Search results for: discrete particle modelling

Authors: Ruchi B. Semwal, Deepak K. Semwal, Thobile A. N. Nkosi, Alvaro M. Viljoen

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The use of Lawsonia inermis L. (Lythraeae), commonly known as henna, has many medicinal benefits and is used as a remedy for the treatment of diarrhoea, cancer, inflammation, headache, jaundice and skin diseases in folk medicine. Although widely used for hair dyeing and temporary tattooing, henna body art has popularized over the last 15 years and changed from being a traditional bridal and festival adornment to an exotic fashion accessory. The naphthoquinone, lawsone, is one of the main constituents of the plant and responsible for its dyeing property. Henna leaves typically contain 1.8–1.9% lawsone, which is used as a marker compound for the quality control of henna products. Adulteration of henna with various toxic chemicals such as p-phenylenediamine, p-methylaminophenol, p-aminobenzene and p-toluenodiamine to produce a variety of colours, is very common and has resulted in serious health problems, including allergic reactions. This study aims to assess the quality of henna products collected from different parts of the world by determining the lawsone content, as well as the concentrations of any adulterants present. Ultra high performance liquid chromatography-mass spectrometry (UPLC-MS) was used to determine the lawsone concentrations in 172 henna products. Separation of the chemical constituents was achieved on an Acquity UPLC BEH C18 column using gradient elution (0.1% formic acid and acetonitrile). The results from UPLC-MS revealed that of 172 henna products, 11 contained 1.0-1.8% lawsone, 110 contained 0.1-0.9% lawsone, whereas 51 samples did not contain detectable levels of lawsone. High performance thin layer chromatography was investigated as a cheaper, more rapid technique for the quality control of henna in relation to the lawsone content. The samples were applied using an automatic TLC Sampler 4 (CAMAG) to pre-coated silica plates, which were subsequently developed with acetic acid, acetone and toluene (0.5: 1.0: 8.5 v/v). A Reprostar 3 digital system allowed the images to be captured. The results obtained corresponded to those from UPLC-MS analysis. Vibrational spectroscopy analysis (MIR or NIR) of the powdered henna, followed by chemometric modelling of the data, indicates that this technique shows promise as an alternative quality control method. Principal component analysis (PCA) was used to investigate the data by observing clustering and identifying outliers. Partial least squares (PLS) multivariate calibration models were constructed for the quantification of lawsone. In conclusion, only a few of the samples analysed contain lawsone in high concentrations, indicating that they are of poor quality. Currently, the presence of adulterants that may have been added to enhance the dyeing properties of the products, is being investigated.

Keywords: Lawsonia inermis, paraphenylenediamine, temporary tattooing, lawsone

Procedia PDF Downloads 437

Authors: Devika Nair, Sean Bellairs, Ken Evans

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Flow and erosion modeling provides an avenue for simulating the fine suspended sediment in surface water systems like streams and creeks. Fine suspended sediment is highly mobile, and many contaminants that may have been released by any sort of catchment disturbance attach themselves to these sediments. Therefore, a knowledge of fine suspended sediment transport is important in assessing contaminant transport. The CAESAR-Lisflood Landform Evolution Model, which includes a hydrologic model (TOPMODEL) and a hydraulic model (Lisflood), is being used to assess the sediment movement in tropical streams on account of a disturbance in the catchment of the creek and to determine the dynamics of sediment quantity in the creek through the years by simulating the model for future years. The accuracy of future simulations depends on the calibration and validation of the model to the past and present events. Calibration and validation of the model involve finding a combination of parameters of the model, which, when applied and simulated, gives model outputs similar to those observed for the real site scenario for corresponding input data. Calibrating the sediment output of the CAESAR-Lisflood model at the catchment level and using it for studying the equilibrium conditions of the landform is an area yet to be explored. Therefore, the aim of the study was to calibrate the CAESAR-Lisflood model and then validate it so that it could be run for future simulations to study how the landform evolves over time. To achieve this, the model was run for a rainfall event with a set of parameters, plus discharge and sediment data for the input point of the catchment, to analyze how similar the model output would behave when compared with the discharge and sediment data for the output point of the catchment. The model parameters were then adjusted until the model closely approximated the real site values of the catchment. It was then validated by running the model for a different set of events and checking that the model gave similar results to the real site values. The outcomes demonstrated that while the model can be calibrated to a greater extent for hydrology (discharge output) throughout the year, the sediment output calibration may be slightly improved by having the ability to change parameters to take into account the seasonal vegetation growth during the start and end of the wet season. This study is important to assess hydrology and sediment movement in seasonal biomes. The understanding of sediment-associated metal dispersion processes in rivers can be used in a practical way to help river basin managers more effectively control and remediate catchments affected by present and historical metal mining.

Keywords: erosion modelling, fine suspended sediments, hydrology, surface water systems

Procedia PDF Downloads 61

Authors: Dimitri Bacco, Arianna Trentini, Fabiana Scotto, Flavio Rovere, Daniele Foscoli, Cinzia Para, Paolo Veronesi, Silvia Sandrini, Claudia Zigola, Michela Comandini, Marilena Montalti, Marco Zamagni, Vanes Poluzzi

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The Po Valley, in the north of Italy, is one of the most polluted areas in Europe. The air quality of the area is linked not only to anthropic activities but also to its geographical characteristics and stagnant weather conditions with frequent inversions, especially in the cold season. Even the coastal areas present high values of particulate matter (PM10 and PM2.5) because the area closed between the Adriatic Sea and the Apennines does not favor the dispersion of air pollutants. The aim of the present work was to identify the main sources of particulate matter in Rimini, a tourist city in northern Italy. Two sampling campaigns were carried out in 2018, one in winter (60 days) and one in summer (30 days), in 4 sites: an urban background, a city hotspot, a suburban background, and a rural background. The samples are characterized by the concentration of the ionic composition of the particulates and of the main a hydro-sugars, in particular levoglucosan, a marker of the biomass burning, because one of the most important anthropogenic sources in the area, both in the winter and surprisingly even in the summer, is the biomass burning. Furthermore, three sampling points were chosen in order to maximize the contribution of a specific biomass source: a point in a residential area (domestic cooking and domestic heating), a point in the agricultural area (weed fires), and a point in the tourist area (restaurant cooking). In these sites, the analyzes were enriched with the quantification of the carbonaceous component (organic and elemental carbon) and with measurement of the particle number concentration and aerosol size distribution (6 - 600 nm). The results showed a very significant impact of the combustion of biomass due to domestic heating in the winter period, even though many intense peaks were found attributable to episodic wood fires. In the summer season, however, an appreciable signal was measured linked to the combustion of biomass, although much less intense than in winter, attributable to domestic cooking activities. Further interesting results were the verification of the total absence of sea salt's contribution in the particulate with the lower diameter (PM2.5), and while in the PM10, the contribution becomes appreciable only in particular wind conditions (high wind from north, north-east). Finally, it is interesting to note that in a small town, like Rimini, in summer, the traffic source seems to be even more relevant than that measured in a much larger city (Bologna) due to tourism.

Keywords: aerosol, biomass burning, seacoast, urban area

Procedia PDF Downloads 109

Authors: Maik Kschischo, Dominik Kahl, Philipp Wendland, Andreas Weber

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Understanding and modelling of real-world complex dynamic systems in biology, engineering and other fields is often made difficult by incomplete knowledge about the interactions between systems states and by unknown disturbances to the system. In fact, most real-world dynamic networks are open systems receiving unknown inputs from their environment. To understand a system and to estimate the state dynamics, these inputs need to be reconstructed from output measurements. Reconstructing the input of a dynamic system from its measured outputs is an ill-posed problem if only a limited number of states is directly measurable. A first requirement for solving this problem is the invertibility of the input-output map. In our work, we exploit the fact that invertibility of a dynamic system is a structural property, which depends only on the network topology. Therefore, it is possible to check for invertibility using a structural invertibility algorithm which counts the number of node disjoint paths linking inputs and outputs. The algorithm is efficient enough, even for large networks up to a million nodes. To understand structural features influencing the invertibility of a complex dynamic network, we analyze synthetic and real networks using the structural invertibility algorithm. We find that invertibility largely depends on the degree distribution and that dense random networks are easier to invert than sparse inhomogeneous networks. We show that real networks are often very difficult to invert unless the sensor nodes are carefully chosen. To overcome this problem, we present a sensor node placement algorithm to achieve invertibility with a minimum set of measured states. This greedy algorithm is very fast and also guaranteed to find an optimal sensor node-set if it exists. Our results provide a practical approach to experimental design for open, dynamic systems. Since invertibility is a necessary condition for unknown input observers and data assimilation filters to work, it can be used as a preprocessing step to check, whether these input reconstruction algorithms can be successful. If not, we can suggest additional measurements providing sufficient information for input reconstruction. Invertibility is also important for systems design and model building. Dynamic models are always incomplete, and synthetic systems act in an environment, where they receive inputs or even attack signals from their exterior. Being able to monitor these inputs is an important design requirement, which can be achieved by our algorithms for invertibility analysis and sensor node placement.

