Search results for: in-situ atmospheric sensing

Authors: Malika Souada, Juanita Rausch, Benjamin Guinot, Christine Bugajny

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The increase of global commerce and tourism makes the shipping sector an important contributor of atmospheric pollution. Both, airborne particles and gaseous pollutants have negative impact on health and climate. This is especially the case in port cities, due to the proximity of the exposed population to the shipping emissions in addition to other multiple sources of pollution linked to the surrounding urban activity. The objective of this study is to determine the concentrations of fine particles (immission), specifically PM2.5, PM1, PM0.3, BC and sulphates, in a context where maritime passenger traffic plays an important role (port area of Bordeaux centre). The methodology is based on high temporal resolution measurements of pollutants, correlated with meteorological and ship movements data. Particles and gaseous pollutants from seven maritime passenger ships were sampled and analysed during the docking, manoeuvring and berthing phases. The particle mass measurements were supplemented by measurements of the number concentration of ultrafine particles (<300 nm diameter). The different measurement points were chosen by taking into account the local meteorological conditions and by pre-modelling the dispersion of the smoke plumes. The results of the measurement campaign carried out during the summer of 2021 in the port of Bordeaux show that the detection of concentrations of particles emitted by ships proved to be punctual and stealthy. Punctual peaks of ultrafine particle concentration in number (P#/m3) and BC (ng/m3) were measured during the docking phases of the ships, but the concentrations returned to their background level within minutes. However, it appears that the influence of the docking phases does not significantly affect the air quality of Bordeaux centre in terms of mass concentration. Additionally, no clear differences in PM2.5 concentrations between the periods with and without ships at berth were observed. The urban background pollution seems to be mainly dominated by exhaust and non-exhaust road traffic emissions. However, temporal high-resolution measurements suggest a probable emission of gaseous precursors responsible for the formation of secondary aerosols related to the ship activities. This was evidenced by the high values of the PM1/BC and PN/BC ratios, tracers of non-primary particle formation, during periods of ship berthing vs. periods without ships at berth. The research findings from this study provide robust support for port area air quality assessment and source apportionment.

Keywords: characterization, fine particulate matter, harbour air quality, shipping impacts

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Authors: Misha Nedeljkovich

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In the film’s famous scene (Roma città aperta-1945), Pina (Anna Magnani) collapses in the street when machined-gunned by a German soldier. Her son Marcello (Vito Annchiarico) tries to revive her. Her death is signaling not closure, but the cycle of life; Marcello saves Francesco with the shawl taken from his mother’s corpse. One pivotal scene in Brief Encounter (1945) occurs in the apartment of Alec’s (Trevor Howard) friend Stephen (Valentine Dyall), when Stephen returns to catch Alec and Laura (Celia Johnson) together alone. David Lean directs this scene using her shawl as a sign of in flagrante delicto. In La Strada (1954), Gelsomina (Giulietta Masina) was waving good bye when her mother sensing impending doom changed her mind and desperately tried to stop her waving back with her shawl: Don’t go my daughter! Your shawl! Your shawl! Gelsomina refuses to return, waving back: It’s time to go! Stanley Kubrick’s tale of a boxer who crosses a mobster to win the heart of a lady, Killer’s Kiss (1955), reminds us that Times Square used to contain sweaty boxing gyms and dance halls. The film’s longest Times Square interlude is its oddest: the boxer Davie Gordon played by Jamie Smith has his shawl stolen by two playful men in Shriners’ hats who are silent except for one who blows a harmonica, faintly heard over honking cabs and overheard conversations. This long sequence appears to be joining in on directors’ shawl conversations with Kubrick’s own twist. Principle characters will never know why all this happened to them that evening. Love, death, happiness and everlasting misery all of that is caused by Dave’s shawl. Finally, the decade of cinematic shawl conversations conclude in Betolucci’s Before the Revolution (Prima della rivoluzione–1964). One of his character’s lifts up a shawl asking if this was a Rossellini’s shawl. I argue that exploring complimentary allusions in a film where directors are acknowledging their own great debt to another film or filmmaker will further our knowledge of film history adding both depth and resonance to the great works in cinema.

Keywords: allusions, Bertolucci, Fellini, homage, Kubrick, lean, Rossellini

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Authors: Deni̇z Ezgi̇ Gülmez, Mesut Kirca

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Nanoporous (np) metals have attracted considerable attention owing to their cellular morphological features at atomistic scale which yield ultra-high specific surface area awarding a great potential to be employed in diverse applications such as catalytic, electrocatalytic, sensing, mechanical and optical. As one of the carbon based nanostructures, fullerenes are also another type of outstanding nanomaterials that have been extensively investigated due to their remarkable chemical, mechanical and optical properties. In this study, the idea of improving the mechanical behavior of nanoporous metals by inclusion of the fullerenes, which offers a new metal-carbon nanocomposite material, is examined and discussed. With this motivation, tensile mechanical behavior of nanoporous metals reinforced with carbon fullerenes is investigated by classical molecular dynamics (MD) simulations. Atomistic models of the nanoporous metals with ultrathin ligaments are obtained through a stochastic process simply based on the intersection of spherical volumes which has been used previously in literature. According to this technique, the atoms within the ensemble of intersecting spherical volumes is removed from the pristine solid block of the selected metal, which results in porous structures with spherical cells. Following this, fullerene units are added into the cellular voids to obtain final atomistic configurations for the numerical tensile tests. Several numerical specimens are prepared with different number of fullerenes per cell and with varied fullerene sizes. LAMMPS code was used to perform classical MD simulations to conduct uniaxial tension experiments on np models filled by fullerenes. The interactions between the metal atoms are modeled by using embedded atomic method (EAM) while adaptive intermolecular reactive empirical bond order (AIREBO) potential is employed for the interaction of carbon atoms. Furthermore, atomic interactions between the metal and carbon atoms are represented by Lennard-Jones potential with appropriate parameters. In conclusion, the ultimate goal of the study is to present the effects of fullerenes embedded into the cellular structure of np metals on the tensile response of the porous metals. The results are believed to be informative and instructive for the experimentalists to synthesize hybrid nanoporous materials with improved properties and multifunctional characteristics.

Keywords: fullerene, intersecting spheres, molecular dynamic, nanoporous metals

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Authors: Tony R. Walker, N. Devin MacAskill, Andrew Thalhiemer

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Sydney Harbour, Nova Scotia has long been subject to effluent and atmospheric inputs of metals, polycyclic aromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) from a large coking operation and steel plant that operated in Sydney for nearly a century until closure in 1988. Contaminated effluents from the industrial site resulted in the creation of the Sydney Tar Ponds, one of Canada’s largest contaminated sites. Since its closure, there have been several attempts to remediate this former industrial site and finally, in 2004, the governments of Canada and Nova Scotia committed to remediate the site to reduce potential ecological and human health risks to the environment. The Sydney Tar Ponds and Coke Ovens cleanup project has become the most prominent remediation project in Canada today. As an integral part of remediation of the site (i.e., which consisted of solidification/stabilization and associated capping of the Tar Ponds), an extensive multiple media environmental effects program was implemented to assess what effects remediation had on the surrounding environment, and, in particular, harbour sediments. Additionally, longer-term natural sediment recovery rates of select contaminants predicted for the harbour sediments were compared to current conditions. During remediation, potential contributions to sediment quality, in addition to remedial efforts, were evaluated which included a significant harbour dredging project, propeller wash from harbour traffic, storm events, adjacent loading/unloading of coal and municipal wastewater treatment discharges. Two sediment sampling methodologies, sediment grab and gravity corer, were also compared to evaluate the detection of subtle changes in sediment quality. Results indicated that overall spatial distribution pattern of historical contaminants remains unchanged, although at much lower concentrations than previously reported, due to natural recovery. Measurements of sediment indicator parameter concentrations confirmed that natural recovery rates of Sydney Harbour sediments were in broad agreement with predicted concentrations, in spite of ongoing remediation activities. Overall, most measured parameters in sediments showed little temporal variability even when using different sampling methodologies, during three years of remediation compared to baseline, except for the detection of significant increases in total PAH concentrations noted during one year of remediation monitoring. The data confirmed the effectiveness of mitigation measures implemented during construction relative to harbour sediment quality, despite other anthropogenic activities and the dynamic nature of the harbour.

