Search results for: power production performance

Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

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Authors: Abubakar Dikko

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The research investigates the causes of unemployment in Namibia, Nigeria and South Africa, and the role of Capital Accumulation in reducing the unemployment profile of these economies as proposed by the post-Keynesian economics. This is conducted through extensive review of literature on the NAIRU models and focused on the post-Keynesian view of unemployment within the NAIRU framework. The NAIRU (non-accelerating inflation rate of unemployment) model has become a dominant framework used in macroeconomic analysis of unemployment. The study views the post-Keynesian economics arguments that capital accumulation is a major determinant of unemployment. Unemployment remains the fundamental socio-economic challenge facing African economies. It has been a burden to citizens of those economies. Namibia, Nigeria and South Africa are great African nations battling with high unemployment rates. In 2013, the countries recorded high unemployment rates of 16.9%, 23.9% and 24.9% respectively. Most of the unemployed in these economies comprises of youth. Roughly about 40% working age South Africans has jobs, whereas in Nigeria and Namibia is less than that. Unemployment in Africa has wide implications on households which has led to extensive poverty and inequality, and created a rampant criminality. Recently in South Africa there has been a case of xenophobic attacks which were caused by the citizens of the country as a result of unemployment. The high unemployment rate in the country led the citizens to chase away foreigners in the country claiming that they have taken away their jobs. The study proposes that there is a strong relationship between capital accumulation and unemployment in Namibia, Nigeria and South Africa, and capital accumulation is responsible for high unemployment rates in these countries. For the economies to achieve steady state level of employment and satisfactory level of economic growth and development there is need for capital accumulation to take place. The countries in the study have been selected after a critical research and investigations. They are selected based on the following criteria; African economies with high unemployment rates above 15% and have about 40% of their workforce unemployed. This level of unemployment is the critical level of unemployment in Africa as expressed by International Labour Organization (ILO). The African countries with low level of capital accumulation. Adequate statistical measures have been employed using a time-series analysis in the study and the results revealed that capital accumulation is the main driver of unemployment performance in the chosen African countries. An increase in the accumulation of capital causes unemployment to reduce significantly. The results of the research work will be useful and relevant to federal governments and ministries, departments and agencies (MDAs) of Namibia, Nigeria and South Africa to resolve the issue of high and persistent unemployment rates in their economies which are great burden that slows growth and development of developing economies. Also, the result can be useful to World Bank, African Development Bank and International Labour Organization (ILO) in their further research and studies on how to tackle unemployment in developing and emerging economies.

Keywords: capital accumulation, unemployment, NAIRU, Post-Keynesian economics

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Authors: Manal M. Kame, Hanan G. El-Baz, Zeinab A.Demerdash, Engy M. Abd El-Moneem, Mohamed A. Hendawy, Ibrahim R. Bayoumi

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There is a constant need to improve the performance of current diagnostic assays of schistosomiasis as well as develop innovative testing strategies to meet new testing challenges. This study aims at increasing the diagnostic efficiency of monoclonal antibody (MAb)-based antigen detection assays through gold nanoparticles conjugated with specific anti-Schistosoma mansoni monoclonal antibodies. In this study, several hybidoma cell lines secreting MAbs against adult worm tegumental Schistosoma antigen (AWTA) were produced at Immunology Department of Theodor Bilharz Research Institute and preserved in liquid nitrogen. One MAb (6D/6F) was chosen for this study due to its high reactivity to schistosome antigens with highest optical density (OD) values. Gold nanoparticles (AuNPs) were functionalized and conjugated with MAb (6D/6F). The study was conducted on serum samples of 116 subjects: 71 patients with S. mansoni eggs in their stool samples group (gp 1), 25 with other parasites (gp2) and 20 negative healthy controls (gp3). Patients in gp1 were further subdivided according to egg count in their stool samples into Light infection {≤ 50 egg per gram(epg) (n= 17)}, moderate {51-100 epg (n= 33)} and severe infection {>100 epg(n= 21)}. Sandwich ELISA was performed using (AuNPs -MAb) for detection of circulating schistosomal antigen (CSA) levels in serum samples of all groups and the results were compared with that after using MAb/ sandwich ELISA system. Results Gold- MAb/ ELISA system reached a lower detection limit of 10 ng/ml compared to 85 ng/ml on using MAb/ ELISA and the optimal concentrations of AuNPs -MAb were found to be 12 folds less than that of MAb/ ELISA system for detection of CSA. The sensitivity and specificity of sandwich ELISA for detection of CSA levels using AuNPs -MAb were 100% & 97.8 % respectively compared to 87.3% &93.38% respectively on using MAb/ ELISA system. It was found that CSA was detected in 9 out of 71 S.mansoni infected patients on using AuNPs - MAb/ ELISA system and was not detected by MAb/ ELISA system. All those patients (9) was found to have an egg count below 50 epg feces (patients with light infections). ROC curve analyses revealed that sandwich ELISA using gold-MAb was an excellent diagnostic investigator that could differentiate Schistosoma patients from healthy controls, on the other hand it revealed that sandwich ELISA using MAb was not accurate enough as it could not recognize nine out of 71 patients with light infections. Conclusion Our data demonstrated that: Loading gold nanoparticles with MAb (6D/6F) increases the sensitivity and specificity of sandwich ELISA for detection of CSA, thus active (early) and light infections could be easily detected. Moreover this binding will decrease the amount of MAb consumed in the assay and lower the coast. The significant positive correlation that was detected between ova count (intensity of infection) and OD reading in sandwich ELISA using gold- MAb enables its use to detect the severity of infections and follow up patients after treatment for monitoring of cure.

Keywords: Schistosomiasis, nanoparticles, gold, monoclonal antibodies, ELISA

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Authors: Atchara Sankom, Warapa Mahakarnchanakul, Ronnarit Rittiron, Tanaboon Sajjaanantakul, Thammasak Thongket

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Vegetables are frequently contaminated with pesticides residues resulting in the most food safety concern among agricultural products. The objective of this work was to develop a method to detect the organophosphate (OP) pesticides residues in vegetables using Near Infrared (NIR) spectroscopy technique. Low concentration (ppm) of OP pesticides in vegetables were investigated. The experiment was divided into 2 sections. In the first section, Chinese kale spiked with different concentrations of chlorpyrifos pesticide residues (0.5-100 ppm) was chosen as the sample model to demonstrate the appropriate conditions of sample preparation, both for a solution or solid sample. The spiked samples were extracted with acetone. The sample extracts were applied as solution samples, while the solid samples were prepared by the dry-extract system for infrared (DESIR) technique. The DESIR technique was performed by embedding the solution sample on filter paper (GF/A) and then drying. The NIR spectra were measured with the transflectance mode over wavenumber regions of 12,500-4000 cm⁻¹. The QuEChERS method followed by gas chromatography-mass spectrometry (GC-MS) was performed as the standard method. The results from the first section showed that the DESIR technique with NIR spectroscopy demonstrated good accurate calibration result with R² of 0.93 and RMSEP of 8.23 ppm. However, in the case of solution samples, the prediction regarding the NIR-PLSR (partial least squares regression) equation showed poor performance (R² = 0.16 and RMSEP = 23.70 ppm). In the second section, the DESIR technique coupled with NIR spectroscopy was applied to the detection of OP pesticides in vegetables. Vegetables (Chinese kale, cabbage and hot chili) were spiked with OP pesticides (chlorpyrifos ethion and profenofos) at different concentrations ranging from 0.5 to 100 ppm. Solid samples were prepared (based on the DESIR technique), then samples were scanned by NIR spectrophotometer at ambient temperature (25+2°C). The NIR spectra were measured as in the first section. The NIR- PLSR showed the best calibration equation for detecting low concentrations of chlorpyrifos residues in vegetables (Chinese kale, cabbage and hot chili) according to the prediction set of R2 and RMSEP of 0.85-0.93 and 8.23-11.20 ppm, respectively. For ethion residues, the best calibration equation of NIR-PLSR showed good indexes of R² and RMSEP of 0.88-0.94 and 7.68-11.20 ppm, respectively. As well as the results for profenofos pesticide, the NIR-PLSR also showed the best calibration equation for detecting the profenofos residues in vegetables according to the good index of R² and RMSEP of 0.88-0.97 and 5.25-11.00 ppm, respectively. Moreover, the calibration equation developed in this work could rapidly predict the concentrations of OP pesticides residues (0.5-100 ppm) in vegetables, and there was no significant difference between NIR-predicted values and actual values (data from GC-MS) at a confidence interval of 95%. In this work, the proposed method using NIR spectroscopy involving the DESIR technique has proved to be an efficient method for the screening detection of OP pesticides residues at low concentrations, and thus increases the food safety potential of vegetables for domestic and export markets.