Keywords: data-driven dynamic systems, inversion of dynamic systems, observability, experimental design, sensor node placement

Procedia PDF Downloads 128

Authors: T. Garlan, I. Gabelotaud, S. Lucas, E. Marchès

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Production of a global sedimentological seabed map has been initiated in 1995 to provide the necessary tool for searches of aircraft and boats lost at sea, to give sedimentary information for nautical charts, and to provide input data for acoustic propagation modelling. This original approach had already been initiated one century ago when the French hydrographic service and the University of Nancy had produced maps of the distribution of marine sediments of the French coasts and then sediment maps of the continental shelves of Europe and North America. The current map of the sediment of oceans presented was initiated with a UNESCO's general map of the deep ocean floor. This map was adapted using a unique sediment classification to present all types of sediments: from beaches to the deep seabed and from glacial deposits to tropical sediments. In order to allow good visualization and to be adapted to the different applications, only the granularity of sediments is represented. The published seabed maps are studied, if they present an interest, the nature of the seabed is extracted from them, the sediment classification is transcribed and the resulted map is integrated in the world map. Data come also from interpretations of Multibeam Echo Sounder (MES) imagery of large hydrographic surveys of deep-ocean. These allow a very high-quality mapping of areas that until then were represented as homogeneous. The third and principal source of data comes from the integration of regional maps produced specifically for this project. These regional maps are carried out using all the bathymetric and sedimentary data of a region. This step makes it possible to produce a regional synthesis map, with the realization of generalizations in the case of over-precise data. 86 regional maps of the Atlantic Ocean, the Mediterranean Sea, and the Indian Ocean have been produced and integrated into the world sedimentary map. This work is permanent and permits a digital version every two years, with the integration of some new maps. This article describes the choices made in terms of sediment classification, the scale of source data and the zonation of the variability of the quality. This map is the final step in a system comprising the Shom Sedimentary Database, enriched by more than one million punctual and surface items of data, and four series of coastal seabed maps at 1:10,000, 1:50,000, 1:200,000 and 1:1,000,000. This step by step approach makes it possible to take into account the progresses in knowledge made in the field of seabed characterization during the last decades. Thus, the arrival of new classification systems for seafloor has improved the recent seabed maps, and the compilation of these new maps with those previously published allows a gradual enrichment of the world sedimentary map. But there is still a lot of work to enhance some regions, which are still based on data acquired more than half a century ago.

Keywords: marine sedimentology, seabed map, sediment classification, world ocean

Procedia PDF Downloads 216

Authors: André Jesus, Yanjie Zhu, Irwanda Laory

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Structural health monitoring is one of the most promising technologies concerning aversion of structural risk and economic savings. Analysts often have to deal with a considerable variety of uncertainties that arise during a monitoring process. Namely the widespread application of numerical models (model-based) is accompanied by a widespread concern about quantifying the uncertainties prevailing in their use. Some of these uncertainties are related with the deterministic nature of the model (code uncertainty) others with the variability of its inputs (parameter uncertainty) and the discrepancy between a model/experiment (systematic uncertainty). The actual process always exhibits a random behaviour (observation error) even when conditions are set identically (residual variation). Bayesian inference assumes that parameters of a model are random variables with an associated PDF, which can be inferred from experimental data. However in many Bayesian methods the determination of systematic uncertainty can be problematic. In this work systematic uncertainty is associated with a discrepancy function. The numerical model and discrepancy function are approximated by Gaussian processes (surrogate model). Finally, to avoid the computational burden of a fully Bayesian approach the parameters that characterise the Gaussian processes were estimated in a four stage process (modular Bayesian approach). The proposed methodology has been successfully applied on fields such as geoscience, biomedics, particle physics but never on the SHM context. This approach considerably reduces the computational burden; although the extent of the considered uncertainties is lower (second order effects are neglected). To successfully identify the considered uncertainties this formulation was extended to consider multiple responses. The efficiency of the algorithm has been tested on a small scale aluminium bridge structure, subjected to a thermal expansion due to infrared heaters. Comparison of its performance with responses measured at different points of the structure and associated degrees of identifiability is also carried out. A numerical FEM model of the structure was developed and the stiffness from its supports is considered as a parameter to calibrate. Results show that the modular Bayesian approach performed best when responses of the same type had the lowest spatial correlation. Based on previous literature, using different types of responses (strain, acceleration, and displacement) should also improve the identifiability problem. Uncertainties due to parametric variability, observation error, residual variability, code variability and systematic uncertainty were all recovered. For this example the algorithm performance was stable and considerably quicker than Bayesian methods that account for the full extent of uncertainties. Future research with real-life examples is required to fully access the advantages and limitations of the proposed methodology.

Keywords: bayesian, calibration, numerical model, system identification, systematic uncertainty, Gaussian process

Procedia PDF Downloads 307

Authors: Utkarsh A. Mishra, Ankit Bansal

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At high temperature, radiative heat transfer is the dominant mode of heat transfer. It is governed by various phenomena such as photon emission, absorption, and scattering. The solution of the governing integrodifferential equation of radiative transfer is a complex process, more when the effect of participating medium and wavelength properties are taken into consideration. Although a generic formulation of such radiative transport problem can be modeled for a wide variety of problems with non-gray, non-diffusive surfaces, there is always a trade-off between simplicity and accuracy of the problem. Recently, solutions of complicated mathematical problems with statistical methods based on randomization of naturally occurring phenomena have gained significant importance. Photon bundles with discrete energy can be replicated with random numbers describing the emission, absorption, and scattering processes. Photon Monte Carlo (PMC) is a simple, yet powerful technique, to solve radiative transfer problems in complicated geometries with arbitrary participating medium. The method, on the one hand, increases the accuracy of estimation, and on the other hand, increases the computational cost. The participating media -generally a gas, such as CO₂, CO, and H₂O- present complex emission and absorption spectra. To model the emission/absorption accurately with random numbers requires a weighted sampling as different sections of the spectrum carries different importance. Importance sampling (IS) was implemented to sample random photon of arbitrary wavelength, and the sampled data provided unbiased training of MC estimators for better results. A better replacement to uniform random numbers is using deterministic, quasi-random sequences. Halton, Sobol, and Faure Low-Discrepancy Sequences are used in this study. They possess better space-filling performance than the uniform random number generator and gives rise to a low variance, stable Quasi-Monte Carlo (QMC) estimators with faster convergence. An optimal supervised learning scheme was further considered to reduce the computation costs of the PMC simulation. A one-dimensional plane-parallel slab problem with participating media was formulated. The history of some randomly sampled photon bundles is recorded to train an Artificial Neural Network (ANN), back-propagation model. The flux was calculated using the standard quasi PMC and was considered to be the training target. Results obtained with the proposed model for the one-dimensional problem are compared with the exact analytical and PMC model with the Line by Line (LBL) spectral model. The approximate variance obtained was around 3.14%. Results were analyzed with respect to time and the total flux in both cases. A significant reduction in variance as well a faster rate of convergence was observed in the case of the QMC method over the standard PMC method. However, the results obtained with the ANN method resulted in greater variance (around 25-28%) as compared to the other cases. There is a great scope of machine learning models to help in further reduction of computation cost once trained successfully. Multiple ways of selecting the input data as well as various architectures will be tried such that the concerned environment can be fully addressed to the ANN model. Better results can be achieved in this unexplored domain.