Keywords: contaminated sediment, monitoring, recovery, remediation

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Authors: Belcher Fulele, W. A. A. Ddamba

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Study of solvent systems contributes to the understanding of intermolecular interactions that occur in binary mixtures. These interactions involves among others strong dipole-dipole interactions and weak van de Waals interactions which are of significant application in pharmaceuticals, solvent extractions, design of reactors and solvent handling and storage processes. Binary mixtures of solvents can thus be used as a model to interpret thermodynamic behavior that occur in a real solution mixture. Densities of pure DFM, n-alkanes (n-pentane, n-hexane, n-heptane and n-octane) and amides (N-methylformamide, N-ethylformamide, N,N-dimethylformamide and N,N-dimethylacetamide) as well as their [DFM + ((C5-C8) n-alkane or amide)] binary mixtures over the entire composition range, have been reported at temperature 293.15, 298.15 and 303.15 K and atmospheric pressure. These data has been used to derive the thermodynamic properties: the excess molar volume of solution, apparent molar volumes, excess partial molar volumes, limiting excess partial molar volumes, limiting partial molar volumes of each component of a binary mixture. The results are discussed in terms of possible intermolecular interactions and structural effects that occur in the binary mixtures. The variation of excess molar volume with DFM composition for the [DFM + (C5-C7) n-alkane] binary mixture exhibit a sigmoidal behavior while for the [DFM + n-octane] binary system, positive deviation of excess molar volume function was observed over the entire composition range. For each of the [DFM + (C5-C8) n-alkane] binary mixture, the excess molar volume exhibited a fall with increase in temperature. The excess molar volume for each of [DFM + (NMF or NEF or DMF or DMA)] binary system was negative over the entire DFM composition at each of the three temperatures investigated. The negative deviations in excess molar volume values follow the order: DMA > DMF > NEF > NMF. Increase in temperature has a greater effect on component self-association than it has on complex formation between molecules of components in [DFM + (NMF or NEF or DMF or DMA)] binary mixture which shifts complex formation equilibrium towards complex to give a drop in excess molar volume with increase in temperature. The Prigogine-Flory-Patterson model has been applied at 298.15 K and reveals that the free volume is the most important contributing term to the excess experimental molar volume data for [DFM + (n-pentane or n-octane)] binary system. For [DFM + (NMF or DMF or DMA)] binary mixture, the interactional term and characteristic pressure term contributions are the most important contributing terms in describing the sign of experimental excess molar volume. The mixture systems contributed to the understanding of interactions of polar solvents with proteins (amides) with non-polar solvents (alkanes) in biological systems.

Keywords: alkanes, amides, excess thermodynamic parameters, Prigogine-Flory-Patterson model

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Authors: S. Chowdhury, A. Corlett

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Large tsunamis strike the British Columbia coast every few hundred years. The Cascadia Subduction Zone, which extends along the Pacific coast from Vancouver Island to Northern California is one of the most seismically active regions in Canada. Significant earthquakes have occurred in this region, including the 1700 Cascade Earthquake with an estimated magnitude of 9.2. Based on geological records, experts have predicted a 'great earthquake' of a similar magnitude within this region may happen any time. This earthquake is expected to generate a large tsunami that could impact the coastal communities on Vancouver Island. Since many of these communities are in remote locations, they are more likely to be vulnerable, as the post-earthquake relief efforts would be impacted by the damage to critical road infrastructures. To assess the coastal vulnerability within these communities, a hydrodynamic model has been developed using MIKE-21 software. We have considered a 500 year probabilistic earthquake design criteria including the subsidence in this model. The bathymetry information was collected from Canadian Hydrographic Services (CHS), and National Oceanic Atmospheric and Administration (NOAA). The arial survey was conducted using a Cessna-172 aircraft for the communities, and then the information was converted to generate a topographic digital elevation map. Both survey information was incorporated into the model, and the domain size of the model was about 1000km x 1300km. This model was calibrated with the tsunami occurred off the west coast of Moresby Island on October 28, 2012. The water levels from the model were compared with two tide gauge stations close to the Vancouver Island and the output from the model indicates the satisfactory result. For this study, the design water level was considered as High Water Level plus the Sea Level Rise for 2100 year. The hourly wind speeds from eight directions were collected from different wind stations and used a 200-year return period wind speed in the model for storm events. The regional model was set for 12 hrs simulation period, which takes more than 16 hrs to complete one simulation using double Xeon-E7 CPU computer plus a K-80 GPU. The boundary information for the local model was generated from the regional model. The local model was developed using a high resolution mesh to estimate the coastal flooding for the communities. It was observed from this study that many communities will be effected by the Cascadia tsunami and the inundation maps were developed for the communities. The infrastructures inside the coastal inundation area were identified. Coastal vulnerability planning and resilient design solutions will be implemented to significantly reduce the risk.

Keywords: tsunami, coastal flooding, coastal vulnerable, earthquake, Vancouver, wave propagation

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Authors: Jhoga Parth, T. Nasar, K. V. Anand

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An idealized definition of shoreline is that it is the zone of coincidence of three spheres such as atmosphere, lithosphere, and hydrosphere. Despite its apparent simplicity, this definition in practice a challenge to apply. In reality, the shoreline location deviates continually through time, because of various dynamic factors such as wave characteristics, currents, coastal orientation and the bathymetry, which makes the shoreline volatile. This necessitates us to monitor the shoreline in a temporal basis. If shoreline’s nature is understood at particular coastal stretch, it need not be the same trend at the other location, though belonging to the same sea front. Shoreline change is hence a local phenomenon and has to be studied with great intensity considering as many factors involved as possible. Erosion and accretion of sediment are such natures of a shoreline, which needs to be quantified by comparing with its predeceasing variations and understood before implementing any coastal projects. In recent years, advent of Global Positioning System (GPS) and Geographic Information System (GIS) acts as an emerging tool to quantify the intra and inter annual sediment rate getting accreted or deposited compared to other conventional methods in regards with time was taken and man power. Remote sensing data, on the other hand, paves way to acquire historical sets of data where field data is unavailable with a higher resolution. Short term and long term period shoreline change can be accurately tracked and monitored using a software residing in GIS - Digital Shoreline Analysis System (DSAS) developed by United States Geological Survey (USGS). In the present study, using DSAS, End Point Rate (EPR) is calculated analyze the intra-annual changes, and Linear Rate Regression (LRR) is adopted to study inter annual changes of shoreline. The shoreline changes are quantified for the scenario during the construction of breakwater in Ponnani river inlet along Kerala coast, India. Ponnani is a major fishing and landing center located 10°47’12.81”N and 75°54’38.62”E in Malappuram district of Kerala, India. The rate of erosion and accretion is explored using satellite and field data. The full paper contains the rate of change of shoreline, and its analysis would provide us understanding the behavior of the inlet at the study area during the construction of the training walls.

Keywords: DSAS, end point rate, field measurements, geo-informatics, shoreline variation

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Authors: Meng Miao, Jeongwoo Han, Cam Nguyen

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Ultra-wideband (UWB) time-domain impulse communication and radar systems use ultra-short duration pulses in the sub-nanosecond regime, instead of continuous sinusoidal waves, to transmit information. The pulse directly generates a very wide-band instantaneous signal with various duty cycles depending on specific usages. In UWB systems, the total transmitted power is spread over an extremely wide range of frequencies; the power spectral density is extremely low. This effectively results in extremely small interference to other radio signals while maintains excellent immunity to interference from these signals. UWB devices can therefore work within frequencies already allocated for other radio services, thus helping to maximize this dwindling resource. Therefore, impulse UWB technique is attractive for realizing high-data-rate, short-range communications, ground penetrating radar (GPR), and military radar with relatively low emission power levels. UWB antennas are the key element dictating the transmitted and received pulse shape and amplitude in both time and frequency domain. They should have good impulse response with minimal distortion. To facilitate integration with transmitters and receivers employing microwave integrated circuits, UWB antennas enabling direct integration are preferred. We present the development of two UWB antennas operating from 3.1 to 10.6 GHz and 0.3-6 GHz for UWB systems that provide direct integration with microwave integrated circuits. The operation of these antennas is based on the principle of wave propagation on a non-uniform transmission line. Time-domain EM simulation is conducted to optimize the antenna structures to minimize reflections occurring at the open-end transition. Calculated and measured results of these UWB antennas are presented in both frequency and time domains. The antennas have good time-domain responses. They can transmit and receive pulses effectively with minimum distortion, little ringing, and small reflection, clearly demonstrating the signal fidelity of the antennas in reproducing the waveform of UWB signals which is critical for UWB sensors and communication systems. Good performance together with seamless microwave integrated-circuit integration makes these antennas good candidates not only for UWB applications but also for integration with printed-circuit UWB transmitters and receivers.

