Search results for: image rights in modeling

Authors: Ting Lu, Ya-Ru Diao, Fei Fan, Ye Xue, Lei Shi, Xian-e Tang, Meng-jun Zhan, Zhen-hua Deng

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Accurate adult age estimation (AAE) is a significant and challenging task in forensic and archeology fields. Attempts have been made to explore optimal adult age metrics, and the rib is considered a potential age marker. The traditional way is to extract age-related features designed by experts from macroscopic or radiological images followed by classification or regression analysis. Those results still have not met the high-level requirements for practice, and the limitation of using feature design and manual extraction methods is loss of information since the features are likely not designed explicitly for extracting information relevant to age. Deep learning (DL) has recently garnered much interest in imaging learning and computer vision. It enables learning features that are important without a prior bias or hypothesis and could be supportive of AAE. This study aimed to develop DL models for AAE based on CT images and compare their performance to the manual visual scoring method. Chest CT data were reconstructed using volume rendering (VR). Retrospective data of 2500 patients aged 20.00-69.99 years were obtained between December 2019 and September 2021. Five-fold cross-validation was performed, and datasets were randomly split into training and validation sets in a 4:1 ratio for each fold. Before feeding the inputs into networks, all images were augmented with random rotation and vertical flip, normalized, and resized to 224×224 pixels. ResNeXt was chosen as the DL baseline due to its advantages of higher efficiency and accuracy in image classification. Mean absolute error (MAE) was the primary parameter. Independent data from 100 patients acquired between March and April 2022 were used as a test set. The manual method completely followed the prior study, which reported the lowest MAEs (5.31 in males and 6.72 in females) among similar studies. CT data and VR images were used. The radiation density of the first costal cartilage was recorded using CT data on the workstation. The osseous and calcified projections of the 1 to 7 costal cartilages were scored based on VR images using an eight-stage staging technique. According to the results of the prior study, the optimal models were the decision tree regression model in males and the stepwise multiple linear regression equation in females. Predicted ages of the test set were calculated separately using different models by sex. A total of 2600 patients (training and validation sets, mean age=45.19 years±14.20 [SD]; test set, mean age=46.57±9.66) were evaluated in this study. Of ResNeXt model training, MAEs were obtained with 3.95 in males and 3.65 in females. Based on the test set, DL achieved MAEs of 4.05 in males and 4.54 in females, which were far better than the MAEs of 8.90 and 6.42 respectively, for the manual method. Those results showed that the DL of the ResNeXt model outperformed the manual method in AAE based on CT reconstruction of the costal cartilage and the developed system may be a supportive tool for AAE.

Keywords: forensic anthropology, age determination by the skeleton, costal cartilage, CT, deep learning

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Authors: Farid Khosravikia, Patricia Clayton

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The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Jiaying Zhang, Xin Mu, Chang Ni, Jeff L. Zhang

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Magnetic resonance elastography (MRE) non-invasively assesses tissue elastic properties, such as shear modulus, by measuring tissue’s displacement in response to mechanical waves. The estimated metrics on tissue elasticity or stiffness have been shown to be valuable for monitoring physiologic or pathophysiologic status of tissue, such as a tumor or fatty liver. To quantify tissue shear modulus from MRE-acquired displacements (essentially an inverse problem), multiple approaches have been proposed, including Local Frequency Estimation (LFE) and Direct Inversion (DI). However, one common problem with these methods is that the estimates are severely noise-sensitive due to either the inverse-problem nature or noise propagation in the pixel-by-pixel process. With the advent of deep learning (DL) and its promise in solving inverse problems, a few groups in the field of MRE have explored the feasibility of using DL methods for quantifying shear modulus from MRE data. Most of the groups chose to use real MRE data for DL model training and to cut training images into smaller patches, which enriches feature characteristics of training data but inevitably increases computation time and results in outcomes with patched patterns. In this study, simulated wave images generated by Finite Differential Time Domain (FDTD) simulation are used for network training, and U-Net is used to extract features from each training image without cutting it into patches. The use of simulated data for model training has the flexibility of customizing training datasets to match specific applications. The proposed method aimed to estimate tissue shear modulus from MRE data with high robustness to noise and high model-training efficiency. Specifically, a set of 3000 maps of shear modulus (with a range of 1 kPa to 15 kPa) containing randomly positioned objects were simulated, and their corresponding wave images were generated. The two types of data were fed into the training of a U-Net model as its output and input, respectively. For an independently simulated set of 1000 images, the performance of the proposed method against DI and LFE was compared by the relative errors (root mean square error or RMSE divided by averaged shear modulus) between the true shear modulus map and the estimated ones. The results showed that the estimated shear modulus by the proposed method achieved a relative error of 4.91%±0.66%, substantially lower than 78.20%±1.11% by LFE. Using simulated data, the proposed method significantly outperformed LFE and DI in resilience to increasing noise levels and in resolving fine changes of shear modulus. The feasibility of the proposed method was also tested on MRE data acquired from phantoms and from human calf muscles, resulting in maps of shear modulus with low noise. In future work, the method’s performance on phantom and its repeatability on human data will be tested in a more quantitative manner. In conclusion, the proposed method showed much promise in quantifying tissue shear modulus from MRE with high robustness and efficiency.

Keywords: deep learning, magnetic resonance elastography, magnetic resonance imaging, shear modulus estimation

Procedia PDF Downloads 37

Authors: Z. M. Biyasheva, M. Zh. Tleubergenova, Y. A. Zaripova, A. L. Shakirov, V. V. Dyachkov

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In recent years, interest in ecogenetic and biomedical problems related to the effects on the population of radon and its daughter decay products has increased significantly. Of particular interest is the assessment of the consequence of irradiation at hazardous radon areas, which includes the Almaty region due to the large number of tectonic faults that enhance radon emanation. In connection with the foregoing, the purpose of this work was to study the genetic effects of exposure to supernormal radon doses on the alpha-radiation model. Irradiation does not affect the growth of the cell, but rather its ability to differentiate. In addition, irradiation can lead to somatic mutations, morphoses and modifications. These damages most likely occur from changes in the composition of the substances of the cell. Such changes are epigenetic since they affect the regulatory processes of ontogenesis. Variability in the expression of regulatory genes refers to conditional mutations that modify the formation of signs of intraspecific similarity. Characteristic features of these conditional mutations are the dominant type of their manifestation, phenotypic asymmetry and their instability in the generations. Currently, the terms “morphosis” and “modification” are used to describe epigenetic variability, which are maintained in Drosophila melanogaster cultures using linkaged X- chromosomes, and the mutant X-chromosome is transmitted along the paternal line. In this paper, we investigated the epigenetic effects of alpha particles, whose source in nature is mainly radon and its daughter decay products. In the experiment, an isotope of plutonium-238 (Pu²³⁸), generating radiation with an energy of about 5500 eV, was used as a source of alpha particles. In an experiment in the first generation (F₁), deformities or morphoses were found, which can be called "radiation syndromes" or mutations, the manifestation of which is similar to the pleiotropic action of genes. The proportion of morphoses in the experiment was 1.8%, and in control 0.4%. In this experiment, the morphoses in the flies of the first and second generation looked like black spots, or melanomas on different parts of the imago body; "generalized" melanomas; curled, curved wings; shortened wing; bubble on one wing; absence of one wing, deformation of thorax, interruption and violation of tergite patterns, disruption of distribution of ocular facets and bristles; absence of pigmentation of the second and third legs. Statistical analysis by the Chi-square method showed the reliability of the difference in experiment and control at P ≤ 0.01. On the basis of this, it can be considered that alpha particles, which in the environment are mainly generated by radon and its isotopes, have a mutagenic effect that manifests itself, mainly in the formation of morphoses or deformities.

