Search results for: features extraction

Authors: Qian Li, Zhaoping Zhong

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Sewage sludge, a typical solid waste, has inevitably been produced in enormous quantities in China. Still worse, the amount of sewage sludge produced has been increasing due to rapid economic development and urbanization. Compared to the conventional method to treat sewage sludge, pyrolysis has been considered an economic and ecological technology because it can significantly reduce the sludge volume, completely kill pathogens, and produce valuable solid, gas, and liquid products. However, the large-scale utilization of sludge biochar has been limited due to the considerable risk posed by heavy metals in the sludge. Heavy metals enriched in pyrolytic biochar could be divided into exchangeable, reducible, oxidizable, and residual forms. The residual form of heavy metals is the most stable and cannot be used by organisms. Kaolin and zeolite are environmentally friendly inorganic minerals with a high surface area and heat resistance characteristics. So, they exhibit the enormous potential to immobilize heavy metals. In order to reduce the risk of leaching heavy metals in the pyrolysis biochar, this study pyrolyzed sewage sludge mixed with kaolin/zeolite in a small rotary kiln. The influences of additives and pyrolysis temperature on the leaching concentration and morphological transformation of heavy metals in pyrolysis biochar were investigated. The potential mechanism of stabilizing heavy metals in the co-pyrolysis of sludge blended with kaolin/zeolite was explained by scanning electron microscopy, X-ray diffraction, and specific surface area and porosity analysis. The European Community Bureau of Reference sequential extraction procedure has been applied to analyze the forms of heavy metals in sludge and pyrolysis biochar. All the concentrations of heavy metals were examined by flame atomic absorption spectrophotometry. Compared with the proportions of heavy metals associated with the F4 fraction in pyrolytic carbon prepared without additional agents, those in carbon obtained by co-pyrolysis of sludge and kaolin/zeolite increased. Increasing the additive dosage could improve the proportions of the stable fraction of various heavy metals in biochar. Kaolin exhibited a better effect on stabilizing heavy metals than zeolite. Aluminosilicate additives with excellent adsorption performance could capture more released heavy metals during sludge pyrolysis. Then heavy metal ions would react with the oxygen ions of additives to form silicate and aluminate, causing the conversion of heavy metals from unstable fractions (sulfate, chloride, etc.) to stable fractions (silicate, aluminate, etc.). This study reveals that the efficiency of stabilizing heavy metals depends on the formation of stable mineral compounds containing heavy metals in pyrolysis biochar.

Keywords: co-pyrolysis, heavy metals, immobilization mechanism, sewage sludge

Procedia PDF Downloads 52

Authors: Elitsa Kolentsova, Dimitar Dimitrov, Vasko Idakiev, Tatyana Tabakova, Krasimir Ivanov

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Formaldehyde production by selective oxidation of methanol is an important industrial process. The main by-products in the waste gas are CO and dimethyl ether (DME). The idea of this study is to combine the advantages of both Cu-Mn and Cu-Co catalytic systems by obtaining a new mixed Cu-Mn-Co catalyst with high activity and selectivity at the simultaneous oxidation of CO, methanol, and DME. Two basic Cu-Mn samples with high activity were selected for further investigation: (i) manganese-rich Cu-Mn/γ–Al2O3 catalyst with Cu/Mn molar ratio 1:5 and (ii) copper-rich Cu-Mn/γ-Al2O3 catalyst with Cu/Mn molar ratio 2:1. Manganese in these samples was replaced by cobalt in the whole concentration region, and catalytic properties were determined. The results show a general trend of decreasing the activity toward DME oxidation and increasing the activity toward CO and methanol oxidation with the increase of cobalt up to 60% for both groups of catalyst. This general trend, however, contains specific features, depending on the composition of the catalyst and the nature of the oxidized gas. The catalytic activity of the sample with Cu/(Mn+Co) molar ratio of 2:1 is gradually changed with increasing the cobalt content. The activity of the sample with Cu/(Mn+Co) molar ratio of 1: 5 passes through a maximum at 60% manganese replacement by cobalt, probably due to the formation of highly dispersed Co-based spinel structures (Co3O4 and/or MnCo2O4). In conclusion, the present study demonstrates that the Cu-Mn-Co/γ–alumina supported catalysts have enhanced activity toward CO, methanol and DME oxidation. Cu/(Mn+Co) molar ratio 1:5 and Co/Mn molar ratio 1.5 in the active component can ensure successful oxidation of CO, CH3OH and DME. The active component of the mixed Cu-Mn-Co/γ–alumina catalysts consists of at least six compounds - CuO, Co3O4, MnO2, Cu1.5Mn1.5O4, MnCo2O4 and CuCo2O4, depending on the Cu/Mn/Co molar ratio. Chemical composition strongly influences catalytic properties, this effect being quite variable with regards to the different processes.

Keywords: Cu-Mn-Co catalysts, oxidation, carbon oxide, VOCs

Procedia PDF Downloads 203

Authors: Mohamed Boullouz, Mohamed Louay Metougui

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Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