Keywords: radiative heat transfer, Monte Carlo Method, pseudo-random numbers, low discrepancy sequences, artificial neural networks

Procedia PDF Downloads 200

Authors: Nasser S. Shebka

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Fuzzy logic is used in complex adaptive systems where classical tools of representing knowledge are unproductive. Nevertheless, the incorporation of fuzzy logic, as it’s the case with all artificial intelligence tools, raised some inconsistencies and limitations in dealing with increased complexity systems and rules that apply to real-life situations and hinders the ability of the inference process of such systems, but it also faces some inconsistencies between inferences generated fuzzy rules of complex or imprecise knowledge-based systems. The use of fuzzy logic enhanced the capability of knowledge representation in such applications that requires fuzzy representation of truth values or similar multi-value constant parameters derived from multi-valued logic, which set the basis for the three t-norms and their based connectives which are actually continuous functions and any other continuous t-norm can be described as an ordinal sum of these three basic ones. However, some of the attempts to solve this dilemma were an alteration to fuzzy logic by means of non-monotonic logic, which is used to deal with the defeasible inference of expert systems reasoning, for example, to allow for inference retraction upon additional data. However, even the introduction of non-monotonic fuzzy reasoning faces a major issue of conflict resolution for which many principles were introduced, such as; the specificity principle and the weakest link principle. The aim of our work is to improve the logical representation and functional modelling of AI systems by presenting a method of resolving existing and potential rule conflicts by representing temporal modalities within defeasible inference rule-based systems. Our paper investigates the possibility of resolving fuzzy rules conflict in a non-monotonic fuzzy reasoning-based system by introducing temporal modalities and Kripke's general weak modal logic operators in order to expand its knowledge representation capabilities by means of flexibility in classifying newly generated rules, and hence, resolving potential conflicts between these fuzzy rules. We were able to address the aforementioned problem of our investigation by restructuring the inference process of the fuzzy rule-based system. This is achieved by using time-branching temporal logic in combination with restricted first-order logic quantifiers, as well as propositional logic to represent classical temporal modality operators. The resulting findings not only enhance the flexibility of complex rule-base systems inference process but contributes to the fundamental methods of building rule bases in such a manner that will allow for a wider range of applicable real-life situations derived from a quantitative and qualitative knowledge representational perspective.

Keywords: fuzzy rule-based systems, fuzzy tense inference, intelligent systems, temporal modalities

Procedia PDF Downloads 67

Authors: Ciwang Teyra, A. H. Y. Lai

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Introduction: Indigenous LGBTQ individuals face with significant life stress such as racial and gender discrimination and microaggressions, which may lead to negative impacts of their mental health. Although studies relevant to Taiwanese indigenous LGBTQpeople gradually increase, most of them are primarily conceptual or qualitative in nature. This research aims to fulfill the gap by offering empirical quantitative evidence, especially investigating the impact of racial and gender microaggressions on mental health among Taiwanese indigenous LGBTQindividuals with an intersectional perspective, as well as examine whether social support can help them to cope with microaggressions. Methods: Participants were (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Standardised measurements was used, including Racial Microaggression Scale (10 items), Gender Microaggression Scale (9 items), Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender, and perceived economic hardships. Structural equation modelling (SEM) was employed using Mplus 8.0 with the latent variables of depression and anxiety as outcomes. A main effect SEM model was first established (Model1).To test the moderation effects of perceived social support, an interaction effect model (Model 2) was created with interaction terms entered into Model1. Numerical integration was used with maximum likelihood estimation to estimate the interaction model. Results: Model fit statistics of the Model 1:X2(df)=1308.1 (795), p<.05; CFI/TLI=0.92/0.91; RMSEA=0.06; SRMR=0.06. For Model, the AIC and BIC values of Model 2 improved slightly compared to Model 1(AIC =15631 (Model1) vs. 15629 (Model2); BIC=16098 (Model1) vs. 16103 (Model2)). Model 2 was adopted as the final model. In main effect model 1, racialmicroaggressionand perceived social support were associated with depression and anxiety, but not sexual orientation microaggression(Indigenous microaggression: b = 0.27 for depression; b=0.38 for anxiety; Social support: b=-0.37 for depression; b=-0.34 for anxiety). Thus, an interaction term between social support and indigenous microaggression was added in Model 2. In the final Model 2, indigenous microaggression and perceived social support continues to be statistically significant predictors of both depression and anxiety. Social support moderated the effect of indigenous microaggression of depression (b=-0.22), but not anxiety. All covariates were not statistically significant. Implications: Results indicated that racial microaggressions have a significant impact on indigenous LGBTQ people’s mental health. Social support plays as a crucial role to buffer the negative impact of racial microaggression. To promote indigenous LGBTQ people’s wellbeing, it is important to consider how to support them to develop social support network systems.

Keywords: microaggressions, intersectionality, indigenous population, mental health, social support

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Authors: Fahad Ibrahim, Raphaël Akamavi

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Bangladesh has encountered several industrial disasters (e.g. fire and building collapse tragedies) leading to the loss of valuable human lives. Irrespective of various institutions’ making effort to improve the safety situation, industry compliance and safety behaviour have not yet been improved. Hence, one question remains, to what extent does the institutional elements efficient enough to make any difference in improving safety behaviours? Thus, this study explores the relationship between institutional perspective and safety performance. Structural equation modelling results, using survey data from 256 RMG workers’ of 128 garments manufacturing factories in Bangladesh, show that institutional facets strongly influence management safety commitment to induce workers participation in safety activities and reduce workplace accident rates. The study also found that by upholding industrial standards and inspecting the safety situations, institutions facets significantly and directly affect workers involvement in safety participations and rate of workplace accidents. Additionally, workers involvement to safety practices significantly predicts the safety environment of the workplace. Subsequently, our findings demonstrate that institutional culture, norms, and regulations enact play an important role in altering management commitment to set-up a safer workplace environment. As a result, when workers’ perceive their management having high level of commitment to safety, they are inspired to be involved more in the safety practices, which significantly alter the workplace safety situation and lessen injury experiences. Due to the fact that institutions have strong influence on management commitment, legislative members should endorse, regulate, and strictly monitor workplace safety laws to be exercised by the factory owners. Further, management should take initiatives for adopting OHS features and conceive strategic directions (i.e., set up safety committees, risk assessments, innovative training) for promoting a positive safety climate to provide a safe workplace environment. Arguably, an inclusive public-private partnership is recommended for ensuring better and safer workplace for RMG workers. However, as our data were under a cross-sectional design; the respondents’ perceptions might get changed over a period of time and hence, a longitudinal study is recommended. Finally, further research is needed to determine the impact of improvement mechanisms on workplace safety performance, such as how workplace design, safety training programs, and institutional enforcement policies protect the well-being of workers.

Keywords: institutional perspective, management commitment, safety participation, work injury, safety performance, occupational health and safety

Procedia PDF Downloads 186

Authors: Lorenzo Petrucci

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This paper is intended to give insight into the potential use of small-scale off-grid trigeneration systems powered by biogas generated in a dairy farm. The off-grid plant object of analysis comprises a dual-fuel Genset as well as electrical and thermal storage equipment and an adsorption machine. The loads are the different apparatus used in the dairy farm, a household where the workers live and a small electric vehicle whose batteries can also be used as a power source in case of emergency. The insertion in the plant of an adsorption machine is mainly justified by the abundance of thermal energy and the simultaneous high cooling demand associated with the milk-chilling process. In the evaluated operational scenario, our research highlights the importance of prioritizing specific small loads which cannot sustain an interrupted supply of power over time. As a consequence, a photovoltaic and thermal panel is included in the plant and is tasked with providing energy independently of potentially disruptive events such as engine malfunctioning or scarce and unstable supplies of fuels. To efficiently manage the plant an energy dispatch strategy is created in order to control the flow of energy between the power sources and the thermal and electric storages. In this article we elaborate on models of the equipment and from these models, we extract parameters useful to build load-dependent profiles of the prime movers and storage efficiencies. We show that under reasonable assumptions the analysis provides a sensible estimate of the generated energy. The simulations indicate that a Diesel Generator sized to a value 25% higher than the total electrical peak demand operates 65% of the time below the minimum acceptable load threshold. To circumvent such a critical operating mode, dump loads are added through the activation and deactivation of small resistors. In this way, the excess of electric energy generated can be transformed into useful heat. The combination of PVT and electrical storage to support the prioritized load in an emergency scenario is evaluated in two different days of the year having the lowest and highest irradiation values, respectively. The results show that the renewable energy component of the plant can successfully sustain the prioritized loads and only during a day with very low irradiation levels it also needs the support of the EVs’ battery. Finally, we show that the adsorption machine can reduce the ice builder and the air conditioning energy consumption by 40%.