Keywords: alpha-radiation, genotoxicity, morphoses, radioecology, radon

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Authors: Matthias Leitner, Gernot Pottlacher

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Experimental determination of critical point data like critical temperature, critical pressure, critical volume and critical compressibility of high-melting metals such as niobium is very rare due to the outstanding experimental difficulties in reaching the necessary extreme temperature and pressure regimes. Experimental techniques to achieve such extreme conditions could be diamond anvil devices, two stage gas guns or metal samples hit by explosively accelerated flyers. Electrical pulse-heating under increased pressures would be another choice. This technique heats thin wire samples of 0.5 mm diameter and 40 mm length from room temperature to melting and then further to the end of the stable phase, the spinodal line, within several microseconds. When crossing the spinodal line, the sample explodes and reaches the gaseous phase. In our laboratory, pulse-heating experiments can be performed under variation of the ambient pressure from 1 to 5000 bar and allow a direct determination of critical point data for low-melting, but not for high-melting metals. However, the critical point also can be estimated by extrapolating the liquid phase density according to theoretical models. A reasonable prerequisite for the extrapolation is the existence of data that cover as much as possible of the liquid phase and at the same time exhibit small uncertainties. Ohmic pulse-heating was therefore applied to determine thermal volume expansion, and from that density of niobium over the entire liquid phase. As a first step, experiments under ambient pressure were performed. The second step will be to perform experiments under high-pressure conditions. During the heating process, shadow images of the expanding sample wire were captured at a frame rate of 4 × 105 fps to monitor the radial expansion as a function of time. Simultaneously, the sample radiance was measured with a pyrometer operating at a mean effective wavelength of 652 nm. To increase the accuracy of temperature deduction, spectral emittance in the liquid phase is also taken into account. Due to the high heating rates of about 2 × 108 K/s, longitudinal expansion of the wire is inhibited which implies an increased radial expansion. As a consequence, measuring the temperature dependent radial expansion is sufficient to deduce density as a function of temperature. This is accomplished by evaluating the full widths at half maximum of the cup-shaped intensity profiles that are calculated from each shadow image of the expanding wire. Relating these diameters to the diameter obtained before the pulse-heating start, the temperature dependent volume expansion is calculated. With the help of the known room-temperature density, volume expansion is then converted into density data. The so-obtained liquid density behavior is compared to existing literature data and provides another independent source of experimental data. In this work, the newly determined off-critical liquid phase density was in a second step utilized as input data for the estimation of niobium’s critical point. The approach used, heuristically takes into account the crossover from mean field to Ising behavior, as well as the non-linearity of the phase diagram’s diameter.

Keywords: critical point data, density, liquid metals, niobium, ohmic pulse-heating, volume expansion

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Authors: Sara Honarparast, Omar Chaallal

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Reinforced concrete (RC) coupled shear walls (CSWs) are very effective structural systems in resisting lateral loads due to winds and earthquakes and are particularly used in medium- to high-rise RC buildings. However, most of existing old RC structures were designed for gravity loads or lateral loads well below the loads specified in the current modern seismic international codes. These structures may behave in non-ductile manner due to poorly designed joints, insufficient shear reinforcement and inadequate anchorage length of the reinforcing bars. This has been the main impetus to investigate an appropriate strengthening method to address or attenuate the deficiencies of these structures. The objective of this paper is to twofold: (i) evaluate the seismic performance of existing reinforced concrete coupled shear walls under reversed cyclic loading; and (ii) investigate the seismic performance of RC CSWs strengthened with externally bonded (EB) carbon fiber reinforced polymer (CFRP) sheets. To this end, two CSWs were considered as follows: (a) the first one is representative of old CSWs and therefore was designed according to the 1941 National Building Code of Canada (NBCC, 1941) with conventionally reinforced coupling beams; and (b) the second one, representative of new CSWs, was designed according to modern NBCC 2015 and CSA/A23.3 2014 requirements with diagonally reinforced coupling beam. Both CSWs were simulated using ANSYS software. Nonlinear behavior of concrete is modeled using multilinear isotropic hardening through a multilinear stress strain curve. The elastic-perfectly plastic stress-strain curve is used to simulate the steel material. Bond stress–slip is modeled between concrete and steel reinforcement in conventional coupling beam rather than considering perfect bond to better represent the slip of the steel bars observed in the coupling beams of these CSWs. The old-designed CSW was strengthened using CFRP sheets bonded to the concrete substrate and the interface was modeled using an adhesive layer. The behavior of CFRP material is considered linear elastic up to failure. After simulating the loading and boundary conditions, the specimens are analyzed under reversed cyclic loading. The comparison of results obtained for the two unstrengthened CSWs and the one retrofitted with EB CFRP sheets reveals that the strengthening method improves the seismic performance in terms of strength, ductility, and energy dissipation capacity.

