Search results for: synthetic aperture imaging

Authors: Hammad Khan, Wookeun Bae

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Major concerns regarding nitritation of low-strength ammonium wastewaters include low ammonium loading rates (usually below 0.2 kg/m3-d) and uncertainty about long-term stability of the process. The purpose of this study was to test a sequencing batch reactor (SBR) filled with cell-immobilized polyethylene glycol (PEG) pellets to see if it could achieve efficient and stable nitritation under various environmental conditions. SBR was fed with synthetic ammonium wastewater of 30±2 mg-N/L and pH: 8±0.05, maintaining the dissolved oxygen concentration of 1.7±0.2 mg/L and the temperature at 30±1oC. The reaction was easily converted to partial nitrification mode within a month by feeding relatively high ammonium substrate (~100 mg-N/L) in the beginning. We observed stable nitritation over 300 days with high ammonium loading rates (as high as ~1.1 kg-N/m3-d), nitrite accumulation rates (mostly over 97%) and ammonium removal rate (mostly over 95%). DO was a major limiting substrate when the DO concentration was below ~4 mg/L and the NH4+-N concentration was above 5 mg/L, giving almost linear increase in the ammonium oxidation rate with the bulk DO increase. Low temperatures mainly affected the reaction rate, which could be compensated for by increasing the pellet volume (i.e. biomass). Our results demonstrated that an SBR filled with small cell-immobilized PEG pellets could achieve very efficient and stable nitritation of a low-strength ammonium wastewater.

Keywords: ammonium loading rate (ALR), cell-immobilization, long-term nitritation, sequencing batch reactor (SBR), sewage treatment

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Authors: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Ali Ben Abbes, Imed Riadh Farah

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Due to the considerable advances in Multi-Temporal Satellite Images (MTSI), remote sensing application became more accurate. Recently, many advances in modeling MTSI are developed using various models. The purpose of this article is to present an overview of studies using Hidden Markov Model (HMM). First of all, we provide a background of using HMM and their applications in this context. A comparison of the different works is discussed, and possible areas and challenges are highlighted. Secondly, we discussed the difference on vegetation monitoring as well as urban growth. Nevertheless, most research efforts have been used only stationary data. From another point of view, in this paper, we describe a new non-stationarity HMM, that is defined with a set of parts of the time series e.g. seasonal, trend and random. In addition, a new approach giving more accurate results and improve the applicability of the HMM in modeling a non-stationary data series. In order to assess the performance of the HMM, different experiments are carried out using Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI time series of the northwestern region of Tunisia and Landsat time series of tres Cantos-Madrid in Spain.

Keywords: multi-temporal satellite image, HMM , nonstationarity, vegetation, urban

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Authors: Suparna Roy, P. Anantharaman

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The aim of this work is to estimate some in-vitro antioxidant activities and total phenols of various extracts such as aqueous, acetone, ethanol, methanol extract of seaweeds and pigments content by Spectrophotometric method. The seaweeds were collected during 2016 from Rameshwaram, southeast coast of India. Among four different extracts, aqueous extracts from all seaweeds had minimum activity than acetone, methanol and ethanol. The Rhodophyta and Phaeophyta had high antioxidant activity in comparing to Chlorophyta. The highest total antioxidant activity was found in acetone extract fromTurbinaria decurrens (98.97±0.00%), followed by its methanol extract (98.81±0.60%) and ethanol extract (98.58±0.53%). The highest reducing power and H2O2 scavenging activity were found in acetone extract of Caulerpa racemosa (383.25±1.04%), and methanol extract from Caulerpa racemosa var. macrophysa (24.91±0.49%). The methanol extract from Caulerpa scalpelliformis contained the highest total phenol (85.23±0.12%). The Chloro-a and Chloro-b contents were the highest in Gracilaria foliifera (13.69±0.38% mg/gm dry wt.) and Caulerpa racemosa var. macrophysa (9.12 ±0.12% mg/gm dry wt.) likewise carotenoid was also the highest in Gracilaria foliifera (0.054±0.0003% mg/gm dry wt.) and Caulerpa racemosa var. macrophysa (0.04 ±0.002% mg/gm dry wt.). It can be concluded from this study that some seaweed extract can be used for natural antioxidant production, after further characterization to negotiate the side effect of synthetic, market available antioxidants.