Keywords: hybrid power plants, mathematical modeling, off-grid plants, renewable energy, trigeneration

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Authors: Priyanka Mondal, Santosh K. Sarkar

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The present study investigated the spatiotemporal distribution and ecological risk assessment of trace elements of surface sediments (top 0 - 5 cm; grain size ≤ 0.63 µm) in relevance to sediment quality characteristics along the Ganges River Estuary, India. Sediment samples were collected during ebb tide from intertidal regions covering seven sampling sites of diverse environmental stresses. The elements were analyzed with the help of ICPAES. This positive, mixohaline, macro-tidal estuary has global significance contributing ecological and economic services. Presence of fine-clayey particle (47.03%) enhances the adsorption as well as transportation of trace elements. There is a remarkable inter-metallic variation (mg kg-1 dry weight) in the distribution pattern in the following manner: Al (31801± 15943) > Fe (23337± 7584) > Mn (461±147) > S(381±235) > Zn(54 ±18) > V(43 ±14) > Cr(39 ±15) > As (34±15) > Cu(27 ±11) > Ni (24 ±9) > Se (17 ±8) > Co(11 ±3) > Mo(10 ± 2) > Hg(0.02 ±0.01). An overall trend of enrichment of majority of trace elements was very much pronounced at the site Lot 8, ~ 35km upstream of the estuarine mouth. In contrast, the minimum concentration was recorded at site Gangasagar, mouth of the estuary, with high energy profile. The prevalent variations in trace element distribution are being liable for a set of cumulative factors such as hydrodynamic conditions, sediment dispersion pattern and textural variations as well as non-homogenous input of contaminants from point and non-point sources. In order to gain insight into the trace elements distribution, accumulation, and their pollution status, geoaccumulation index (Igeo) and enrichment factor (EF) were used. The Igeo indicated that surface sediments were moderately polluted with As (0.60) and Mo (1.30) and strongly contaminated with Se (4.0). The EF indicated severe pollution of Se (53.82) and significant pollution of As (4.05) and Mo (6.0) and indicated the influx of As, Mo and Se in sediments from anthropogenic sources (such as industrial and municipal sewage, atmospheric deposition, agricultural run-off, etc.). The significant role of the megacity Calcutta in relevance to the untreated sewage discharge, atmospheric inputs and other anthropogenic activities is worthwhile to mention. The ecological risk for different trace elements was evaluated using sediment quality guidelines, effects range low (ERL), and effect range median (ERM). The concentration of As, Cu and Ni at 100%, 43% and 86% of the sampling sites has exceeded the ERL value while none of the element concentration exceeded ERM. The potential ecological risk index values revealed that As at 14.3% of the sampling sites would pose relatively moderate risk to benthic organisms. The effective role of finer clay particles for trace element distribution was revealed by multivariate analysis. The authors strongly recommend regular monitoring emphasizing on accurate appraisal of the potential risk of trace elements for effective and sustainable management of this estuarine environment.

Keywords: pollution assessment, sediment contamination, sediment quality, trace elements

Procedia PDF Downloads 241

Authors: Gideon C. Joseph

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The ability to localize mobile devices is quite important, as some applications may require location information of these devices to operate or deliver better services to the users. Although there are several ways of acquiring location data of mobile devices, the WLAN fingerprinting approach has been considered in this work. This approach uses the Received Signal Strength Indicator (RSSI) measurement as a function of the position of the mobile device. RSSI is a quantitative technique of describing the radio frequency power carried by a signal. RSSI may be used to determine RF link quality and is very useful in dense traffic scenarios where interference is of major concern, for example, indoor environments. This research aims to design a system that can predict the location of a mobile device, when supplied with the mobile’s RSSIs. The developed system takes as input the RSSIs relating to the mobile device, and outputs parameters that describe the location of the device such as the longitude, latitude, floor, and building. The relationship between the Received Signal Strengths (RSSs) of mobile devices and their corresponding locations is meant to be modelled; hence, subsequent locations of mobile devices can be predicted using the developed model. It is obvious that describing mathematical relationships between the RSSIs measurements and localization parameters is one option to modelling the problem, but the complexity of such an approach is a serious turn-off. In contrast, we propose an intelligent system that can learn the mapping of such RSSIs measurements to the localization parameters to be predicted. The system is capable of upgrading its performance as more experiential knowledge is acquired. The most appealing consideration to using such a system for this task is that complicated mathematical analysis and theoretical frameworks are excluded or not needed; the intelligent system on its own learns the underlying relationship in the supplied data (RSSI levels) that corresponds to the localization parameters. These localization parameters to be predicted are of two different tasks: Longitude and latitude of mobile devices are real values (regression problem), while the floor and building of the mobile devices are of integer values or categorical (classification problem). This research work presents artificial neural network based intelligent systems to model the relationship between the RSSIs predictors and the mobile device localization parameters. The designed systems were trained and validated on the collected WLAN fingerprint database. The trained networks were then tested with another supplied database to obtain the performance of trained systems on achieved Mean Absolute Error (MAE) and error rates for the regression and classification tasks involved therein.

Keywords: indoor localization, WLAN fingerprinting, neural networks, classification, regression

Procedia PDF Downloads 318

Authors: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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Authors: Feiyu Yang, Chunfang Ni, Rong Wang, Yun Zou, Wenbin Liu, Chenggong Zhang, Fenjin Sun, Chun Wang

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Cocaine is the most frequently used illegal drug globally, with the global annual prevalence of cocaine used ranging from 0.3% to 0.4 % of the adult population aged 15–64 years. Growing consumption trend of abused cocaine and drug crimes are a great concern, therefore urine sample testing has become an important noninvasive sampling whereas cocaine and its metabolites (COCs) are usually present in high concentrations and relatively long detection windows. However, direct analysis of urine samples is not feasible because urine complex medium often causes low sensitivity and selectivity of the determination. On the other hand, presence of low doses of analytes in urine makes an extraction and pretreatment step important before determination. Especially, in gathered taking drug cases, the pretreatment step becomes more tedious and time-consuming. So developing a sensitive, rapid and high-throughput method for detection of COCs in human body is indispensable for law enforcement officers, treatment specialists and health officials. In this work, a new automated magnetic dispersive solid-phase extraction (MDSPE) sampling method followed by high performance liquid chromatography-mass spectrometry (HPLC-MS) was developed for quantitative enrichment of COCs from human urine, using prepared magnetic nanoparticles as absorbants. The nanoparticles were prepared by silanizing magnetic Fe3O4 nanoparticles and modifying them with divinyl benzene and vinyl pyrrolidone, which possesses the ability for specific adsorption of COCs. And this kind of magnetic particle facilitated the pretreatment steps by electromagnetically controlled extraction to achieve full automation. The proposed device significantly improved the sampling preparation efficiency with 32 samples in one batch within 40mins. Optimization of the preparation procedure for the magnetic nanoparticles was explored and the performances of magnetic nanoparticles were characterized by scanning electron microscopy, vibrating sample magnetometer and infrared spectra measurements. Several analytical experimental parameters were studied, including amount of particles, adsorption time, elution solvent, extraction and desorption kinetics, and the verification of the proposed method was accomplished. The limits of detection for the cocaine and cocaine metabolites were 0.09-1.1 ng·mL-1 with recoveries ranging from 75.1 to 105.7%. Compared to traditional sampling method, this method is time-saving and environmentally friendly. It was confirmed that the proposed automated method was a kind of highly effective way for the trace cocaine and cocaine metabolites analyses in human urine.

Keywords: automatic magnetic dispersive solid-phase extraction, cocaine detection, magnetic nanoparticles, urine sample testing

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Authors: Mumuni Sumaila, Viness Pillay, Yahya E. Choonara, Pradeep Kumar, Pierre P. Kondiah

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Tuberculosis (TB) remains a serious challenge to public health globally, despite every effort put together to curb the disease. Current TB therapeutics available have proven to be inefficient due to a multitude of drawbacks that range from serious adverse effects/drug toxicity to inconsistent bioavailability, which ultimately contributes to the emergence of drug-resistant TB. An effective ‘cargo’ system designed to cleverly deliver therapeutic doses of anti-TB drugs to infection sites and in a sustained-release manner may provide a better therapeutic choice towards winning the war against TB. In the current study, we investigated mannose-functionalized lipopolysaccharide hybrid nanoparticles for safety and efficacy towards macrophage-targeted simultaneous delivery of the two first-line anti-TB drugs, rifampicin (RF) and isoniazid (IS). RF-IS-loaded lipopolysaccharide hybrid nanoparticles were fabricated using the solvent injection technique (SIT), incorporating soy lecithin (SL) and low molecular weight chitosan (CS) as the lipid and polysaccharide components, respectively. Surface-functionalized nanoparticles were obtained through the reaction of the aldehyde group of mannose with free amine functionality present at the surface of the nanoparticles. The functionalized nanocarriers were spherical with average particle size and surface charge of 107.83 nm and +21.77 mV, respectively, and entrapment efficiencies (EE) were 53.52% and 69.80% for RF and IS, respectively. FTIR spectrum revealed high-intensity bands between 1663 cm⁻¹ and 1408 cm⁻¹ wavenumbers (absent in non-functionalized nanoparticles), which could be attributed to the C=N stretching vibration produced by the formation of Schiff’s base (–N=CH–) during the mannosylation reaction. In vitro release studies showed a sustained-release profile for RF and IS, with less than half of the total payload released over a 48-hour period. The nanocarriers were biocompatible and safe, with more than 80% cell viability achieved when incubated with RAW 264.7 cells at concentrations 30 to 500 μg/mL over a 24-hour period. Cellular uptake studies (after a 24-hour incubation period with the murine macrophage cells, RAW 264.7) revealed a 13- and a 9-fold increase in intracellular accumulation of RF and IS, respectively, when compared with the unformulated RF+IS solution. A 6- and a 3-fold increase in intracellular accumulation of RF and IS, respectively, were observed when compared with the non-functionalized nanoparticles. Furthermore, fluorescent microscopy images showed nanoparticle internalization and accumulation within the RAW 264.7 cells, which was more significant in the mannose-functionalized system compared to the non-functionalized nanoparticles. The overall results suggested that the fabricated mannose-functionalized lipopolysaccharide nanoparticles are a safe and promising platform for macrophage-targeted delivery of anti-TB therapeutics. However, in vivo pharmacokinetic/pharmacodynamics studies are required to further substantiate the therapeutic efficacy of the nanosystem.

