathy tend to take more action in helping. Attitude change is not necessary for prosocial behavior. The controversy of the scenarios and how familiar participants are towards target groups play very important roles. Finally, people with high PP tend to show more public prosocial behavior due to their affective empathy deficit. Pre-existing value and belief as well as recent dramatic social events seem to have a big impact and possibly reduce the effect of the independent variables (IV) in our paradigm.

Keywords: empathy, cognitive, emotional, psychopathy

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Authors: Jiajia Yao, Guanlin Wu, Fang Liu, Junshuai Xue, Yue Hao

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As the production process of self-standing GaN substrates evolves, the commercialization of low dislocation density, large-scale, semi-insulating self-standing GaN substrates is gradually becoming a reality. This advancement has given rise to increased interest in GaN materials' homoepitaxial technology. However, at the homoepitaxial interface, there are considerable concentrations of impurity elements, including C, Si, and O, which generate parasitic leakage channels at the re-growth junction. This phenomenon results in leaked HEMTs that prove difficult to switch off, rendering them effectively non-functional. The emergence of leakage channels can also degrade the high-frequency properties and lower the power devices' breakdown voltage. In this study, the uniform epitaxy of AlGaN/GaN heterojunction with high electron mobility was accomplished through the surface treatment of the GaN substrates prior to growth and the design of the AlN isolation layer structure. By employing a procedure combining gallium atom in-situ cleaning and plasma nitridation, the C and O impurity concentrations at the homoepitaxial interface were diminished to the scale of 10¹⁷ cm-³. Additionally, the 1.5 nm nitrogen-rich AlN isolation layer successfully prevented the diffusion of Si impurities into the GaN channel layer. The result was an AlGaN/GaN heterojunction with an electron mobility of 1552 cm²/Vs and an electron density of 1.1 × 10¹³ cm-² at room temperature, obtained on a Fe-doped semi-insulating GaN substrate.

Keywords: MBE, AlGaN/GaN, homogenerous epitaxy, HEMT

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Authors: Sanaz Alizadeh, Yves Comeau, Arshath Abdul Rahim, Sunhasis Ghoshal

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The application of silver nanoparticles (AgNPs) in personal care products, various household and industrial products has resulted in an inevitable environmental exposure of such engineered nanoparticles (ENPs). Ag ENPs, released via household and industrial wastes, reach water resource recovery facilities (WRRFs), yet the fate and transport of ENPs in WRRFs and their potential risk in the biological wastewater processes are poorly understood. Accordingly, our main objective was to elucidate the impact of long-term continuous exposure to AgNPs on biological activity of aerobic wastewater biofilm. The fate, transport and toxicity of 10 μg.L-1and 100 μg.L-1 PVP-stabilized AgNPs (50 nm) were evaluated in an attached growth biological treatment process, using lab-scale moving bed bioreactors (MBBRs). Two MBBR systems for organic matter removal were fed with a synthetic influent and operated at a hydraulic retention time (HRT) of 180 min and 60% volumetric filling ratio of Anox-K5 carriers with specific surface area of 800 m2/m3. Both reactors were operated for 85 days after reaching steady state conditions to develop a mature biofilm. The impact of AgNPs on the biological performance of the MBBRs was characterized over a period of 64 days in terms of the filtered biodegradable COD (SCOD) removal efficiency, the biofilm viability and key enzymatic activities (α-glucosidase and protease). The AgNPs were quantitatively characterized using single-particle inductively coupled plasma mass spectroscopy (spICP-MS), determining simultaneously the particle size distribution, particle concentration and dissolved silver content in influent, bioreactor and effluent samples. The generation of reactive oxygen species and the oxidative stress were assessed as the proposed toxicity mechanism of AgNPs. Results indicated that a low concentration of AgNPs (10 μg.L-1) did not significantly affect the SCOD removal efficiency whereas a significant reduction in treatment efficiency (37%) was observed at 100 μg.L-1AgNPs. Neither the viability nor the enzymatic activities of biofilm were affected at 10 μg.L-1AgNPs but a higher concentration of AgNPs induced cell membrane integrity damage resulting in 31% loss of viability and reduced α-glucosidase and protease enzymatic activities by 31% and 29%, respectively, over the 64-day exposure period. The elevated intercellular ROS in biofilm at a higher AgNPs concentration over time was consistent with a reduced biological biofilm performance, confirming the occurrence of a nanoparticle-induced oxidative stress in the heterotrophic biofilm. The spICP-MS analysis demonstrated a decrease in the nanoparticles concentration over the first 25 days, indicating a significant partitioning of AgNPs into the biofilm matrix in both reactors. The concentration of nanoparticles increased in effluent of both reactors after 25 days, however, indicating a decreased retention capacity of AgNPs in biofilm. The observed significant detachment of biofilm also contributed to a higher release of nanoparticles due to cell-wall destabilizing properties of AgNPs as an antimicrobial agent. The removal efficiency of PVP-AgNPs and the biofilm biological responses were a function of nanoparticle concentration and exposure time. This study contributes to a better understanding of the fate and behavior of AgNPs in biological wastewater processes, providing key information that can be used to predict the environmental risks of ENPs in aquatic ecosystems.