Keywords: seaweeds, antioxidant, total phenol, pigment, Olaikuda, Vadakkadu, Rameshwaram

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Authors: Krasimir Ivanov, Dimitar Dimitrov, Tatyana Tabakova, Stefka Kirkova, Anna Stoilova, Violina Angelova

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It has been suggested that nicotine, CO and tar in mainstream smoke are the most important substances and have been judged as the most harmful compounds, responsible for the health hazards of smoking. As nicotine is extremely important for smoking qualities of cigarettes and the tar yield in the tobacco smoke is significantly reduced due to the use of filters with various content and design, the main efforts of cigarettes researchers and manufacturers are related to the search of opportunities for CO content reduction. Highly active ceria supported gold catalyst was prepared by the deposition-precipitation method, and the possibilities for CO oxidation in the synthetic gaseous mixture were evaluated using continuous flow equipment with fixed bed glass reactor at atmospheric pressure. The efficiently of the catalyst in CO oxidation in the real cigarette smoke was examined by a single port, puf-by-puff smoking machine. Quality assessment of smoking using cigarette holder containing catalyst was carried out. It was established that the catalytic activity toward CO oxidation in cigarette smoke rapidly decreases from 70% for the first cigarette to nearly zero for the twentieth cigarette. The present study shows that there are two critical factors which do not permit the successful use of catalysts to reduce the CO content in the mainstream cigarette smoke: (i) significant influence of the processes of adsorption and oxidation on the main characteristics of tobacco products and (ii) rapid deactivation of the catalyst due to the covering of the catalyst’s grains with condensate.

Keywords: cigarette smoke, CO oxidation, gold catalyst, mainstream

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Authors: Matthew Ndubuisi Abonyi, Christopher Chiedozie Obi, Joseph Tagbo Nwabanne

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This review focuses on the application of Metal-Organic Frameworks (MOF)-based catalysts in the degradation of organic pollutants in wastewater. The degradation of organic pollutants in wastewater remains a critical environmental challenge, necessitating innovative solutions for effective treatment. MOFs have garnered significant attention as promising catalysts for this purpose, owing to their exceptional surface area, tunable porosity, and diverse chemical functionalities. It explores various catalytic mechanisms, including photocatalysis, Fenton-like reactions, and other advanced oxidation processes facilitated by MOFs. The review also explores the design strategies that enhance the catalytic performance of MOFs, such as structural modifications, composite formation, and post-synthetic modifications. Furthermore, real-world case studies are presented, highlighting the practical applications and environmental impact of MOF-based catalysts in wastewater treatment. Challenges associated with the scalability and stability of these materials are discussed, along with future directions for research and development. This review highlights the significant potential of MOF-based catalysts in addressing the pressing issue of water pollution and advocates for continued innovation to optimize their application in wastewater treatment.

Keywords: metal-organic frameworks (MOFs), catalysis, wastewater treatment, organic pollutant degradation, photocatalysis

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Authors: Moses Emetere, Marvel Akinyemi, S. E. Sanni

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At the moment, AERONET or AMMA database shows a large volume of data loss. With only about 47% data set available to the scientist, it is evident that accurate nowcast or forecast cannot be guaranteed. The calibration constants of most radiosonde or weather stations are not compatible with the atmospheric conditions of the West African climate. A dispersion model was developed to incorporate salient mathematical representations like a Unified number. The Unified number was derived to describe the turbulence of the aerosols transport in the frictional layer of the lower atmosphere. Fourteen years data set from Multi-angle Imaging SpectroRadiometer (MISR) was tested using the dispersion model. A yearly estimation of the atmospheric constants over Ouagadougou using the model was obtained with about 87.5% accuracy. It further revealed that the average atmospheric constant for Ouagadougou-Niger is a_1 = 0.626, a_2 = 0.7999 and the tuning constants is n_1 = 0.09835 and n_2 = 0.266. Also, the yearly atmospheric constants affirmed the lower atmosphere of Ouagadougou is very dynamic. Hence, it is recommended that radiosonde and weather station manufacturers should constantly review the atmospheric constant over a geographical location to enable about eighty percent data retrieval.

Keywords: aerosols retention, aerosols loading, statistics, analytical technique

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Authors: L. Khalfa, M. Bagane, M. L. Cervera, S. Najjar

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The aim of this work is to present a low cost adsorbent for removing toxic heavy metals from aqueous solutions. Therefore, we are interested to investigate the efficiency of natural clay minerals collected from south Tunisia and their modified form using sulfuric acid in the removal of toxic metal ions: Zn(II) and Pb(II) from synthetic waste water solutions. The obtained results indicate that metal uptake is pH-dependent and maximum removal was detected to occur at pH 6. Adsorption equilibrium is very rapid and it was achieved after 90 min for both metal ions studied. The kinetics results show that the pseudo-second-order model describes the adsorption and the intraparticle diffusion models are the limiting step. The treatment of natural clay with sulfuric acid creates more active sites and increases the surface area, so it showed an increase of the adsorbed quantities of lead and zinc in single and binary systems. The competitive adsorption study showed that the uptake of lead was inhibited in the presence of 10 mg/L of zinc. An antagonistic binary adsorption mechanism was observed. These results revealed that clay is an effective natural material for removing lead and zinc in single and binary systems from aqueous solution.