Keywords: anti-tuberculosis therapeutics, hybrid nanosystem, lipopolysaccharide nanoparticles, macrophage-targeted delivery

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Mariam Mtunguja, Henry Laswai, Yasinta Muzanilla, Joseph Ndunguru

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Starchy tuberous roots of cassava provide food for people but also find application in various industries. Recently there has been the focus of concentrated research efforts to fully exploit its potential as a sustainable multipurpose crop. High starch yield is the important trait for commercial cassava production for the starch industries. Furthermore, cyanide present in cassava root poses a health challenge in the use of cassava for food. Farming communities where cassava is a staple food, prefer bitter (high cyanogenic) varieties as protection from predators and thieves. As a result, food insecure farmers prefer growing bitter cassava. This has led to cyanide intoxication to this farming communities. Cassava farmers can benefit from marketing cassava to starch producers thereby improving their income and food security. This will decrease dependency on cassava as staple food as a result of increased income and be able to afford other food sources. To achieve this, adequate information is required on the right cassava cultivars and appropriate harvesting period so as to maximize cassava production and profitability. This study aimed at identifying suitable cassava cultivars and optimum time of harvest to maximize starch production. Six commonly grown cultivars were identified and planted in a complete random block design and further analysis was done to assess variation in physicochemical characteristics, starch yield and cyanogenic potentials across three environments. The analysis showed that there is a difference in physicochemical characteristics between landraces (p ≤ 0.05), and can be targeted to different industrial applications. Among landraces, dry matter (30-39%), amylose (11-19%), starch (74-80%) and reducing sugars content (1-3%) varied when expressed on a dry weight basis (p ≤ 0.05); however, only one of the six genotypes differed in crystallinity and mean starch granule particle size, while glucan chain distribution and granule morphology were the same. In contrast, the starch functionality features measured: swelling power, solubility, syneresis, and digestibility differed (p ≤ 0.05). This was supported by Partial least square discriminant analysis (PLS-DA), which highlighted the divergence among the cassavas based on starch functionality, permitting suggestions for the targeted uses of these starches in diverse industries. The study also illustrated genotypic difference in starch yield and cyanogenic potential. Among landraces, Kiroba showed potential for maximum starch yield (12.8 t ha-1) followed by Msenene (12.3 t ha-1) and third was Kilusungu (10.2 t ha-1). The cyanide content of cassava landraces was between 15 and 800 ppm across all trial sites. GGE biplot analysis further confirmed that Kiroba was a superior cultivar in terms of starch yield. Kilusungu had the highest cyanide content and average starch yield, therefore it can also be suitable for use in starch production.

Keywords: cyanogen, cassava starch, food security, starch yield

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Authors: Yang Yang, Luciana Magalhães Rebelo Alencar, Martha Sahylí Ortega Pijeira, Beatriz da Silva Batista, Alefe Roger Silva França, Erick Rafael Dias Rates, Ruana Cardoso Lima, Sara Gemini-Piperni, Ralph Santos-Oliveira

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Radium-²²³ dichloride ([²²³Rₐ]RₐCl₂) is an alpha particle-emitting radiopharmaceutical currently approved for the treatment of patients with castration-resistant prostate cancer, symptomatic bone metastases, and no known visceral metastatic disease. [²²³Rₐ]RₐCl₂ is bone-seeking calcium mimetic that bonds into the newly formed bone stroma, especially osteoblastic or sclerotic metastases, killing the tumor cells by inducing DNA breaks in a potent and localized manner. Nonetheless, the successful therapy of osteosarcoma as primary bone tumors is still a challenge. Nanomicelles are colloidal nanosystems widely used in drug development to improve blood circulation time, bioavailability, and specificity of therapeutic agents, among other applications. In addition, the enhanced permeability and retention effect of the nanosystems, and the renal excretion of the nanomicelles reported in most cases so far, are very attractive to achieve selective and increased accumulation in tumor site as well as to increase the safety of [²²³Rₐ]RₐCl₂ in the clinical routine. In the present work, [²²³Rₐ]RₐCl₂ nanomicelles were produced, characterized, in vitro evaluated, and compared with pure [²²³Rₐ]RₐCl2 solution using SAOS2 osteosarcoma cells. The [²²³Rₐ]RₐCl₂ nanomicelles were prepared using the amphiphilic copolymer Pluronic F127. The dynamic light scattering analysis of freshly produced [²²³Rₐ]RₐCl₂ nanomicelles demonstrated a mean size of 129.4 nm with a polydispersity index (PDI) of 0.303. After one week stored in the refrigerator, the mean size of the [²²³Rₐ]RₐCl₂ nanomicelles increased to 169.4 with a PDI of 0.381. Atomic force microscopy analysis of [223Rₐ]RₐCl₂ nanomicelles exhibited spherical structures whose heights reach 1 µm, suggesting the filling of 127-Pluronic nanomicelles with [²²³Rₐ]RₐCl₂. The viability assay with [²²³Rₐ]RₐCl₂ nanomicelles displayed a dose-dependent response as it was observed using pure [²²³Rₐ]RₐCl2. However, at the same dose, [²²³Rₐ]RₐCl₂ nanomicelles were 20% higher efficient in killing SAOS2 cells when compared with pure [²²³Rₐ]RₐCl₂. These findings demonstrated the effectiveness of the nanosystem validating the application of nanotechnology in targeted alpha therapy with [²²³Ra]RₐCl₂. In addition, the [²²³Rₐ]RaCl₂nanomicelles may be decorated and incorporated with a great variety of agents and compounds (e.g., monoclonal antibodies, aptamers, peptides) to overcome the limited use of [²²³Ra]RₐCl₂.

Keywords: nanomicelles, osteosarcoma, radium dichloride, targeted alpha therapy

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Authors: Lynette Lincoln, Sunil S. More

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With the rising demand of sugar used today, it is proposed that world sugar is expected to escalate up to 203 million tonnes by 2021. Hydrolysis of sucrose (table sugar) into glucose and fructose equimolar mixture is catalyzed by β-D-fructofuranoside fructohydrolase (EC 3.2.1.26), commonly called as invertase. For fluid filled center in chocolates, preparation of artificial honey, as a sweetener and especially to ensure that food stuffs remain fresh, moist and soft for longer spans invertase is applied widely and is extensively being used. From an industrial perspective, properties such as increased solubility, osmotic pressure and prevention of crystallization of sugar in food products are highly desired. Screening for invertase does not involve plate assay/qualitative test to determine the enzyme production. In this study, we use a three-step screening strategy for identification of a novel bacterial isolate from soil which is positive for invertase production. The primary step was serial dilution of soil collected from sugarcane fields (black soil, Maddur region of Mandya district, Karnataka, India) was grown on a Czapek-Dox medium (pH 5.0) containing sucrose as the sole C-source. Only colonies with the capability to utilize/breakdown sucrose exhibited growth. Bacterial isolates released invertase in order to take up sucrose, splitting the disaccharide into simple sugars. Secondly, invertase activity was determined from cell free extract by measuring the glucose released in the medium at 540 nm. Morphological observation of the most potent bacteria was examined by several identification tests using Bergey’s manual, which enabled us to know the genus of the isolate to be Bacillus. Furthermore, this potent bacterial colony was subjected to 16S rDNA PCR amplification and a single discrete PCR amplicon band of 1500 bp was observed. The 16S rDNA sequence was used to carry out BLAST alignment search tool of NCBI Genbank database to obtain maximum identity score of sequence. Molecular sequencing and identification was performed by Xcelris Labs Ltd. (Ahmedabad, India). The colony was identified as Bacillus sp. BAB-3434, indicating to be the first novel strain for extracellular invertase production. Molasses, a by-product of the sugarcane industry is a dark viscous liquid obtained upon crystallization of sugar. An enhanced invertase production and optimization studies were carried out by one-factor-at-a-time approach. Crucial parameters such as time course (24 h), pH (6.0), temperature (45 °C), inoculum size (2% v/v), N-source (yeast extract, 0.2% w/v) and C-source (molasses, 4% v/v) were found to be optimum demonstrating an increased yield. The findings of this study reveal a simple screening method of an extracellular invertase from a rapidly growing Bacillus sp., and selection of best factors that elevate enzyme activity especially utilization of molasses which served as an ideal substrate and also as C-source, results in a cost-effective production under submerged conditions. The invert mixture could be a replacement for table sugar which is an economic advantage and reduce the tedious work of sugar growers. On-going studies involve purification of extracellular invertase and determination of transfructosylating activity as at high concentration of sucrose, invertase produces fructooligosaccharides (FOS) which possesses probiotic properties.