Keywords: carbon fiber reinforced polymer, coupled shear wall, coupling beam, finite element analysis, modern code, old code, strengthening

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Authors: Waleed Omri

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With the growth of the small business sector in emerging markets, developing a better understanding of what drives 'day-to-day' entrepreneurial activities has become an important issue for academicians and practitioners. Innovation, as an entrepreneurial behavior, revolves around individuals who creatively engage in new organizational efforts. In a similar vein, the innovation behaviors and processes at the organizational member level are central to any corporate entrepreneurship strategy. Despite the broadly acknowledged importance of entrepreneurship and innovation at the individual level in the establishment of successful ventures, the literature lacks evidence on how entrepreneurs can effectively harness their skills and knowledge in the workplace. The existing literature illustrates that religion can impact the day-to-day work behavior of entrepreneurs, managers, and employees. Religious beliefs and practices could affect daily entrepreneurial activities by fostering mental abilities and traits such as creativity, intelligence, and self-efficacy. In the present study, we define religious capital as a set of personal and intangible resources, skills, and competencies that emanate from an individual’s religious values, beliefs, practices, and experiences and may be used to increase the quality of economic activities. Religious beliefs and practices give individuals a religious satisfaction, which can lead them to perform better in the workplace. In addition, religious ethics and practices have been linked to various positive employee outcomes in terms of organizational change, job satisfaction, and entrepreneurial intensity. As investigations of their consequences beyond direct task performance are still scarce, we explore if religious capital plays a role in entrepreneurs’ innovative behavior. In sum, this study explores the determinants of individual entrepreneurial behavior by investigating the relationship between religious capital and entrepreneurs’ innovative behavior in the context of small businesses. To further explain and clarify the religious capital-innovative behavior link, the present study proposes a model to examine the mediating role of entrepreneurial creativity. We use both Islamic work ethics (IWE) and Islamic religious practices (IRP) to measure Islamic religious capital. We use structural equation modeling with a robust maximum likelihood estimation to analyze data gathered from 289 Tunisian small businesses and to explore the relationships among the above-described variables. In line with the theory of planned behavior, only religious work ethics are found to increase the innovative behavior of small businesses’ owner-managers. Our findings also clearly demonstrate that the connection between religious capital-related variables and innovative behavior is better understood if the influence of entrepreneurial creativity, as a mediating variable of the aforementioned relationship, is taken into account. By incorporating both religious capital and entrepreneurial creativity into the innovative behavior analysis, this study provides several important practical implications for promoting innovation process in small businesses.

Keywords: entrepreneurial behavior, small business, religion, creativity

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Authors: Iman Janghorban Esfahani

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Due to the increased use of irrigation in agriculture, the importance and need for highly reliable water pumping systems have significantly increased. The pumping of the groundwater is essential to provide water for both drip and furrow irrigation to increase the agricultural yield, especially in arid regions that suffer from scarcities of surface water. The most common irrigation pumping systems (IPS) consume conventional energies through the use of electric motors and generators or connecting to the electricity grid. Due to the shortage and transportation difficulties of fossil fuels, and unreliable access to the electricity grid, especially in the rural areas, and the adverse environmental impacts of fossil fuel usage, such as greenhouse gas (GHG) emissions, the need for renewable energy sources such as photovoltaic systems (PVS) as an alternative way of powering irrigation pumping systems is urgent. Integration of the photovoltaic systems with irrigation pumping systems as the Photovoltaic Powered-Irrigation Pumping System (PVP-IPS) can avoid fossil fuel dependency and the subsequent greenhouse gas emissions, as well as ultimately lower energy costs and improve efficiency, which made PVP-IPS systems as an environmentally and economically efficient solution for agriculture irrigation in every region. The greatest problem faced by integration of PVP with IPS systems is matching the intermittence of the energy supply with the dynamic water demand. The best solution to overcome the intermittence is to incorporate a storage system into the PVP-IPS to provide water-on-demand as a highly reliable stand-alone irrigation pumping system. The water storage tank (WST) is the most common storage device for PVP-IPS systems. In the integrated PVP-IPS with a water storage tank (PVP-IPS-WST), a water storage tank stores the water pumped by the IPS in excess of the water demand and then delivers it when demands are high. The Freshwater pinch analysis (FWaPA) as an alternative to mathematical modeling was used by other researchers for retrofitting the off-grid battery less photovoltaic-powered reverse osmosis system. However, the Freshwater pinch analysis has not been used to integrate the photovoltaic systems with irrigation pumping system with water storage tanks. In this study, FWaPA graphical and numerical tools were used for retrofitting an existing PVP-IPS system located in Salahadin, Republic of Iraq. The plant includes a 5 kW submersible water pump and 7.5 kW solar PV system. The Freshwater Composite Curve as the graphical tool and Freashwater Storage Cascade Table as the numerical tool were constructed to determine the minimum required outsourced water during operation, optimal amount of delivered electricity to the water pump, and optimal size of the water storage tank for one-year operation data. The results of implementing the FWaPA on the case study show that the PVP-IPS system with a WST as the reliable system can reduce outsourced water by 95.41% compare to the PVP-IPS system without storage tank.

Keywords: irrigation, photovoltaic, pinch analysis, pumping, solar energy

Procedia PDF Downloads 114

Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Isaiah Ifeanyichukwu Agbo

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Human speech is capable of serving many purposes. Power and control are not always exercised overtly by linguistic acts, but maybe enacted and exercised in the myriad of taken-for-granted actions of everyday life. Domination, power control, discrimination and mind control exist in human speech and may lead to asymmetrical power relations. In discourse, there are persuasive and manipulative linguistic acts that serve to establish solidarity and identification with the 'we group' and polarize with the 'they group'. Political discourse is crafted to defend and promote the problematic narrative of outright controversial events in a nation’s history thereby sustaining domination, marginalization, manipulation, inequalities and injustices, often without the dominated and marginalized group being aware of them. They are designed and positioned to serve the political and social needs of the producers. Political crisis speeches in Nigeria, just like in other countries concentrate on positive self-image, de-legitimization of political opponents, reframing accusation to one’s advantage, redefining problematic terms and adopting reversal strategy. In most cases, the people are ignorant of the hidden ideological positions encoded in the text. Few researches have been conducted adopting the frameworks of critical discourse analysis and systemic functional linguistics to investigate this situation in the political crisis speeches in Nigeria. In this paper, we focus attention on the analyses of the linguistic, semantic, and ideological elements in selected political crisis speeches in Nigeria to investigate if they create and sustain unequal power relations and manipulative tendencies from the perspectives of Critical Discourse Analysis (CDA) and Systemic Functional Linguistics (SFL). Critical Discourse Analysis unpacks both opaque and transparent structural relationships of power dominance, power relations and control as manifested in language. Critical discourse analysis emerged from a critical theory of language study which sees the use of language as a form of social practice where social relations are reproduced or contested and different interests are served. Systemic function linguistics relates the structure of texts to their function. Fairclough’s model of CDA and Halliday’s systemic functional approach to language study are adopted in this paper. This paper probes into language use that perpetuates inequalities. This study demystifies the hidden implicature of the selected political crisis speeches and reveals the existence of information that is not made explicit in what the political actors actually say. The analysis further reveals the ideological configurations present in the texts. These ideological standpoints are the basis for naturalizing implicit ideologies and hegemonic influence in the texts. The analyses of the texts further uncovered the linguistic and discursive strategies deployed by text producers to manipulate the unsuspecting members of the public both mentally and conceptually in order to enact, sustain and maintain unhealthy power relations at crisis times in the Nigerian political history.