Keywords: heavy metal, activated clay, kinetic study, competitive adsorption, modeling

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Authors: Behnoush Sabayan, Ali Alidadi, Saeid Ebarhimi, N. M. Bakhshani

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Hemodialysis (HD) patients are at a high risk of atherosclerotic and vascular disease; also little information is available for the HD impact on brain structure of these patients. We studied the brain abnormalities in HD patients. The aim of this study was to investigate the effect of long term HD on brain structure of HD patients. Non-contrast MRI was used to evaluate imaging findings. Our study included 80 HD patients of whom 39 had less than six months of HD and 41 patients had a history of HD more than six months. The population had a mean age of 51.60 years old and 27.5% were female. According to study, HD patients who have been hemodialyzed for a long time (median time of HD was up to 4 years) had small vessel ischemia than the HD patients who underwent HD for a shorter term, which the median time was 3 to 5 months. Most of the small vessel ischemia was located in pre-ventricular, subcortical and white matter (1.33± .471, 1.23± .420 and 1.39±.490). However, the other brain damages like: central pons abnormality, global brain atrophy, thinning of corpus callosum and frontal lobe atrophy were found (P<0.01). The present study demonstrated that HD patients who were under HD for a longer time had small vessel ischemia and we conclude that this small vessel ischemia might be a causative mechanism of brain atrophy in chronic hemodialysis patients. However, additional researches are needed in this area.

Keywords: Hemodialysis Patients, Duration of Hemodialysis, MRI, Zahedan

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Authors: Saeed Eskandari, Seyed Rasoul Mehdikhani

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Radiation sources have been used in many industries, such as gamma sources in medical imaging. These waves have destructive effects on humans and the environment. It is very important to detect and find the source of these waves because these sources cannot be seen by the eye. A portable robot has been designed and built with the purpose of revealing radiation sources that are able to scan the place from 5 to 20 meters away and shows the location of the sources according to the intensity of the waves on a two-dimensional digital image. The operation of the robot is done by measuring the pixels separately. By increasing the image measurement resolution, we will have a more accurate scan of the environment, and more points will be detected. But this causes a lot of time to be spent on scanning. In this paper, to overcome this challenge, we designed a method that can optimize this time. In this method, a small number of important points of the environment are measured. Hence the remaining pixels are predicted and estimated by regression algorithms in machine learning. The research method is based on comparing the actual values of all pixels. These steps have been repeated with several other radiation sources. The obtained results of the study show that the values estimated by the regression method are very close to the real values.

Keywords: regression, machine learning, scan radiation, robot

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Authors: Mohammad Alfaifi

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Organophosphates are among the most widely used synthetic insect pesticides. The widespread use of organophosphates has stimulated research into the possible existence of effects related with their reproductive toxic activity. The present study aimed to assess the effects of diazinon (DIZ) on male reproductive system. DIZ at the dose levels of 1.5, 3.0 and 9.0 mg/kg b. wt./day was administered orally to male rats of Wistar strain for 30 days to evaluate the toxic alterations in testicular histology, biochemistry, sperm dynamics, and testosterone levels. The body weight of animals did not show any significant changes, however, a significant reduction was observed in testes weight. DIZ also brought about marked reduction in epididymal and testicular sperm counts in exposed males and a decrease in serum testosterone concentration. Histopathological examination of testes showed mild to severe degenerative changes in seminiferous tubules at various dose levels. Fertility test showed 79% negative results. All these toxic effects are moderate at low doses and become severe at higher dose levels. From the results of the present study it is concluded that DIZ induces severe testicular damage and results in reduction in sperm count and thus affect fertility. Small changes in sperm counts are known to have adverse affects on human fertility. Therefore, application of such insecticide should be limited to a designed programme.

Keywords: reproductive toxicity, fertility, diazinon, sperm count

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Authors: Amanda C. Evans

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Enabling technologies such as continuous processing (CP) approaches can provide the tools needed to control and manipulate reactivities and transform chemical reactions into micro-controlled in-flow processes. Traditional synthetic approaches can be radically transformed by the application of CP, facilitating the pairing of chemical methodologies with technologies from other disciplines. CP supports sustainable processes that controllably generate reaction specificity utilizing supramolecular interactions. Continuous photochemical processing is an emerging field of investigation. The use of light to drive chemical reactivity is not novel, but the controlled use of specific and tunable wavelengths of light to selectively generate molecular structure under continuous processing conditions is an innovative approach towards chemical synthesis. This investigation focuses on the use of circularly polarized (cp) light as a sustainable catalyst for the CP generation of asymmetric molecules. Chiral photolysis has already been achieved under batch, solid-phase conditions: using synchrotron-sourced cp light, asymmetric photolytic selectivities of up to 4.2% enantiomeric excess (e.e.) have been reported. In order to determine the optimal wavelengths to use for irradiation with cp light for any given molecular building block, CD and anisotropy spectra for each building block of interest have been generated in two different solvents (water, hexafluoroisopropanol) across a range of wavelengths (130-400 nm). These spectra are being used to support a series of CP experiments using cp light to generate enantioselectivity.