Keywords: Bacillus sp., invertase, molasses, screening, submerged fermentation

Procedia PDF Downloads 218

Authors: Pratima Pokharel

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When sewer overflow due to rainfall in urban areas, this leads to public health risks when an individual is exposed to that contaminated floodwater. Nevertheless, it is still unclear the extent to which the infections pose a risk to public health. This study analyzed reported diarrheal cases by month and age in Bangkok, Thailand. The results showed that the cases are reported higher in the wet season than in the dry season. It was also found that in Bangkok, the probability of infection with diarrheal diseases in the wet season is higher for the age group between 15 to 44. However, the probability of infection is highest for kids under 5 years, but they are not influenced by wet weather. Further, this study introduced a vulnerability that leads to health risks from urban flooding. This study has found some vulnerability variables that contribute to health risks from flooding. Thus, for vulnerability analysis, the study has chosen two variables, economic status, and age, that contribute to health risk. Assuming that the people's economic status depends on the types of houses they are living in, the study shows the spatial distribution of economic status in the vulnerability maps. The vulnerability map result shows that people living in Sukhumvit have low vulnerability to health risks with respect to the types of houses they are living in. In addition, from age the probability of infection of diarrhea was analyzed. Moreover, a field survey was carried out to validate the vulnerability of people. It showed that health vulnerability depends on economic status, income level, and education. The result depicts that people with low income and poor living conditions are more vulnerable to health risks. Further, the study also carried out 1D Hydrodynamic Advection-Dispersion modelling with 2-year rainfall events to simulate the dispersion of fecal coliform concentration in the drainage network as well as 1D/2D Hydrodynamic model to simulate the overland flow. The 1D result represents higher concentrations for dry weather flows and a large dilution of concentration on the commencement of a rainfall event, resulting in a drop of the concentration due to runoff generated after rainfall, whereas the model produced flood depth, flood duration, and fecal coliform concentration maps, which were transferred to ArcGIS to produce hazard and risk maps. In addition, the study also simulates the 5-year and 10-year rainfall simulations to show the variation in health hazards and risks. It was found that even though the hazard coverage is very high with a 10-year rainfall events among three rainfall events, the risk was observed to be the same with a 5-year and 10-year rainfall events.

Keywords: urban flooding, risk, hazard, vulnerability, health risk, framework

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Authors: E. H. Walsh, J. McMahon, M. P. Herring

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Post-primary school-based suicide prevention (PSSP) is a valuable avenue to reduce suicidal behaviours in adolescents. The aims of this meta-analysis and meta-regression were 1) to quantify the effect of PSSP interventions on adolescent suicide ideation (SI) and suicide attempts (SA), and 2) to explore how intervention effects may vary based on important contextual and intervention factors. This study provides further support to the benefits of PSSP by demonstrating lower suicide outcomes in over 30,000 adolescents following PSSP and mental health interventions and tentatively suggests that intervention effectiveness may potentially vary based on intervention factors. The protocol for this study is registered on PROSPERO (ID=CRD42020168883). Population, intervention, comparison, outcomes, and study design (PICOs) defined eligible studies as cluster randomised studies (n=12) containing PSSP and measuring suicide outcomes. Aggregate electronic database EBSCO host, Web of Science, and Cochrane Central Register of Controlled Trials databases were searched. Cochrane bias tools for cluster randomised studies demonstrated that half of the studies were rated as low risk of bias. The Egger’s Regression Test adapted for multi-level modelling indicated that publication bias was not an issue (all ps > .05). Crude and corresponding adjusted pooled log odds ratios (OR) were computed using the Metafor package in R, yielding 12 SA and 19 SI effects. Multi-level random-effects models accounting for dependencies of effects from the same study revealed that in crude models, compared to controls, interventions were significantly associated with 13% (OR=0.87, 95% confidence interval (CI), [0.78,0.96], Q18 =15.41, p=0.63) and 34% (OR=0.66, 95%CI [0.47,0.91], Q10=16.31, p=0.13) lower odds of SI and SA, respectively. Adjusted models showed similar odds reductions of 15% (OR=0.85, 95%CI[0.75,0.95], Q18=10.04, p=0.93) and 28% (OR=0.72, 95%CI[0.59,0.87], Q10=10.46, p=0.49) for SI and SA, respectively. Within-cluster heterogeneity ranged from no heterogeneity to low heterogeneity for SA across crude and adjusted models (0-9%). No heterogeneity was identified for SI across crude and adjusted models (0%). Pre-specified univariate moderator analyses were not significant for SA (all ps < 0.05). Variations in average pooled SA odds reductions across categories of various intervention characteristics were observed (all ps < 0.05), which preliminarily suggests that the effectiveness of interventions may potentially vary across intervention factors. These findings have practical implications for researchers, clinicians, educators, and decision-makers. Further investigation of important logical, theoretical, and empirical moderators on PSSP intervention effectiveness is recommended to establish how and when PSSP interventions best reduce adolescent suicidal behaviour.

Keywords: adolescents, contextual factors, post-primary school-based suicide prevention, suicide ideation, suicide attempts

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Authors: Phillipa Evans, Christopher Trotter

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Aims: This study aims to examine the effectiveness of a practice skills framework implemented in three youth detention centres in Juvenile Justice in New South Wales (NSW), Australia. The study is supported by a grant from and Australian Research Council and NSW Juvenile Justice. Recent years have seen a number of incidents in youth detention centres in Australia and other places. These have led to inquiries and reviews with some suggesting that detention centres often do not even meet basic human rights and do little in terms of providing opportunities for rehabilitation of residents. While there is an increasing body of research suggesting that community based supervision can be effective in reducing recidivism if appropriate skills are used by supervisors, there has been less work considering worker skills in youth detention settings. The research that has been done, however, suggest that teaching interpersonal skills to youth officers may be effective in enhancing the rehabilitation culture of centres. Positive outcomes have been seen in a UK detention centre for example, from teaching staff to do five-minute problem-solving interventions. The aim of this project is to examine the effectiveness of training and coaching youth detention staff in three NSW detention centres in interpersonal practice skills. Effectiveness is defined in terms of reductions in the frequency of critical incidents and improvements in the well-being of staff and young people. The research is important as the results may lead to the development of more humane and rehabilitative experiences for young people. Method: The study involves training staff in core effective practice skills and supporting staff in the use of those skills through supervision and de-briefing. The core effective practice skills include role clarification, pro-social modelling, brief problem solving, and relationship skills. The training also addresses some of the background to criminal behaviour including trauma. Data regarding critical incidents and well-being before and after the program implementation are being collected. This involves interviews with staff and young people, the completion of well-being scales, and examination of departmental records regarding critical incidents. In addition to the before and after comparison a matched control group which is not offered the intervention is also being used. The study includes more than 400 young people and 100 youth officers across 6 centres including the control sites. Data collection includes interviews with workers and young people, critical incident data such as assaults, use of lock ups and confinement and school attendance. Data collection also includes analysing video-tapes of centre activities for changes in the use of staff skills. Results: The project is currently underway with ongoing training and supervision. Early results will be available for the conference.