Keywords: NIR spectroscopy, organophosphate pesticide, vegetable, food safety

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Authors: Min Han, Di Wu, Lin Yuan, Fei Liu

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Mechanical sensors have undergone a continuous evolution and have become an important part of many industries, ranging from manufacturing to process, chemicals, machinery, health-care, environmental monitoring, automotive, avionics, and household appliances. Concurrently, the microelectronics and microfabrication technology have provided us with the means of producing mechanical microsensors characterized by high sensitivity, small size, integrated electronics, on board calibration, and low cost. Here we report a new kind of mechanical sensors based on the quantum transport process of electrons in the closely spaced nanoparticle films covering a flexible polymer sheet. The nanoparticle films were fabricated by gas phase depositing of preformed metal nanoparticles with a controlled coverage on the electrodes. To amplify the conductance of the nanoparticle array, we fabricated silver interdigital electrodes on polyethylene terephthalate(PET) by mask evaporation deposition. The gaps of the electrodes ranged from 3 to 30μm. Metal nanoparticles were generated from a magnetron plasma gas aggregation cluster source and deposited on the interdigital electrodes. Closely spaced nanoparticle arrays with different coverage could be gained through real-time monitoring the conductance. In the film coulomb blockade and quantum, tunneling/hopping dominate the electronic conduction mechanism. The basic principle of the mechanical sensors relies on the mechanical deformation of the fabricated devices which are translated into electrical signals. Several kinds of sensing devices have been explored. As a strain sensor, the device showed a high sensitivity as well as a very wide dynamic range. A gauge factor as large as 100 or more was demonstrated, which can be at least one order of magnitude higher than that of the conventional metal foil gauges or even better than that of the semiconductor-based gauges with a workable maximum applied strain beyond 3%. And the strain sensors have a workable maximum applied strain larger than 3%. They provide the potential to be a new generation of strain sensors with performance superior to that of the currently existing strain sensors including metallic strain gauges and semiconductor strain gauges. When integrated into a pressure gauge, the devices demonstrated the ability to measure tiny pressure change as small as 20Pa near the atmospheric pressure. Quantitative vibration measurements were realized on a free-standing cantilever structure fabricated with closely-spaced nanoparticle array sensing element. What is more, the mechanical sensor elements can be easily scaled down, which is feasible for MEMS and NEMS applications.

Keywords: gas phase deposition, mechanical sensors, metallic nanoparticle arrays, quantum conductance

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Authors: Davide Palma, Dimitra Papagiannaki, Marco Minella, Manuel Lai, Rita Binetti, Claire Richard

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Modern analytical technologies allow us to detect water contaminants at trace and ultra-trace concentrations highlighting how a large number of organic compounds is not efficiently abated by most wastewater treatment facilities relying on biological processes; we usually refer to these micropollutants as contaminants of emerging concern (CECs). The availability of reliable end effective technologies, able to guarantee the high standards of water quality demanded by legislators worldwide, has therefore become a primary need. In this context, water plasma stands out among developing technologies as it is extremely effective in the abatement of numerous classes of pollutants, cost-effective, and environmentally friendly. In this work, a custom-built non-thermal pulsed plasma discharge generator was used to abate the concentration of selected CECs in the water samples. Samples were treated in a 50 mL pyrex reactor using two different types of plasma discharge occurring at the surface of the treated solution or, underwater, working with positive polarity. The distance between the tips of the electrodes determined where the discharge was formed: underwater when the distance was < 2mm, at the water surface when the distance was > 2 mm. Peak voltage was in the 100-130kV range with typical current values of 20-40 A. The duration of the pulse was 500 ns, and the frequency of discharge could be manually set between 5 and 45 Hz. Treatment of 100 µM diclofenac solution in MilliQ water, with a pulse frequency of 17Hz, revealed that surface discharge was more efficient in the degradation of diclofenac that was no longer detectable after 6 minutes of treatment. Over 30 minutes were required to obtain the same results with underwater discharge. These results are justified by the higher rate of H₂O₂ formation (21.80 µmolL⁻¹min⁻¹ for surface discharge against 1.20 µmolL⁻¹min⁻¹ for underwater discharge), larger discharge volume and UV light emission, high rate of ozone and NOx production (up to 800 and 1400 ppb respectively) observed when working with surface discharge. Then, the surface discharge was used for the treatment of the three selected perfluoroalkyl compounds, namely, perfluorooctanoic acid (PFOA), perfluorohexanoic acid (PFHxA), and pefluorooctanesulfonic acid (PFOS) both individually and in mixture, in ultrapure and groundwater matrices with initial concentration of 1 ppb. In both matrices, PFOS exhibited the best degradation reaching complete removal after 30 min of treatment (degradation rate 0.107 min⁻¹ in ultrapure water and 0.0633 min⁻¹ in groundwater), while the degradation rate of PFOA and PFHxA was slower of around 65% and 80%, respectively. Total nitrogen (TN) measurements revealed levels up to 45 mgL⁻¹h⁻¹ in water samples treated with surface discharge, while, in analogous samples treated with underwater discharge, TN increase was 5 to 10 times lower. These results can be explained by the significant NOx concentrations (over 1400 ppb) measured above functioning reactor operating with superficial discharge; rapid NOx hydrolysis led to nitrates accumulation in the solution explaining the observed evolution of TN values. Ionic chromatography measures confirmed that the vast majority of TN was under the form of nitrates. In conclusion, non-thermal pulsed plasma discharge, obtained with a custom-built generator, was proven to effectively degrade diclofenac in water matrices confirming the potential interest of this technology for wastewater treatment. The surface discharge was proven to be more effective in CECs removal due to the high rate of formation of H₂O₂, ozone, reactive radical species, and strong UV light emission. Furthermore, nitrates enriched water obtained after treatment could be an interesting added-value product to be used as fertilizer in agriculture. Acknowledgment: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 765860.

Keywords: CECs removal, nitrogen fixation, non-thermal plasma, water treatment

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Authors: Dragan Ribarić

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We employ the so-called problem-dependent linked interpolation concept to develop two cubic 4-node quadrilateral Mindlin plate finite elements with 12 external degrees of freedom. In the problem-independent linked interpolation, the interpolation functions are independent of any problem material parameters and the rotation fields are not expressed in terms of the nodal displacement parameters. On the contrary, in the problem-dependent linked interpolation, the interpolation functions depend on the material parameters and the rotation fields are expressed in terms of the nodal displacement parameters. Two cubic 4-node quadrilateral plate elements are presented, named Q4-U3 and Q4-U3R5. The first one is modelled with one displacement and two rotation degrees of freedom in every of the four element nodes and the second element has five additional internal degrees of freedom to get polynomial completeness of the cubic form and which can be statically condensed within the element. Both elements are able to pass the constant-bending patch test exactly as well as the non-zero constant-shear patch test on the oriented regular mesh geometry in the case of cylindrical bending. In any mesh shape, the elements have the correct rank and only the three eigenvalues, corresponding to the solid body motions are zero. There are no additional spurious zero modes responsible for instability of the finite element models. In comparison with the problem-independent cubic linked interpolation implemented in Q9-U3, the nine-node plate element, significantly less degrees of freedom are employed in the model while retaining the interpolation conformity between adjacent elements. The presented elements are also compared to the existing problem-independent quadratic linked-interpolation element Q4-U2 and to the other known elements that also use the quadratic or the cubic linked interpolation, by testing them on several benchmark examples. Simple functional upgrading from the quadratic to the cubic linked interpolation, implemented in Q4-U3 element, showed no significant improvement compared to the quadratic linked form of the Q4-U2 element. Only when the additional bubble terms are incorporated in the displacement and rotation function fields, which complete the full cubic linked interpolation form, qualitative improvement is fulfilled in the Q4-U3R5 element. Nevertheless, the locking problem exists even for the both presented elements, like in all pure displacement elements when applied to very thin plates modelled by coarse meshes. But good and even slightly better performance can be noticed for the Q4-U3R5 element when compared with elements from the literature, if the model meshes are moderately dense and the plate thickness not extremely thin. In some cases, it is comparable to or even better than Q9-U3 element which has as many as 12 more external degrees of freedom. A significant improvement can be noticed in particular when modeling very skew plates and models with singularities in the stress fields as well as circular plates with distorted meshes.