Keywords: anisotropy, asymmetry, flow chemistry, active pharmaceutical ingredients

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Authors: Sweta Iyer, Nemeshwaree Behary, Vincent Nierstrasz

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Various organisms involve bioluminescence for their particular biological function. The bio-based molecules responsible for bioluminescence vary from one species to another, research has been done to identify the chemistry and different mechanisms involved in light production in living organisms. The light emitting chemical systems such as firefly and bacterial luminous mostly involves enzyme-catalyzed reactions and is widely used for ATP measurement, bioluminescence imaging, environmental biosensors etc. Our strategy is to design bioluminescent textiles using such bioluminescent systems. Hence, a detailed literature work was carried out to study on how to mimic bioluminescence effect seen in nature. Reaction mechanisms in various bioluminescent living organisms were studied and the components or molecules responsible for luminescence were identified. However, the challenge is to obtain the same effect on textiles by immobilizing enzymes responsible for light creation. Another challenge is also to regenerate substrates involved in the reaction system to create a longer lasting illumination in bioluminescent textiles. Natural film-forming polymers were used to immobilize the reactive components including enzymes on textile materials to design a biomimetic luminescent textile.

Keywords: bioluminescence, biomimetic, immobilize, luminescent textile

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Authors: Plessen Mogens Graf

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Within the context of multivariate time series segmentation, this paper proposes a method inspired by a posteriori optimal trading. After a normalization step, time series are treated channelwise as surrogate stock prices that can be traded optimally a posteriori in a virtual portfolio holding either stock or cash. Linear transaction costs are interpreted as hyperparameters for noise filtering. Trading signals, as well as trading signals obtained on the reversed time series, are used for unsupervised channelwise labeling before a consensus over all channels is reached that determines the final segmentation time instants. The method is model-free such that no model prescriptions for segments are made. Benefits of proposed approach include simplicity, computational efficiency, and adaptability to a wide range of different shapes of time series. Performance is demonstrated on synthetic and real-world data, including a large-scale dataset comprising a multivariate time series of dimension 1000 and length 2709. Proposed method is compared to a popular model-based bottom-up approach fitting piecewise affine models and to a recent model-based top-down approach fitting Gaussian models and found to be consistently faster while producing more intuitive results in the sense of segmenting time series at peaks and valleys.

Keywords: time series segmentation, model-free, trading-inspired, multivariate data

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Authors: Olivier Mulisya, Guelord Barasima, Henry Mark Lugobe, Philémon Matumo, Bienfait Mumbere Vahwere, Hilaire Mutuka, Zawadi Léocadie, Wesley Lumika

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Abdominal pregnancy is defined as pregnancy anywhere within the peritoneal cavity, exclusive of tubal, ovarian, or broad ligament locations. It is a rare form of ectopic pregnancy with high morbidity and mortality for both the mother and the fetus. Diagnosis can be frequently missed in most poor-resource settings because of poor antenatal coverage, low socioeconomic status in most of the patients as well as lack of adequate medical resources. Clinical diagnosis can be very difficult and an ultrasound scan is very helpful during the early stages of gestation but can also be disappointing in the later stages. We report a case of a 25-year-old woman with severe abdominal pain not amended with any medication. A clinical picture of shock lead to an emergency laparotomy which confirmed the diagnosis of abdominal pregnancy. The ministry of health in developing countries should make an effort to make routine early ultrasounds accessible to pregnant women, and obstetricians should keep in mind the possibility of ectopic pregnancy, irrespective of the gestational age.

Keywords: abdominal pregnancy, live new bron, ultrasound imaging, abdominal pain

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Authors: Mohammad Alfaifi, Mohammed Alshehri

Abstract:

Organophosphates are among the most widely used synthetic insect pesticides. The widespread use of organophosphates has stimulated research into the possible existence of effects related with their reproductive toxic activity. The present study aimed to assess the effects of diazinon (DIZ) on male reproductive system. DIZ at the dose levels of 1.5, 3.0 and 9.0 mg/kg b. wt./day was administered orally to male rats of Wistar strain for 30 days to evaluate the toxic alterations in testicular histology, biochemistry, sperm dynamics and testosterone levels. The body weight of animals did not show any significant changes; however, a significant reduction was observed in testes weight. DIZ also brought about a marked reduction in epididymal and testicular sperm counts in exposed males and a decrease in serum testosterone concentration. Histopathological examination of testes showed mild to severe degenerative changes in seminiferous tubules at various dose levels. Fertility test showed 79% negative results. All these toxic effects are moderate at low doses and become severe at higher dose levels. From the results of the present study, it is concluded that DIZ induces severe testicular damage and results in a reduction in sperm count and thus affect fertility. Small changes in sperm counts are known to have adverse effects on human fertility. Therefore, application of such insecticide should be limited to a designed programme.