Procedia PDF Downloads 47

Authors: Perizat Aitmaganbet, Kerbez Kimatova, Gulmira Umarova

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As a result of medical check-up conducted in the framework of this research study an evaluation of the health status of the population living in the oil-producing regions, namely Sarkul and Kenkiyak villages in Aktobe was examined. With the help of the Spearman correlation, the connection between the level of hazard chemical elements in the atmosphere and the health of population living in the regions of oil and gas industry was estimated. Background & Objective. The oil and gas resource-extraction industries play an important role in improving the economic conditions of the Republic of Kazakhstan, especially for the oil-producing administrative regions. However, environmental problems may adversely affect the health of people living in that area. Thus, the aim of the study is to evaluate the exposure to negative environmental factors of the adult population living in Sarkul and Kenkiyak villages, the oil and gas producing areas in the Aktobe region. Methods. After conducting medical check-up among the population of Sarkul and Kenkiyak villages. A single cross-sectional study was conducted. The population consisted of randomly sampled 372 adults (181 males and 191 females). Also, atmospheric air probes were taken to measure the level of hazardous chemical elements in the air. The nonparametric method of the Spearman correlation analysis was performed between the mean concentration of substances exceeding the Maximum Permissible Concentration and the classes of newly diagnosed diseases. Selection and analysis of air samples were carried out according to the developed research protocol; the qualitative-quantitative analysis was carried out on the Gas analyzer HANK-4 apparatus. Findings. The medical examination of the population identified the following diseases: the first two dominant were diseases of the circulatory and digestive systems, in the 3rd place - diseases of the genitourinary system, and the nervous system and diseases of the ear and mastoid process were on the fourth and fifth places. Moreover, significant pollution of atmospheric air by carbon monoxide (MPC-5,0 mg/m3), benzapyrene (MPC-1mg/m3), dust (MPC-0,5 mg/m3) and phenol (МРС-0,035mg/m3) were identified in places. Correlation dependencies between these pollutants of air and the diseases of the population were established, as a result of diseases of the circulatory system (r = 0,7), ear and mastoid process (r = 0,7), nervous system (r = 0,6) and digestive organs(r = 0,6 ); between the concentration of carbon monoxide and diseases of the circulatory system (r = 0.6), the digestive system(r = 0.6), the genitourinary system (r = 0.6) and the musculoskeletal system; between nitric oxide and diseases of the digestive system (r = 0,7) and the circulatory system (r = 0,6); between benzopyrene and diseases of the digestive system (r = 0,6), the genitourinary system (r = 0,6) and the nervous system (r = 0,4). Conclusion. The positive correlation was found between air pollution and the health of the population living in Sarkul and Kenkiyak villages. To enhance the reliability of the results we are going to continue this study further.

Keywords: atmospheric air, chemical substances, oil and gas, public health

Procedia PDF Downloads 93

Authors: Tooran Tavangar, Masoud Hosseinpoor, Jeffrey S. Marshall, Ammar Yahia, Kamal Henri Khayat

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In this study, a four-way coupled CFD-DEM methodology was used to simulate the behavior of concrete pipe flow. Fresh concrete, characterized as a biphasic suspension, features aggregates comprising the solid-suspended phase with diverse particle-size distributions (PSD) within a non-Newtonian cement paste/mortar matrix forming the liquid phase. The fluid phase was simulated using CFD, while the aggregates were modeled using DEM. Interaction forces between the fluid and solid particles were considered through CFD-DEM computations. To capture the viscoelastic characteristics of the suspending fluid, a bi-viscous approach was adopted, incorporating a critical shear rate proportional to the yield stress of the mortar. In total, three diphasic suspensions were simulated, each featuring distinct particle size distributions and a concentration of 10% for five subclasses of spherical particles ranging from 1 to 17 mm in a suspending fluid. The adopted bi-viscous approach successfully simulated both un-sheared (plug flow) and sheared zones. Furthermore, shear-induced particle migration (SIPM) was assessed by examining coefficients of variation in particle concentration across the pipe. These SIPM values were then compared with results obtained using CFD-DEM under the Newtonian assumption. The study highlighted the crucial role of yield stress in the mortar phase, revealing that lower yield stress values can lead to increased flow rates and higher SIPM across the pipe.

Keywords: computational fluid dynamics, concrete pumping, coupled CFD-DEM, discrete element method, plug flow, shear-induced particle migration.

Procedia PDF Downloads 44

Authors: Venkat S. Somayajula

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Ground surface temperature history prediction model plays a vital role in determining standards for international nuclear waste management. International standards for borehole based nuclear waste disposal require paleoclimate cycle predictions on scale of a million forward years for the place of waste disposal. This research focuses on developing a paleoclimate cycle prediction model using Bayesian long-short term memory (LSTM) neural architecture operated on accumulated borehole temperature history data. Bayesian models have been previously used for paleoclimate cycle prediction based on Monte-Carlo weight method, but due to limitations pertaining model coupling with certain other prediction networks, Bayesian models in past couldn’t accommodate prediction cycle’s over 1000 years. LSTM has provided frontier to couple developed models with other prediction networks with ease. Paleoclimate cycle developed using this process will be trained on existing borehole data and then will be coupled to surface temperature history prediction networks which give endpoints for backpropagation of LSTM network and optimize the cycle of prediction for larger prediction time scales. Trained LSTM will be tested on past data for validation and then propagated for forward prediction of temperatures at borehole locations. This research will be beneficial for study pertaining to nuclear waste management, anthropological cycle predictions and geophysical features

Keywords: Bayesian long-short term memory neural network, borehole temperature, ground surface temperature history, paleoclimate cycle

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Authors: Tayyaba Azim, Bibi Amina

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The increase in the popularity of opinion mining with the rapid growth in the availability of social networks has attracted a lot of opportunities for research in the various domains of Sentiment Analysis and Natural Language Processing (NLP) using Artificial Intelligence approaches. The latest trend allows the public to actively use the internet for analyzing an individual’s opinion and explore the effectiveness of published facts. The main theme of this research is to account the public opinion on the most crucial and extensively discussed development projects, China Pakistan Economic Corridor (CPEC), considered as a game changer due to its promise of bringing economic prosperity to the region. So far, to the best of our knowledge, the theme of CPEC has not been analyzed for sentiment determination through the ML approach. This research aims to demonstrate the use of ML approaches to spontaneously analyze the public sentiment on Twitter tweets particularly about CPEC. Support Vector Machine SVM is used for classification task classifying tweets into positive, negative and neutral classes. Word2vec and TF-IDF features are used with the SVM model, a comparison of the trained model on manually labelled tweets and automatically generated lexicon is performed. The contributions of this work are: Development of a sentiment analysis system for public tweets on CPEC subject, construction of an automatic generation of the lexicon of public tweets on CPEC, different themes are identified among tweets and sentiments are assigned to each theme. It is worth noting that the applications of web mining that empower e-democracy by improving political transparency and public participation in decision making via social media have not been explored and practised in Pakistan region on CPEC yet.