Keywords: critical discourse analysis, language, political crisis, power relations, systemic functional linguistics

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Authors: U. E. Mochalova, A. V. Demeneva, Shilkin A. G., J. Yu. Artiushina

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Objective. In medical ophthalmology OCT has been actively used in the last decade. It is a modern non-invasive method of high-precision hardware examination, which gives a detailed cross-sectional image of eye tissues structure with a high level of resolution, which provides in vivo morphological information at the microscopic level about corneal tissue, structures of the anterior segment, retina and optic nerve. The purpose of this study was to explore the possibility of using the OCT technology in complex ophthalmological examination in dogs and cats, to characterize the revealed pathological structural changes in corneal tissue in cats and dogs with some of the most common corneal diseases. Procedures. Optical coherence tomography of the cornea was performed in 112 animals: 68 dogs and 44 cats. In total, 224 eyes were examined. Pathologies of the organ of vision included: dystrophy and degeneration of the cornea, endothelial corneal dystrophy, dry eye syndrome, chronic superficial vascular keratitis, pigmented keratitis, corneal erosion, ulcerative stromal keratitis, corneal sequestration, chronic glaucoma and also postoperative period after performed keratoplasty. When performing OCT, we used certified medical devices: "Huvitz HOCT-1/1F», «Optovue iVue 80» and "SOCT Copernicus Revo (60)". Results. The results of a clinical study on the use of optical coherence tomography (OCT)of the cornea in cats and dogs, performed by the authors of the article in the complex diagnosis of keratopathies of variousorigins: endothelial corneal dystrophy, pigmented keratitis, chronic keratoconjunctivitis, chronic herpetic keratitis, ulcerative keratitis, traumatic corneal damage, sequestration of the cornea of cats, chronic keratitis, complicating the course of glaucoma. The characteristics of the OCT scans are givencorneas of cats and dogs that do not have corneal pathologies. OCT scans of various corneal pathologies in dogs and cats with a description of the revealed pathological changes are presented. Of great clinical interest are the data obtained during OCT of the cornea of animals undergoing keratoplasty operations using various forms of grafts. Conclusions. OCT makes it possible to assess the thickness and pathological structural changes of the corneal surface epithelium, corneal stroma and descemet membrane. We can measure them, determine the exact localization, and record pathological changes. Clinical observation of the dynamics of the pathological process in the cornea using OCT makes it possible to evaluate the effectiveness of drug treatment. In case of negative dynamics of corneal disease, it is necessary to determine the indications for surgical treatment (to assess the thickness of the cornea, the localization of its thinning zones, to characterize the depth and area of pathological changes). According to the OCT of the cornea, it is possible to choose the optimal surgical treatment for the patient, the technique and depth of optically constructive surgery (penetrating or anterior lamellar keratoplasty).; determine the depth and diameter of the planned microsurgical trepanation of corneal tissue, which will ensure good adaptation of the edges of the donor material.

Keywords: optical coherence tomography, corneal sequestration, optical coherence tomography of the cornea, corneal transplantation, cat, dog

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Authors: Olga Kruzhkova, Irina Vorobyeva, Roman Porozov

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Vandalism is a common phenomenon, but its definition is still not clearly defined. In the public sense, vandalism is the blatant cases of pogroms in cemeteries, destruction of public places (regardless of whether these actions are authorized), damage to significant objects of culture and history (monuments, religious buildings). From a legal point of view, only such an act can be called vandalism, which is aimed at 'desecrating buildings or other structures, damaging property on public transport or in other public places'. The key here is the notion of public property that is being damaged. In addition, the principal is the semantics of messages, expressed in a kind of sign system (drawing, inscription, symbol), which initially threatens public order, the calmness of citizens, public morality. Because of this, the legal qualification of vandalism doesn’t include a sufficiently wide layer of environmental destructions that are common in modern urban space (graffiti and other damage to private property, broken shop windows, damage to entrances and elevator cabins), which in ordinary consciousness are seen as obvious facts of vandalism. At the same time, the understanding of vandalism from the position of psychology implies an appeal to the question of the limits of the activity of the subject of vandalism and his motivational basis. Also recently, the discourse on the positive meaning of some forms of vandalism (graffiti, street-art, etc.) has been activated. But there is no discussion of the role and significance of vandalism in public and individual life, although, like any socio-cultural and socio-psychological phenomenon, vandalism is not groundless and meaningless. Our aim of the study was to identify and describe the functions of vandalism as a socio-cultural and socio-psychological phenomenon of the life of the urban community, as well as personal determinants of its manifestations. The study was conducted in the spatial environment of the Russian megalopolis (Ekaterinburg) by photographing visual results of vandal acts (6217 photos) with subsequent trace-assessment and image content analysis, as well as diagnostics of personal characteristics and motivational basis of vandal activity of possible subjects of vandalism among youth. The results of the study allowed to identify the functions of vandalism at the socio-environmental and individual-subjective levels. The socio-environmental functions of vandalism include the signaling function, the function of preparing of social changes, the constructing function, and the function of managing public moods. The demonstrative-protest function, the response function, the refund function, and the self-expression function are assigned to the individual-subjective functions of vandalism. A two-dimensional model of vandal functions has been formed, where functions are distributed in the spaces 'construction reconstruction', 'emotional regulation/moral regulation'. It is noted that any function of vandal activity at the individual level becomes a kind of marker of 'points of tension' at the social and environmental level. Acknowledgment: The research was supported financially by Russian Science Foundation, (Project No. 17-18-01278).

Keywords: destruction, urban environment, vandal behavior, vandalism, vandalism functions

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Authors: Rahul Patel, S. P. Dave, M. V Shah