Keywords: organophosphates, reproductive toxicity, diazinon, fertility

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Authors: Peregrine James Dalziel, Philip Vu Tran

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Objective / Introduction: Demand for radiology services from Emergency Departments (ED) continues to increase with greater demands placed on radiology staff providing reports for the management of complex cases. Queuing theory indicates that wide variability of process time with the random nature of request arrival increases the probability of significant queues. This can lead to delays in the time-to-availability of radiology reports (TTA-RR) and potentially impaired ED patient flow. In addition, greater “cognitive workload” of greater volume may lead to reduced productivity and increased errors. We sought to quantify the potential ED flow improvements obtainable from increased radiology providers serving 3 public hospitals in Melbourne Australia. We sought to assess the potential productivity gains, quality improvement and the cost-effectiveness of increased labor inputs. Methods & Materials: The Western Health Medical Imaging Department moved from single resident coverage on weekend days 8:30 am-10:30 pm to a limited period of 2 resident coverage 1 pm-6 pm on both weekend days. The TTA-RR for weekend CT scans was calculated from the PACs database for the 8 month period symmetrically around the date of staffing change. A multivariate linear regression model was developed to isolate the improvement in TTA-RR, between the two 4-months periods. Daily and hourly scan volume at the time of each CT scan was calculated to assess the impact of varying department workload. To assess any improvement in report quality/errors a random sample of 200 studies was assessed to compare the average number of clinically significant over-read addendums to reports between the 2 periods. Cost-effectiveness was assessed by comparing the marginal cost of additional staffing against a conservative estimate of the economic benefit of improved ED patient throughput using the Australian national insurance rebate for private ED attendance as a revenue proxy. Results: The primary resident on call and the type of scan accounted for most of the explained variability in time to report availability (R2=0.29). Increasing daily volume and hourly volume was associated with increased TTA-RR (1.5m (p<0.01) and 4.8m (p<0.01) respectively per additional scan ordered within each time frame. Reports were available 25.9 minutes sooner on average in the 4 months post-implementation of double coverage (p<0.01) with additional 23.6 minutes improvement when 2 residents were on-site concomitantly (p<0.01). The aggregate average improvement in TTA-RR was 24.8 hours per weekend day This represents the increased decision-making time available to ED physicians and potential improvement in ED bed utilisation. 5% of reports from the intervention period contained clinically significant addendums vs 7% in the single resident period but this was not statistically significant (p=0.7). The marginal cost was less than the anticipated economic benefit based assuming a 50% capture of improved TTA-RR inpatient disposition and using the lowest available national insurance rebate as a proxy for economic benefit. Conclusion: TTA-RR improved significantly during the period of increased staff availability, both during the specific period of increased staffing and throughout the day. Increased labor utilisation is cost-effective compared with the potential improved productivity for ED cases requiring CT imaging.

Keywords: workflow, quality, administration, CT, staffing

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Authors: Medhat Abdallah, Ahmed Abdrabou

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Tutankhamen tomb was discovered on November 1922 by Howard carter, the grave was relatively intact and crammed full of the most beautiful burial items and furniture, the black shrine-shaped boxes on sleds studied here founded in treasury chamber. This study aims to identify the wood species used in making those shrines, illustrate technology of manufacture. Optical Microscope (OM), 3D software and Imaging Processes including; Visible light, Raking light and Visible-induced infrared luminescence were effective in illustrating wooden joints and techniques of manufacture. The results revealed that cedar of Lebanon Cedrus libani and sycamore fig Ficus sycomorus had been used for making the shrines’ boards and sleds while tamarisk Tamarix sp., Turkey Oak Quercus cerris L., and Sidder (nabk) Zizyphus spina christi used for making dowels. The wooden joint of mortise and tenon was used to connect the body of the shrine to the sled, while wooden pegs used to connect roof and cornice to the shrine body.

Keywords: Tutankhamen, wood species, optical microscope, Cedrus libani, Ficus sycomorus

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Authors: Ermelinda Bloise, Giuseppe Mele

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In recent years, Cashew Nut Shell Liquid (CNSL) has received great attention from researchers because it is an abundant waste material from the agri-food industry that fits perfectly into the idea of reusing waste from renewable resources for the production of new functional materials. The different components of this waste showed a certain chemical versatility and, above all, various biological activities. Take advantage of their surface-active capacity in particular conditions, various amphiphilic nanostructures have been prepared through sustainable chemical processes using cardanol (CA) and anacardic acid (AA) as two main components of the CNSL. In-batch solvent-free method has been developed to obtain new versatile green nanovesicles capable of effectively incorporating and stabilizing both hydrophobic and hydrophilic bioactive molecules. Furthermore, these nanosystems have shown antioxidant and cytotoxic properties and, in vitroinvestigations, established that they efficiently taken-up some human cells. With the idea of meeting the principles of green chemistry, even more, some improvements of the synthetic procedure have been implemented in terms of milder temperature and pH conditions, producing one-component nanovesicles, in which the AA and CA-derivatives are the sole building block of the green nanosystems. Finally, a new experimental approach has been carried out by a microfluidic route, with the advantage to operate at continuous flows, with a reduced amount of reagents, waste, and at lower temperatures, ensuring the achievement of size-monodisperse amphiphilic nanostructures that do not need further purification steps.