Keywords: antennas, ultra-wideband, UWB, UWB communication systems, UWB radar systems

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Authors: Sai Snehitha Yadavalli, K. Sruthi, Swati Ghosh Acharyya

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Heavy metal ions are toxic to humans and all living species when exposed in large quantities or for long durations. Though Fe acts as a nutrient, when intake is in large quantities, it becomes toxic. These toxic heavy metal ions, when consumed through water, will cause many disorders and are harmful to all flora and fauna through biomagnification. Specifically, humans are prone to innumerable diseases ranging from skin to gastrointestinal, neurological, etc. In higher quantities, they even cause cancer in humans. Detection of these toxic heavy metal ions in water is thus important. Traditionally, the detection of heavy metal ions in water has been done by techniques like Inductively Coupled Plasma Mass Spectroscopy (ICPMS) and Atomic Absorption Spectroscopy (AAS). Though these methods offer accurate quantitative analysis, they require expensive equipment and cannot be used for on-site measurements. Anodic Stripping Voltammetry is a good alternative as the equipment is affordable, and measurements can be made at the river basins or lakes. In the current study, Square Wave Anodic Stripping Voltammetry (SWASV) was used to detect the heavy metal ions in water. Literature reports various electrodes on which deposition of heavy metal ions was carried out like Bismuth, Polymers, etc. The working electrode used in this study is a polyvinyl chloride (PVC) modified glassy carbon electrode (GCE). Ag/AgCl reference electrode and Platinum counter electrode were used. Biologic Potentiostat SP 300 was used for conducting the experiments. Through this work of simultaneous detection, four heavy metal ions were successfully detected at a time. The influence of modifying GCE with PVC was studied in comparison with unmodified GCE. The simultaneous detection of Cd⁺², Fe⁺², Co⁺², Pb⁺² heavy metal ions was done using PVC modified GCE by drop casting 1 wt.% of PVC dissolved in Tetra Hydro Furan (THF) solvent onto GCE. The concentration of all heavy metal ions was 0.2 mg/L, as shown in the figure. The scan rate was 0.1 V/s. Detection parameters like pH, scan rate, temperature, time of deposition, etc., were optimized. It was clearly understood that PVC helped in increasing the sensitivity and selectivity of detection as the current values are higher for PVC-modified GCE compared to unmodified GCE. The peaks were well defined when PVC-modified GCE was used.

Keywords: cadmium, cobalt, electrochemical sensing, glassy carbon electrodes, heavy metal Ions, Iron, lead, polyvinyl chloride, potentiostat, square wave anodic stripping voltammetry

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Authors: Shelley Harrington

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As a result of increasingly dynamic business environments, the creation and fostering of dynamic capabilities, [those capabilities that enable sustained competitive success despite of dynamism through the awareness and reconfiguration of internal and external competencies], supported by organisational learning [a dynamic capability] has gained increased and prevalent momentum in the research arena. Presenting findings funded by the Economic Social Research Council, this paper investigates the extent to which Senior Management Team (SMT) personality (at the trait and facet level) is associated with the creation of dynamic managerial capabilities at the team level, and effective organisational learning/knowledge sharing within the firm. In doing so, this research highlights the importance of micro-foundations in organisational psychology and specifically dynamic capabilities, a field which to date has largely ignored the importance of psychology in understanding these important and necessary capabilities. Using a direct measure of personality (NEO PI-3) at the trait and facet level across 32 high technology and finance firms in the UK, their CEOs (N=32) and their complete SMTs [N=212], a new measure of dynamic managerial capabilities at the team level was created and statistically validated for use within the work. A quantitative methodology was employed with regression and gap analysis being used to show the empirical foundations of personality being positioned as a micro-foundation of dynamic capabilities. The results of this study found that personality homogeneity within the SMT was required to strengthen the dynamic managerial capabilities of sensing, seizing and transforming, something which was required to reflect strong organisational learning at middle management level [N=533]. In particular, it was found that the greater the difference [t-score gaps] between the personality profiles of a Chief Executive Officer (CEO) and their complete, collective SMT, the lower the resulting self-reported nature of dynamic managerial capabilities. For example; the larger the difference between a CEOs level of dutifulness, a facet contributing to the definition of conscientiousness, and their SMT’s level of dutifulness, the lower the reported level of transforming, a capability fundamental to strategic change in a dynamic business environment. This in turn directly questions recent trends, particularly in upper echelons research highlighting the need for heterogeneity within teams. In doing so, it successfully positions personality as a micro-foundation of dynamic capabilities, thus contributing to recent discussions from within the strategic management field calling for the need to empirically explore dynamic capabilities at such a level.

Keywords: dynamic managerial capabilities, senior management teams, personality, dynamism

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Authors: H. E. Elzain, S. Y. Chung, V. Senapathi, Kye-Hun Park

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Groundwater is considered a significant source for drinking and irrigation purposes in Miryang city, and it is attributed to a limited number of a surface water reservoirs and high seasonal variations in precipitation. Population growth in addition to the expansion of agricultural land uses and industrial development may affect the quality and management of groundwater. This research utilized multidisciplinary approaches of geostatistics such as multivariate statistics, factor analysis, cluster analysis and kriging technique in order to identify the hydrogeochemical process and characterizing the control factors of the groundwater geochemistry distribution for developing risk maps, exploiting data obtained from chemical investigation of groundwater samples under the area of study. A total of 79 samples have been collected and analyzed using atomic absorption spectrometer (AAS) for major and trace elements. Chemical maps using 2-D spatial Geographic Information System (GIS) of groundwater provided a powerful tool for detecting the possible potential sites of groundwater that involve the threat of contamination. GIS computer based map exhibited that the higher rate of contamination observed in the central and southern area with relatively less extent in the northern and southwestern parts. It could be attributed to the effect of irrigation, residual saline water, municipal sewage and livestock wastes. At wells elevation over than 85m, the scatter diagram represents that the groundwater of the research area was mainly influenced by saline water and NO3. Level of pH measurement revealed low acidic condition due to dissolved atmospheric CO2 in the soil, while the saline water had a major impact on the higher values of TDS and EC. Based on the cluster analysis results, the groundwater has been categorized into three group includes the CaHCO3 type of the fresh water, NaHCO3 type slightly influenced by sea water and Ca-Cl, Na-Cl types which are heavily affected by saline water. The most predominant water type was CaHCO3 in the study area. Contamination sources and chemical characteristics were identified from factor analysis interrelationship and cluster analysis. The chemical elements that belong to factor 1 analysis were related to the effect of sea water while the elements of factor 2 associated with agricultural fertilizers. The degree level, distribution, and location of groundwater contamination have been generated by using Kriging methods. Thus, geostatistics model provided more accurate results for identifying the source of contamination and evaluating the groundwater quality. GIS was also a creative tool to visualize and analyze the issues affecting water quality in the Miryang city.