Keywords: machine learning, natural language processing, sentiment analysis, support vector machine, Word2vec

Procedia PDF Downloads 128

Authors: Oleg Redkin, Olga Bernikova

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Globalization and migrations have made cross-cultural contacts more frequent and intensive. Sometimes, these contacts may lead to misunderstanding between partners of communication and misinterpretations of the verbal messages that some researchers tend to consider as the 'clash of civilizations'. In most cases, reasons for that may be found in cultural and linguistic differences and hence misinterpretations of intentions and behavior. The current research examines factors of verbal and non-verbal communication that should be taken into consideration in verbal and non-verbal contacts. Language is one of the most important manifestations of the cultural code, and it is often considered as one of the special features of a civilization. The Arabic language, in particular, is commonly associated with Islam and the language and the Arab-Muslim civilization. It is one of the most important markers of self-identification for more than 200 million of native speakers. Arabic is the language of the Quran and hence the symbol of religious affiliation for more than one billion Muslims around the globe. Adequate interpretation of Arabic texts requires profound knowledge of its grammar, semantics of its vocabulary. Communicating sides who belong to different cultural groups are guided by different models of behavior and hierarchy of values, besides that the vocabulary each of them uses in the dialogue may convey different semantic realities and vary in connotations. In this context direct, literal translation in most cases cannot adequately convey the original meaning of the original message. Besides that peculiarities and diversities of the extralinguistic information, such as the body language, communicative etiquette, cultural background and religious affiliations may make the dialogue even more difficult. It is very likely that the so called 'clash of civilizations' in most cases is due to misinterpretation of counterpart's means of discourse such as language, cultural codes, and models of behavior rather than lies in basic contradictions between partners of communication. In the process of communication, one has to rely on universal values rather than focus on cultural or religious peculiarities, to take into account current linguistic and extralinguistic context.

Keywords: Arabic, civilization, discourse, language, linguistic

Procedia PDF Downloads 204

Authors: Mudassir Ghafoor, Irsalan Arif, Shuaib Salamat

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This paper presents modeling and analysis of different intake bump (compression surface) configurations and comparison with an existing supersonic aircraft having bump intake configuration. Many successful aircraft models have shown that Diverter less Supersonic Inlet (DSI) as compared to conventional intake can reduce weight, complexity and also maintenance cost. The research is divided into two parts. In the first part, four different intake bumps are modeled for comparative analysis keeping in view the consistency of outer perimeter dimensions of fighter aircraft and various characteristics such as flow behavior, boundary layer diversion and pressure recovery are analyzed. In the second part, modeled bumps are integrated with intake duct for performance analysis and comparison with existing supersonic aircraft data is carried out. The bumps are named as uniform large (Config 1), uniform small (Config 2), uniform sharp (Config 3), non-uniform (Config 4) based on their geometric features. Analysis is carried out at different Mach Numbers to analyze flow behavior in subsonic and supersonic regime. Flow behavior, boundary layer diversion and Pressure recovery are examined for each bump characteristics, and comparative study is carried out. The analysis reveals that at subsonic speed, Config 1 and Config 2 give similar pressure recoveries as diverterless supersonic intake, but difference in pressure recoveries becomes significant at supersonic speed. It was concluded from research that Config 1 gives better results as compared to Config 3. Also, higher amplitude (Config 1) is preferred over lower (Config 2 and 4). It was observed that maximum height of bump is preferred to be placed near cowl lip of intake duct.

Keywords: bump intake, boundary layer, computational fluid dynamics, diverter-less supersonic inlet

Procedia PDF Downloads 227

Authors: Sakeena Naikwadi, K. Jagaluraiah Sannapapamma

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Vetiveria zizanioides is an aromatic grass and traditionally been used in aromatherapy and ayurvedic medicine. Vetiver root is multi-functional biopolymer and has highly aromatic, antimicrobial, UV blocking, antioxidant properties suitable for textile finishing. The vetiver root (Gulabi) powder of different concentration (2, 4, 6,8 percent) were extracted by aqueous and solvent methods subjected to bioassay for antimicrobial efficiency and GCMS spectral analysis. The organic cotton fabric was finished with vetiver root extract (8 percent) by exhaust and pad dry cure methods. The finished fabric was assessed for functional properties viz., UV protective factor, antimicrobial efficiency and aroma intensity. The results revealed that Ethanol extraction showed a greater zone of inhibition compared to aqueous extract in root powder. Among the concentrations, 8 percent root extract in ethanol showed a greater zone of inhibition against gram-positive organism S. aureus and gram-negative organism E. coli. The major compounds present in vetiver root extracts were diethyl pathalate with greater percentage (87.73 %) followed by 7- Isopropyl dimethyl carboxylic acid (4.05 %), 2-butanone 4-trimethyle cyclohexen (1.21 %), phenanthrene carboxylic acid (1.03 %), naphthalene pentanoic acid (0.99 %), 1-phenanthrene carboxylic acid and 1 cyclohexenone 2-methyl oxobuty (0.89 %). The sample finished by pad dry cure method exhibited better UV protection even after 10th wash as compared to exhaust method. Vetiver extract treated samples exhibited maximum zone of inhibition against S. aureus than the E. coli organism. The vetiver root extract treated organic cotton fabric through pad dry cure method possessed good antimicrobial activity against S. aureus and E. coli even after 20th washes compared to vetiver root extract treated by exhaust method. The olfactory analysis was carried out by 30 panels of members and opined that vetiver root extract treated fabric has very good and pleasant aroma with better tactile properties that provide cooling, soothing effect and enhances the mood of the wearer. Vetiver root extract finished organic cotton fabric possessed aroma, antimicrobial and UV properties which are aptly suitable for medical and healthcare textiles viz., wound dressing, bandage gauze, surgical cloths, baby diapers and sanitary napkins. It can be used as after finishing agent for variegated garments and made-ups and can be replaced with commercial after finishing agents.