Keywords: bioactive nanosystems, bio-based renewables, cashew oil, green nanoformulations

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Authors: Elżbieta Antczak

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Cities offer important opportunities for economic development and for expanding access to basic services, including health care and education, for large numbers of people. Moreover, green areas (as an integral part of sustainable urban development) present a major opportunity for improving urban environments, quality of lives and livelihoods. This paper examines, using spatial concentration and spatial taxonomic measures, regional diversification of greenery in the cities of Poland. The analysis includes location quotients, Lorenz curve, Locational Gini Index, and the synthetic index of greenery and spatial statistics tools: (1) To verify the occurrence of strong concentration or dispersion of the phenomenon in time and space depending on the variable category, and, (2) To study if the level of greenery depends on the spatial autocorrelation. The data includes the greatest Polish cities, categories of the urban greenery (parks, lawns, street greenery, and green areas on housing estates, cemeteries, and forests) and the time span 2004-2015. According to the obtained estimations, most of cites in Poland are already taking measures to become greener. However, in the country there are still many barriers to well-balanced urban greenery development (e.g. uncontrolled urban sprawl, poor management as well as lack of spatial urban planning systems).

Keywords: greenery, urban areas, regional spatial diversification and concentration, spatial taxonomic measure

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Authors: Sahithi Yarlagadda

Abstract:

The design of antenna is constrained by mathematical and geometrical parameters. Though there are diverse antenna structures with wide range of feeds yet, there are many geometries to be tried, which cannot be customized into predefined computational methods. The antenna design and optimization qualify to apply evolutionary algorithmic approach since the antenna parameters weights dependent on geometric characteristics directly. The evolutionary algorithm can be explained simply for a given quality function to be maximized. We can randomly create a set of candidate solutions, elements of the function's domain, and apply the quality function as an abstract fitness measure. Based on this fitness, some of the better candidates are chosen to seed the next generation by applying recombination and permutation to them. In conventional approach, the quality function is unaltered for any iteration. But the antenna parameters and geometries are wide to fit into single function. So, the weight coefficients are obtained for all possible antenna electrical parameters and geometries; the variation is learnt by mining the data obtained for an optimized algorithm. The weight and covariant coefficients of corresponding parameters are logged for learning and future use as datasets. This paper drafts an approach to obtain the requirements to study and methodize the evolutionary approach to automated antenna design for our past work on Vivaldi antenna as test candidate. The antenna parameters like gain, directivity, etc. are directly caged by geometries, materials, and dimensions. The design equations are to be noted here and valuated for all possible conditions to get maxima and minima for given frequency band. The boundary conditions are thus obtained prior to implementation, easing the optimization. The implementation mainly aimed to study the practical computational, processing, and design complexities that incur while simulations. HFSS is chosen for simulations and results. MATLAB is used to generate the computations, combinations, and data logging. MATLAB is also used to apply machine learning algorithms and plotting the data to design the algorithm. The number of combinations is to be tested manually, so HFSS API is used to call HFSS functions from MATLAB itself. MATLAB parallel processing tool box is used to run multiple simulations in parallel. The aim is to develop an add-in to antenna design software like HFSS, CSTor, a standalone application to optimize pre-identified common parameters of wide range of antennas available. In this paper, we have used MATLAB to calculate Vivaldi antenna parameters like slot line characteristic impedance, impedance of stripline, slot line width, flare aperture size, dielectric and K means, and Hamming window are applied to obtain the best test parameters. HFSS API is used to calculate the radiation, bandwidth, directivity, and efficiency, and data is logged for applying the Evolutionary genetic algorithm in MATLAB. The paper demonstrates the computational weights and Machine Learning approach for automated antenna optimizing for Vivaldi antenna.