Keywords: groundwater characteristics, GIS chemical maps, factor analysis, cluster analysis, Kriging techniques

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Authors: Ming-Chien Su, Yi-Zih Chen, Nien-Hsin Kao, Hideaki Shibata

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The major component of the atmosphere is nitrogen, yet atmospheric nitrogen has limited availability for biological use. Human activities have produced different types of nitrogen related compounds such as nitrogen oxides from combustion, nitrogen fertilizers from farming, and the nitrogen compounds from waste and wastewater, all of which have impacted the environment. Many studies have indicated the N-footprint is dominated by food, followed by housing, transportation, and goods and services sectors. To solve the impact issues from agricultural land, nitrogen cycle research is one of the key solutions. The study site is located in Hualien County, Taiwan, a major rice and food production area of Taiwan. Importantly, environmentally friendly farming has been promoted for years, and an environmental indicator system has been established by previous authors based on the concept of resilience capacity index (RCI) and environmental performance index (EPI). Nitrogen management is required for food production, as excess N causes environmental pollution. Therefore it is very important to develop a roadmap of the nitrogen footprint, and to integrate it with environmental indicators. The key focus of the study thus addresses (1) understanding the environmental impact caused by the nitrogen cycle of food products and (2) uncovering the trend of the N-footprint of agricultural products in Hualien, Taiwan. The N-footprint model was applied, which included both crops and energy consumption in the area. All data were adapted from government statistics databases and crosschecked for consistency before modeling. The actions involved with agricultural production were evaluated and analyzed for nitrogen loss to the environment, as well as measuring the impacts to humans and the environment. The results showed that rice makes up the largest share of agricultural production by weight, at 80%. The dominant meat production is pork (52%) and poultry (40%); fish and seafood were at similar levels to pork production. The average per capita food consumption in Taiwan is 2643.38 kcal capita−1 d−1, primarily from rice (430.58 kcal), meats (184.93 kcal) and wheat (ca. 356.44 kcal). The average protein uptake is 87.34 g capita−1 d−1, and 51% is mainly from meat, milk, and eggs. The preliminary results showed that the nitrogen footprint of food production is 34 kg N per capita per year, congruent with the results of Shibata et al. (2014) for Japan. These results provide a better understanding of the nitrogen demand and loss in the environment, and the roadmap can furthermore support the establishment of nitrogen policy and strategy. Additionally, the results serve to develop a roadmap of the nitrogen cycle of an environmentally friendly farming area, thus illuminating the nitrogen demand and loss of such areas.

Keywords: agriculture productions, energy consumption, environmental indicator, nitrogen footprint

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Fabiana Franceschi, Martha Cobo, Manuel Figueredo

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Bogotá, the capital of Colombia, is its largest city and one of the most polluted in Latin America due to the fast economic growth over the last ten years. Bogotá has been affected by high pollution events which led to the high concentration of PM10 and NO2, exceeding the local 24-hour legal limits (100 and 150 g/m3 each). The most important pollutants in the city are PM10 and PM2.5 (which are associated with respiratory and cardiovascular problems) and it is known that their concentrations in the atmosphere depend on the local meteorological factors. Therefore, it is necessary to establish a relationship between the meteorological variables and the concentrations of the atmospheric pollutants such as PM10, PM2.5, CO, SO2, NO2 and O3. This study aims to determine the interrelations between meteorological variables and air pollutants in Bogotá, using data mining techniques. Data from 13 monitoring stations were collected from the Bogotá Air Quality Monitoring Network within the period 2010-2015. The Principal Component Analysis (PCA) algorithm was applied to obtain primary relations between all the parameters, and afterwards, the K-means clustering technique was implemented to corroborate those relations found previously and to find patterns in the data. PCA was also used on a per shift basis (morning, afternoon, night and early morning) to validate possible variation of the previous trends and a per year basis to verify that the identified trends have remained throughout the study time. Results demonstrated that wind speed, wind direction, temperature, and NO2 are the most influencing factors on PM10 concentrations. Furthermore, it was confirmed that high humidity episodes increased PM2,5 levels. It was also found that there are direct proportional relationships between O3 levels and wind speed and radiation, while there is an inverse relationship between O3 levels and humidity. Concentrations of SO2 increases with the presence of PM10 and decreases with the wind speed and wind direction. They proved as well that there is a decreasing trend of pollutant concentrations over the last five years. Also, in rainy periods (March-June and September-December) some trends regarding precipitations were stronger. Results obtained with K-means demonstrated that it was possible to find patterns on the data, and they also showed similar conditions and data distribution among Carvajal, Tunal and Puente Aranda stations, and also between Parque Simon Bolivar and las Ferias. It was verified that the aforementioned trends prevailed during the study period by applying the same technique per year. It was concluded that PCA algorithm is useful to establish preliminary relationships among variables, and K-means clustering to find patterns in the data and understanding its distribution. The discovery of patterns in the data allows using these clusters as an input to an Artificial Neural Network prediction model.

Keywords: air pollution, air quality modelling, data mining, particulate matter

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Authors: Kumar Shashvat, Amol P. Bhondekar

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In the midst of the five senses, odor is the most reminiscent and least understood. Odor testing has been mysterious and odor data fabled to most practitioners. The delinquent of recognition and classification of odor is important to achieve. The facility to smell and predict whether the artifact is of further use or it has become undesirable for consumption; the imitation of this problem hooked on a model is of consideration. The general industrial standard for this classification is color based anyhow; odor can be improved classifier than color based classification and if incorporated in machine will be awfully constructive. For cataloging of odor for peas, trees and cashews various discriminative approaches have been used Discriminative approaches offer good prognostic performance and have been widely used in many applications but are incapable to make effectual use of the unlabeled information. In such scenarios, generative approaches have better applicability, as they are able to knob glitches, such as in set-ups where variability in the series of possible input vectors is enormous. Generative models are integrated in machine learning for either modeling data directly or as a transitional step to form an indeterminate probability density function. The algorithms or models Linear Discriminant Analysis and Naive Bayes Classifier have been used for classification of the odor of cashews. Linear Discriminant Analysis is a method used in data classification, pattern recognition, and machine learning to discover a linear combination of features that typifies or divides two or more classes of objects or procedures. The Naive Bayes algorithm is a classification approach base on Bayes rule and a set of qualified independence theory. Naive Bayes classifiers are highly scalable, requiring a number of restraints linear in the number of variables (features/predictors) in a learning predicament. The main recompenses of using the generative models are generally a Generative Models make stronger assumptions about the data, specifically, about the distribution of predictors given the response variables. The Electronic instrument which is used for artificial odor sensing and classification is an electronic nose. This device is designed to imitate the anthropological sense of odor by providing an analysis of individual chemicals or chemical mixtures. The experimental results have been evaluated in the form of the performance measures i.e. are accuracy, precision and recall. The investigational results have proven that the overall performance of the Linear Discriminant Analysis was better in assessment to the Naive Bayes Classifier on cashew dataset.

Keywords: odor classification, generative models, naive bayes, linear discriminant analysis

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Authors: H. Arzani, Z. Arzani

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Every piece of rangeland has a different set of physical and biological characteristics. This requires the manager to synthesis various information for regular monitoring to define changes trend to get wright decision for sustainable management. So range managers need to use computerized technologies to monitor rangeland, and select. The best management practices. There are four examples of computerized technologies that can benefit sustainable management: (1) Photographic method for cover measurement: The method was tested in different vegetation communities in semi humid and arid regions. Interpretation of pictures of quadrats was done using Arc View software. Data analysis was done by SPSS software using paired t test. Based on the results, generally, photographic method can be used to measure ground cover in most vegetation communities. (2) GPS application for corresponding ground samples and satellite pixels: In two provinces of Tehran and Markazi, six reference points were selected and in each point, eight GPS models were tested. Significant relation among GPS model, time and location with accuracy of estimated coordinates was found. After selection of suitable method, in Markazi province coordinates of plots along four transects in each 6 sites of rangelands was recorded. The best time of GPS application was in the morning hours, Etrex Vista had less error than other models, and a significant relation among GPS model, time and location with accuracy of estimated coordinates was found. (3) Application of satellite data for rangeland monitoring: Focusing on the long term variation of vegetation parameters such as vegetation cover and production is essential. Our study in grass and shrub lands showed that there were significant correlations between quantitative vegetation characteristics and satellite data. So it is possible to monitor rangeland vegetation using digital data for sustainable utilization. (4) Rangeland suitability classification with GIS: Range suitability assessment can facilitate sustainable management planning. Three sub-models of sensitivity to erosion, water suitability and forage production out puts were entered to final range suitability classification model. GIS was facilitate classification of range suitability and produced suitability maps for sheep grazing. Generally digital computers assist range managers to interpret, modify, calibrate or integrating information for correct management.