Keywords: Mindlin plate theory, problem-independent linked interpolation, problem-dependent interpolation, quadrilateral displacement-based plate finite elements

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Authors: Emma S. Bowers

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Perturbations in global environments and temperatures have heightened the urgency of creating cost-efficient, energy-neutral building techniques. Structural responses to this thermal crisis have included designs (including those of the building standard PassivHaus) with airtightness, window placement, insulation, solar orientation, shading, and heat-exchange ventilators as potential solutions or interventions. Limitations in the predictability of the circulation of cooled air through the ambient temperature gradients throughout a structure are one of the major obstacles facing these enhanced building methods. A diverse range of air-cooling devices utilizing varying technologies is implemented around the world. Many of them worsen the problem of climate change by consuming energy. Using natural ventilation principles of air buoyancy and density to circulate fresh air throughout a building with no energy input can combat these obstacles. A unique prototype of an energy-neutral air-circulation system was constructed in order to investigate potential temperature and pressure gradients related to the stack effect (updraft of air through a building due to changes in air pressure). The stack effect principle maintains that since warmer air rises, it will leave an area of low pressure that cooler air will rush in to fill. The result is that warmer air will be expelled from the top of the building as cooler air is directed through the bottom, creating an updraft. Stack effect can be amplified by cooling the air near the bottom of a building and heating the air near the top. Using readily available, mostly recyclable or biodegradable materials, an insulated building module was constructed. A tri-part construction model was utilized: a subterranean earth-tube heat exchanger constructed of PVC pipe and placed in a horizontally oriented trench, an insulated, airtight cube aboveground to represent a building, and a solar chimney (painted black to increase heat in the out-going air). Pressure and temperature sensors were placed at four different heights within the module as well as outside, and data was collected for a period of 21 days. The air pressures and temperatures over the course of the experiment were compared and averaged. The promise of this design is that it represents a novel approach which directly addresses the obstacles of air flow and expense, using the physical principle of stack effect to draw a continuous supply of fresh air through the structure, using low-cost and readily available materials (and zero manufactured energy). This design serves as a model for novel approaches to creating temperature controlled buildings using zero energy and opens the door for future research into the effects of increasing module scale, increasing length and depth of the earth tube, and shading the building. (Model can be provided).

Keywords: air circulation, PassivHaus, stack effect, thermal gradient

Procedia PDF Downloads 139

Authors: Marcela Davalos Lopez

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The history of the circulation of hygienic knowledge and the consolidation of public health in Latin American cities towards the end of the 19th century is well known. Among them, Mexico City was inserted in international politics, strengthened institutions, medical knowledge, applied parameters of modernity and built sanitary engineering works. Despite the power that this hygienist system achieved, its scope was relative: it cannot be generalized to all cities. From a comparative and contextual analysis, it will be shown that conclusions derived from modern urban historiography present, from our contemporary observations, fractures. Between 1890 and 1930, the small cities and areas surrounding the Mexican capital adapted in their own way the international and federal public health regulations. This will be shown for neighborhoods located around Mexico City and in a medium city, close to the Mexican capital (about 80 km), called Cuernavaca. While the inhabitants of the neighborhoods kept awaiting the evolutionary process and the forms that public hygiene policies were taking (because they were witnesses and affected in their territories), in Cuernavaca, the dictates came as an echo. While the capital was drained, large roads were opened, roundabouts were erected, residents were expelled, and drains, sewers, drinking water pipes, etc., were built; Cuernavaca was sheltered in other times and practices. What was this due to? Undoubtedly, the time and energy that it took politicians and the group of "scientists" to carry out these enormous works in the Mexican capital took them away from addressing the issue in remote villages. It was not until the 20th century that the federal hygiene policy began to be strengthened. Despite this, there are other factors that emphasize the particularities of each site. I would like to draw attention here to the different receptions that each town prepared on public hygiene. We will see that Cuernavaca responded to its own semi-rural culture, history, orography and functions, prolonging for much longer, for example, the use of its deep ravines as sewers. For their part, the neighborhoods surrounding the capital, although affected and excluded from hygienist policies, chose to move away from them and solve the deficiencies with their own resources (they resorted to the waste that was left from the dried lake of Mexico to continue their lake practices). All of this points to a paradox that shapes our contemporary concerns: on the one hand, the benefits derived from medical knowledge and its technological applications (in this work referring particularly to the urban health system) and, on the other, the alteration it caused in environmental settings. Places like Cuernavaca (classified by the nineteenth-century and hygienists of the first decades of the twentieth century as backward), as well as landscapes such as neighborhoods, affected by advances in sanitary engineering, keep in their memory buried practices that we observe today as possible ways to reestablish environmental balances: alternative uses of water; recycling of organic materials; local uses of fauna; various systems for breaking down excreta, and so on. In sum, what the nineteenth and first half of the twentieth centuries graduated as levels of backwardness or progress, turn out to be key information to rethink the routes of environmental conservation. When we return to the observations of the scientists, politicians and lawyers of that period, we find historically rejected cultural alterity. Populations such as Cuernavaca that, due to their history, orography and/or insufficiency of federal policies, kept different relationships with the environment, today give us clues to reorient basic elements of cities: alternative uses of water, waste of raw materials, organic or consumption of local products, among others. It is, therefore, a matter of unearthing the rejected that cries out to emerge to the surface.

Keywords: sanitary hygiene, Mexico city, cultural alterity, environmental conservation, environmental history

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Authors: Abderrazak Bannari, Ghadeer Kadhem

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The objectives of this paper are the validation and the evaluation of MBES-CARIS BASE surface data performance for bathymetric mapping of shallow water in the Kingdom of Bahrain. The latter is an archipelago with a total land area of about 765.30 km², approximately 126 km of coastline and 8,000 km² of marine area, located in the Arabian Gulf, east of Saudi Arabia and west of Qatar (26° 00’ N, 50° 33’ E). To achieve our objectives, bathymetric attributed grid files (X, Y, and depth) generated from the coverage of ship-track MBSE data with 300 x 300 m cells, processed with CARIS-HIPS, were downloaded from the General Bathymetric Chart of the Oceans (GEBCO). Then, brought into ArcGIS and converted into a raster format following five steps: Exportation of GEBCO BASE surface data to the ASCII file; conversion of ASCII file to a points shape file; extraction of the area points covering the water boundary of the Kingdom of Bahrain and multiplying the depth values by -1 to get the negative values. Then, the simple Kriging method was used in ArcMap environment to generate a new raster bathymetric grid surface of 30×30 m cells, which was the basis of the subsequent analysis. Finally, for validation purposes, 2200 bathymetric points were extracted from a medium scale nautical map (1:100 000) considering different depths over the Bahrain national water boundary. The nautical map was scanned, georeferenced and overlaid on the MBES-CARIS generated raster bathymetric grid surface (step 5 above), and then homologous depth points were selected. Statistical analysis, expressed as a linear error at the 95% confidence level, showed a strong correlation coefficient (R² = 0.96) and a low RMSE (± 0.57 m) between the nautical map and derived MBSE-CARIS depths if we consider only the shallow areas with depths of less than 10 m (about 800 validation points). When we consider only deeper areas (> 10 m) the correlation coefficient is equal to 0.73 and the RMSE is equal to ± 2.43 m while if we consider the totality of 2200 validation points including all depths, the correlation coefficient is still significant (R² = 0.81) with satisfactory RMSE (± 1.57 m). Certainly, this significant variation can be caused by the MBSE that did not completely cover the bottom in several of the deeper pockmarks because of the rapid change in depth. In addition, steep slopes and the rough seafloor probably affect the acquired MBSE raw data. In addition, the interpolation of missed area values between MBSE acquisition swaths-lines (ship-tracked sounding data) may not reflect the true depths of these missed areas. However, globally the results of the MBES-CARIS data are very appropriate for bathymetric mapping of shallow water areas.