Keywords: biofilm, silver nanoparticle, single particle ICP-MS, toxicity, wastewater

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Authors: Tamer Mesallam, Medhat Yousef, Ayna Almasaad

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BACKGROUND: Cochlear implantation (CI) in children with additional disabilities can be a fundamental and supportive intervention. Although, there may be some positive impacts of CI on children with multiple disabilities such as better outcomes of communication skills, development, and quality of life, the families of those children complain from the post-implant habilitation efforts that considered as a burden. OBJECTIVE: To investigate the outcomes of CI children with different co-disabilities through using the Meaningful Auditory Integration Scale (MAIS) and the Meaningful Use of Speech Scale (MUSS) as outcome measurement tools. METHODS: The study sample comprised 25 hearing-impaired children with co-disability who received cochlear implantation. Age and gender-matched control group of 25 cochlear-implanted children without any other disability has been also included. The participants' auditory skills and speech outcomes were assessed using MAIS and MUSS tests. RESULTS: There was a statistically significant difference in the different outcomes measure between the two groups. However, the outcomes of some multiple disabilities subgroups were comparable to the control group. Around 40% of the participants with co-disabilities experienced advancement in their methods of communication from behavior to oral mode. CONCLUSION: Cochlear-implanted children with multiple disabilities showed variable degrees of auditory and speech outcomes. The degree of benefits depends on the type of the co-disability. Long-term follow-up is recommended for those children.

Keywords: children with disabilities, Cochlear implants, hearing impairment, language development

Procedia PDF Downloads 119

Authors: Mark Archei O. Javier

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The Fourth Industrial Revolution (FIR) is a major industrial era characterized by the fusion of technologies that is blurring the lines between the physical, digital, and biological spheres. Since this era teaches us how to thrive in the fast-paced developing world, it is important to be able to adapt. With this, there is a need to make learning and teaching in the bioscience laboratory more challenging and engaging. The goal of the research is to find out if using in silico and in vitro laboratory activities compared to the conventional conduct laboratory activities would have positive impacts on the academic performance of the learners. The potential contribution of the research is that it would improve the teachers’ methods in delivering the content to the students when it comes to topics that need laboratory activities. This study will develop a method by which teachers can provide learning materials to the students. A one-tailed t-Test for independent samples was used to determine the significant difference in the pre- and post-test scores of students. The tests of hypotheses were done at a 0.05 level of significance. Based on the results of the study, the gain scores of the experimental group are greater than the gain scores of the control group. This implies that using in silico and in vitro labs for the experimental group is more effective than the conventional method of doing laboratory activities.