Keywords: computer, GPS, GIS, remote sensing, photographic method, monitoring, rangeland ecosystem, management, suitability, sheep grazing

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Authors: Vinu Viswanath, Lawrence Dsouza, Ugo Ravon

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Syngas typically and intermediary gas product has a wide range of application of producing various chemical products, such as mixed alcohols, hydrogen, ammonia, Fischer-Tropsch products methanol, ethanol, aldehydes, alcohols, etc. There are several technologies available for the syngas production. An alternative to the conventional processes an attractive route of utilizing carbon dioxide and methane in equimolar ratio to generate syngas of ratio close to one has been developed which is also termed as Dry Reforming of Methane technology. It also gives the privilege to utilize the greenhouse gases like CO2 and CH4. The dry reforming process is highly endothermic, and indeed, ΔG becomes negative if the temperature is higher than 900K and practically, the reaction occurs at 1000-1100K. At this temperature, the sintering of the metal particle is happening that deactivate the catalyst. However, by using this strategy, the methane is just partially oxidized, and some cokes deposition occurs that causing the catalyst deactivation. The current research work was focused to mitigate the main challenges of dry reforming process such coke deposition, and metal sintering at high temperature.To achieve these objectives, we employed three different strategies of catalyst development. 1) Use of bulk catalysts such as olivine and pyrochlore type materials. 2) Use of metal doped support materials, like spinel and clay type material. 3) Use of core-shell model catalyst. In this approach, a thin layer (shell) of redox metal oxide is deposited over the MgAl2O4 /Al2O3 based support material (core). For the core-shell approach, an active metal is been deposited on the surface of the shell. The shell structure formed is a doped metal oxide that can undergo reduction and oxidation reactions (redox), and the core is an alkaline earth aluminate having a high affinity towards carbon dioxide. In the case of metal-doped support catalyst, the enhanced redox properties of doped CeO2 oxide and CO2 affinity property of alkaline earth aluminates collectively helps to overcome coke formation. For all of the mentioned three strategies, a systematic screening of the metals is carried out to optimize the efficiency of the catalyst. To evaluate the performance of them, the activity and stability test were carried out under reaction conditions of temperature ranging from 650 to 850 ̊C and an operating pressure ranging from 1 to 20 bar. The result generated infers that the core-shell model catalyst showed high activity and better stable DR catalysts under atmospheric as well as high-pressure conditions. In this presentation, we will show the results related to the strategy.

Keywords: carbon dioxide, dry reforming, supports, core shell catalyst

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Authors: Samineh Barmaki, Ville Jokinen, Esko Kankuri

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We report a microfluidic chip that can be used to modify the gaseous microenvironment of a cell-culture in ambient atmospheric conditions. The aim of the study is to show the cellular response to nitric oxide (NO) under hypoxic (oxygen < 5%) condition. Simultaneously targeting to hypoxic and nitric oxide will provide an opportunity for NO‑based therapeutics. Studies on cellular responses to lowered oxygen concentration or to gaseous mediators are usually carried out under a specific macro environment, such as hypoxia chambers, or with specific NO donor molecules that may have additional toxic effects. In our study, the chip consists of a microfluidic layer and a cell culture well, separated by a thin gas permeable polydimethylsiloxane (PDMS) membrane. The main design goal is to separate the gas oxygen scavenger and NO donor solutions, which are often toxic, from the cell media. Two different types of gas exchangers, titled 'pool' and 'meander' were tested. We find that the pool design allows us to reach a higher level of oxygen depletion than meander (24.32 ± 19.82 %vs -3.21 ± 8.81). Our microchip design can make the cells culture more simple and makes it easy to adapt existing cell culture protocols. Our first application is utilizing the chip to create hypoxic conditions on targeted areas of cell culture. In this study, oxygen scavenger sodium sulfite generates hypoxia and its effect on human embryonic kidney cells (HEK-293). The PDMS membrane was coated with fibronectin before initiating cell cultures, and the cells were grown for 48h on the chips before initiating the gas control experiments. The hypoxia experiments were performed by pumping of O₂-depleted H₂O into the microfluidic channel with a flow-rate of 0.5 ml/h. Image-iT® reagent as an oxygen level responser was mixed with HEK-293 cells. The fluorescent signal appears on cells stained with Image-iT® hypoxia reagent (after 6h of pumping oxygen-depleted H₂O through the microfluidic channel in pool area). The exposure to different levels of O₂ can be controlled by varying the thickness of the PDMS membrane. Recently, we improved the design of the microfluidic chip, which can control the microenvironment of two different gases at the same time. The hypoxic response was also improved from the new design of microchip. The cells were grown on the thin PDMS membrane for 30 hours, and with a flowrate of 0.1 ml/h; the oxygen scavenger was pumped into the microfluidic channel. We also show that by pumping sodium nitroprusside (SNP) as a nitric oxide donor activated under light and can generate nitric oxide on top of PDMS membrane. We are aiming to show cellular microenvironment response of HEK-293 cells to both nitric oxide (by pumping SNP) and hypoxia (by pumping oxygen scavenger solution) in separated channels in one microfluidic chip.

Keywords: hypoxia, nitric oxide, microenvironment, microfluidic chip, sodium nitroprusside, SNP

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Authors: Shawn G. Gallaher, Lilli E. Hirth

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As permafrost thaws with the continued warming of the Alaskan North Slope, a progressively thicker active thaw layer is evidently releasing previously sequestered nutrients, metals, and particulate matter exposed to fluvial transport. In this study, we estimate material fluxes on the North Slope of Alaska during the 2019-2022 melt seasons. The watershed of the Alaskan North Slope can be categorized into three regions: mountains, tundra, and coastal plain. Precipitation and discharge data were collected from repeat visits to 14 sample sites for biogeochemical surface water samples, 7 point discharge measurements, 3 project deployed meteorology stations, and 2 U. S. Geological Survey (USGS) continuous discharge observation sites. The timing, intensity, and spatial distribution of precipitation determine the material flux composition in the Sagavanirktok and surrounding bodies of water, with geogenic constituents (e.g., dissolved inorganic carbon (DIC)) expected from mountain flushed events and biogenic constituents (e.g., dissolved organic compound (DOC)) expected from transitional tundra precipitation events. Project goals include connecting late summer precipitation events to peak discharge to determine the responses of the watershed to localized atmospheric forcing. Field study measurements showed widespread precipitation in August 2019, generating an increase in total suspended solids, dissolved organic carbon, and iron fluxes from the tundra, shifting the main-stem mountain river biogeochemistry toward tundra source characteristics typically only observed during the spring floods. Intuitively, a large-scale precipitation event (as defined by this study as exceeding 12.5 mm of precipitation on a single observation day) would dilute a body of water; however, in this study, concentrations increased with higher discharge responses on several occasions. These large-scale precipitation events continue to produce peak constituent fluxes as the thaw layer increases in depth and late summer precipitation increases, evidenced by 6 large-scale events in July 2022 alone. This increase in late summer events is in sharp contrast to the 3 or fewer large events in July in each of the last 10 years. Changes in precipitation intensity, timing, and location have introduced late summer peak constituent flux events previously confined to the spring freshet.