Keywords: bathymetry mapping, multibeam echosounder systems, CARIS-HIPS, shallow water

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Authors: L. Malic, X. Zhang, D. Brassard, L. Clime, J. Daoud, C. Luebbert, V. Barrere, A. Boutin, S. Bidawid, N. Corneau, J. Farber, T. Veres

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The incidence of infections caused by foodborne pathogens such as Listeria monocytogenes (L. monocytogenes) poses a great potential threat to public health and safety. These issues are further exacerbated by legal repercussions due to “zero tolerance” food safety standards adopted in developed countries. Unfortunately, a large number of related disease outbreaks are caused by pathogens present in extremely low counts currently undetectable by available techniques. The development of highly sensitive and rapid detection of foodborne pathogens is therefore crucial, and requires robust and efficient pre-analytical sample preparation. Immunomagnetic separation is a popular approach to sample preparation. Microfluidic chips combined with external magnets have emerged as viable high throughput methods. However, external magnets alone are not suitable for the capture of nanoparticles, as very strong magnetic fields are required. Devices that incorporate externally applied magnetic field and microstructures of a soft magnetic material have thus been used for local field amplification. Unfortunately, very complex and costly fabrication processes used for integration of soft magnetic materials in the reported proof-of-concept devices would prohibit their use as disposable tools for food and water safety or diagnostic applications. We present a sample preparation magnetic microfluidic device implemented in low-cost thermoplastic polymers using fabrication techniques suitable for mass-production. The developed magnetic capture chip (M-chip) was employed for rapid capture and release of L. monocytogenes conjugated to immunomagnetic nanoparticles (IMNs) in buffer and beef filtrate. The M-chip relies on a dense array of Nickel-coated high-aspect ratio pillars for capture with controlled magnetic field distribution and a microfluidic channel network for sample delivery, waste, wash and recovery. The developed Nickel-coating process and passivation allows generation of switchable local perturbations within the uniform magnetic field generated with a pair of permanent magnets placed at the opposite edges of the chip. This leads to strong and reversible trapping force, wherein high local magnetic field gradients allow efficient capture of IMNs conjugated to L. monocytogenes flowing through the microfluidic chamber. The experimental optimization of the M-chip was performed using commercially available magnetic microparticles and fabricated silica-coated iron-oxide nanoparticles. The fabricated nanoparticles were optimized to achieve the desired magnetic moment and surface functionalization was tailored to allow efficient capture antibody immobilization. The integration, validation and further optimization of the capture and release protocol is demonstrated using both, dead and live L. monocytogenes through fluorescence microscopy and plate- culture method. The capture efficiency of the chip was found to vary as function of listeria to nanoparticle concentration ratio. The maximum capture efficiency of 30% was obtained and the 24-hour plate-culture method allowed the detection of initial sample concentration of only 16 cfu/ml. The device was also very efficient in concentrating the sample from a 10 ml initial volume. Specifically, 280% concentration efficiency was achieved in 17 minutes only, demonstrating the suitability of the system for food safety applications. In addition, flexible design and low-cost fabrication process will allow rapid sample preparation for applications beyond food and water safety, including point-of-care diagnosis.

Keywords: array of pillars, bacteria isolation, immunomagnetic sample preparation, polymer microfluidic device

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Authors: Hassiba Benguergoura, Kamal Chanane, Sâad Moulay

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Pervaporation (PV), a membrane-based separation technology, has gained much attention because of its energy saving capability and low-cost, especially for separation of azeotropic or close-boiling liquid mixtures. There are two crucial issues for industrial application of pervaporation process. The first is developing membrane material and tailoring membrane structure to obtain high pervaporation performances. The second is modeling pervaporation transport to better understand of the above-mentioned structure–pervaporation relationship. Many models were proposed to predict the mass transfer process, among them, solution-diffusion model is most widely used in describing pervaporation transport including preferential sorption, diffusion and evaporation steps. For modeling pervaporation transport, the permeation flux, which depends on the solubility and diffusivity of components in the membrane, should be obtained first. Traditionally, the solubility was calculated according to the Flory–Huggins theory. Separation of the benzene (Bz)/cyclohexane (Cx) mixture is industrially significant. Numerous papers have been focused on the Bz/Cx system to assess the PV properties of membrane materials. Membranes with both high permeability and selectivity are desirable for practical application. Several new polymers have been prepared to get both high permeability and selectivity. Styrene-butadiene rubbers (SBR), dense membranes cross-linked by chloromethylation were used in the separation of benzene/cyclohexane mixtures. The impact of chloromethylation reaction as a new method of cross-linking SBR on the pervaporation performance have been reported. In contrast to the vulcanization with sulfur, the cross-linking takes places on styrene units of polymeric chains via a methylene bridge. The partial pervaporative (PV) fluxes of benzene/cyclohexane mixtures in styrene-butadiene rubber (SBR) were predicted using Fick's first law. The predicted partial fluxes and the PV separation factor agreed well with the experimental data by integrating Fick's law over the benzene concentration. The effects of feed concentration and operating temperature on the predicted permeation flux by this proposed model are investigated. The predicted permeation fluxes are in good agreement with experimental data at lower benzene concentration in feed, but at higher benzene concentration, the model overestimated permeation flux. The predicted and experimental permeation fluxes all increase with operating temperature increasing. Solvent sorption levels for benzene/ cyclohexane mixtures in a SBR membrane were determined experimentally. The results showed that the solvent sorption levels were strongly affected by the feed composition. The Flory- Huggins equation generates higher R-square coefficient for the sorption selectivity.

Keywords: benzene, cyclohexane, pervaporation, permeation, sorption modeling, SBR

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Authors: Wisam H. Benamer, Ehab A. Elfallah, Mohamed A. Elshaari, Farag A. Elshaari

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A challenge for laboratories is to provide bacterial identification and antibiotic sensitivity results within a short time. Hence, advancement in the required technology is desirable to improve timing, accuracy and quality. Even with the current advances in methods used for both phenotypic and genotypic identification of bacteria the need is there to develop method(s) that enhance the outcome of bacteriology laboratories in accuracy and time. The hypothesis introduced here is based on the assumption that the chromosome of any bacteria contains unique sequences that can be used for its identification and typing. The outcome of a pilot study designed to test this hypothesis is reported in this manuscript. Methods: The complete chromosome sequences of several bacterial species were downloaded to use as search targets for unique sequences. Visual basic and SQL server (2014) were used to generate a complete set of 18-base long primers, a process started with reverse translation of randomly chosen 6 amino acids to limit the number of the generated primers. In addition, the software used to scan the downloaded chromosomes using the generated primers for similarities was designed, and the resulting hits were classified according to the number of similar chromosomal sequences, i.e., unique or otherwise. Results: All primers that had identical/similar sequences in the selected genome sequence(s) were classified according to the number of hits in the chromosomes search. Those that were identical to a single site on a single bacterial chromosome were referred to as unique. On the other hand, most generated primers sequences were identical to multiple sites on a single or multiple chromosomes. Following scanning, the generated primers were classified based on ability to differentiate between medically important bacterial and the initial results looks promising. Conclusion: A simple strategy that started by generating primers was introduced; the primers were used to screen bacterial genomes for match. Primer(s) that were uniquely identical to specific DNA sequence on a specific bacterial chromosome were selected. The identified unique sequence can be used in different molecular diagnostic techniques, possibly to identify bacteria. In addition, a single primer that can identify multiple sites in a single chromosome can be exploited for region or genome identification. Although genomes sequences draft of isolates of organism DNA enable high throughput primer design using alignment strategy, and this enhances diagnostic performance in comparison to traditional molecular assays. In this method the generated primers can be used to identify an organism before the draft sequence is completed. In addition, the generated primers can be used to build a bank for easy access of the primers that can be used to identify bacteria.

Keywords: bacteria chromosome, bacterial identification, sequence, primer generation

Procedia PDF Downloads 176

Authors: T. Lazzarini, M. Imbiki, P. E. Sutter, G. Borragan

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While several strategies, such as the development of more efficient appliances, the financing of insulation programs or the rolling out of smart meters represent promising tools to reduce future energy consumption, their implementation relies on people’s decisions-actions. Likewise, engaging with consumers to reshape their behavior has shown to be another important way to reduce energy usage. For these reasons, integrating the human factor in the energy transition has become a major objective for researchers and policymakers. Digital education programs based on tangible and gamified user interfaces have become a new tool with potential effects to reduce energy consumption4. The B2020 program, developed by the firm “Économie d’Énergie SAS”, proposes a digital platform to encourage pro-environmental behavior change among employees and citizens. The platform integrates 160 eco-behaviors to help saving energy and water and reducing waste and CO2 emissions. A total of 13,146 citizens have used the tool so far to declare the range of eco-behaviors they adopt in their daily lives. The present work seeks to build on this database to identify the potential impact of adopted energy-saving behaviors (n=62) to reduce the use of energy in buildings. To this end, behaviors were classified into three categories regarding the nature of its implementation (Eco-habits: e.g., turning-off the light, Eco-actions: e.g., installing low carbon technology such as led light-bulbs and Home-Refurbishments: e.g., such as wall-insulation or double-glazed energy efficient windows). General Linear Models (GLM) disclosed the existence of a significantly higher frequency of Eco-habits when compared to the number of home-refurbishments realized by the platform users. While this might be explained in part by the high financial costs that are associated with home renovation works, it also contrasts with the up to three times larger energy-savings that can be accomplished by these means. Furthermore, multiple regression models failed to disclose the expected relationship between energy-savings and frequency of adopted eco behaviors, suggesting that energy-related practices are not necessarily driven by the correspondent energy-savings. Finally, our results also suggested that people adopting more Eco-habits and Eco-actions were more likely to engage in Home-Refurbishments. Altogether, these results fit well with a growing body of scientific research, showing that energy-related practices do not necessarily maximize utility, as postulated by traditional economic models, and suggest that other variables might be triggering them. Promoting home refurbishments could benefit from the adoption of complementary energy-saving habits and actions.