Keywords: academic performance, general biology, in silico laboratory, in vivo laboratory, virtual laboratory

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Authors: T. Hari Prasath, P. Ithaya Rani

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In the world of visual technology, recognizing emotions from the face images is a challenging task. Several related methods have not utilized the dynamic facial features effectively for high performance. This paper proposes a method for emotions recognition using dynamic facial features with high performance. Initially, local features are captured by Gabor filter with different scale and orientations in each frame for finding the position and scale of face part from different backgrounds. The Gabor features are sent to the ensemble classifier for detecting Gabor facial features. The region of dynamic features is captured from the Gabor facial features in the consecutive frames which represent the dynamic variations of facial appearances. In each region of dynamic features is normalized using Z-score normalization method which is further encoded into binary pattern features with the help of threshold values. The binary features are passed to Multi-class AdaBoost classifier algorithm with the well-trained database contain happiness, sadness, surprise, fear, anger, disgust, and neutral expressions to classify the discriminative dynamic features for emotions recognition. The developed method is deployed on the Ryerson Multimedia Research Lab and Cohn-Kanade databases and they show significant performance improvement owing to their dynamic features when compared with the existing methods.

Keywords: detecting face, Gabor filter, multi-class AdaBoost classifier, Z-score normalization

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Authors: Vivek Hokam, Vishrut Landge

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An ideal maintenance program for an industrial road network is one that would maintain all sections at a sufficiently high level of functional and structural conditions. However, due to various constraints such as budget, manpower and equipment, it is not possible to carry out maintenance on all the needy industrial road sections within a given planning period. A rational and systematic priority scheme needs to be employed to select and schedule industrial road sections for maintenance. Priority analysis is a multi-criteria process that determines the best ranking list of sections for maintenance based on several factors. In priority setting, difficult decisions are required to be made for selection of sections for maintenance. It is more important to repair a section with poor functional conditions which includes uncomfortable ride etc. or poor structural conditions i.e. sections those are in danger of becoming structurally unsound. It would seem therefore that any rational priority setting approach must consider the relative importance of functional and structural condition of the section. The maintenance priority index and pavement performance models tend to focus mainly on the pavement condition, traffic criteria etc. There is a need to develop the model which is suitably used with respect to limited budget provisions for maintenance of pavement. Linear programming is one of the most popular and widely used quantitative techniques. A linear programming model provides an efficient method for determining an optimal decision chosen from a large number of possible decisions. The optimum decision is one that meets a specified objective of management, subject to various constraints and restrictions. The objective is mainly minimization of maintenance cost of roads in industrial area. In order to determine the objective function for analysis of distress model it is necessary to fix the realistic data into a formulation. Each type of repair is to be quantified in a number of stretches by considering 1000 m as one stretch. A stretch considered under study is having 3750 m length. The quantity has to be put into an objective function for maximizing the number of repairs in a stretch related to quantity. The distress observed in this stretch are potholes, surface cracks, rutting and ravelling. The distress data is measured manually by observing each distress level on a stretch of 1000 m. The maintenance and rehabilitation measured that are followed currently are based on subjective judgments. Hence, there is a need to adopt a scientific approach in order to effectively use the limited resources. It is also necessary to determine the pavement performance and deterioration prediction relationship with more accurate and economic benefits of road networks with respect to vehicle operating cost. The infrastructure of road network should have best results expected from available funds. In this paper objective function for distress model is determined by linear programming and deterioration model considering overloading is discussed.

Keywords: budget, maintenance, deterioration, priority

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Authors: Henok Hailemariam, Frank Wuttke