Keywords: Alaska North Slope, arctic rivers, material flux, precipitation

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Authors: Patrícia T. Souza, Marina Ansolin, Eduardo A. C. Batista, Antonio J. A. Meirelles, Matthieu Tubino

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Lipid oxidation is a major cause of the deterioration of the quality of the biodiesel, because the waste generated damages the engines. Among the main undesirable effects are the increase of viscosity and acidity, leading to the formation of insoluble gums and sediments which cause the blockage of fuel filters. The auto-oxidation is defined as the spontaneous reaction of atmospheric oxygen with lipids. Unsaturated fatty acids are usually the components affected by such reactions. They are present as free fatty acids, fatty esters and glycerides. To determine the oxidative stability of biodiesels, through the induction period, IP, the Rancimat method is used, which allows continuous monitoring of the induced oxidation process of the samples. During the oxidation of the lipids, volatile organic acids are produced as byproducts, in addition, other byproducts, including alcohols and carbonyl compounds, may be further oxidized to carboxylic acids. By the methodology developed in this work using ion chromatography, IC, analyzing the water contained in the conductimetric vessel, were quantified organic anions of carboxylic acids in samples subjected to oxidation induced by Rancimat. The optimized chromatographic conditions were: eluent water:acetone (80:20 v/v) with 0.5 mM sulfuric acid; flow rate 0.4 mL min-1; injection volume 20 µL; eluent suppressor 20 mM LiCl; analytical curve from 1 to 400 ppm. The samples studied were methyl biodiesel from soybean oil and unsaturated fatty acids standards: oleic, linoleic and linolenic. The induced oxidation kinetics curves were constructed by analyzing the water contained in the conductimetric vessels which were removed, each one, from the Rancimat apparatus at prefixed intervals of time. About 3 g of sample were used under the conditions of 110 °C and air flow rate of 10 L h-1. The water of each conductimetric Rancimat measuring vessel, where the volatile compounds were collected, was filtered through a 0.45 µm filter and analyzed by IC. Through the kinetic data of the formation of the organic anions of carboxylic acids, the formation rates of the same were calculated. The observed order of the rates of formation of the anions was: formate >>> acetate > hexanoate > valerate for the oleic acid; formate > hexanoate > acetate > valerate for the linoleic acid; formate >>> valerate > acetate > propionate > butyrate for the linolenic acid. It is possible to suppose that propionate and butyrate are obtained mainly from linolenic acid and that hexanoate is originated from oleic and linoleic acid. For the methyl biodiesel the order of formation of anions was: formate >>> acetate > valerate > hexanoate > propionate. According to the total rate of formation these anions produced during the induced degradation of the fatty acids can be assigned the order of reactivity: linolenic acid > linoleic acid >>> oleic acid.

Keywords: anions of carboxylic acids, biodiesel, ion chromatography, oxidation

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Authors: Huinan Zhang, Wenjie Jiang

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Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Tony R. Walker, N. Devin MacAskill, Andrew Thalhiemer

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Sydney Harbour, Nova Scotia, Canada has long been subject to effluent and atmospheric inputs of contaminants, including thousands of tons of PAHs from a large coking and steel plant which operated in Sydney for nearly a century. Contaminants comprised of coal tar residues which were discharged from coking ovens into a small tidal tributary, which became known as the Sydney Tar Ponds (STPs), and subsequently discharged into Sydney Harbour. An Environmental Impact Statement concluded that mobilization of contaminated sediments posed unacceptable ecological risks, therefore immobilizing contaminants in the STPs using solidification and stabilization was identified as a primary source control remediation option to mitigate against continued transport of contaminated sediments from the STPs into Sydney Harbour. Recent developments in contaminant mass flux techniques focus on understanding “mobile” vs. “immobile” contaminants at remediation sites. Forensic source evaluations are also increasingly used for understanding origins of PAH contaminants in soils or sediments. Flux and forensic source evaluation-informed remediation decision-making uses this information to develop remediation end point goals aimed at reducing off-site exposure and managing potential ecological risk. This study included reviews of previous flux studies, calculating current mass flux estimates and a forensic assessment using PAH fingerprint techniques, during remediation of one of Canada’s most polluted sites at the STPs. Historically, the STPs was thought to be the major source of PAH contamination in Sydney Harbour with estimated discharges of nearly 800 kg/year of PAHs. However, during three years of remediation monitoring only 17-97 kg/year of PAHs were discharged from the STPs, which was also corroborated by an independent PAH flux study during the first year of remediation which estimated 119 kg/year. The estimated mass efflux of PAHs from the STPs during remediation was in stark contrast to ~2000 kg loading thought necessary to cause a short term increase in harbour sediment PAH concentrations. These mass flux estimates during remediation were also between three to eight times lower than PAHs discharged from the STPs a decade prior to remediation, when at the same time, government studies demonstrated on-going reduction in PAH concentrations in harbour sediments. Flux results were also corroborated using forensic source evaluations using PAH fingerprint techniques which found a common source of PAHs for urban soils, marine and aquatic sediments in and around Sydney. Coal combustion (from historical coking) and coal dust transshipment (from current coal transshipment facilities), are likely the principal source of PAHs in these media and not migration of PAH laden sediments from the STPs during a large scale remediation project.

Keywords: contaminated sediment, mass flux, forensic source evaluations, remediation

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Authors: Sulemana Ibrahim

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Food security remains a paramount global challenge, with vulnerable regions grappling with issues of hunger and malnutrition. This study embarks on a comprehensive exploration of data-driven strategies aimed at ameliorating food security in such regions. Our research employs a multifaceted approach, integrating data analytics to predict crop yields, optimizing supply chains, and enhancing food distribution networks. The study unfolds as a multi-dimensional analysis, commencing with the development of robust machine learning models harnessing remote sensing data, historical crop yield records, and meteorological data to foresee crop yields. These predictive models, underpinned by convolutional and recurrent neural networks, furnish critical insights into anticipated harvests, empowering proactive measures to confront food insecurity. Subsequently, the research scrutinizes supply chain optimization to address food security challenges, capitalizing on linear programming and network optimization techniques. These strategies intend to mitigate loss and wastage while streamlining the distribution of agricultural produce from field to fork. In conjunction, the study investigates food distribution networks with a particular focus on network efficiency, accessibility, and equitable food resource allocation. Network analysis tools, complemented by data-driven simulation methodologies, unveil opportunities for augmenting the efficacy of these critical lifelines. This study also considers the ethical implications and privacy concerns associated with the extensive use of data in the realm of food security. The proposed methodology outlines guidelines for responsible data acquisition, storage, and usage. The ultimate aspiration of this research is to forge a nexus between data science and food security policy, bestowing actionable insights to mitigate the ordeal of food insecurity. The holistic approach converging data-driven crop yield forecasts, optimized supply chains, and improved distribution networks aspire to revitalize food security in the most vulnerable regions, elevating the quality of life for millions worldwide.

Keywords: data-driven strategies, crop yield prediction, supply chain optimization, food distribution networks

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Authors: Marita Heyns

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Job insecurity is a distressing phenomenon which has far reaching consequences for both employees and their organizations. Previously, much attention has been given to the link between job insecurity and individual level performance outcomes, while less is known about how subjectively perceived job insecurity might transfer beyond the individual level to affect performance of the organization on an aggregated level. Research focusing on how employees’ fear of job loss might affect the organization’s ability to respond proactively to volatility and drastic change through applying its capabilities of sensing, seizing, and reconfiguring, appears to be practically non-existent. Equally little is known about the potential underlying mechanisms through which job insecurity might affect the dynamic capabilities of an organization. This study examines how job insecurity might affect dynamic organizational capability through trust as an underling process. More specifically, it considered the simultaneous roles of trust at an impersonal (organizational) level as well as trust at an interpersonal level (in leaders and co-workers) as potential underlying mechanisms through which job insecurity might affect the organization’s dynamic capability to respond to opportunities and imminent, drastic change. A quantitative research approach and a stratified random sampling technique enabled the collection of data among 314 managers at four different plant sites of a large South African steel manufacturing organization undergoing dramatic changes. To assess the study hypotheses, the following statistical procedures were employed: Structural equation modelling was performed in Mplus to evaluate the measurement and structural models. The Chi-square values test for absolute fit as well as alternative fit indexes such as the Comparative Fit Index and the Tucker-Lewis Index, the Root Mean Square Error of Approximation and the Standardized Root Mean Square Residual were used as indicators of model fit. Composite reliabilities were calculated to evaluate the reliability of the factors. Finally, interaction effects were tested by using PROCESS and the construction of two-sided 95% confidence intervals. The findings indicate that job insecurity had a lower-than-expected detrimental effect on evaluations of the organization’s dynamic capability through the conducive buffering effects of trust in the organization and in its leaders respectively. In contrast, trust in colleagues did not seem to have any noticeable facilitative effect. The study proposes that both job insecurity and dynamic capability can be managed more effectively by also paying attention to factors that could promote trust in the organization and its leaders; some practical recommendations are given in this regard.