Keywords: custody, practice skills, training, youth workers

Procedia PDF Downloads 80

Authors: Niharika Kaushal, Minni Singh

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Fruit crops are widely cultivated throughout the World, with citrus being one of the most common. Mandarins, oranges, grapefruits, lemons, and limes are among the most frequently grown varieties. Citrus cultivars are industrially processed into juice, resulting in approx. 25-40% by wt. of biomass in the form of peels and seeds, generally considered as waste. In consequence, a significant amount of this nutraceutical-enriched biomass goes to waste, which, if utilized wisely, could revolutionize the functional food industry, as this biomass possesses a wide range of bioactive compounds, mainly within the class of polyphenols and terpenoids, making them an abundant source of functional bioactive. Mandarin is a potential source of bioflavonoids with putative antioxidative properties, and its potential application for developing value-added products is obvious. In this study, ‘kinnow’ mandarin (Citrus nobilis X Citrus deliciosa) biomass was studied for its flavonoid profile. For this, dried and pulverized peels were subjected to green and sustainable extraction techniques, namely, supercritical fluid extraction carried out under conditions pressure: 330 bar, temperature: 40 ̊ C and co-solvent: 10% ethanol. The obtained extract was observed to contain 47.3±1.06 mg/ml rutin equivalents as total flavonoids. Mass spectral analysis revealed the prevalence of polymethoxyflavones (PMFs), chiefly tangeretin and nobiletin. Furthermore, the antioxidant potential was analyzed by the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method, which was estimated to be at an IC₅₀ of 0.55μg/ml. The pre-systemic metabolism of flavonoids limits their functionality, as was observed in this study through in vitro gastrointestinal studies where nearly 50.0% of the flavonoids were degraded within 2 hours of gastric exposure. We proposed nanoencapsulation as a means to overcome this problem, and flavonoids-laden polylactic-co-glycolic acid (PLGA) nano encapsulates were bioengineered using solvent evaporation method, and these were furnished to a particle size between 200-250nm, which exhibited protection of flavonoids in the gastric environment, allowing only 20% to be released in 2h. A further step involved impregnating the nano encapsulates within alginate hydrogels which were fabricated by ionic cross-linking, which would act as delivery vehicles within the gastrointestinal (GI) tract. As a result, 100% protection was achieved from the pre-systemic release of bioflavonoids. These alginate hydrogels had key significant features, i.e., less porosity of nearly 20.0%, and Cryo-SEM (Cryo-scanning electron microscopy) images of the composite corroborate the packing ability of the alginate hydrogel. As a result of this work, it is concluded that the waste can be used to develop functional biomaterials while retaining the functionality of the bioactive itself.

Keywords: bioflavonoids, gastrointestinal, hydrogels, mandarins

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Authors: Elizabeth Parrott, Harry Pointon, Frederic Bezombes, Heather Panter

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Unmanned aerial vehicles (UAV’s) are making a profound effect within policing, forensic and fire service procedures worldwide. These intelligent devices have already proven useful in photographing and recording large-scale outdoor and indoor sites using orthomosaic and three-dimensional (3D) modelling techniques, for the purpose of capturing and recording sites during and post-incident. UAV’s are becoming an established tool as they are extending the reach of the photographer and offering new perspectives without the expense and restrictions of deploying full-scale aircraft. 3D reconstruction quality is directly linked to the resolution of captured images; therefore, close proximity flights are required for more detailed models. As technology advances deployment of UAVs in confined spaces is becoming more common. With this in mind, this study investigates the effects of UAV operation within active crimes scenes with regard to the dispersal of particulate evidence. To date, there has been little consideration given to the potential effects of using UAV’s within active crime scenes aside from a legislation point of view. Although potentially the technology can reduce the likelihood of contamination by replacing some of the roles of investigating practitioners. There is the risk of evidence dispersal caused by the effect of the strong airflow beneath the UAV, from the downwash of the propellers. The initial results of this study are therefore presented to determine the height of least effect at which to fly, and the commercial propeller type to choose to generate the smallest amount of disturbance from the dataset tested. In this study, a range of commercially available 4-inch propellers were chosen as a starting point due to the common availability and their small size makes them well suited for operation within confined spaces. To perform the testing, a rig was configured to support a single motor and propeller powered with a standalone mains power supply and controlled via a microcontroller. This was to mimic a complete throttle cycle and control the device to ensure repeatability. By removing the variances of battery packs and complex UAV structures to allow for a more robust setup. Therefore, the only changing factors were the propeller and operating height. The results were calculated via computer vision analysis of the recorded dispersal of the sample particles placed below the arm-mounted propeller. The aim of this initial study is to give practitioners an insight into the technology to use when operating within confined spaces as well as recognizing some of the issues caused by UAV’s within active crime scenes.

Keywords: dispersal, evidence, propeller, UAV

Procedia PDF Downloads 143

Authors: Anna V. Zaporozhchenko, Dmytro Kutnyakhov, Katherina Medjanik, Christian Tusche, Hans-Joachim Elmers, Olena Fedchenko, Sergey Chernov, Martin Ellguth, Sergej A. Nepijko, Gerd Schoenhense

Abstract:

Graphene reveals a unique electronic structure that predetermines many intriguing properties such as massless charge carriers, optical transparency and high velocity of fermions at the Fermi level, opening a wide horizon of future applications. Hence, a detailed investigation of the electronic structure of graphene is crucial. The method of choice is angular resolved photoelectron spectroscopy ARPES. Here we present experiments using time-of-flight (ToF) momentum microscopy, being an alternative way of ARPES using full-field imaging of the whole Brillouin zone (BZ) and simultaneous acquisition of up to several 100 energy slices. Unlike conventional ARPES, k-microscopy is not limited in simultaneous k-space access. We have recorded the whole first BZ of graphene on Ir(111) including all six Dirac cones. As excitation source we used synchrotron radiation from BESSY II (Berlin) at the U125-2 NIM, providing linearly polarized (both polarizations p- and s-) VUV radiation. The instrument uses a delay-line detector for single-particle detection up the 5 Mcps range and parallel energy detection via ToF recording. In this way, we gather a 3D data stack I(E,kx,ky) of the full valence electronic structure in approx. 20 mins. Band dispersion stacks were measured in the energy range of 14 eV up to 23 eV with steps of 1 eV. The linearly-dispersing graphene bands for all six K and K’ points were simultaneously recorded. We find clear features of hybridization with the substrate, in particular in the linear dichroism in the angular distribution (LDAD). Recording of the whole Brillouin zone of graphene/Ir(111) revealed new features. First, the intensity differences (i.e. the LDAD) are very sensitive to the interaction of graphene bands with substrate bands. Second, the dark corridors are investigated in detail for both, p- and s- polarized radiation. They appear as local distortions of photoelectron current distribution and are induced by quantum mechanical interference of graphene sublattices. The dark corridors are located in different areas of the 6 Dirac cones and show chirality behaviour with a mirror plane along vertical axis. Moreover, two out of six show an oval shape while the rest are more circular. It clearly indicates orientation dependence with respect to E vector of incident light. Third, a pattern of faint but very sharp lines is visible at energies around 22eV that strongly remind on Kikuchi lines in diffraction. In conclusion, the simultaneous study of all six Dirac cones is crucial for a complete understanding of dichroism phenomena and the dark corridor.

Keywords: band structure, graphene, momentum microscopy, LDAD

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Authors: Liudmila Shabalinskaya, Victor Golovanov, Liudmila Milinis, Sergey Loponos, Alexander Maslov, D. O. Frolov

Abstract:

The work is devoted to the rapid laboratory diagnosis of the condition of aircraft friction units, based on the application of the nondestructive testing method by analyzing the parameters of wear particles, or tribodiagnostics. The most important task of tribodiagnostics is to develop recommendations for the selection of more advanced designs, materials and lubricants based on data on wear processes for increasing the life and ensuring the safety of the operation of machines and mechanisms. The object of tribodiagnostics in this work are the tooth gears of the central drive and the gearboxes of the gas turbine engine of the civil aviation PS-90A type, in which rolling friction and sliding friction with slip occur. The main criterion for evaluating the technical state of lubricated friction units of a gas turbine engine is the intensity and rate of wear of the friction surfaces of the friction unit parts. When the engine is running, oil samples are taken and the state of the friction surfaces is evaluated according to the parameters of the wear particles contained in the oil sample, which carry important and detailed information about the wear processes in the engine transmission units. The parameters carrying this information include the concentration of wear particles and metals in the oil, the dispersion composition, the shape, the size ratio and the number of particles, the state of their surfaces, the presence in the oil of various mechanical impurities of non-metallic origin. Such a morphological analysis of wear particles has been introduced into the order of monitoring the status and diagnostics of various aircraft engines, including a gas turbine engine, since the type of wear characteristic of the central drive and the drive box is surface fatigue wear and the beginning of its development, accompanied by the formation of microcracks, leads to the formation of spherical, up to 10 μm in size, and in the aftermath of flocculent particles measuring 20-200 μm in size. Tribodiagnostics using the morphological analysis of wear particles includes the following techniques: ferrography, filtering, and computer analysis of the classification and counting of wear particles. Based on the analysis of several series of oil samples taken from the drive box of the engine during their operating time, a study was carried out of the processes of wear kinetics. Based on the results of the study and comparing the series of criteria for tribodiagnostics, wear state ratings and statistics of the results of morphological analysis, norms for the normal operating regime were developed. The study allowed to develop levels of wear state for friction surfaces of gearing and a 10-point rating system for estimating the likelihood of the occurrence of an increased wear mode and, accordingly, prevention of engine failures in flight.