Keywords: antimicrobial, olfactory analysis, UV protection factor, vetiver root extract

Procedia PDF Downloads 209

Authors: Zoltan Sebestyen, Eszter Barta-Rajnai, Emma Jakab, Zsuzsanna Czegeny

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Extraction of the energy content of lignocellulosic biomass is one of the possible pathways to reduce the greenhouse gas emission derived from the burning of the fossil fuels. The application of the bioenergy can mitigate the energy dependency of a country from the foreign natural gas and the petroleum. The diversity of the plant materials makes difficult the utilization of the raw biomass in power plants. This problem can be overcome by the application of thermochemical techniques. Pyrolysis is the thermal decomposition of the raw materials under inert atmosphere at high temperatures, which produces pyrolysis gas, biooil and charcoal. The energy content of these products can be exploited by further utilization. The differences in the chemical and physical properties of the raw biomass materials can be reduced by the use of torrefaction. Torrefaction is a promising mild thermal pretreatment method performed at temperatures between 200 and 300 °C in an inert atmosphere. The goal of the pretreatment from a chemical point of view is the removal of water and the acidic groups of hemicelluloses or the whole hemicellulose fraction with minor degradation of cellulose and lignin in the biomass. Thus, the stability of biomass against biodegradation increases, while its energy density increases. The volume of the raw materials decreases so the expenses of the transportation and the storage are reduced as well. Biooil is the major product during pyrolysis and an important by-product during torrefaction of biomass. The composition of biooil mostly depends on the quality of the raw materials and the applied temperature. In this work, thermoanalytical techniques have been used to study the qualitative and quantitative composition of the pyrolysis and torrefaction oils of a woody (black locust) and two herbaceous samples (rape straw and wheat straw). The biooil contains C5 and C6 anhydrosugar molecules, as well as aromatic compounds originating from hemicellulose, cellulose, and lignin, respectively. In this study, special emphasis was placed on the formation of the lignin monomeric products. The structure of the lignin fraction is different in the wood and in the herbaceous plants. According to the thermoanalytical studies the decomposition of lignin starts above 200 °C and ends at about 500 °C. The lignin monomers are present among the components of the torrefaction oil even at relatively low temperatures. We established that the concentration and the composition of the lignin products vary significantly with the applied temperature indicating that different decomposition mechanisms dominate at low and high temperatures. The evolutions of decomposition products as well as the thermal stability of the samples were measured by thermogravimetry/mass spectrometry (TG/MS). The differences in the structure of the lignin products of woody and herbaceous samples were characterized by the method of pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS). As a statistical method, principal component analysis (PCA) has been used to find correlation between the composition of lignin products of the biooil and the applied temperatures.

Keywords: pyrolysis, torrefaction, biooil, lignin

Procedia PDF Downloads 300

Authors: Bülent Kantar, Numan Ünaldı

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This paper presents a new method which includes robust and invisible digital watermarking on images that is colored. Colored images are used as watermark. Frequency region is used for digital watermarking. Discrete wavelet transform and discrete stationary wavelet transform are used for frequency region transformation. Low, medium and high frequency coefficients are obtained by applying the two-level discrete wavelet transform to the original image. Low frequency coefficients are obtained by applying one level discrete stationary wavelet transform separately to all frequency coefficient of the two-level discrete wavelet transformation of the original image. For every low frequency coefficient obtained from one level discrete stationary wavelet transformation, watermarks are added. Watermarks are added to all frequency coefficients of two-level discrete wavelet transform. Totally, four watermarks are added to original image. In order to get back the watermark, the original and watermarked images are applied with two-level discrete wavelet transform and one level discrete stationary wavelet transform. The watermark is obtained from difference of the discrete stationary wavelet transform of the low frequency coefficients. A total of four watermarks are obtained from all frequency of two-level discrete wavelet transform. Obtained watermark results are compared with real watermark results, and a similarity result is obtained. A watermark is obtained from the highest similarity values. Proposed methods of watermarking are tested against attacks of the geometric and image processing. The results show that proposed watermarking method is robust and invisible. All features of frequencies of two level discrete wavelet transform watermarking are combined to get back the watermark from the watermarked image. Watermarks have been added to the image by converting the binary image. These operations provide us with better results in getting back the watermark from watermarked image by attacking of the geometric and image processing.

Keywords: watermarking, DWT, DSWT, copy right protection, RGB

Procedia PDF Downloads 511

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

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The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

Procedia PDF Downloads 489

Authors: Xianping Du, Runlu Miao, Guanjun Zhang, Libo Cao, Feng Zhu

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Current vehicle safety standards and human body injury criteria were established based on the biomechanical response of Euro-American human body, without considering the difference in the body anthropometry and injury characteristics among different races, particularly the East Asian people with smaller body size. Absence of such race specific design considerations will negatively influence the protective performance of safety products for these populations, and weaken the accuracy of injury thresholds derived. To resolve these issues, in this study, we aim to develop a race specific finite element model to simulate the impact response of the lower extremity of a 50th percentile East Asian (Chinese) male. The model was built based on medical images for the leg of an average size Chinese male and slightly adjusted based on the statistical data. The model includes detailed anatomic features and is able to simulate the muscle active force. Thirteen biomechanical tests available in the literature were used to validate its biofidelity. Using the validated model, a pedestrian-car impact accident taking place in China was re-constructed computationally. The results show that the newly developed lower leg model has a good performance in predicting dynamic response and tibia fracture pattern. An additional comparison on the fracture tolerance of the East Asian and Euro-American lower limb suggests that the current injury criterion underestimates the degree of injury of East Asian human body.

Keywords: lower limb, East Asian body characteristics, traffic accident reconstruction, finite element analysis, injury tolerance

Procedia PDF Downloads 267

Authors: Mansoor Soomro

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The evolution of power electronic equipment has been pivotal in making industrial processes productive, efficient and safe. Despite its attractive features, it has been due to nonlinear loads which make it vulnerable to power quality conditions. Harmonics is one of the power quality problem in which the harmonic frequency is integral multiple of supply frequency. Therefore, the supply voltage and supply frequency do not last within their tolerable limits. As a result, distorted current and voltage waveform may appear. Attributes of low power quality confirm that an electrical device or equipment is likely to malfunction, fail promptly or unable to operate under all applied conditions. The electrical power system is designed for delivering power reliably, namely maximizing power availability to customers. However, power quality events are largely untracked, and as a result, can take out a process as many as 20 to 30 times a year, costing utilities, customers and suppliers of load equipment, a loss of millions of dollars. The ill effects of current harmonics reduce system efficiency, cause overheating of connected equipment, result increase in electrical power and air conditioning costs. With the passage of time and the rapid growth of power electronic converters has highlighted the damages of current harmonics in the electrical power system. Therefore, it has become essential to address the bad influence of current harmonics while planning any suitable changes in the electrical installations. In this paper, an effort has been made to mitigate the effects of dominant 3rd order current harmonics. Passive filtering technique with six pulse multiplication converter has been employed to mitigate them. Since, the standards of power quality are to maintain the supply voltage and supply current within certain prescribed standard limits. For this purpose, the obtained results are validated as per specifications of IEEE 519-1992 and IEEE 519-2014 performance standards.