Keywords: dynamic organizational capability, impersonal trust, interpersonal trust, job insecurity

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Authors: Masauso Moses Phiri

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Frequent glucose monitoring is essential to the management of diabetes. Plasmonic enzyme-based glucose biosensors have the advantages of greater specificity, simplicity and rapidity. The aim of this study was to develop a rapid plasmonic colorimetric glucose biosensor based on biocatalytic enlargement of AuNS guided by GOx. Gold nanoparticles of 18 nm in diameter were synthesized using the citrate method. Using these as seeds, a modified seeded method for the synthesis of monodispersed gold nanostars was followed. Both the spherical and star-shaped nanoparticles were characterized using ultra-violet visible spectroscopy, agarose gel electrophoresis, dynamic light scattering, high-resolution transmission electron microscopy and energy-dispersive X-ray spectroscopy. The feasibility of a plasmonic colorimetric assay through growth of AuNS by silver coating in the presence of hydrogen peroxide was investigated by several control and optimization experiments. Conditions for excellent sensing such as the concentration of the detection solution in the presence of 20 µL AuNS, 10 mM of 2-(N-morpholino) ethanesulfonic acid (MES), ammonia and hydrogen peroxide were optimized. Using the optimized conditions, the glucose assay was developed by adding 5mM of GOx to the solution and varying concentrations of glucose to it. Kinetic readings, as well as color changes, were observed. The results showed that the absorbance values of the AuNS were blue shifting and increasing as the concentration of glucose was elevated. Control experiments indicated no growth of AuNS in the absence of GOx, glucose or molecular O₂. Increased glucose concentration led to an enhanced growth of AuNS. The detection of glucose was also done by naked-eye. The color development was near complete in ± 10 minutes. The kinetic readings which were monitored at 450 and 560 nm showed that the assay could discriminate between different concentrations of glucose by ± 50 seconds and near complete at ± 120 seconds. A calibration curve for the qualitative measurement of glucose was derived. The magnitude of wavelength shifts and absorbance values increased concomitantly with glucose concentrations until 90 µg/mL. Beyond that, it leveled off. The lowest amount of glucose that could produce a blue shift in the localized surface plasmon resonance (LSPR) absorption maxima was found to be 10 – 90 µg/mL. The limit of detection was 0.12 µg/mL. This enabled the construction of a direct sensitivity plasmonic colorimetric detection of glucose using AuNS that was rapid, sensitive and cost-effective with naked-eye detection. It has great potential for transfer of technology for point-of-care devices.

Keywords: colorimetric, gold nanostars, glucose, glucose oxidase, plasmonic

Procedia PDF Downloads 153

Authors: Matteo Gentilucci, Marco Materazzi, Gilberto Pambianchi

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Climate change is an increasingly central issue in the world, because it affects many of human activities. In this context regional studies are of great importance because they sometimes differ from the general trend. This research focuses on a small area of central Italy which overlooks the Adriatic Sea, the province of Macerata. The aim is to analyze space-based climate changes, for precipitation and temperatures, in the last 3 climatological standard normals (1961-1990; 1971-2000; 1981-2010) through GIS software. The data collected from 30 weather stations for temperature and 61 rain gauges for precipitation were subject to quality controls: validation and homogenization. These data were fundamental for the spatialization of the variables (temperature and precipitation) through geostatistical techniques. To assess the best geostatistical technique for interpolation, the results of cross correlation were used. The co-kriging method with altitude as independent variable produced the best cross validation results for all time periods, among the methods analysed, with 'root mean square error standardized' close to 1, 'mean standardized error' close to 0, 'average standard error' and 'root mean square error' with similar values. The maps resulting from the analysis were compared by subtraction between rasters, producing 3 maps of annual variation and three other maps for each month of the year (1961/1990-1971/2000; 1971/2000-1981/2010; 1961/1990-1981/2010). The results show an increase in average annual temperature of about 0.1°C between 1961-1990 and 1971-2000 and 0.6 °C between 1961-1990 and 1981-2010. Instead annual precipitation shows an opposite trend, with an average difference from 1961-1990 to 1971-2000 of about 35 mm and from 1961-1990 to 1981-2010 of about 60 mm. Furthermore, the differences in the areas have been highlighted with area graphs and summarized in several tables as descriptive analysis. In fact for temperature between 1961-1990 and 1971-2000 the most areally represented frequency is 0.08°C (77.04 Km² on a total of about 2800 km²) with a kurtosis of 3.95 and a skewness of 2.19. Instead, the differences for temperatures from 1961-1990 to 1981-2010 show a most areally represented frequency of 0.83 °C, with -0.45 as kurtosis and 0.92 as skewness (36.9 km²). Therefore it can be said that distribution is more pointed for 1961/1990-1971/2000 and smoother but more intense in the growth for 1961/1990-1981/2010. In contrast, precipitation shows a very similar shape of distribution, although with different intensities, for both variations periods (first period 1961/1990-1971/2000 and second one 1961/1990-1981/2010) with similar values of kurtosis (1st = 1.93; 2nd = 1.34), skewness (1st = 1.81; 2nd = 1.62 for the second) and area of the most represented frequency (1st = 60.72 km²; 2nd = 52.80 km²). In conclusion, this methodology of analysis allows the assessment of small scale climate change for each month of the year and could be further investigated in relation to regional atmospheric dynamics.

Keywords: climate change, GIS, interpolation, co-kriging

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Authors: Robert Kwame Kpaliba, Dennis Kpakpor Adotey, Yaw Serfor-Armah

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Increase in the oceanic carbon dioxide absorbance from the atmosphere due to climate change has led to appreciable change in the chemistry of the oceans. The change in oceanic pH referred to as ocean acidification poses multiple threats and stresses on marine species, biodiversity, goods and services, and livelihoods. Marine ecosystems are continuously threatened by plethora of natural and anthropogenic stressors including carbon dioxide (CO₂) emissions causing a lot of changes which has not been experienced for approximately 60 years. Little has been done in Africa as a whole and Ghana in particular to improve the understanding of the variations of the carbonate chemistry of seawater and the biophysical impacts of ocean acidification on security of seafood, nutrition, climate and environmental change. There is, therefore, the need for regular monitoring of carbonate chemistry of seawater along Ghana’s coastline to generate reliable data to aid marine policy formulation. Samples of seawater were collected thrice every month for a one-year period from five study sites for the various parameters to be analyzed. Analysis of the measured physico-chemical and the carbonate chemistry parameters was done using simple statistics. Correlation test and ANOVA were run on both of the physico-chemical and carbonate chemistry parameters. The carbonate chemistry parameters were measured using computer software programme (CO₂cal v4.0.9) except total alkalinity and pH. The study assessed the variability of seawater carbonate chemistry in selected portions of the Central Atlantic Coastline of Ghana (Tsokomey/Bortianor, Kokrobitey, Gomoa Nyanyanor, Gomoa Fetteh, and Senya Breku landing beaches) over a 1-year period (June 2016–May 2017). For physico-chemical parameters, there was insignificant variation in nitrate (NO₃⁻) (1.62 - 2.3 mg/L), ammonia (NH₃) (1.52 - 2.05 mg/L), and salinity (sal) (34.50 - 34.74 ppt). Carbonate chemistry parameters for all the five study sites showed significant variation: partial pressure of carbon dioxide (pCO₂) (414.08-715.5 µmol/kg), carbonate ion (CO₃²⁻) (115-157.92 µmol/kg), pH (7.9-8.12), total alkalinity (TA) (1711.8-1986 µmol/kg), total carbon dioxide (TCO₂) (1512.1 - 1792 µmol/kg), dissolved carbon dioxide (CO₂aq) (10.97-18.92 µmol/kg), Revelle Factor (RF) (9.62-11.84), aragonite (ΩAr) (0.75-1.48) and calcite (ΩCa) (1.08-2.14). The study revealed that the partial pressure of carbon dioxide and temperature did not have a significant effect on each other (r² = 0.31) (p-value = 0.0717). There was an appreciable effect of pH on dissolved carbon dioxide (r² = 0.921) (p-value = 0.0000). The variation between total alkalinity and dissolved carbon dioxide was appreciable (r² = 0.731) (p-value = 0.0008). There was a significant correlation between total carbon dioxide and dissolved carbon dioxide (r² = 0.852) (p-value = 0.0000). Revelle factor correlated strongly with dissolved carbon dioxide (r² = 0.982) (p-value = 0.0000). Partial pressure of carbon dioxide corresponds strongly with atmospheric carbon dioxide (r² = 0.9999) (p-value = 0.00000).