Keywords: energy-saving behavior, human performance, behavioral change, energy efficiency

Procedia PDF Downloads 176

Authors: A. Alyaaria, b, J. P. Wignerona, A. Ducharneb, Y. Kerrc, P. de Rosnayd, R. de Jeue, A. Govinda, A. Al Bitarc, C. Albergeld, J. Sabaterd, C. Moisya, P. Richaumec, A. Mialonc

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Global Level-3 surface soil moisture (SSM) maps from the passive microwave soil moisture and Ocean Salinity satellite (SMOSL3) have been released. To further improve the Level-3 retrieval algorithm, evaluation of the accuracy of the spatio-temporal variability of the SMOS Level 3 products (referred to here as SMOSL3) is necessary. In this study, a comparative analysis of SMOSL3 with a SSM product derived from the observations of the Advanced Microwave Scanning Radiometer (AMSR-E) computed by implementing the Land Parameter Retrieval Model (LPRM) algorithm, referred to here as AMSRM, is presented. The comparison of both products (SMSL3 and AMSRM) were made against SSM products produced by a numerical weather prediction system (SM-DAS-2) at ECMWF (European Centre for Medium-Range Weather Forecasts) for the 03/2010-09/2011 period at global scale. The latter product was considered here a 'reference' product for the inter-comparison of the SMOSL3 and AMSRM products. Three statistical criteria were used for the evaluation, the correlation coefficient (R), the root-mean-squared difference (RMSD), and the bias. Global maps of these criteria were computed, taking into account vegetation information in terms of biome types and Leaf Area Index (LAI). We found that both the SMOSL3 and AMSRM products captured well the spatio-temporal variability of the SM-DAS-2 SSM products in most of the biomes. In general, the AMSRM products overestimated (i.e., wet bias) while the SMOSL3 products underestimated (i.e., dry bias) SSM in comparison to the SM-DAS-2 SSM products. In term of correlation values, the SMOSL3 products were found to better capture the SSM temporal dynamics in highly vegetated biomes ('Tropical humid', 'Temperate Humid', etc.) while best results for AMSRM were obtained over arid and semi-arid biomes ('Desert temperate', 'Desert tropical', etc.). When removing the seasonal cycles in the SSM time variations to compute anomaly values, better correlation with the SM-DAS-2 SSM anomalies were obtained with SMOSL3 than with AMSRM, in most of the biomes with the exception of desert regions. Eventually, we showed that the accuracy of the remotely sensed SSM products is strongly related to LAI. Both the SMOSL3 and AMSRM (slightly better) SSM products correlate well with the SM-DAS2 products over regions with sparse vegetation for values of LAI < 1 (these regions represent almost 50% of the pixels considered in this global study). In regions where LAI>1, SMOSL3 outperformed AMSRM with respect to SM-DAS-2: SMOSL3 had almost consistent performances up to LAI = 6, whereas AMSRM performance deteriorated rapidly with increasing values of LAI.

Keywords: remote sensing, microwave, soil moisture, AMSR-E, SMOS

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Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

Procedia PDF Downloads 221

Authors: Taher Abofol, Yaakov Kareev, Judith Avrahami, Peter M. Todd

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Are children sensitive to their relative strength in competitions against others? Performance on tasks that require cooperation or coordination (e.g. the Ultimatum Game) indicates that early precursors of adult-like notions of fairness and reciprocity, as well as altruistic behavior, are evident at an early age. However, not much is known regarding developmental changes in interactive decision-making, especially in competitive interactions. Thus, it is important to study the developmental aspects of strategic behavior in these situations. The present research focused on cognitive-developmental changes in a competitive interaction. Specifically, it aimed at revealing how children engage in strategic interactions that involve the allocation of limited resources over a number of fields of competition, by manipulating relative strength. Relative strength refers to situations in which player strength changes midway through the game: the stronger player becomes the weaker one, while the weaker player becomes the stronger one. An experiment was conducted to find out if the behavior of children of different age groups differs in the following three aspects: 1. Perception of relative strength. 2. Ability to learn while gaining experience. 3. Ability to adapt to change in relative strength. The task was composed of a resource allocation game. After the players allocated their resources (privately and simultaneously), a competition field was randomly chosen for each player. The player who allocated more resources to the field chosen was declared the winner of that round. The resources available to the two competitors were unequal (or equal, for control). The theoretical solution for this game is that the weaker player should give up on a certain number of fields, depending on the stronger opponent’s relative strength, in order to be able to compete with the opponent on equal footing in the remaining fields. Participants were of three age groups, first-graders (N = 36, mean age = 6), fourth-graders (N = 36, mean age = 10), and eleventh-graders (N = 72, mean age = 16). The games took place between players of the same age and lasted for 16 rounds. There were two experimental conditions – a control condition, in which players were of equal strength, and an experimental condition, in which players differed in strength. In the experimental condition, players' strength was changed midway through the session. Results indicated that players in all age groups were sensitive to their relative strength, and played in line with the theoretical solution: the weaker players gave up on more fields than the stronger ones. This understanding, as well as the consequent difference in allocation between weak and strong players, was more pronounced among older participants. Experience led only to minimal behavioral change. Finally, the children from the two older groups, particularly the eleventh graders adapted quickly to the midway switch in relative strength. In contrast, the first-graders hardly changed their behavior with the change in their relative strength, indicating a limited ability to adapt. These findings highlight young children’s ability to consider their relative strength in strategic interactions and its boundaries.

Keywords: children, competition, decision making, developmental changes, strategic behavior

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Authors: Josie West

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This paper focuses on the conflicts and utility of Marxist Feminist frames for sex work research, drawing on findings uncovered through in-depth interviews with online sex workers, alongside critical discourse analysis of media and political commentary. It brings the critical perspective of women into digital workerism and gig economy dialogue who, despite their significant presence within online work, have been overlooked. The autonomist Marxist concept of class composition is adopted to unpack the social, technical and political composition of this often-invisible segment of the service sector. Autonomism makes visible the perspective of workers engaged in processes of mobilization and demobilizaiton. This allows researchers to find everyday forms of resistance which occur within and outside trade unions. On the other hand, Marxist feminist arguments about invisibility politics can generate unhelpful allegories about sex work as domestic labour within the reproductive sphere. Nick Srnicek’s development of Marx’s notion of infrastructure rents helps theorize experiences of unpaid labour within online sex work. Moreover, debates about anti-work politics can cause conflict among sex workers fighting for the labour movement and those rejecting the capitalist work ethic. This illuminates’ tensions caused by white privilege and differing experiences of sex work. The monopolistic and competitive nature of sex work platforms within platform capitalism, and the vulnerable position of marginalised workers within stigmatized/criminalised markets, complicates anti-work politics further. This paper is situated within the feminist sex wars and the intensely divisive question of whether sex workers are victims of the patriarchy or symbols of feminist resistance. Camgirls are shown to engage in radical tactics of resistance against their technical composition on popular sex work platforms. They also engage in creative acts of resistance through performance art, in an attempt to draw attention to stigma and anti-criminalization politics. This sector offers a fascinating window onto grassroots class-action, alongside education about ‘whorephobia.’ A case study of resistance against Only Fans, and a small workers co-operative which emerged during the pandemic, showcases how workers engage in socialist and political acts without the aid of unions. Workers are victims of neoliberalism and simultaneous adopters of neoliberal strategies of survival. The complex dynamics within unions are explored, including tensions with grass-roots resistance, financial pressures and intersecting complications of class, gender and race.