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Collapsible soils are weak soils that appear to be stable in their natural state, normally dry condition, but rapidly deform under saturation (wetting), thus generating large and unexpected settlements which often yield disastrous consequences for structures unwittingly built on such deposits. In this study, a prediction model for the relative subsidence of stressed collapsible soils based on dielectric permittivity measurement is presented. Unlike most existing methods for soil subsidence prediction, this model does not require moisture content as an input parameter, thus providing the opportunity to obtain accurate estimation of the relative subsidence of collapsible soils using dielectric measurement only. The prediction model is developed based on an existing relative subsidence prediction model (which is dependent on soil moisture condition) and an advanced theoretical frequency and temperature-dependent electromagnetic mixing equation (which effectively removes the moisture content dependence of the original relative subsidence prediction model). For large scale sub-surface soil exploration purposes, the spatial sub-surface soil dielectric data over wide areas and high depths of weak (collapsible) soil deposits can be obtained using non-destructive high frequency electromagnetic (HF-EM) measurement techniques such as ground penetrating radar (GPR). For laboratory or small scale in-situ measurements, techniques such as an open-ended coaxial line with widely applicable time domain reflectometry (TDR) or vector network analysers (VNAs) are usually employed to obtain the soil dielectric data. By using soil dielectric data obtained from small or large scale non-destructive HF-EM investigations, the new model can effectively predict the relative subsidence of weak soils without the need to extract samples for moisture content measurement. Some of the resulting benefits are the preservation of the undisturbed nature of the soil as well as a reduction in the investigation costs and analysis time in the identification of weak (problematic) soils. The accuracy of prediction of the presented model is assessed by conducting relative subsidence tests on a collapsible soil at various initial soil conditions and a good match between the model prediction and experimental results is obtained.

Keywords: collapsible soil, dielectric permittivity, moisture content, relative subsidence

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Authors: Clara Oliver, Oibar Martinez, Jose Miguel Miranda

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This paper is devoted to the study of the most suitable protocols to verify the lightning protection and ground resistance quality in a large-scale scientific facility located in a harsh environment. We illustrate this work by reviewing a case study: the largest telescopes of the Northern Hemisphere Cherenkov Telescope Array, CTA-N. This array hosts sensitive and high-speed optoelectronics instrumentation and sits on a clear, free from obstacle terrain at around 2400 m above sea level. The site offers a top-quality sky but also features challenging conditions for a lightning protection system: the terrain is volcanic and has resistivities well above 1 kOhm·m. In addition, the environment often exhibits humidities well below 5%. On the other hand, the high complexity of a Cherenkov telescope structure does not allow a straightforward application of lightning protection standards. CTA-N has been conceived as an array of fourteen Cherenkov Telescopes of two different sizes, which will be constructed in La Palma Island, Spain. Cherenkov Telescopes can provide valuable information on different astrophysical sources from the gamma rays reaching the Earth’s atmosphere. The largest telescopes of CTA are called LST’s, and the construction of the first one was finished in October 2018. The LST has a shape which resembles a large parabolic antenna, with a 23-meter reflective surface supported by a tubular structure made of carbon fibers and steel tubes. The reflective surface has 400 square meters and is made of an array of segmented mirrors that can be controlled individually by a subsystem of actuators. This surface collects and focuses the Cherenkov photons into the camera, where 1855 photo-sensors convert the light in electrical signals that can be processed by dedicated electronics. We describe here how the risk assessment of direct strike impacts was made and how down conductors and ground system were both tested. The verification protocols which should be applied for the commissioning and operation phases are then explained. We stress our attention on the ground resistance quality assessment.

Keywords: grounding, large scale scientific instrument, lightning risk assessment, lightning standards and safety

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Authors: Mirjana Dragas, Marli Gonan Bozac, Morena Paulisic

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Corporate social responsibility (CSR) is a balance between strategic and financial goals of companies, as well as social needs. The integration of competitive strategy and CSR in food and beverage industry has allowed companies to find new sources of competitive advantage. The paper discusses the fact that socially responsible companies encourage co-operation with socially responsible suppliers in order to strengthen market competitiveness. In addition to the descriptive interpretation of the results obtained by a questionnaire, factor analysis was used, while principal components analysis was applied as a factor extraction method. The research results based on two multiple regression analyses show that: (1) selecting the CSR supplier explains a statistically significant part of the variance of the results on the scale of financial aspects of competitiveness (as much as 44.7% of the explained variance); and (2) selecting the CSR supplier is a significant predictor of non-financial aspects of competitiveness (explains 43.9% of the variance of the results on the scale of non-financial aspects of competitiveness). A successful competitive strategy must ultimately support the growth strategy. This implies an analytical approach to finding factors that influence competitiveness through socially sustainable solutions and satisfactory top management decisions.