Keywords: aviation, box of drives, morphological analysis, tribodiagnostics, tribology, ferrography, filtering, wear particle

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Authors: Swapnil Kumar Singh

Abstract:

Gamma-ray bursts (GRB's), short and intense pulses of low-energy γ rays, have fascinated astronomers and astrophysicists since their unexpected discovery in the late sixties. GRB'sare accompanied by long-lasting afterglows, and they are associated with core-collapse supernovae. The detection of delayed emission in X-ray, optical, and radio wavelength, or "afterglow," following a γ-ray burst can be described as the emission of a relativistic shell decelerating upon collision with the interstellar medium. While it is fair to say that there is strong diversity amongst the afterglow population, probably reflecting diversity in the energy, luminosity, shock efficiency, baryon loading, progenitor properties, circumstellar medium, and more, the afterglows of GRBs do appear more similar than the bursts themselves, and it is possible to identify common features within afterglows that lead to some canonical expectations. After an initial flash of gamma rays, a longer-lived "afterglow" is usually emitted at longer wavelengths (X-ray, ultraviolet, optical, infrared, microwave, and radio). It is a slowly fading emission at longer wavelengths created by collisions between the burst ejecta and interstellar gas. In X-ray wavelengths, the GRB afterglow fades quickly at first, then transitions to a less-steep drop-off (it does other stuff after that, but we'll ignore that for now). During these early phases, the X-ray afterglow has a spectrum that looks like a power law: flux F∝ E^β, where E is energy and beta is some number called the spectral index. This kind of spectrum is characteristic of synchrotron emission, which is produced when charged particles spiral around magnetic field lines at close to the speed of light. In addition to the outgoing forward shock that ploughs into the interstellar medium, there is also a so-called reverse shock, which propagates backward through the ejecta. In many ways," reverse" shock can be misleading; this shock is still moving outward from the restframe of the star at relativistic velocity but is ploughing backward through the ejecta in their frame and is slowing the expansion. This reverse shock can be dynamically important, as it can carry comparable energy to the forward shock. The early phases of the GRB afterglow still provide a good description even if the GRB is highly collimated since the individual emitting regions of the outflow are not in causal contact at large angles and so behave as though they are expanding isotropically. The majority of afterglows, at times typically observed, fall in the slow cooling regime, and the cooling break lies between the optical and the X-ray. Numerous observations support this broad picture for afterglows in the spectral energy distribution of the afterglow of the very bright GRB. The bluer light (optical and X-ray) appears to follow a typical synchrotron forward shock expectation (note that the apparent features in the X-ray and optical spectrum are due to the presence of dust within the host galaxy). We need more research in GRB and Particle Physics in order to unfold the mysteries of afterglow.

Keywords: GRB, synchrotron, X-ray, isotropic energy

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Authors: Z. Karahaliloğlu, E. Yalçın, M. Demirbilek, E.B. Denkbaş

Abstract:

Critical-sized bone defects caused by trauma, bone diseases, prosthetic implant revision or tumor excision cannot be repaired by physiological regenerative processes. Current orthopedic applications for critical-sized bone defects are to use autologous bone grafts, bone allografts, or synthetic graft materials. However, these strategies are unable to solve completely the problem, and motivate the development of novel effective biological scaffolds for tissue engineering applications and regenerative medicine applications. In particular, scaffolds combined with a variety of bio-agents as fundamental tools emerge to provide the regeneration of damaged bone tissues due to their ability to promote cell growth and function. In this study, a magnetic silk fibroin (SF) hydrogel scaffold was prepared by electrogelation process of the concentrated Bombxy mori silk fibroin (8 %wt) aqueous solution. For enhancement of osteoblast-like cells (SaOS-2) growth and adhesion, basal fibroblast growth factor (bFGF) were conjugated physically to the HSA-coated magnetic nanoparticles (Fe3O4) and magnetic SF e-gel scaffolds were prepared by incorporation of Fe3O4, HSA (human serum albumin)=Fe3O4 and HSA=Fe3O4-bFGF nanoparticles. HSA=Fe3O4, HSA=Fe3O4-bFGF loaded and bare SF e-gels scaffolds were characterized using scanning electron microscopy (SEM.) For cell studies, human osteoblast-like cell line (SaOS-2) was used and an MTT assay was used to assess the cytotoxicity of magnetic silk fibroin e-gel scaffolds and cell density on these surfaces. For the evaluation osteogenic activation, ALP (alkaline phosphatase), the amount of mineralized calcium, total protein and collagen were studied. Fe3O4 nanoparticles were successfully synthesized and bFGF was conjugated to HSA=Fe3O4 nanoparticles with %97.5 of binding yield which has a particle size of 71.52±2.3 nm. Electron microscopy images of the prepared HSA and bFGF incorporated SF e-gel scaffolds showed a 3D porous morphology. In terms of water uptake results, bFGF conjugated HSA=Fe3O4 nanoparticles has the best water absorbability behavior among all groups. In the in-vitro cell culture studies realized using SaOS-2 cell line, the coating of Fe3O4 nanoparticles surface with a protein enhance the cell viability and HSA coating and bFGF conjugation, the both have an inductive effect in the cell proliferation. One of the markers of bone formation and osteoblast differentiation, according to the ALP activity and total protein results, HSA=Fe3O4-bFGF loaded SF e-gels had significantly enhanced ALP activity. Osteoblast cultured HSA=Fe3O4-bFGF loaded SF e-gels deposited more calcium compared with SF e-gel. The proposed magnetic scaffolds seem to be promising for bone tissue regeneration and used in future work for various applications.

Keywords: basic fibroblast growth factor (bFGF), e-gel, iron oxide nanoparticles, silk fibroin

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Authors: Sanchita Baitalik, Nijhuma Kayal, Omprakash Chakrabarti

Abstract:

Recently SiC ceramics have been a focus of interest in the field of porous materials due to their unique combination of properties and hence they are considered as an ideal candidate for catalyst supports, thermal insulators, high-temperature structural materials, hot gas particulate separation systems etc. in different industrial processes. Several processing methods are followed for fabrication of porous SiC at low temperatures but all these methods are associated with several disadvantages. Therefore processing of porous SiC ceramics at low temperatures is still challenging. Concerning that of incorporation of secondary bond phase additives by an infiltration technique should result in a homogenous distribution of bond phase in the final ceramics. Present work is aimed to synthesis cordierite (2MgO.2Al2O3.5SiO2) bonded porous SiC ceramics following incorporation of sol-gel bond phase precursor into powder compacts of SiC and heat treating the infiltrated body at 1400 °C. In this paper the primary aim was to study the effect of infiltration of a precursor sol of cordierite into a porous SiC powder compact prepared with pore former of different particle sizes on the porosity, pore size, microstructure and the mechanical properties of the porous SiC ceramics. Cordierite sol was prepared by mixing a solution of magnesium nitrate hexahydrate and aluminium nitrate nonahydrate in 2:4 molar ratio in ethanol another solution containing tetra-ethyl orthosilicate and ethanol in 1:3 molar ratio followed by stirring for several hours. Powders of SiC (α-SiC; d50 =22.5 μm) and 10 wt. % polymer microbead of two sizes 8 and 50µm as the pore former were mixed in a suitable liquid medium, dried and pressed in the form of bars (50×20×16 mm3) at 23 MPa pressure. The well-dried bars were heat treated at 1100° C for 4 h with a hold at 750 °C for 2 h to remove the pore former. Bars were evacuated for 2 hr upto 0.3 mm Hg pressure into a vacuum chamber and infiltrated with cordierite precursor sol. The infiltrated samples were dried and the infiltration process was repeated until the weight gain became constant. Finally the infiltrated samples were sintered at 1400 °C to prepare cordierite bonded porous SiC ceramics. Porous ceramics prepared with 8 and 50 µm sized microbead exhibited lower oxidation degrees of respectively 7.8 and 4.8 % than the sample (23 %) prepared with no microbead. Depending on the size of pore former, the porosity of the final ceramic varied in the range of 36 to 40 vol. % with a variation of flexural strength from 33.7 to 24.6 MPa. XRD analysis showed major crystalline phases of the ceramics as SiC, SiO2 and cordierite. Two forms of cordierite, α-(hexagonal) and µ-(cubic), were detected by the XRD analysis. The SiC particles were observed to be bonded both by cristobalite with fish scale morphology and cordierite with rod shape morphology and thereby formed a porous network. The material and mechanical properties of cordierite bonded porous SiC ceramics are good in agreement to carry out further studies like thermal shock, corrosion resistance etc.

Keywords: cordierite, infiltration technique, porous ceramics, sol-gel

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