Keywords: autonomist marxism, digital labor, feminism, neoliberalism, sex work, platform capitalism

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Authors: E. M. Condori-Peñaloza, S. S. Costa

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Eleusine indica L, known as goose-grass, is considered a troublesome weed that can cause important economic losses in the agriculture worldwide. However, this grass is used as a medicinal plant in some regions of Brazil to treat influenza and pneumonia. In Africa and Asia, it is used to treat malaria and as diuretic, anti-helminthic, among other uses. Despite its therapeutic potential, little is known about the chemical composition and bioactive compounds of E. indica. Hitherto, two major flavonoids, schaftoside and vitexin, were isolated from aerial part of the species and showed inhibitory activity on lung neutrophil influxes in mice, suggesting a beneficial effect on airway inflammation. Therefore, the aim of this study was to analyze the chemical profile of aqueous extracts from aerial parts of Eleusine indica specimens using high performance liquid chromatography (HPLC-DAD) and 1H nuclear magnetic resonance spectroscopy (NMR), with emphasis on phenolic compounds. Specimens of E. indica were collected in Minas Gerais state, Brazil. Aerial parts of fresh plants were extracted by decoction (10% p/v). After spontaneous precipitation of the aqueous extract at 10-12°C for 24 hours, the supernatant obtained was frozen and lyophilized. After that, 1 g of the extract was dissolved into 25 mL of water and fractionated on a reverse phase chromatography column (RP-2), eluted with a gradient of H2O/EtOH. Five fractions were obtained. The extract and fractions had their chemical profile analyzed by using HPLC-DAD (C-18 column: 20 μL, 256 -365 nm; gradient water 0.01% phosphoric acid/ acetonitrile. The extract was also analyzed by NMR (1H, 500 MHz, D2O) in order to access its global chemical composition. HPLC-DAD analyses of crude extract allowed the identification of ten phenolic compounds. Fraction 1, eluted with 100% water, was poor in phenolic compounds and no major peak was detected. In fraction 2, eluted with 100% water, it was possible to observe one major peak at retention time (RT) of 23.75 minutes compatible with flavonoid; fraction 3, also eluted with 100% water, showed four peaks at RT= 21.47, 23.52, 24.33 and 25.84 minutes, all of them compatible with flavonoid. In fraction 4, eluted with 50%/ethanol/50% water, it was possible to observe 3 peaks compatible with flavonoids at RT=24.65, 26.81, 27.49 minutes, and one peak (28.83 min) compatible with a phenolic acid derivative. Finally, in fraction 5, eluted with 100% ethanol, no phenolic substance was detected. The UV spectra of all flavonoids detected were compatible with the flavone subclass (λ= 320-345 nm). The 1H NMR spectra of aerial parts extract showed signals in three regions: δ 0.8-3.0 ppm (aliphatic compounds), δ 3.0-5.5 ppm corresponding to carbohydrates (signals most abundant and overlapped), and δ 6.0-8.5 ppm (aromatic compounds). Signals compatible with flavonoids (rings A and B) could also be detected in the crude extract spectra. These results suggest the presence of several flavonoids in E. indica, which reinforces their therapeutic potential. The pharmacological activities of Eleusine indica extracts and fractions will be further evaluated.

Keywords: flavonoids, HPLC, NMR, phenolic compounds

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Authors: Elkington S. Mnguni

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Water and sanitation services in South Africa are characterized by both achievements and challenges. After the end of apartheid in 1994 the newly elected government faced the challenge of eradicating backlogs with respect to access to basic services, including water and sanitation. Capital investment made in the development of new water and sanitation infrastructure to provide basic services to previously disadvantaged communities has grown, to a certain extent, at the expense of investment in the operation and maintenance of new and existing infrastructure. Challenges resulting from aging infrastructure and poor plant performance highlight the need for investing in the maintenance, rehabilitation, and replacement of existing infrastructure to optimize the return on investment. Advanced water infrastructure asset management (IAM) is key to achieving adequate levels of service, particularly with regard to reliable and high quality drinking water supply, prevention of urban flooding, efficient use of natural resources and prevention of pollution and associated risks. Against this backdrop, this paper presents an appraisal of water and sanitation IAM systems in South Africa’s three utilities, being metropolitan cities in the Gauteng Province. About a quarter of the national population lives in the three rapidly urbanizing cities of Johannesburg, Ekurhuleni and Tshwane, located in a semi-arid region. A literature review has been done and field visits to some of the utility facilities are being conducted. Semi-structured interviews will be conducted with the three utilities. The following critical factors are being analysed in terms of compliance with the national Water Services IAM Strategy (2011) and other applicable legislation: asset registers; capacity of assets; current and predicted demand; funding availability / budget allocations; plans: operation & maintenance, renewal & replacement, and risk management; no-drop status (non-revenue water levels); blue drop status (water quality); green drop status (effluent quality); and skills availability. Some of the key challenges identified in the literature review include: funding constraints, Skills shortage, and wastewater treatment plants operating beyond their design capacities. These challenges will be verified during field visits and research interviews. Gaps between literature and practice will be identified and relevant recommendations made if necessary. The objective of this study is to contribute to the resolution of the challenges brought about by the backlogs in the operation and maintenance of water and sanitation assets in the country in general, and in the three cities in particular, thus improving the sustainability thereof.

Keywords: asset management, backlogs, levels of service, sustainability, water and sanitation infrastructure

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Authors: Abid Hussain, Binay Kumar

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Environment-friendly lead-free Na₀.₅₂K₀.₄₄Li₀.₀₄Nb₀.₈₄Ta₀.₁₀Sb₀.₀₆O₃ (NKLNTS) ceramic was synthesized by solid-state reaction method in search of a potential candidate to replace lead-based ceramics such as PbZrO₃-PbTiO₃ (PZT), Pb(Mg₁/₃Nb₂/₃)O₃-PbTiO₃ (PMN-PT) etc., for various applications. The ceramic was calcined at temperature 850 ᵒC and sintered at 1090 ᵒC. The powder X-Ray Diffraction (XRD) pattern revealed the formation of pure perovskite phase having tetragonal symmetry with space group P4mm of the synthesized ceramic. The surface morphology of the ceramic was studied using Field Emission Scanning Electron Microscopy (FESEM) technique. The well-defined grains with homogeneous microstructure were observed. The average grain size was found to be ~ 0.6 µm. A very large value of piezoelectric charge coefficient (d₃₃ ~ 754 pm/V) was obtained for the synthesized ceramic which indicated its potential for use in transducers and actuators. In dielectric measurements, a high value of ferroelectric to paraelectric phase transition temperature (Tm~305 ᵒC), a high value of maximum dielectric permittivity ~ 2110 (at 1 kHz) and a very small value of dielectric loss ( < 0.6) were obtained which suggested the utility of NKLNTS ceramic in high-temperature ferroelectric devices. Also, the degree of diffuseness (γ) was found to be 1.61 which confirmed a relaxor ferroelectric behavior in NKLNTS ceramic. P-E hysteresis loop was traced and the value of spontaneous polarization was found to be ~11μC/cm² at room temperature. The pyroelectric coefficient was obtained to be very high (p ∼ 1870 μCm⁻² ᵒC⁻¹) for the present case indicating its applicability in pyroelectric detector applications including fire and burglar alarms, infrared imaging, etc. NKLNTS ceramic showed fatigue free behavior over 107 switching cycles. Remanent hysteresis task was performed to determine the true-remanent (or intrinsic) polarization of NKLNTS ceramic by eliminating non-switchable components which showed that a major portion (83.10 %) of the remanent polarization (Pr) is switchable in the sample which makes NKLNTS ceramic a suitable material for memory switching devices applications. Time-Dependent Compensated (TDC) hysteresis task was carried out which revealed resistive leakage free nature of the ceramic. The performance of NKLNTS ceramic was found to be superior to many lead based piezoceramics and hence can effectively replace them for use in piezoelectric, pyroelectric and long duration ferroelectric applications.