Keywords: competitiveness, corporate social responsibility, food and beverage industry, supply chain decision making

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Authors: Ndidi Ofole

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Ongoing Boko Haram crisis and instability in North-Eastern Nigeria has placed additional stress on academic resilience of female undergraduates who are already challenged by gender discrimination in educational opportunities. Students without resilience lack stress hardiness to cope with academic challenges. There is a limited study on academic resilience targeting this disadvantaged population in Nigeria. Consequently, survey research design was employed to investigate the contextual and personal factors that could predict academic resilience among female undergraduates in Boko Haram Neighbourhood in North-Eastern, Nigeria. Five hundred and thirty female students with age range of 18 to 24 years ( = 19.2; SD=6.9) were randomly drawn from 3 Universities in North-Eastern Nigeria. They responded to five instruments, namely; Academic Resilience scale (r=0.72); Social Support questionnaire (r=0. 64); Social Connectedness questionnaire (r=0.75); Self-Efficacy scale (r=0. 68) and Emotional Regulation questionnaire (r=78). Results showed that there was significant positive relationship between the four independent variables and academic resilience. The variables jointly contributed 5.9% variance in the prediction of academic resilience. In terms of magnitude, social support was most potent while self-efficacy was the least. It concluded that the factors considered in this study are academic resilience facilitators. The outcomes of the study have both theoretical and practical implications.

Keywords: academic resilience, emotional regulation, school connectedness, self-efficacy , social support

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Authors: Patrícia Branco, Catarina Prista, Helena Albergaria

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Industrial fuel-ethanol fermentations are carried out under non-sterile conditions, which favors the development of microbial contaminants, leading to huge economic losses. Wild yeasts such as Brettanomyces bruxellensis and lactic acid bacteria are the main contaminants of industrial bioethanol fermentation, affecting Saccharomyces cerevisiae performance and decreasing ethanol yields and productivity. In order to control microbial contaminations, the fuel-ethanol industry uses different treatments, including acid washing and antibiotics. However, these control measures carry environmental risks such as acid toxicity and the rise of antibiotic-resistant bacteria. Therefore, it is crucial to develop and apply less toxic and more environmentally friendly biocontrol methods. In the present study, an industrial fuel-ethanol starter, S. cerevisiae Ethanol-Red, was genetically modified to over-express AMPs with activity against fuel-ethanol microbial contaminants and evaluated regarding its biocontrol effect during mixed-culture alcoholic fermentations artificially contaminated with B. bruxellensis. To achieve this goal, S. cerevisiae Ethanol-Red strain was transformed with a plasmid containing the AMPs-codifying genes, i.e., partial sequences of TDH1 (925-963 bp) and TDH2/3 (925-963 bp) and a geneticin resistance marker. The biocontrol effect of those genetically modified strains was evaluated against B. bruxellensis and compared with the antagonistic effect exerted by the modified strain with an empty plasmid (without the AMPs-codifying genes) and the non-modified strain S. cerevisiae Ethanol-Red. For that purpose, mixed-culture alcoholic fermentations were performed in a synthetic must use the modified S. cerevisiae Ethanol-Red strains together with B. bruxellensis. Single-culture fermentations of B. bruxellensis strains were also performed as a negative control of the antagonistic effect exerted by S. cerevisiae strains. Results clearly showed an improved biocontrol effect of the genetically-modified strains against B. bruxellensis when compared with the modified Ethanol-Red strain with the empty plasmid (without the AMPs-codifying genes) and with the non-modified Ethanol-Red strain. In mixed-culture fermentation with the modified S. cerevisiae strain, B. bruxellensis culturability decreased from 5×104 CFU/mL on day-0 to less than 1 CFU/mL on day-10, while in single-culture B. bruxellensis increased its culturability from 6×104 to 1×106 CFU/mL in the first 6 days and kept this value until day-10. Besides, the modified Ethanol-Red strain exhibited an enhanced antagonistic effect against B. bruxellensis when compared with that induced by the non-modified Ethanol-Red strain. Indeed, culturability loss of B. bruxellensis after 10 days of fermentation with the modified Ethanol-Red strain was 98.7 and 100% higher than that occurred in fermentations performed with the non-modified Ethanol-Red and the empty-plasmid modified strain, respectively. Therefore, one can conclude that the S. cerevisiae genetically modified strain obtained in the present work may be a valuable solution for the mitigation of microbial contamination in fuel-ethanol fermentations, representing a much safer and environmentally friendly preservation strategy than the antimicrobial treatments (acid washing and antibiotics) currently applied in fuel-ethanol industry.