Keywords: machine learning, Vivaldi, evolutionary algorithm, genetic algorithm

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Authors: Nuraddeen Usman, Khiruddin Abdullah, Mohd Nawawi, Amin Khalil Ismail

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A magnetic survey is carried out in order to locate the remains of construction items, specifically concrete pillars. The conventional Euler deconvolution technique can perform the task but it requires the use of fixed structural index (SI) and the construction items are made of materials with different shapes which require different SI (unknown). A Euler deconvolution technique that estimate background, horizontal coordinate (xo and yo), depth and structural index (SI) simultaneously is prepared and used for this task. The synthetic model study carried indicated the new methodology can give a good estimate of location and does not depend on magnetic latitude. For field data, both the total magnetic field and gradiometer reading had been collected simultaneously. The computed vertical derivatives and gradiometer readings are compared and they have shown good correlation signifying the effectiveness of the method. The filtering is carried out using automated procedure, analytic signal and other traditional techniques. The clustered depth solutions coincided with the high amplitude/values of analytic signal and these are the possible target positions of the concrete pillars being sought. The targets under investigation are interpreted to be located at the depth between 2.8 to 9.4 meters. More follow up survey is recommended as this mark the preliminary stage of the work.

Keywords: concrete pillar, magnetic survey, geotechnical investigation, Euler Deconvolution

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Authors: Rachid El Aidani, Phuong Nguyen-Tri, Toan Vu-Khanh

Abstract:

The filter media in synthetic fibre is the most geotextile materials used in aerosol and drainage filtration, particularly for buildings soil reinforcement in civil engineering due to its appropriated properties and its low cost. However, the current understanding of the durability and stability of this material in real service conditions, especially under severe long-term conditions are completely limited. This study has examined the effects of the chemical aging of a filter media in polyester non-woven under different temperatures (50, 70 and 80˚C) and pH (2. 7 and 12). The effect of aging conditions on mechanical properties, morphology, permeability, thermal stability and molar weigh changes is investigated. The results showed a significant reduction of mechanical properties in term of tensile strength, puncture force and tearing forces of the filter media after chemical aging due to the chemical degradation. The molar mass and mechanical properties changes in different temperature and pH showed a complex dependence of material properties on environmental conditions. The SEM and AFM characterizations showed a significant impact of the thermal aging on the morphological properties of the fibers. Based on the obtained results, the lifetime of the material in different temperatures was determined by the use of the Arrhenius model. These results provide useful information to better understand phenomena occurring during chemical aging of the filter media and may help to predict the service lifetime of this material in real used conditions.

Keywords: nonwoven membrane, chemical aging, mechanical properties, lifetime, filter media

Procedia PDF Downloads 318

Authors: Aysun Sezer

Abstract:

Magnetic Resonance Imaging (MRI) is one of the advanced diagnostic tools for evaluating shoulder pathologies. Proton Density (PD)-weighted MRI sequences prove highly effective in detecting edema. However, they are deficient in the anatomical identification of bones due to a trauma-induced decrease in signal-to-noise ratio and blur in the traumatized cortices. Computer-based diagnostic systems require precise segmentation, identification, and localization of anatomical regions in medical imagery. Deep learning-based object detection algorithms exhibit remarkable proficiency in real-time object identification and localization. In this study, the YOLOv8 model was employed to detect humeral head and scapular regions in 665 axial PD-weighted MR images. The YOLOv8 configuration achieved an overall success rate of 99.60% and 89.90% for detecting the humeral head and scapula, respectively, with an intersection over union (IoU) of 0.5. Our findings indicate a significant promise of employing YOLOv8-based detection for the humerus and scapula regions, particularly in the context of PD-weighted images affected by both noise and intensity inhomogeneity.

Keywords: YOLOv8, object detection, humerus, scapula, IRM

Procedia PDF Downloads 66

Authors: Tolulope Aremu

Abstract:

The key process steps to produce liquid detergent products will introduce potential defects, such as formulation, mixing, filling, and packaging, which might compromise product quality, consumer safety, and operational efficiency. Real-time identification and characterization of such defects are of prime importance for maintaining high standards and reducing waste and costs. Usually, defect detection is performed by human inspection or rule-based systems, which is very time-consuming, inconsistent, and error-prone. The present study overcomes these limitations in dealing with optimization in defect characterization within the process for making liquid detergents using Machine Learning algorithms. Performance testing of various machine learning models was carried out: Support Vector Machine, Decision Trees, Random Forest, and Convolutional Neural Network on defect detection and classification of those defects like wrong viscosity, color deviations, improper filling of a bottle, packaging anomalies. These algorithms have significantly benefited from a variety of optimization techniques, including hyperparameter tuning and ensemble learning, in order to greatly improve detection accuracy while minimizing false positives. Equipped with a rich dataset of defect types and production parameters consisting of more than 100,000 samples, our study further includes information from real-time sensor data, imaging technologies, and historic production records. The results are that optimized machine learning models significantly improve defect detection compared to traditional methods. Take, for instance, the CNNs, which run at 98% and 96% accuracy in detecting packaging anomaly detection and bottle filling inconsistency, respectively, by fine-tuning the model with real-time imaging data, through which there was a reduction in false positives of about 30%. The optimized SVM model on detecting formulation defects gave 94% in viscosity variation detection and color variation. These values of performance metrics correspond to a giant leap in defect detection accuracy compared to the usual 80% level achieved up to now by rule-based systems. Moreover, this optimization with models can hasten defect characterization, allowing for detection time to be below 15 seconds from an average of 3 minutes using manual inspections with real-time processing of data. With this, the reduction in time will be combined with a 25% reduction in production downtime because of proactive defect identification, which can save millions annually in recall and rework costs. Integrating real-time machine learning-driven monitoring drives predictive maintenance and corrective measures for a 20% improvement in overall production efficiency. Therefore, the optimization of machine learning algorithms in defect characterization optimum scalability and efficiency for liquid detergent companies gives improved operational performance to higher levels of product quality. In general, this method could be conducted in several industries within the Fast moving consumer Goods industry, which would lead to an improved quality control process.