Keywords: carbonate chemistry, seawater, central atlantic coastline, Ghana, ocean acidification

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Authors: Mari A. Virtanen, Elina Haavisto, Eeva Liikanen, Maria Kääriäinen

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Rapid technological development and digitalization has affected also on higher education. During last twenty years multiple of electronic and mobile learning (e-learning, m-learning) platforms have been developed and have become prevalent in many universities and in the all fields of education. Ubiquitous learning (u-learning) is not that widely known or used. Ubiquitous learning environments (ULE) are the new era of computer-assisted learning. They are based on ubiquitous technology and computing that fuses the learner seamlessly into learning process by using sensing technology as tags, badges or barcodes and smart devices like smartphones and tablets. ULE combines real-life learning situations into virtual aspects and can be flexible used in anytime and anyplace. The aim of this study was to assess the effects of ubiquitous 360 o learning environment on higher education students’ clinical histotechnology competence. A quasi-experimental study design was used. 57 students in biomedical laboratory science degree program was assigned voluntarily to experiment (n=29) and to control group (n=28). Experimental group studied via ubiquitous 360o learning environment and control group via traditional web-based learning environment (WLE) in a 8-week educational intervention. Ubiquitous 360o learning environment (ULE) combined authentic learning environment (histotechnology laboratory), digital environment (virtual laboratory), virtual microscope, multimedia learning content, interactive communication tools, electronic library and quick response barcodes placed into authentic laboratory. Web-based learning environment contained equal content and components with the exception of the use of mobile device, interactive communication tools and quick response barcodes. Competence of clinical histotechnology was assessed by using knowledge test and self-report developed for this study. Data was collected electronically before and after clinical histotechnology course and analysed by using descriptive statistics. Differences among groups were identified by using Wilcoxon test and differences between groups by using Mann-Whitney U-test. Statistically significant differences among groups were identified in both groups (p<0.001). Competence scores in post-test were higher in both groups, than in pre-test. Differences between groups were very small and not statistically significant. In this study the learning environment have developed based on 360o technology and successfully implemented into higher education context. And students’ competence increases when ubiquitous learning environment were used. In the future, ULE can be used as a learning management system for any learning situation in health sciences. More studies are needed to show differences between ULE and WLE.

Keywords: competence, higher education, histotechnology, ubiquitous learning, u-learning, 360o

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Authors: Kaling Taki, Rohit Gahlot, Manish Kumar

Abstract:

Disposal of Sewage Sludge (SS) is a big issue especially in developing nation like India, where there is no control in the dynamicity of SS produced. The present research work demonstrates the potential application of SS amended with varying percentage (0-100%) of Fly Ash (FA) for brick manufacturing as an alternative of SS management. SS samples were collected from Jaspur sewage treatment plant (Ahmedabad, India) and subjected to different preconditioning treatments: (i) atmospheric drying (ii) pulverization (iii) heat treatment in oven (110°C, moisture removal) and muffle furnace (440°C, organic content removal). Geotechnical parameters of the SS were obtained as liquid limit (52%), plastic limit (24%), shrinkage limit (10%), plasticity index (28%), differential free swell index (DFSI, 47%), silt (68%), clay (27%), organic content (5%), optimum moisture content (OMC, 20%), maximum dry density (MDD, 1.55gm/cc), specific gravity (2.66), swell pressure (57kPa) and unconfined compressive strength (UCS, 207kPa). For FA liquid limit, plastic limit and specific gravity was 44%, 0% and 2.2 respectively. Initially, for brick casting pulverized SS sample was heat treated in a muffle furnace around 440℃ (5 hours) for removal of organic matter. Later, mixing of SS, FA and water by weight ratio was done at OMC. 7*7*7 cm3 sample mold was used for casting bricks at MDD. Brick samples were then first dried in room temperature for 24 hours, then in oven at 100℃ (24 hours) and finally firing in muffle furnace for 1000℃ (10 hours). The fired brick samples were then cured for 3 days according to Indian Standards (IS) common burnt clay building bricks- specification (5th revision). The Compressive strength of brick samples (0, 10, 20, 30, 40, 50 ,60, 70, 80, 90, 100%) of FA were 0.45, 0.76, 1.89, 1.83, 4.02, 3.74, 3.42, 3.19, 2.87, 0.78 and 4.95MPa when evaluated through compressive testing machine (CTM) for a stress rate of 14MPa/min. The highest strength was obtained at 40% FA mixture i.e. 4.02MPa which is much higher than the pure SS brick sample. According to IS 1077: 1992 this combination gives strength more than 3.5 MPa and can be utilized as common building bricks. The loss in weight after firing was much higher than the oven treatment, this might be due to degradation temperature higher than 100℃. The thermal conductivity of the fired brick was obtained as 0.44Wm-1K-1, indicating better insulation properties than other reported studies. TCLP (Toxicity characteristic leaching procedure) test of Cr, Cu, Co, Fe and Ni in raw SS was found as 69, 70, 21, 39502 and 47 mg/kg. The study positively concludes that SS and FA at optimum ratio can be utilized as common building bricks such as partitioning wall and other small strength requirement works. The uniqueness of the work is it emphasizes on utilization of FA for stabilizing SS as construction material as a replacement of natural clay as reported in existing studies.

Keywords: Compressive strength, Curing, Fly Ash, Sewage Sludge.

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Authors: Prabhat Kashyap, Krishan Kumar

Abstract:

Delhi, the capital of India, is one of the most populated and polluted city among the world. In terms of air quality, Delhi’s air is degrading day by day & becomes worst of any major city in the world. The role of biogenic volatile organic compounds (BVOCs) is not much studied in cities like Delhi as a culprit for degraded air quality. They not only play a critical role in rural areas but also determine the atmospheric chemistry of urban areas as well. Particularly, Isoprene (2-methyl 1,3-butadiene, C5H8) is the single largest emitted compound among other BVOCs globally, that influence the tropospheric ozone chemistry in urban environment as the ozone forming potential of isoprene is very high. It is mainly emitted by vegetation & a small but significant portion is also released by vehicular exhaust of petrol operated vehicles. This study investigates the spatial and temporal variations of quantitative measurements of isoprene emissions along with different traffic tracers in 2 different seasons (post-monsoon & winter) at four different locations of Delhi. For the quantification of anthropogenic and biogenic isoprene, two sites from traffic intersections (Punjabi Bagh & CRRI) and two sites from vegetative locations (JNU & Yamuna Biodiversity Park) were selected in the vicinity of isoprene emitting tree species like Ficus religiosa, Dalbergia sissoo, Eucalyptus species etc. The concentrations of traffic tracers like benzene, toluene were also determined & their robust ratios with isoprene were used to differentiate anthropogenic isoprene with biogenic portion at each site. The ozone forming potential (OFP) of all selected species along with isoprene was also estimated. For collection of intra-day samples (3 times a day) in each season, a pre-conditioned fenceline monitoring (FLM) carbopack X thermal desorption tubes were used and further analysis was done with Gas chromatography attached with mass spectrometry (GC-MS). The results of the study proposed that the ambient air isoprene is always higher in post-monsoon season as compared to winter season at all the sites because of high temperature & intense sunlight. The maximum isoprene emission flux was always observed during afternoon hours in both seasons at all sites. The maximum isoprene concentration was found to be 13.95 ppbv at Biodiversity Park during afternoon time in post monsoon season while the lower concentration was observed as low as 0.07 ppbv at the same location during morning hours in winter season. OFP of isoprene at vegetation sites is very high during post-monsoon because of high concentrations. However, OFP for other traffic tracers were high during winter seasons & at traffic locations. Furthermore, high correlation between isoprene emissions with traffic volume at traffic sites revealed that a noteworthy share of its emission also originates from road traffic.

Keywords: biogenic VOCs, isoprene emission, anthropogenic isoprene, urban vegetation

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