Keywords: antimicrobial peptides, fuel-ethanol microbial contaminations, fuel-ethanol fermentation, biocontrol agents, genetically-modified yeasts

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Authors: Anwar Hasan Abdullah Othman, Ahamed Kameel, Hasanuddeen Abdul Aziz

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In this study, an attempt has been made to investigate the relationship specifically the causal relation between fund unit prices of Islamic equity unit trust fund which measure by fund NAV and the selected macro-economic variables of Malaysian economy by using VECM causality test and Granger causality test. Monthly data has been used from Jan, 2006 to Dec, 2012 for all the variables. The findings of the study showed that industrial production index, political election and financial crisis are the only variables having unidirectional causal relationship with fund unit price. However, the global oil prices is having bidirectional causality with fund NAV. Thus, it is concluded that the equity unit trust fund industry in Malaysia is an inefficient market with respect to the industrial production index, global oil prices, political election and financial crisis. However, the market is approaching towards informational efficiency at least with respect to four macroeconomic variables, treasury bill rate, money supply, foreign exchange rate and corruption index.

Keywords: fund unit price, unit trust industry, Malaysia, macroeconomic variables, causality

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Authors: Rouzbeh Jafari, Joe Nava

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This study includes learnings from an engineering practice normally performed on large scale biohydrogen processes. If properly scale-up is done, biohydrogen can be a reliable pathway for biowaste valorization. Most of the studies on biohydrogen process development have used model feedstock to investigate process key performance indicators (KPIs). This study does not intend to compare different technologies with model feedstock. However, it reports economic drivers and technical challenges which help in developing a road map for expanding biohydrogen economy deployment in Canada. BBA is a consulting firm responsible for the design of hydrogen production projects. Through executing these projects, activity has been performed to identify, register and mitigate technical drawbacks of large-scale hydrogen production. Those learnings, in this study, have been applied to the biohydrogen process. Through data collected by a comprehensive literature review, a base case has been considered as a reference, and several case studies have been performed. Critical parameters of the process were identified and through common engineering practice (process design, simulation, cost estimate, and life cycle assessment) impact of these parameters on the commercialization risk matrix and class 5 cost estimations were reported. The process considered in this study is food waste and woody biomass dark fermentation. To propose a reliable road map to develop a sustainable biohydrogen production process impact of critical parameters was studied on the end-to-end process. These parameters were 1) feedstock composition, 2) feedstock pre-treatment, 3) unit operation selection, and 4) multi-product concept. A couple of emerging technologies also were assessed such as photo-fermentation, integrated dark fermentation, and using ultrasound and microwave to break-down feedstock`s complex matrix and increase overall hydrogen yield. To properly report the impact of each parameter KPIs were identified as 1) Hydrogen yield, 2) energy consumption, 3) secondary waste generated, 4) CO2 footprint, 5) Product profile, 6) $/kg-H2 and 5) environmental impact. The feedstock is the main parameter defining the economic viability of biohydrogen production. Through parametric studies, it was found that biohydrogen production favors feedstock with higher carbohydrates. The feedstock composition was varied, by increasing one critical element (such as carbohydrate) and monitoring KPIs evolution. Different cases were studied with diverse feedstock, such as energy crops, wastewater slug, and lignocellulosic waste. The base case process was applied to have reference KPIs values and modifications such as pretreatment and feedstock mix-and-match were implemented to investigate KPIs changes. The complexity of the feedstock is the main bottleneck in the successful commercial deployment of the biohydrogen process as a reliable pathway for waste valorization. Hydrogen yield, reaction kinetics, and performance of key unit operations highly impacted as feedstock composition fluctuates during the lifetime of the process or from one case to another. In this case, concept of multi-product becomes more reliable. In this concept, the process is not designed to produce only one target product such as biohydrogen but will have two or multiple products (biohydrogen and biomethane or biochemicals). This new approach is being investigated by the BBA team and the results will be shared in another scientific contribution.