Keywords: liquid detergent manufacturing, defect detection, machine learning, support vector machines, convolutional neural networks, defect characterization, predictive maintenance, quality control, fast-moving consumer goods

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Authors: C. Gopi Jinimole, A. Harsha

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For detecting strokes, Computed Tomography (CT) scan is preferred for imaging the abnormalities or infarction in the brain. Because of the problems in the window settings used to evaluate brain CT images, they are very poor in the early stage infarction detection. This paper presents an automatic estimation method for the window settings of the CT images for proper contrast of the hyper infarction present in the brain. In the proposed work the window width is estimated automatically for each slice and the window centre is changed to a new value of 31HU, which is the average of the HU values of the grey matter and white matter in the brain. The automatic window width estimation is based on the average of median of statistical central moments. Thus with the new suggested window centre and estimated window width, the hyper infarction or post-stroke regions in CT brain images are properly detected. The proposed approach assists the radiologists in CT evaluation for early quantitative signs of delayed stroke, which leads to severe hemorrhage in the future can be prevented by providing timely medication to the patients.

Keywords: computed tomography (CT), hyper infarction or post stroke region, Hounsefield Unit (HU), window centre (WC), window width (WW)

Procedia PDF Downloads 203

Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

Procedia PDF Downloads 260

Authors: Reza Hosseinpourpia, Stergios Adamopoulos, Carsten Mai

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Medium density fiberboard (MDF) is a common category of wood-based panels that are widely used in the furniture industry. Fine lignocellulosic fibres are combined with a synthetic resin, mostly urea formaldehyde (UF), and joined together under heat and pressure to form panels. Like solid wood, MDF is a hygroscopic material; therefore, its moisture content depends on the surrounding relative humidity and temperature. In addition, UF is a hydrophilic resin and susceptible to hydrolysis under certain conditions of elevated temperatures and humidity, which cause dimensional instability of the panels. The latter directly affect the performance of final products such as furniture, when they are used in situations of high relative humidity. Existing water-repellent formulations, such as paraffin, present limitations related to their non-renewable nature, cost and highest allowed added amount. Therefore, the aim of the present study was to test the suitability of renewable water repellents as alternative chemicals for enhancing the dimensional stability of MDF panels. A small amount of tall oil based formulations were used as water-repellent agents in the manufacturing of laboratory scale MDF. The effects on dimensional stability, internal bond strength and formaldehyde release of MDF were tested. The results indicated a good potential of tall oil as a bio-based substance of water repellent formulations for improving the dimensional stability of MDF.

Keywords: dimensional stability, medium density fiberboard, tall oil, urea formaldehyde

Procedia PDF Downloads 241

Authors: Georgios Charizanos, Haydar Demirhan, Duygu Icen

Abstract:

Two of the most impactful issues in classical logistic regression are class imbalance and complete separation. These can result in model predictions heavily leaning towards the imbalanced class on the binary response variable or over-fitting issues. Fuzzy methodology offers key solutions for handling these problems. However, most studies propose the transformation of the binary responses into a continuous format limited within [0,1]. This is called the possibilistic approach within fuzzy logistic regression. Following this approach is more aligned with straightforward regression since a logit-link function is not utilized, and fuzzy probabilities are not generated. In contrast, we propose a method of fuzzifying binary response variables that allows for the use of the logit-link function; hence, a probabilistic fuzzy logistic regression model with the Monte Carlo method. The fuzzy probabilities are then classified by selecting a fuzzy threshold. Different combinations of fuzzy and crisp input, output, and coefficients are explored, aiming to understand which of these perform better under different conditions of imbalance and separation. We conduct numerical experiments using both synthetic and real datasets to demonstrate the performance of the fuzzy logistic regression framework against seven crisp machine learning methods. The proposed framework shows better performance irrespective of the degree of imbalance and presence of separation in the data, while the considered machine learning methods are significantly impacted.

Keywords: fuzzy logistic regression, fuzzy, logistic, machine learning

Procedia PDF Downloads 76