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Ahmedabad is a rapidly growing city in western India that is experiencing significant urbanization and industrialization. With projections indicating that it will become a metropolitan city in the near future, various construction activities are taking place, making soil testing a crucial requirement before construction can commence. To achieve this, construction companies and contractors need to periodically conduct soil testing. This study focuses on the process of creating a spatial database that is digitally formatted and integrated with geotechnical data and a Geographic Information System (GIS). Building a comprehensive geotechnical Geo-database involves three essential steps. Firstly, borehole data is collected from reputable sources. Secondly, the accuracy and redundancy of the data are verified. Finally, the geotechnical information is standardized and organized for integration into the database. Once the Geo-database is complete, it is integrated with GIS. This integration allows users to visualize, analyze, and interpret geotechnical information spatially. Using a Topographic to Raster interpolation process in GIS, estimated values are assigned to all locations based on sampled geotechnical data values. The study area was contoured for SPT N-Values, Soil Classification, Φ-Values, and Bearing Capacity (T/m2). Various interpolation techniques were cross-validated to ensure information accuracy. The GIS map generated by this study enables the calculation of SPT N-Values, Φ-Values, and bearing capacities for different footing widths and various depths. This approach highlights the potential of GIS in providing an efficient solution to complex phenomena that would otherwise be tedious to achieve through other means. Not only does GIS offer greater accuracy, but it also generates valuable information that can be used as input for correlation analysis. Furthermore, this system serves as a decision support tool for geotechnical engineers. The information generated by this study can be utilized by engineers to make informed decisions during construction activities. For instance, they can use the data to optimize foundation designs and improve site selection. In conclusion, the rapid growth experienced by Ahmedabad requires extensive construction activities, necessitating soil testing. This study focused on the process of creating a comprehensive geotechnical database integrated with GIS. The database was developed by collecting borehole data from reputable sources, verifying its accuracy and redundancy, and organizing the information for integration. The GIS map generated by this study is an efficient solution that offers greater accuracy and generates valuable information that can be used as input for correlation analysis. It also serves as a decision support tool for geotechnical engineers, allowing them to make informed decisions during construction activities.

Keywords: arcGIS, borehole data, geographic information system (GIS), geo-database, interpolation, SPT N-value, soil classification, φ-value, bearing capacity

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Authors: Yu Zhang, Jie Wu, Li Dong

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Rural tourism is the service industry which regards the agricultural production, rural life, rural nature and cultural landscape as the tourist attraction. It aims to meet the needs of the city tourists such as country sightseeing, vacation, and leisure. According to the difference of the tourist resources, the rural settlements can be divided into different types: The type of tourism resources, scenic spot, and peri-urban. In the past ten years, the rural tourism has promoted the industrial transformation and economic growth in rural areas of China. And it is conducive to the coordinated development of urban and rural areas and has greatly improved the ecological environment and the standard of living for farmers in rural areas. At the same time, a large number of buildings and sites are built in the countryside in order to enhance the tourist attraction and the ability of tourist reception and also to increase the travel comfort and convenience, which has significant influence on the spatial evolution of the village settlement. This article takes the XiangYing Subdistrict, which is in JinPu District of Dalian in China as the exemplification and uses the technology of Remote Sensing (RS), Geographic Information System (GIS) and the technology of Landscape Spatial Analysis to study the influence of the rural tourism development in the rural settlement spaces in four steps. First, acquiring the remote sensing image data at different times of 8 administrative villages in the XiangYing Subdistrict, by using the remote sensing application EDRAS8.6; second, vectoring basic maps of XiangYing Subdistrict including its land-use map with the application of ArcGIS 9.3, associating with social and economic attribute data of rural settlements and analyzing on the rural evolution visually; third, quantifying the comparison of these patches in rural settlements by using the landscape spatial calculation application Fragstats 3.3 and analyzing on the evolution of the spatial structure of settlement in macro and medium scale; finally, summarizing the evolution characteristics and internal reasons of tourism-oriented rural settlements. The main findings of this article include: first of all, there is difference in the evolution of the spatial structure between the developing rural settlements and undeveloped rural settlements among the eight administrative villages; secondly, the villages relying on the surrounding tourist attractions, the villages developing agricultural ecological garden and the villages with natural or historical and cultural resources have different laws of development; then, the rural settlements whose tourism development in germination period, development period and mature period have different characteristics of spatial evolution; finally, the different evolution modes of the tourism-oriented rural settlement space have different influences on the protection and inheritance of the village scene. The development of tourism has a significant impact on the spatial evolution of rural settlement. The intensive use of rural land and natural resources is the fundamental principle to protect the rural cultural landscape and ecological environment as well as the critical way to improve the attraction of rural tourism and promote the sustainable development of countryside.

Keywords: landscape pattern, rural settlement, spatial evolution, tourism-oriented, Xiangying Subdistrict

Procedia PDF Downloads 258

Authors: M. V. Rane, Tareke Tekia

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Liquid desiccant based fresh air dehumidifiers can be gainfully deployed for air-conditioning, agro-produce drying and in many industrial processes. Regeneration of liquid desiccant can be done using direct firing, high temperature waste heat or solar energy. Solar energy is clean and available in abundance; however, it is costly to collect. A two stage liquid desiccant fresh air dehumidification system can offer Coefficient of Performance (COP), in the range of 1.6 to 2 for comfort air conditioning applications. High COP helps reduce the size and cost of collectors required. Performance tests on high temperature regenerator of a two stage liquid desiccant fresh air dehumidifier coupled with seasonally tracked flat plate like solar collector will be presented in this paper. The two stage fresh air dehumidifier has four major components: High Temperature Regenerator (HTR), Low Temperature Regenerator (LTR), High and Low Temperature Solution Heat Exchangers and Fresh Air Dehumidifier (FAD). This open system can operate at near atmospheric pressure in all the components. These systems can be simple, maintenance-free and scalable. Environmentally benign, non-corrosive, moderately priced Potassium Formate, KCOOH, is used as a liquid desiccant. Typical KCOOH concentration in the system is expected to vary between 65 and 75%. Dilute liquid desiccant at 65% concentration exiting the fresh air dehumidifier will be pumped and preheated in solution heat exchangers before entering the high temperature solar regenerator. In the solar collector, solution will be regenerated to intermediate concentration of 70%. Steam and saturated solution exiting the solar collector array will be separated. Steam at near atmospheric pressure will then be used to regenerate the intermediate concentration solution up to a concentration of 75% in a low temperature regenerator where moisture vaporized be released in to atmosphere. Condensed steam can be used as potable water after adding a pinch of salt and some nutrient. Warm concentrated liquid desiccant will be routed to solution heat exchanger to recycle its heat to preheat the weak liquid desiccant solution. Evacuated glass tube based seasonally tracked solar collector is used for regeneration of liquid desiccant at high temperature. Temperature of regeneration for KCOOH is 133°C at 70% concentration. The medium temperature collector was designed for temperature range of 100 to 150°C. Double wall polycarbonate top cover helps reduce top losses. Absorber integrated heat storage helps stabilize the temperature of liquid desiccant exiting the collectors during intermittent cloudy conditions, and extends the operation of the system by couple of hours beyond the sunshine hours. This solar collector is light in weight, 12 kg/m2 without absorber integrated heat storage material, and 27 kg/m2 with heat storage material. Cost of the collector is estimated to be 10,000 INR/m2. Theoretical modeling of the collector has shown that the optical efficiency is 62%. Performance test of regeneration of KCOOH will be reported.