Keywords: current harmonics, power quality, passive filters, power electronic converters

Procedia PDF Downloads 281

Authors: Justin Nwabanne, Sam Omenyi, Jeremiah Chukwuneke

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This work presents structural nonlinear static analysis of a horizontal taut cable using Finite Element Analysis (FEA) method. The FEA was performed analytically to determine the tensions at each nodal point and subsequently, performed based on finite element displacement method computationally using the FEA software, ANSYS 14.0 to determine their behaviour under the influence of aerodynamic forces imposed on the cable. The convergence procedure is adapted into the method to prevent excessive displacements through the computations. The work compared the two FEA cases by examining the effectiveness of the analytical model in describing the response with few degrees of freedom and the ability of the nonlinear finite element procedure adopted to capture the complex features of cable dynamics with reference to the aerodynamic external influence. Results obtained from this work explain that the analytic FEM results without aerodynamic influence show a parabolic response with an optimum deflection at nodal points 12 and 13 with the cable weight at nodes 12 and 13 having the value -1.002936N while for the cable tension shows an optimum deflection value for nodes 12 and 13 at -189396.97kg/km. The maximum displacement for the cable system was obtained from ANSYS 14.0 as 4483.83 mm for X, Y and Z components of displacements at node number 2 while the maximum displacement obtained is 4218.75mm for all the directional components. The dynamic behaviour of a taut cable investigated has application in a typical power transmission line. Aerodynamic influences on the cables were considered using FEA approach by employing ANSYS 14.0 showed a complex modal behaviour as expected.

Keywords: aerodynamics, cable tension and weight, finite element analysis, nodal, non-linear model, optimum deflection, suspended cable, transmission line

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Authors: Tsega Asresa, Getahun Tigistu, Melaku Bayih

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Computer vision is a subfield of artificial intelligence that allows computers and systems to extract meaning from digital images and video. It is used in a wide range of fields of study, including self-driving cars, video surveillance, medical diagnosis, manufacturing, law, agriculture, quality control, health care, facial recognition, and military applications. Aromatic medicinal plants are botanical raw materials used in cosmetics, medicines, health foods, essential oils, decoration, cleaning, and other natural health products for therapeutic and Aromatic culinary purposes. These plants and their products not only serve as a valuable source of income for farmers and entrepreneurs but also going to export for valuable foreign currency exchange. In Ethiopia, there is a lack of technologies for the classification and identification of Aromatic medicinal plant parts and disease type cured by aromatic medicinal plants. Farmers, industry personnel, academicians, and pharmacists find it difficult to identify plant parts and disease types cured by plants before ingredient extraction in the laboratory. Manual plant identification is a time-consuming, labor-intensive, and lengthy process. To alleviate these challenges, few studies have been conducted in the area to address these issues. One way to overcome these problems is to develop a deep learning model for efficient identification of Aromatic medicinal plant parts with their corresponding disease type. The objective of the proposed study is to identify the aromatic medicinal plant parts and their disease type classification using computer vision technology. Therefore, this research initiated a model for the classification of aromatic medicinal plant parts and their disease type by exploring computer vision technology. Morphological characteristics are still the most important tools for the identification of plants. Leaves are the most widely used parts of plants besides roots, flowers, fruits, and latex. For this study, the researcher used RGB leaf images with a size of 128x128 x3. In this study, the researchers trained five cutting-edge models: convolutional neural network, Inception V3, Residual Neural Network, Mobile Network, and Visual Geometry Group. Those models were chosen after a comprehensive review of the best-performing models. The 80/20 percentage split is used to evaluate the model, and classification metrics are used to compare models. The pre-trained Inception V3 model outperforms well, with training and validation accuracy of 99.8% and 98.7%, respectively.

Keywords: aromatic medicinal plant, computer vision, convolutional neural network, deep learning, plant classification, residual neural network

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Authors: Saeeda Batool, Ather Maqsood Ahmed

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This study investigates the impact of public healthcare facilities and socio-economic circumstances on the status of child health in Pakistan. The complete analysis is carried out in correspondence with fourth and sixth millennium development goals. Further, the health variables chosen are also inherited from targeted indicators of the mentioned goals (MDGs). Trends in the Human Opportunity Index (HOI) for both health inequalities and coverage are analyzed using the Pakistan Social and Living Standards Measurement (PLSM) data set for 2001-02 to 2012-13 at the national and provincial level. To reveal the relative importance of each circumstance in achieving the targeted values for child health, Shorrocks decomposition is applied on HOI. The annual point average growth rate of HOI is used to simulate the time period for the achievement of target set by MDGs and universal access also. The results indicate an improvement in HOI for a reduction in child mortality rates from 52.1% in 2001-02 to 67.3% in 2012-13, which confirms the availability of healthcare opportunities to a larger segment of society. Similarly, immunization against measles and other diseases such as Diphtheria, Polio, Bacillus Calmette-Guerin (BCG), and Hepatitis has also registered an improvement from 51.6% to 69.9% during the period of study at the national level. On a positive note, no gender disparity has been found for child health indicators and that health outcome is mostly affected by the parental and geographical features and availability of health infrastructure. However, the study finds that this achievement has been uneven across provinces. Pakistan is not only lagging behind in achieving its health goals, disappointingly with the current rate of health care provision, but it will take many additional years to achieve its targets.

Keywords: socio-economic circumstances, unmet MDGs, public healthcare services, child and infant mortality

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Authors: Aymen Laadhari

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During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

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Authors: Zainab Mutlaq Ibrahim, Mohamed Bader-El-Den, Mihaela Cocea

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Students' textual feedback can hold unique patterns and useful information about learning process, it can hold information about advantages and disadvantages of teaching methods, assessment components, facilities, and other aspects of teaching. The results of analysing such a feedback can form a key point for institutions’ decision makers to advance and update their systems accordingly. This paper proposes a data mining framework for analysing end of unit general textual feedback using part of speech feature (PoS) with four machine learning algorithms: support vector machines, decision tree, random forest, and naive bays. The proposed framework has two tasks: first, to use the above algorithms to build an optimal model that automatically classifies the whole data set into two subsets, one subset is tailored to assessment practices (assessment related), and the other one is the non-assessment related data. Second task to use the same algorithms to build an optimal model for whole data set, and the new data subsets to automatically detect their sentiment. The significance of this paper is to compare the performance of the above four algorithms using part of speech feature to the performance of the same algorithms using n-grams feature. The paper follows Knowledge Discovery and Data Mining (KDDM) framework to construct the classification and sentiment analysis models, which is understanding the assessment domain, cleaning and pre-processing the data set, selecting and running the data mining algorithm, interpreting mined patterns, and consolidating the discovered knowledge. The results of this paper experiments show that both models which used both features performed very well regarding first task. But regarding the second task, models that used part of speech feature has underperformed in comparison with models that used unigrams and bigrams.