Keywords: dielectric properties, ferroelectric properties , lead free ceramic, piezoelectric property, solid state reaction, true-remanent polarization

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Jianan Sun, Ziwen Ye

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Multidimensional computerized adaptive testing (MCAT) is a popular research topic in psychometrics. It is important for practitioners to clearly know the item-trait patterns of administered items when a test like MCAT is operated. Item-trait pattern recognition refers to detecting which latent traits in a psychological test are measured by each of the specified items. If the item-trait patterns of the replenished items in MCAT item pool are well detected, the interpretability of the items can be improved, which can further promote the abilities of the examinees who attending the MCAT to be accurately estimated. This research explores to solve the item-trait pattern recognition problem of the replenished items in MCAT item pool from the perspective of statistical variable selection. The popular multidimensional item response theory model, multidimensional two-parameter logistic model, is assumed to fit the response data of MCAT. The proposed method uses the least absolute shrinkage and selection operator (LASSO) to detect item-trait patterns of replenished items based on the essential information of item responses and ability estimates of examinees collected from a designed MCAT procedure. Several advantages of the proposed method are outlined. First, the proposed method does not strictly depend on the relative order between the replenished items and the selected operational items, so it allows the replenished items to be mixed into the operational items in reasonable order such as considering content constraints or other test requirements. Second, the LASSO used in this research improves the interpretability of the multidimensional replenished items in MCAT. Third, the proposed method can exert the advantage of shrinkage method idea for variable selection, so it can help to check item quality and key dimension features of replenished items and saves more costs of time and labors in response data collection than traditional factor analysis method. Moreover, the proposed method makes sure the dimensions of replenished items are recognized to be consistent with the dimensions of operational items in MCAT item pool. Simulation studies are conducted to investigate the performance of the proposed method under different conditions for varying dimensionality of item pool, latent trait correlation, item discrimination, test lengths and item selection criteria in MCAT. Results show that the proposed method can accurately detect the item-trait patterns of the replenished items in the two-dimensional and the three-dimensional item pool. Selecting enough operational items from the item pool consisting of high discriminating items by Bayesian A-optimality in MCAT can improve the recognition accuracy of item-trait patterns of replenished items for the proposed method. The pattern recognition accuracy for the conditions with correlated traits is better than those with independent traits especially for the item pool consisting of comparatively low discriminating items. To sum up, the proposed data-driven method based on the LASSO can accurately and efficiently detect the item-trait patterns of replenished items in MCAT.

Keywords: item-trait pattern recognition, least absolute shrinkage and selection operator, multidimensional computerized adaptive testing, variable selection

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Authors: Ocsana Opris, Ildiko Lung, Maria L. Soran, Alexandra Ciorita, Lucian Copolovici

Abstract:

The effects assessment of environmental stress factors on both crop and wild plants of nutritional value are a very important research topic. Continuously worldwide consumption of drugs leads to significant environmental pollution, thus generating environmental stress. Understanding the effects of the important drugs on plant composition and ultrastructural modification is still limited, especially at environmentally relevant concentrations. The aim of the present work was to investigate the influence of three non-steroidal anti-inflammatory drugs (NSAIDs) on chlorophylls content, carotenoids content, total polyphenols content, antioxidant capacity, and ultrastructure of orache (Atriplex patula L.) and spinach (Spinacia oleracea L.). All green leafy vegetables selected for this study were grown in controlled conditions and treated with solutions of different concentrations (0.1‒1 mg L⁻¹) of diclofenac, ibuprofen, and naproxen. After eight weeks of exposure of the plants to NSAIDs, the chlorophylls and carotenoids content were analyzed by high-performance liquid chromatography coupled with photodiode array and mass spectrometer detectors, total polyphenols and antioxidant capacity by ultraviolet-visible spectroscopy. Also, the ultrastructural analyses of the vegetables were performed using transmission electron microscopy in order to assess the influence of the selected NSAIDs on cellular organisms, mainly photosynthetic organisms (chloroplasts), energy supply organisms (mitochondria) and nucleus as a cellular metabolism coordinator. In comparison with the control plants, decreases in the content of chlorophylls were observed in the case of the Atriplex patula L. plants treated with ibuprofen (11-34%) and naproxen (25-52%). Also, the chlorophylls content from Spinacia oleracea L. was affected, the lowest decrease (34%) being obtained in the case of the treatment with naproxen (1 mg L⁻¹). Diclofenac (1 mg L⁻¹) affected the total polyphenols content (a decrease of 45%) of Atriplex patula L. and ibuprofen (1 mg L⁻¹) affected the total polyphenols content (a decrease of 20%) of Spinacia oleracea L. The results obtained also indicate a moderate reduction of carotenoids and antioxidant capacity in the treated plants, in comparison with the controls. The investigations by transmission electron microscopy demonstrated that the green leafy vegetables were affected by the selected NSAIDs. Thus, this research contributes to a better understanding of the adverse effects of these drugs on studied plants. Important to mention is that the dietary intake of these drugs contaminated plants, plants with important nutritional value, may also presume a risk to human health, but currently little is known about the fate of the drugs in plants and their effect on or risk to the ecosystem.

Keywords: abiotic stress, green leafy vegetables, pigments content, ultra structure

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Authors: Julien Benomar

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The World Bank report published in April 2023 called “Migrants, Refugees and Society” allows us to first distinguish migrants in search of economic opportunities and refugees that flee a situation of danger and choose their destination based on their immediate need for safety. Amongst those two categories, the report distinguished people having professional skills adapted to the labor market of the host country and those who have not. Out of that distinction of four categories, we choose to focus our research on refugees that do not have professional skills adapted to the labor market of the host country. Given that refugees generally have no recourse to public assistance schemes and cannot count on the support of their entourage or support network, we propose to examine the extent to which external assistance, such as international humanitarian action, is likely to accompany refugees' transition to financial empowerment through entrepreneurship. To this end, we propose to carry out a case study structured in three stages: (i) an exchange with a Non-Governmental Organisation (NGO) active in supporting refugee populations from Congo and Burundi to Rwanda, enabling us to (i.i) define together a financial empowerment income, and (i. ii) learn about the content of the support measures taken for the beneficiaries of the humanitarian project; (ii) monitor the population of 118 beneficiaries, including 73 refugees and 45 Rwandans (reference population); (iii) conduct a participatory analysis to identify the level of performance of the project and areas for improvement. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO that has been funding this economic aid project through entrepreneurship since 2021. The case study thus involved the staff of an international NGO active in helping refugees from Rwanda since 2015 and the staff of a Luxembourg NGO, which has been funding this economic aid through an entrepreneurship project since 2021, and took place over a 48-day period between April and May 2023. The main results are of two types: (i) the need to associate indicators for monitoring the impact of the project on the indirect beneficiaries of the project (refugee community) and (ii) the identification of success factors making it possible to bring concrete and relevant responses to the constraints encountered. The first result thus made it possible to identify the following indicators: Indicator of community potential ((jobs, training or mentoring) promoted by the activity of the entrepreneur), Indicator of social contribution (tax paid by the entrepreneur), Indicator of resilience (savings and loan capacity generated, and finally impact on social cohesion. The second result made it possible to identify that among the 7 success factors tested, the sector of activity chosen and the level of experience in the sector of the future activity are those that stand out the most clearly.

Keywords: entrepreuneurship, refugees, financial empowerment, international aid

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Authors: Jean Pierre Ribeiro Daquila

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This paper aims to analyze the use of the Theory of Multiple Intelligences as a tool to facilitate students’ learning. This theory, proposed by the American psychologist and educator Howard Gardner, was first established in 1983 and advocates that human beings possess eight intelligence and not only one, as defended by psychologists prior to his theory. These intelligence are bodily-kinesthetic intelligence, musical, linguistic, logical-mathematical, spatial, interpersonal, intrapersonal, and naturalist. This paper will focus on bodily-kinesthetic intelligence. Spatial and bodily-kinesthetic intelligences are sensed by athletes, dancers, and others who use their bodies in ways that exceed normal abilities. These are intelligences that are closely related. A quarterback or a ballet dancer needs to have both an awareness of body motions and abilities as well as a sense of the space involved in the action. Nevertheless, there are many reasons which make classical ballet dance more integrated with other intelligences. Ballet dancers make it look effortless as they move across the stage, from the lifts to the toe points; therefore, there is acting both in the performance of the repertoire and in hiding the pain or physical stress. The ballet dancer has to have great mathematical intelligence to perform a fast allegro; for instance, each movement has to be executed in a specific millisecond. Flamenco dancers need to rely as well on their mathematic abilities, as the footwork requires the ability to make half, two, three, four or even six movements in just one beat. However, the precision of the arm movements is freer than in ballet dance; for this reason, ballet dancers need to be more holistically aware of their movements; therefore, our experiment will test whether this greater attention required by ballet dancers makes them acquire better results in the training sessions when compared to flamenco dancers. An experiment will be carried out in this study by training ballet dancers through dance (four years of experience dancing minimum – experimental group 1); a group of flamenco dancers (four years of experience dancing minimum – experimental group 2). Both experimental groups will be trained in two different domains – phonetics and chemistry – to examine whether there is a significant improvement in these areas compared to the control group (a group of regular students who will receive the same training through a traditional method). However, this paper will focus on phonetic training. Experimental group 1 will be trained with the aid of classical music plus bodily work. Experimental group 2 will be trained with flamenco rhythm and kinesthetic work. We would like to highlight that this study takes dance as an example of a possible area of strength; nonetheless, other types of arts can and should be used to support students, such as drama, creative writing, music and others. The main aim of this work is to suggest that other intelligences, in the case of this study, bodily-kinesthetic, can be used to help improve pronunciation.