Keywords: solar, liquid desiccant, dehumidification, air conditioning, regeneration

Procedia PDF Downloads 327

Authors: Bhupendra G. Prajapati, Alpesh R. Patel

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The aim of this research work is to develop sustained release multi-particulates dosage form of Dexketoprofen trometamol, which is the pharmacologically active isomer of ketoprofen. The objective is to utilization of active enantiomer with minimal dose and administration frequency, extended release multi-particulates dosage form development for better patience compliance was explored. Drug loaded and sustained release coated pellets were prepared by fluidized bed coating principle by wurster coater. Microcrystalline cellulose as core pellets, povidone as binder and talc as anti-tacking agents were selected during drug loading while Kollicoat SR 30D as sustained release polymer, triethyl citrate as plasticizer and micronized talc as an anti-adherent were used in sustained release coating. Binder optimization trial in drug loading showed that there was increase in process efficiency with increase in the binder concentration. 5 and 7.5%w/w concentration of Povidone K30 with respect to drug amount gave more than 90% process efficiency while higher amount of rejects (agglomerates) were observed for drug layering trial batch taken with 7.5% binder. So for drug loading, optimum Povidone concentration was selected as 5% of drug substance quantity since this trial had good process feasibility and good adhesion of the drug onto the MCC pellets. 2% w/w concentration of talc with respect to total drug layering solid mass shows better anti-tacking property to remove unnecessary static charge as well as agglomeration generation during spraying process. Optimized drug loaded pellets were coated for sustained release coating from 16 to 28% w/w coating to get desired drug release profile and results suggested that 22% w/w coating weight gain is necessary to get the required drug release profile. Three critical process parameters of Wurster coating for sustained release were further statistically optimized for desired quality target product profile attributes like agglomerates formation, process efficiency, and drug release profile using central composite design (CCD) by Minitab software. Results show that derived design space consisting 1.0 to 1.2 bar atomization air pressure, 7.8 to 10.0 gm/min spray rate and 29-34°C product bed temperature gave pre-defined drug product quality attributes. Scanning Image microscopy study results were also dictate that optimized batch pellets had very narrow particle size distribution and smooth surface which were ideal properties for reproducible drug release profile. The study also focused on optimized dexketoprofen trometamol pellets formulation retain its quality attributes while administering with common vehicle, a liquid (water) or semisolid food (apple sauce). Conclusion: Sustained release multi-particulates were successfully developed for dexketoprofen trometamol which may be useful to improve acceptability and palatability of a dosage form for better patient compliance.

Keywords: dexketoprofen trometamol, pellets, fluid bed technology, central composite design

Procedia PDF Downloads 112

Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

Procedia PDF Downloads 58

Authors: Young Ik Suh, Tywan G. Martin

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Sports apps in a smartphone provide up-to-date information and fast and convenient access to live games. The market of sports apps has emerged as the second fastest growing app category worldwide. Further, many sports fans use their smartphones to know the schedule of sporting events, players’ position and bios, videos and highlights. In recent years, a growing number of scholars and practitioners alike have emphasized the importance of interactivity with sports apps, hypothesizing that interactivity plays a significant role in enticing sports apps users and that it is a key component in measuring the success of sports apps. Interactivity in sports apps focuses primarily on two functions: (1) two-way communication and (2) active user control, neither of which have been applicable through traditional mass media and communication technologies. Therefore, the purpose of this study is to examine whether the interactivity function on sports apps leads to positive outcomes such as intent to revisit. More specifically, this study investigates how three major functions of interactivity (i.e., two-way communication, active user control, and real-time information) influence the attitude of sports apps users and their intent to revisit the sports apps. The following hypothesis is proposed; interactivity functions will be positively associated with both attitudes toward sports apps and intent to revisit sports apps. The survey questionnaire includes four parts: (1) an interactivity scale, (2) an attitude scale, (3) a behavioral intention scale, and (4) demographic questions. Data are to be collected from ESPN apps users. To examine the relationships among the observed and latent variables and determine the reliability and validity of constructs, confirmatory factor analysis (CFA) is conducted. Structural equation modeling (SEM) is utilized to test hypothesized relationships among constructs. Additionally, this study compares the proposed interactivity model with a rival model to identify the role of attitude as a mediating factor. The findings of the current sports apps study provide several theoretical and practical contributions and implications by extending the research and literature associated with the important role of interactivity functions in sports apps and sports media consumption behavior. Specifically, this study may improve the theoretical understandings of whether the interactivity functions influence user attitudes and intent to revisit sports apps. Additionally, this study identifies which dimensions of interactivity are most important to sports apps users. From practitioners’ perspectives, this findings of this study provide significant implications. More entrepreneurs and investors in the sport industry need to recognize that high-resolution photos, live streams, and up-to-date stats are in the sports app, right at sports fans fingertips. The result will imply that sport practitioners may need to develop sports mobile apps that offer greater interactivity functions to attract sport fans.

Keywords: interactivity, two-way communication, active user control, real time information, sports apps, attitude, intent to revisit

Procedia PDF Downloads 129

Authors: C. Deangeli, P. Obentaku Obenebot, O. Omwanghe

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The study focuses on the analysis of wellbore instability in rock masses affected by weakness planes. The occurrence of failure in such a type of rocks can occur in the rock matrix and/ or along the weakness planes, in relation to the mud weight gradient. In this case the simple Kirsch solution coupled with a failure criterion cannot supply a suitable scenario for borehole instabilities. Two different numerical approaches have been used in order to investigate the onset of local failure at the wall of a borehole. For each type of approach the influence of the inclination of weakness planes has been investigates, by considering joint sets at 0°, 35° and 90° to the horizontal. The first set of models have been carried out with FLAC 2D (Fast Lagrangian Analysis of Continua) by considering the rock material as a continuous medium, with a Mohr Coulomb criterion for the rock matrix and using the ubiquitous joint model for accounting for the presence of the weakness planes. In this model yield may occur in either the solid or along the weak plane, or both, depending on the stress state, the orientation of the weak plane and the material properties of the solid and weak plane. The second set of models have been performed with PFC2D (Particle Flow code). This code is based on the Discrete Element Method and considers the rock material as an assembly of grains bonded by cement-like materials, and pore spaces. The presence of weakness planes is simulated by the degradation of the bonds between grains along given directions. In general the results of the two approaches are in agreement. However the discrete approach seems to capture more complex phenomena related to local failure in the form of grain detachment at wall of the borehole. In fact the presence of weakness planes in the discontinuous medium leads to local instability along the weak planes also in conditions not predicted from the continuous solution. In general slip failure locations and directions do not follow the conventional wellbore breakout direction but depend upon the internal friction angle and the orientation of the bedding planes. When weakness plane is at 0° and 90° the behaviour are similar to that of a continuous rock material, but borehole instability is more severe when weakness planes are inclined at an angle between 0° and 90° to the horizontal. In conclusion, the results of the numerical simulations show that the prediction of local failure at the wall of the wellbore cannot disregard the presence of weakness planes and consequently the higher mud weight required for stability for any specific inclination of the joints. Despite the discrete approach can simulate smaller areas because of the large number of particles required for the generation of the rock material, however it seems to investigate more correctly the occurrence of failure at the miscroscale and eventually the propagation of the failed zone to a large portion of rock around the wellbore.