Keywords: assessment, part of speech, sentiment analysis, student feedback

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Authors: Safieh Javadinejad

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In order to make well-informed decisions respecting long-term system planning, resource managers and policy creators necessitate to comprehend the interconnections among energy and water utilization and manufacture—and also the energy-water nexus. Planning and assessment issues contain the enhancement of strategies for declining the water and energy system’s vulnerabilities to climate alteration with also emissions of decreasing greenhouse gas. In order to deliver beneficial decision support for climate adjustment policy and planning, understanding the regionally-specific features of the energy-water nexus, and the history-future of the water and energy source systems serving is essential. It will be helpful for decision makers understand the nature of current water-energy system conditions and capacity for adaptation plans for future. This research shows an integrated hydrology/energy modeling platform which is able to extend water-energy examines based on a detailed illustration of local circumstances. The modeling links the Water Evaluation and Planning (WEAP) and the Long Range Energy Alternatives Planning (LEAP) system to create full picture of water-energy processes. This will allow water managers and policy-decision makers to simply understand links between energy system improvements and hydrological processing and realize how future climate change will effect on water-energy systems. The Zayandeh Rud river basin in Iran is selected as a case study to show the results and application of the analysis. This region is known as an area with large integration of both the electric power and water sectors. The linkages between water, energy and climate change and possible adaptation strategies are described along with early insights from applications of the integration modeling system.

Keywords: climate impacts, hydrology, water systems, adaptation planning, electricity, integrated modeling

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Authors: Rafael do Amaral Teodoro, Leandro Augusto da Silva

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Originated from graphite, graphene is a two-dimensional (2D) material that promises to revolutionize technology in many different areas, such as energy, telecommunications, civil construction, aviation, textile, and medicine. This is possible because its structure, formed by carbon bonds, provides desirable optical, thermal, and mechanical characteristics that are interesting to multiple areas of the market. Thus, several research and development centers are studying different manufacturing methods and material applications of graphene, which are often compromised by the scarcity of more agile and accurate methodologies to characterize the material – that is to determine its composition, shape, size, and the number of layers and crystals. To engage in this search, this study proposes a computational methodology that applies deep learning to identify graphene oxide crystals in order to characterize samples by crystal sizes. To achieve this, a fully convolutional neural network called U-net has been trained to segment SEM graphene oxide images. The segmentation generated by the U-net is fine-tuned with a standard deviation technique by classes, which allows crystals to be distinguished with different labels through an object delimitation algorithm. As a next step, the characteristics of the position, area, perimeter, and lateral measures of each detected crystal are extracted from the images. This information generates a database with the dimensions of the crystals that compose the samples. Finally, graphs are automatically created showing the frequency distributions by area size and perimeter of the crystals. This methodological process resulted in a high capacity of segmentation of graphene oxide crystals, presenting accuracy and F-score equal to 95% and 94%, respectively, over the test set. Such performance demonstrates a high generalization capacity of the method in crystal segmentation, since its performance considers significant changes in image extraction quality. The measurement of non-overlapping crystals presented an average error of 6% for the different measurement metrics, thus suggesting that the model provides a high-performance measurement for non-overlapping segmentations. For overlapping crystals, however, a limitation of the model was identified. To overcome this limitation, it is important to ensure that the samples to be analyzed are properly prepared. This will minimize crystal overlap in the SEM image acquisition and guarantee a lower error in the measurements without greater efforts for data handling. All in all, the method developed is a time optimizer with a high measurement value, considering that it is capable of measuring hundreds of graphene oxide crystals in seconds, saving weeks of manual work.

Keywords: characterization, graphene oxide, nanomaterials, U-net, deep learning

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Authors: Ruby Jean Hornsby

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In our rapidly advancing techno-moral world, human-robot relationships are increasingly becoming a part of intimate human life. Indeed, social robots - that is, autonomous or semi-autonomous embodied artificial agents that generally possess human or animal-like qualities (such as responding to environmental stimuli, communicating, learning, performing human tasks, and making autonomous decisions) - have been designed to function as human friends. In light of such advances, immediate philosophical scrutiny is imperative in order to examine the extent to which human-robot interactions constitute genuine friendship and therefore contribute towards the good human life. Aristotle's conception of friendship is philosophically illuminating and sufficiently broad in scope to guide such analysis. On his account, it is necessary (though not sufficient) that for a friendship to exist between two agents - A and B - both agents must have a mutual love for one another. Aristotle claims that A loves B if: Condition 1: A desires those apparent good (qua pleasant, useful, or virtuous) properties attributable to B, and Condition 2: A has goodwill (wishes what is best) for B. This paper argues that human-robot interaction can (and does) successfully meet both conditions; as such, it demonstrates that robots and humans can reciprocally love one another. It will argue for this position by first justifying the claim that a human can desire apparent good features attributable to a robot (i.e., by taking them to be pleasant and/or useful) and outlining how it is that a human can wish a robot well in light of that robot's (quasi-) interests. Next, the paper will argue that a robot can (quasi-)desire certain properties that are attributable to a human before elucidating how it is possible for a robot to act in the interests of a human. Accordingly, this paper will conclude that it is already the case that humans can formulate relationships with robots that involve reciprocated love. This is significant because it suggests that social robots are candidates for human friendship and can therefore contribute toward flourishing human futures.