Keywords: multiple intelligences, pronunciation, effective pronunciation trainings, short drills, musical intelligence, bodily-kinesthetic intelligence

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Authors: Aziz Ikhlef

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Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Lakshmidevi Sreeramareddy, Komalpreet Kaur, Nane Pothier

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Graphical-based passwords have existed for decades. Their major advantage is that they are easier to remember than an alphanumeric password. However, their disadvantage (especially recognition-based passwords) is the smaller password space, making them more vulnerable to brute force attacks. Graphical passwords are also highly susceptible to the shoulder-surfing effect. The gesture-based password method that we developed is a grid-free, template-free method. In this study, we evaluated the gesture-based passwords for usability and vulnerability. The results of the study are significant. We developed a gesture-based password application for data collection. Two modes of data collection were used: Creation mode and Replication mode. In creation mode (Session 1), users were asked to create six different passwords and reenter each password five times. In replication mode, users saw a password image created by some other user for a fixed duration of time. Three different duration timers, such as 5 seconds (Session 2), 10 seconds (Session 3), and 15 seconds (Session 4), were used to mimic the shoulder-surfing attack. After the timer expired, the password image was removed, and users were asked to replicate the password. There were 74, 57, 50, and 44 users participated in Session 1, Session 2, Session 3, and Session 4 respectfully. In this study, the machine learning algorithms have been applied to determine whether the person is a genuine user or an imposter based on the password entered. Five different machine learning algorithms were deployed to compare the performance in user authentication: namely, Decision Trees, Linear Discriminant Analysis, Naive Bayes Classifier, Support Vector Machines (SVMs) with Gaussian Radial Basis Kernel function, and K-Nearest Neighbor. Gesture-based password features vary from one entry to the next. It is difficult to distinguish between a creator and an intruder for authentication. For each password entered by the user, four features were extracted: password score, password length, password speed, and password size. All four features were normalized before being fed to a classifier. Three different classifiers were trained using data from all four sessions. Classifiers A, B, and C were trained and tested using data from the password creation session and the password replication with a timer of 5 seconds, 10 seconds, and 15 seconds, respectively. The classification accuracies for Classifier A using five ML algorithms are 72.5%, 71.3%, 71.9%, 74.4%, and 72.9%, respectively. The classification accuracies for Classifier B using five ML algorithms are 69.7%, 67.9%, 70.2%, 73.8%, and 71.2%, respectively. The classification accuracies for Classifier C using five ML algorithms are 68.1%, 64.9%, 68.4%, 71.5%, and 69.8%, respectively. SVMs with Gaussian Radial Basis Kernel outperform other ML algorithms for gesture-based password authentication. Results confirm that the shorter the duration of the shoulder-surfing attack, the higher the authentication accuracy. In conclusion, behavioral features extracted from the gesture-based passwords lead to less vulnerable user authentication.

Keywords: authentication, gesture-based passwords, machine learning algorithms, shoulder-surfing attacks, usability

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Authors: Claire Tranter, Coral Dando

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Gathering information from others is a fundamental goal for those concerned with investigating crime, and protecting national and international security. Persuading an individual to move from an opposing to converging viewpoint, and an understanding on the cognitive style behind this change can serve to increase understanding of traditional face-to-face interactions, as well as synthetic environments (SEs) often used for communication across varying geographical locations. SEs are growing in usage, and with this increase comes an increase in crime being undertaken online. Communication technologies can allow people to mask their real identities, supporting anonymous communication which can raise significant challenges for investigators when monitoring and managing these conversations inside SEs. To date, the psychological literature concerning how to maximise information-gain in SEs for real-world interviewing purposes is sparse, and as such this aspect of social cognition is not well understood. Here, we introduce an overview of a novel programme of PhD research which seeks to enhance understanding of cross-cultural and cross-gender communication in SEs for maximising information gain. Utilising a dyadic jury paradigm, participants interacted with a confederate who attempted to persuade them to the opposing verdict across three distinct environments: face-to-face, instant messaging, and a novel virtual reality environment utilising avatars. Participants discussed a criminal scenario, acting as a two-person (male; female) jury. Persuasion was manipulated by the confederate claiming an opposing viewpoint (guilty v. not guilty) to the naïve participants from the outset. Pre and post discussion data, and observational digital recordings (voice and video) of participant’ discussion performance was collected. Information regarding cognitive style was also collected to ascertain participants need for cognitive closure and biases towards jumping to conclusions. Findings revealed that individuals communicating via an avatar in a virtual reality environment reacted in a similar way, and thus equally persuasive, when compared to individuals communicating face-to-face. Anonymous instant messaging however created a resistance to persuasion in participants, with males showing a significant decline in persuasive outcomes compared to face to face. The findings reveal new insights particularly regarding the interplay of persuasion on gender and modality, with anonymous instant messaging enhancing resistance to persuasion attempts. This study illuminates how varying SE can support new theoretical and applied understandings of how judgments are formed and modified in response to advocacy.

Keywords: applied cognition, persuasion, social media, virtual reality

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Authors: Atbin Mahabbati, Jason Beringer, Matthias Leopold

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To address the global challenges of climate and environmental changes, there is a need for quantifying and reducing uncertainties in environmental data, including observations of carbon, water, and energy. Global eddy covariance flux tower networks (FLUXNET), and their regional counterparts (i.e., OzFlux, AmeriFlux, China Flux, etc.) were established in the late 1990s and early 2000s to address the demand. Despite the capability of eddy covariance in validating process modelling analyses, field surveys and remote sensing assessments, there are some serious concerns regarding the challenges associated with the technique, e.g. data gaps and uncertainties. To address these concerns, this research has developed an ensemble model to fill the data gaps of CO₂ flux to avoid the limitations of using a single algorithm, and therefore, provide less error and decline the uncertainties associated with the gap-filling process. In this study, the data of five towers in the OzFlux Network (Alice Springs Mulga, Calperum, Gingin, Howard Springs and Tumbarumba) during 2013 were used to develop an ensemble machine learning model, using five feedforward neural networks (FFNN) with different structures combined with an eXtreme Gradient Boosting (XGB) algorithm. The former methods, FFNN, provided the primary estimations in the first layer, while the later, XGB, used the outputs of the first layer as its input to provide the final estimations of CO₂ flux. The introduced model showed slight superiority over each single FFNN and the XGB, while each of these two methods was used individually, overall RMSE: 2.64, 2.91, and 3.54 g C m⁻² yr⁻¹ respectively (3.54 provided by the best FFNN). The most significant improvement happened to the estimation of the extreme diurnal values (during midday and sunrise), as well as nocturnal estimations, which is generally considered as one of the most challenging parts of CO₂ flux gap-filling. The towers, as well as seasonality, showed different levels of sensitivity to improvements provided by the ensemble model. For instance, Tumbarumba showed more sensitivity compared to Calperum, where the differences between the Ensemble model on the one hand and the FFNNs and XGB, on the other hand, were the least of all 5 sites. Besides, the performance difference between the ensemble model and its components individually were more significant during the warm season (Jan, Feb, Mar, Oct, Nov, and Dec) compared to the cold season (Apr, May, Jun, Jul, Aug, and Sep) due to the higher amount of photosynthesis of plants, which led to a larger range of CO₂ exchange. In conclusion, the introduced ensemble model slightly improved the accuracy of CO₂ flux gap-filling and robustness of the model. Therefore, using ensemble machine learning models is potentially capable of improving data estimation and regression outcome when it seems to be no more room for improvement while using a single algorithm.

Keywords: carbon flux, Eddy covariance, extreme gradient boosting, gap-filling comparison, hybrid model, OzFlux network

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