Keywords: continuous- discontinuous, numerical modelling, weakness planes wellbore, FLAC 2D

Procedia PDF Downloads 477

Authors: Vladimir Messerle, Alfred Mosse, Alexandr Ustimenko, Oleg Lavrichshev

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Hygiene and sanitary study of typical medical-biological waste made in Kazakhstan, Russia, Belarus and other countries show that their risk to the environment is much higher than that of most chemical wastes. For example, toxicity of solid waste (SW) containing cytotoxic drugs and antibiotics is comparable to toxicity of radioactive waste of high and medium level activity. This report presents the results of the thermodynamic analysis of thermal processing of SW and experiments at the developed plasma unit for SW processing. Thermodynamic calculations showed that the maximum yield of the synthesis gas at plasma gasification of SW in air and steam mediums is achieved at a temperature of 1600K. At the air plasma gasification of SW high-calorific synthesis gas with a concentration of 82.4% (СO – 31.7%, H2 – 50.7%) can be obtained, and at the steam plasma gasification – with a concentration of 94.5% (СO – 33.6%, H2 – 60.9%). Specific heat of combustion of the synthesis gas produced by air gasification amounts to 14267 kJ/kg, while by steam gasification - 19414 kJ/kg. At the optimal temperature (1600 K), the specific power consumption for air gasification of SW constitutes 1.92 kWh/kg, while for steam gasification - 2.44 kWh/kg. Experimental study was carried out in a plasma reactor. This is device of periodic action. The arc plasma torch of 70 kW electric power is used for SW processing. Consumption of SW was 30 kg/h. Flow of plasma-forming air was 12 kg/h. Under the influence of air plasma flame weight average temperature in the chamber reaches 1800 K. Gaseous products are taken out of the reactor into the flue gas cooling unit, and the condensed products accumulate in the slag formation zone. The cooled gaseous products enter the gas purification unit, after which via gas sampling system is supplied to the analyzer. Ventilation system provides a negative pressure in the reactor up to 10 mm of water column. Condensed products of SW processing are removed from the reactor after its stopping. By the results of experiments on SW plasma gasification the reactor operating conditions were determined, the exhaust gas analysis was performed and the residual carbon content in the slag was determined. Gas analysis showed the following composition of the gas at the exit of gas purification unit, (vol.%): СO – 26.5, H2 – 44.6, N2–28.9. The total concentration of the syngas was 71.1%, which agreed well with the thermodynamic calculations. The discrepancy between experiment and calculation by the yield of the target syngas did not exceed 16%. Specific power consumption for SW gasification in the plasma reactor according to the results of experiments amounted to 2.25 kWh/kg of working substance. No harmful impurities were found in both gas and condensed products of SW plasma gasification. Comparison of experimental results and calculations showed good agreement. Acknowledgement—This work was supported by Ministry of Education and Science of the Republic of Kazakhstan and Ministry of Education and Science of the Russian Federation (Agreement on grant No. 14.607.21.0118, project RFMEF160715X0118).

Keywords: coal, efficiency, ignition, numerical modeling, plasma-fuel system, plasma generator

Procedia PDF Downloads 232

Authors: Aleksandra Dudkowska, Gabriela Gic-Grusza

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Wind wave-induced sediment transport is an important multidimensional and multiscale dynamic process affecting coastal seabed changes and coastline evolution. The knowledge about sediment transport rate is important to solve many environmental and geotechnical issues. There are many types of sediment transport models but none of them is widely accepted. It is bacause the process is not fully defined. Another problem is a lack of sufficient measurment data to verify proposed hypothesis. There are different types of models for longshore sediment transport (LST, which is discussed in this work) and cross-shore transport which is related to different time and space scales of the processes. There are models describing bed-load transport (discussed in this work), suspended and total sediment transport. LST models use among the others the information about (i) the flow velocity near the bottom, which in case of wave-currents interaction in coastal zone is a separate problem (ii) critical bed shear stress that strongly depends on the type of sediment and complicates in the case of heterogeneous sediment. Moreover, LST rate is strongly dependant on the local environmental conditions. To organize existing knowledge a series of sediment transport models intercomparisons was carried out as a part of the project “Development of a predictive model of morphodynamic changes in the coastal zone”. Four classical one-grid-point models were studied and intercompared over wide range of bottom shear stress conditions, corresponding with wind-waves conditions appropriate for coastal zone in polish marine areas. The set of models comprises classical theories that assume simplified influence of turbulence on the sediment transport (Du Boys, Meyer-Peter & Muller, Ribberink, Engelund & Hansen). It turned out that the values of estimated longshore instantaneous mass sediment transport are in general in agreement with earlier studies and measurements conducted in the area of interest. However, none of the formulas really stands out from the rest as being particularly suitable for the test location over the whole analyzed flow velocity range. Therefore, based on the models discussed a new unified formula for longshore sediment transport rate estimation is introduced, which constitutes the main original result of this study. Sediment transport rate is calculated based on the bed shear stress and critical bed shear stress. The dependence of environmental conditions is expressed by one coefficient (in a form of constant or function) thus the model presented can be quite easily adjusted to the local conditions. The discussion of the importance of each model parameter for specific velocity ranges is carried out. Moreover, it is shown that the value of near-bottom flow velocity is the main determinant of longshore bed-load in storm conditions. Thus, the accuracy of the results depends less on the sediment transport model itself and more on the appropriate modeling of the near-bottom velocities.