Keywords: ancient philosophy, friendship, inter-disciplinary applied ethics, love, social robotics

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Authors: Camilo Andrés Agudelo Vélez, Lina María Martínez Sánchez, Isabel Cristina Ortiz Trujillo, Evert Armando Jiménez Cotes, Natalia Perilla Hernández, María de los Ángeles Rodríguez Gázquez, Daniel Duque Restrepo, Felipe Hernández Restrepo, Dayana Andrea Quintero Moreno, Juan José Builes Gómez, Camilo Ruiz Mejía, Ana Lucia Arango Gómez

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Preeclampsia is a clinical complication during pregnancy with high incidence in Colombia; therefore, it is important to evaluate the influence of external conditions and medical interventions, in order to promote measures that encourage improvements in the quality of life. Objective: Determine clinical and sociodemographic variables in women with preeclampsia. Methods: This cross-sectional study enrolled 50 patients with the diagnosis of preeclampsia, from a private institution in Medellin, during 2015. We used the software SPSS ver.20 for statistical analysis. For the qualitative variables, we calculated the mean and standard deviation, while, for ordinal and nominal levels of quantitative variables, ratios were estimated. Results: The average age was 26.8±5.9 years. The predominant characteristics were socioeconomic stratum 2 (48%), students (55%), mixed race (46%) and middle school as level of education (38%). As for clinical features, 72% of the cases were mild preeclampsia, and 22% were severe forms. The most common clinical manifestations were edema (46%), headache (62%), and proteinuria (55%). As for the Gyneco-obstetric history, 8% reported previous episodes of this disease and it was the first pregnancy for 60% of the patients. Conclusions: Preeclampsia is a frequent condition in young women; on the other hand, headache and edema were the most common reasons for consultation, therefore, doctors need to be aware of these symptoms in pregnant women.

Keywords: pre-eclampsia, hypertension, pregnancy complications, pregnancy, abdominal, edema

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Authors: Gianni Blasi, Daniele Perrone, Maria Antonietta Aiello

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The seismic vulnerability of non-structural components is nowadays recognized to be a key issue in performance-based earthquake engineering. Recent loss estimation studies, as well as the damage observed during past earthquakes, evidenced how non-structural damage represents the highest rate of economic loss in a building and can be in many cases crucial in a life-safety view during the post-earthquake emergency. The procedures developed to evaluate the seismic demand on non-structural components have been constantly improved and recent studies demonstrated how the existing formulations provided by main Standards generally ignore features which have a sensible influence on the definition of the seismic acceleration/displacements subjecting non-structural components. Since the influence of the infills on the dynamic behaviour of RC structures has already been evidenced by many authors, it is worth to be noted that the evaluation of the seismic demand on non-structural components should consider the presence of the infills as well as their mechanical properties. This study focuses on the evaluation of time-history floor acceleration in RC buildings; which is a useful mean to perform seismic vulnerability analyses of non-structural components through the well-known cascade method. Dynamic analyses are performed on an 8-storey RC frame, taking into account the presence of the infills; the influence of the elastic modulus of the panel on the results is investigated as well as the presence of openings. Floor accelerations obtained from the analyses are used to evaluate the floor response spectra, in order to define the demand on non-structural components depending on the properties of the infills. Finally, the results are compared with formulations provided by main International Standards, in order to assess the accuracy and eventually define the improvements required according to the results of the present research work.

Keywords: floor spectra, infilled RC frames, non-structural components, seismic demand

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Authors: Aleksandra Dragojlov

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Since the election of Aleksandar Vučić and the Progressives, Serbia has witnessed a slow decline in media freedom, which has been worse than in the 1990s. Although the government adopted a package of three laws in August 2014 to bring the media landscape up to European standards, the implementation of the laws has been limited and marginal, with the progressives engaging in fake compliance. The adoption of the new media strategy for 2020-2025 in 2020 has not led to genuine domestic reform and compliance with EU conditionality. In fact, the EU Commission and journalists’ associations in Serbia have criticised the decline in Serbia’s media freedom citing continued attacks on journalists and indirect political and economic control through advertising and project co-financing, which continue to be features of the Serbian media landscape. In the absence of clear and credible EU conditionality, the decline of media freedom is in the eye of the beholder, where the gap between public engagements with Serbian politicians and the critical stance of progress reports regarding the degradation of the media have enabled Serbian elites to exploit this ambiguity to continue their strategy of fake compliance vis-a-vis rule of law. This study used a mixed methods approach combining both primary and secondary sources with those semi-structured interviews via Zoom, email, and in person with EU and Serbian officials and journalists. Our findings add to the studies where the lack of clear and credible conditionality has allowed Serbia politicians to exploit them in a manner that would suit their own interests, finding new means to retain their control over the media. We argued and concluded that it is this discrepancy between public engagements with Serbia and the progress reports in the area of freedom of expression that has not led to genuine domestic media reforms in Serbia and instead allowed Serbian elites to engage in a strategy of fake and even non-compliance towards media freedom conditionality.

Keywords: media freedom, EU conditionality, Serbia, fake compliance, EU integration, Chapter 23, justice and fundamental rights

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Authors: Jeff Chak-Fu Wong, Tony Chun Yin Yip

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The transition from secondary school to university seems exciting for many first-year students but can be more challenging than expected. Enabling instructors to know students’ learning habits and styles enhances their understanding of the students’ learning backgrounds, allows teachers to provide better support for their students, and has therefore high potential to improve teaching quality and learning, especially in any mathematics-related courses. The aim of this research is to collect students’ data using online surveys, to analyze students’ factors using learning analytics and educational data mining and to discover the characteristics of the students at risk of falling behind in their studies based on students’ previous academic backgrounds and collected data. In this paper, we use correlation-based distance methods and mutual information for measuring student factor relationships. We then develop a factor network using the Minimum Spanning Tree method and consider further study for analyzing the topological properties of these networks using social network analysis tools. Under the framework of mutual information, two graph-based feature filtering methods, i.e., unsupervised and supervised infinite feature selection algorithms, are used to analyze the results for students’ data to rank and select the appropriate subsets of features and yield effective results in identifying the factors affecting students at risk of failing. This discovered knowledge may help students as well as instructors enhance educational quality by finding out possible under-performers at the beginning of the first semester and applying more special attention to them in order to help in their learning process and improve their learning outcomes.