Keywords: biohydrogen, process scale-up, economic evaluation, commercialization uncertainties, hydrogen economy

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Authors: Ezgiamn Abraha Hagos

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The primary objective of this study was to assess the existential concerns and related manifestations of higher learning students by investigating their perception of meaningful life and evaluating their purpose in life. In addition, this study was aimed at assessing the manifestations of existential pain among the students. Data was procured using Purpose in Life test (PIL), Well-being Manifestation Measure Scale (WBMMS), and focus group discussion. The total numbers of participants was 478, of which 299 were males and the remaining 179 females. They were selected using a simple random sampling technique. Data was analyzed using two ways. SPSS-version 20 was used to analyze the quantitative part, and narrative modes were utilized to analyze the qualitative data. The research finding revealed that students are involved in risk taking behaviors like alcohol ingestion, drug use, Khat (chat) chewing, and unsafe sex. In line with this it is found out that life in campus was perceived as temporary and as a result the sense of hedonism was prevalent at any cost. Of course, the most important thing for the majority of the students was to know about the purpose of life. Regarding WBMMS, there was no statistically significant difference among males and females and with the exception of the sub-scale of happiness; in all the sub-scales the mean is low. At last, assisting adolescents to develop holistically in terms of body, mind, and spirit is recommended.

Keywords: existential concerns, higher learning institutions, Ethiopia, Aksum University

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Authors: Nathenal Thomas

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In the food chain and in many other agricultural products, corn, also known as maize, which goes by the scientific name Zea mays subsp, is a widely produced agricultural product. Corn has the highest adaptability. It comes in many different types, is employed in many different industrial processes, and is more adaptable to different agro-climatic situations. In Ethiopia, maize is among the most widely grown crop. Small-scale corn farming may be a household's only source of food in developing nations like Ethiopia. The aforementioned data demonstrates that the country's requirement for this crop is excessively high, and conversely, the crop's productivity is very low for a variety of reasons. The most damaging disease that greatly contributes to this imbalance between the crop's supply and demand is the corn disease. The failure to diagnose diseases in maize plant until they are too late is one of the most important factors influencing crop output in Ethiopia. This study will aid in the early detection of such diseases and support farmers during the cultivation process, directly affecting the amount of maize produced. The diseases in maize plants, such as northern leaf blight and cercospora leaf spot, have distinct symptoms that are visible. This study aims to detect the most frequent and degrading maize diseases using the most efficiently used subset of machine learning technology, deep learning so, called Image Processing. Deep learning uses networks that can be trained from unlabeled data without supervision (unsupervised). It is a feature that simulates the exercises the human brain goes through when digesting data. Its applications include speech recognition, language translation, object classification, and decision-making. Convolutional Neural Network (CNN) for Image Processing, also known as convent, is a deep learning class that is widely used for image classification, image detection, face recognition, and other problems. it will also use this algorithm as the state-of-the-art for my research to detect maize diseases by photographing maize leaves using a mobile phone.

Keywords: CNN, zea mays subsp, leaf blight, cercospora leaf spot

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Authors: Yue Shuai Zhao, Rong Ping Shao, Wei Sun, Guo Hua Ren, Yong Wang, Li Chen Sun

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A large-scale cryopump (DN1250) used in large vacuum leak detecting system was designed and its performance experimentally investigated by Beijing Institute of Spacecraft Environment Engineering. The cryopump was cooled by four closed cycle helium refrigerators (two dual stage refrigerators and two single stage refrigerators). Detailed numerical analysis of the heat transfer in the first stage array and the second stage array were performed by using computational fluid dynamic method (CFD). Several design parameters were considered to find the effect on the temperature distribution and the cooldown time. The variation of thermal conductivity and heat capacity with temperature was taken into account. The thermal analysis method based on numerical techniques was introduced in this study, the heat transfer in the first stage array and the second stage cryopanel was carefully analyzed to determine important considerations in the thermal design of the cryopump. A performance test system according to the RNEUROP standards was built to test main performance of the cryopump. The experimental results showed that the structure of first stage array which was optimized by the method could meet the requirement of the cryopump well. The temperature of the cryopanel was down to 10K within 300 min, and the result of the experiment was accordant with theoretical analysis' conclusion. The test also showed that the pumping speed for N2 of the pump was up to 57,000 L/s, and the crossover was over than 300,000 Pa•L.

Keywords: cryopump, temperature distribution, thermal analysis, CFD Simulation

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Authors: G. Venkatesha, Urs Samarth, H. K. Ramaraju, Arun Kumar Sharma

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The projection for Groundwater states that the total domestic water demand for greater Bangalore would increase from 1,170 MLD in 2010 to 1,336 MLD in 2016. Dependence on groundwater is ever increasing due to rapid Industrialization & Urbanization. It is estimated that almost 40% of the population of Bangalore is dependent on groundwater. Due to the unscientific disposal of domestic and industrial waste generated, groundwater is getting highly polluted in the city. The scale of this impact will depend mainly upon the water-service infrastructure, the superficial geology and the regional setting. The quality of ground water is equally important as that of quantity. Jointed and fractured granites and gneisses constitute the major aquifer system of BBMP area. Two new observatory Borewells were drilled and lithology report has been prepared. Petrographic Analysis (XRD/XRF) and Water quality Analysis were carried out as per the standard methods. Petrographic samples were analysed by collecting chip of rock from the borewell for every 20ft depth, most of the samples were similar and samples were identified as Biotite-Gneiss, Schistose Amphibolite. Water quality analysis was carried out for individual chemical parameters for two borewells drilled. 1st Borewell struck water at 150ft (Total depth-200ft) & 2nd struck at 740ft (Total depth-960ft). 5 water samples were collected till end of depth in each borewell. Chemical parameter values such as, Total Hardness (360-348, 280-320) mg/ltr, Nitrate (12.24-13.5, 45-48) mg/ltr, Chloride (104-90, 70-70)mg/ltr, Fe (0.75-0.09, 1.288-0.312)mg/ltr etc. are calculated respectively. Water samples were analysed from various parts of BBMP covering 750 sq kms, also thematic maps (IDW method) of water quality is generated for these samples for Post-Monsoon season. The study aims to explore the sub-surface Lithological layers and the thickness of weathered zone, which indirectly helps to know the Groundwater pollution source near surface water bodies, dug wells, etc. The above data are interpreted for future ground water resources planning and management.

Keywords: lithology, petrographic, pollution, urbanization

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Authors: Jannes Quer, Amir Niknejad, Marcus Weber

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Computational Drug Design is often based on Molecular Dynamics simulations of molecular systems. Molecular Dynamics can be used to simulate, e.g., the binding and unbinding event of a small drug-like molecule with regard to the active site of an enzyme or a receptor. However, the time-scale of the overall binding event is many orders of magnitude longer than the time-scale of simulation. Thus, there is a need to speed-up molecular simulations. In order to speed up simulations, the molecular dynamics trajectories have to be ”steared” out of local minimizers of the potential energy surface – the so-called metastabilities – of the molecular system. Increasing the kinetic energy (temperature) is one possibility to accelerate simulated processes. However, with temperature the entropy of the molecular system increases, too. But this kind ”stearing” is not directed enough to stear the molecule out of the minimum toward the saddle point. In this article, we give a new mathematical idea, how a potential energy surface can be changed in such a way, that entropy is kept under control while the trajectories are still steared out of the metastabilities. In order to compute the unsteared transition behaviour based on a steared simulation, we propose to use extrapolation methods. In the end we mathematically show, that our method accelerates the simulations along the direction, in which the curvature of the potential energy surface changes the most, i.e., from local minimizers towards saddle points.

Keywords: extrapolation, Eyring-Kramers, metastability, multilevel sampling

Procedia PDF Downloads 328