Keywords: students' academic performance, correlation-based distance method, social network analysis, feature selection, graph-based feature filtering method

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Authors: Valliyil Govindankutty

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Human civilizations across the globe stand testimony to water being one of the major interaction points with nature. The interactions with nature especially in drier areas revolve around water, be it harnessing, transporting, usage and management. Many ingenious ideas were born, nurtured and developed for harnessing, transporting, storing and distributing water through the areas in the drier parts of the world. Many methods of water extraction, collection and management could be found throughout the world, some of which are associated with efficient, sustained use of surface water, ground water and rain water. Karez is one such ingenious method of collection, transportation, storage and distribution of ground water. Most of the Karez systems in India were developed during reign of Muslim dynasties with ruling class descending from Persia or having influential connections and inviting expert engineers from there. Karez have strongly influenced the village socio-economic organisations due to multitude of uses they were brought into. These are masterpiece engineering structures to collect groundwater and direct it, through a subsurface gallery with a gradual slope, to surface canals that provide water to settlements and agricultural fields. This ingenious technology, karez was result of need for harnessing groundwater in arid areas like that of Bidar. The study views this traditional technology in historical perspective linked to sustainable utilization and management of groundwater and above all the immediate environment. The karez system is one of the best available demonstration of human ingenuity and adaptability to situations and locations of water scarcity. Bidar, capital of erstwhile Bahmani sultanate with a history of more than 700 years or more is one of the heritage cities of present Karnataka State. The unique water systems of Bidar along with other historic entities have been listed under World Heritage Watch List by World Monument Fund. The Historical or cultural landscape in Bidar is very closely associated to the natural resources of the region, Karez systems being one of the best examples. The Karez systems were the lifeline of Bidar’s historical period providing potable water, fulfilling domestic and irrigation needs, both within and outside the fort enclosures. These systems are still functional, but under great pressure and threat of rapid and unplanned urbanisation. The change in land use and fragmentation of land are already paving way for irreversible modification of the karez cultural and geographic landscape. The Paper discusses the significance of character defining elements of Naubad Karez Landscape, highlights the importance of conserving cultural heritage and presents a geographical approach to its revival.

Keywords: Karez, groundwater, traditional water harvesting, cultural heritage landscape, urban planning

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Authors: Ghada Esheba, Ebtisam Aljerayan, Afnan Al-Ghamdi, Atheer Alsharif, Hanan alzahrani

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Background: Primary ovarian neoplasms comprise a heterogeneous group of tumors of three main subtypes: surface epithelial, germ cell, and sex cord-stromal. The wide morphological variation within and between these groups can result in diagnostic difficulties. Gonadal sex cord-stromal tumors (SCST) represent one of the most heterogeneous categories of human neoplasms, because they may contain various combinations of different gonadal sex cord and stromal element. Aim: The aim of this work is to highlight the clinicopathological characteristics of SCST and to assess the value of alpha-inhibin and calretinin in the distinction between SCST and their mimics. Material and methods: This study was carried out on 100 cases using full tissue sections; 70 cases were SCST and 30 cases were histological mimics of SCST. The cases were studied using immunohistochemically using alpha-inhibin. In addition, an ovarian tissue microarray containing 170 benign and malignant ovarian neoplasms was also studied immunohistochemically for calretinin expression. The ovarian microarray included 14 SCST, 59 ovarian serous borderline tumors, 17 mucinous borderline tumors, 10 mucinous adenocarcinomas, 32 endometrioid adenocarcinomas, 34 clear cell carcinomas, and 4 germ cell tumors. Results: 99% of SCST examined using full tissue sections exhibited positive cytoplasmic staining for inhibin. On the contrary, only 7% of the histological mimics (P value < 0.0001). 86% of SCST in the tissue microarray were positive for calretinin with nuclear and/or cytoplasmic staining compared to only 7% of the other tumor types (P value < 0.0001). Conclusions: SCST have characteristic clinicopathological and immunohistochemical features and their recognition is crucial for proper diagnosis and treatment. Alpha-inhibin and calretinin are of great help in the diagnosis of sex cord-stromal tumors.

Keywords: calretinin, granulosa cell tumor, inhibin, sex cord-stromal tumors

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Authors: G. Dadashova, A. Bakhshaliyev

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Aim: Determine gender differences in the etiology and clinical outcomes, as well as in the remodeling of the left ventricle (LV) in patients with chronic heart failure (CHF), suffering from arterial hypertension (AH) and coronary heart disease (CHD). Material and methods: The study included 112 patients of both sexes; aged 45 to 60 years with postinfarction cardiosclerosis had functional class (FC) heart failure II-IV of NYHA which were examined on the basis of Azerbaijan Scientific Research Institute of Cardiology. The patients were divided into 2 groups: 1st c. 60 males, mean age 54,8 ± 3,3 years, and 2nd gr 52 women, mean age 55,8 ± 3,1 years. To assess cardiac hemodynamic all patients underwent echocardiography (B-M-modes) using ‘Vivid 3’. Thus on the basis of indicators such as the index of the relative thickness of the left ventricle wall and the index of left ventricular mass (LVMI) was identified the architectonic model of the left ventricle. Results: According to our research leading cause of heart failure in women is 50.5% of cases of hypertension, ischemic heart disease 23.7% (with 79.5% of the cases developed in patients with chronic heart failure who did not have a history of myocardial infarction). While in men is the undisputed leader of CHD, forming 78.3% of CHF (80.3% in men with CHF occurred after myocardial infarction). According to our research in women more often than men CHF develops a type of diastolic dysfunction (DD, and left ventricular ejection fraction remained unchanged. Since DD occurs in men at 65,8% vs. 76,4% of women when p < 0,05. In the group of women was more common prognostic neblagopryatnye remodeling - eccentric hypertrophy of the left ventricle: 68% vs. 54.5% among men (p < 0,05), concentric left ventricular hypertrophy: 21% in women vs 19,1% (p > 0,05 ). Conclusions: Patients with heart failure are a number of gender-specific: the prevalence of hypertension in women, and coronary heart disease in men. While in women with heart failure often recorded diastolic dysfunction and characterized by the development of prognostically unfavorable remodeling types: eccentric and concentric LV hypertrophy.

Keywords: chronic heart failure, arterial hypertension, remodeling, diastolic dysfunction, men, women, ischemic heart disease

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