Keywords: bedload transport, longshore sediment transport, sediment transport models, coastal zone

Procedia PDF Downloads 367

Authors: Yi Wang, Greg Hearn, Terry Flew

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In order to understand how cultural innovation occurs, this paper explores the interaction in Shenzhen of China between universities, creative industries, and government in creative economic using the Triple Helix framework. During the past two decades, Triple Helix has been recognized as a new theory of innovation to inform and guide policy-making in national and regional development. Universities and governments around the world, especially in developing countries, have taken actions to strengthen connections with creative industries to develop regional economies. To date research based on the Triple Helix model has focused primarily on Science and Technology collaborations, largely ignoring other fields. Hence, there is an opportunity for work to be done in seeking to better understand how the Triple Helix framework might apply in the field of creative industries and what knowledge might be gleaned from such an undertaking. Since the late 1990s, the concept of ‘creative industries’ has been introduced as policy and academic discourse. The development of creative industries policy by city agencies has improved city wealth creation and economic capital. It claims to generate a ‘new economy’ of enterprise dynamics and activities for urban renewal through the arts and digital media, via knowledge transfer in knowledge-based economies. Creative industries also involve commercial inputs to the creative economy, to dynamically reshape the city into an innovative culture. In particular, this paper will concentrate on creative spaces (incubators, digital tech parks, maker spaces, art hubs) where academic, industry and government interact. China has sought to enhance the brand of their manufacturing industry in cultural policy. It aims to transfer the image of ‘Made in China’ to ‘Created in China’ as well as to give Chinese brands more international competitiveness in a global economy. Shenzhen is a notable example in China as an international knowledge-based city following this path. In 2009, the Shenzhen Municipal Government proposed the city slogan ‘Build a Leading Cultural City”’ to show the ambition of government’s strong will to develop Shenzhen’s cultural capacity and creativity. The vision of Shenzhen is to become a cultural innovation center, a regional cultural center and an international cultural city. However, there has been a lack of attention to the triple helix interactions in the creative industries in China. In particular, there is limited knowledge about how interactions in creative spaces co-location within triple helix networks significantly influence city based innovation. That is, the roles of participating institutions need to be better understood. Thus, this paper discusses the interplay between university, creative industries and government in Shenzhen. Secondary analysis and documentary analysis will be used as methods in an effort to practically ground and illustrate this theoretical framework. Furthermore, this paper explores how are creative spaces being used to implement Triple Helix in creative industries. In particular, the new combination of resources generated from the synthesized consolidation and interactions through the institutions. This study will thus provide an innovative lens to understand the components, relationships and functions that exist within creative spaces by applying Triple Helix framework to the creative industries.

Keywords: cultural policy, creative industries, creative city, triple Helix

Procedia PDF Downloads 174

Authors: Marielcio Lacerda, Angelo Paulino, Elcio Shiguemori, Alvaro Damiao, Lamartine Guimaraes, Camila Anjos

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Accurate information about the terrain is extremely important in disaster management activities or conflict. This paper proposes the use of the Unmanned Aircraft Systems (UAS) at the identification of Airdrop Zones (AZs) and Helicopter Landing Zones (HLZs). In this paper we consider the AZs the zones where troops or supplies are dropped by parachute, and HLZs areas where victims can be rescued. The use of digital image processing enables the automatic generation of an orthorectified mosaic and an actual Digital Surface Model (DSM). This methodology allows obtaining this fundamental information to the terrain’s comprehension post-disaster in a short amount of time and with good accuracy. In order to get the identification and classification of AZs and HLZs images from DJI drone, model Phantom 4 have been used. The images were obtained with the knowledge and authorization of the responsible sectors and were duly registered in the control agencies. The flight was performed on May 24, 2017, and approximately 1,300 images were obtained during approximately 1 hour of flight. Afterward, new attributes were generated by Feature Extraction (FE) from the original images. The use of multispectral images and complementary attributes generated independently from them increases the accuracy of classification. The attributes of this work include the Declivity Map and Principal Component Analysis (PCA). For the classification four distinct classes were considered: HLZ 1 – small size (18m x 18m); HLZ 2 – medium size (23m x 23m); HLZ 3 – large size (28m x 28m); AZ (100m x 100m). The Decision Tree method Random Forest (RF) was used in this work. RF is a classification method that uses a large collection of de-correlated decision trees. Different random sets of samples are used as sampled objects. The results of classification from each tree and for each object is called a class vote. The resulting classification is decided by a majority of class votes. In this case, we used 200 trees for the execution of RF in the software WEKA 3.8. The classification result was visualized on QGIS Desktop 2.12.3. Through the methodology used, it was possible to classify in the study area: 6 areas as HLZ 1, 6 areas as HLZ 2, 4 areas as HLZ 3; and 2 areas as AZ. It should be noted that an area classified as AZ covers the classifications of the other classes, and may be used as AZ, HLZ of large size (HLZ3), medium size (HLZ2) and small size helicopters (HLZ1). Likewise, an area classified as HLZ for large rotary wing aircraft (HLZ3) covers the smaller area classifications, and so on. It was concluded that images obtained through small UAV are of great use in calamity situations since they can provide data with high accuracy, with low cost, low risk and ease and agility in obtaining aerial photographs. This allows the generation, in a short time, of information about the features of the terrain in order to serve as an important decision support tool.

Keywords: disaster management, unmanned aircraft systems, helicopter landing zones, airdrop zones, random forest

Procedia PDF Downloads 151

Authors: Zongyan Yang, Gagan K. Jena, Sankar B. Karanam, Noora M. A. Hokal

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Jumeirah First beach, a segment of coastline of length 1.5 km, is one of the popular public beaches in Dubai, UAE. The stability of the beach has been affected by several coastal developmental projects, including The World, Island 2 and La Mer. A comprehensive stabilization scheme comprising of two composite groynes (of lengths 90 m and 125m), modification to the northern breakwater of Jumeirah Fishing Harbour and beach re-nourishment was implemented by Dubai Municipality in 2012. However, the performance of the implemented stabilization scheme has been compromised by La Mer project (built in 2016), which modified the wave climate at the Jumeirah First beach. The objective of the coastal modelling studies is to establish design basis for further beach stabilization scheme(s). Comprehensive coastal modelling studies had been conducted to establish the nearshore wave climate, equilibrium beach orientations and stable beach plan forms. Based on the outcomes of the modeling studies, recommendation had been made to extend the composite groynes to stabilize the Jumeirah First beach. Wave transformation was performed following an interpolation approach with wave transformation matrixes derived from simulations of a possible range of wave conditions in the region. The Dubai coastal wave model is developed with MIKE21 SW. The offshore wave conditions were determined from PERGOS wave data at 4 offshore locations with consideration of the spatial variation. The lateral boundary conditions corresponding to the offshore conditions, at Dubai/Abu Dhabi and Dubai Sharjah borders, were derived with application of LitDrift 1D wave transformation module. The Dubai coastal wave model was calibrated with wave records at monitoring stations operated by Dubai Municipality. The wave transformation matrix approach was validated with nearshore wave measurement at a Dubai Municipality monitoring station in the vicinity of the Jumeirah First beach. One typical year wave time series was transformed to 7 locations in front of the beach to count for the variation of wave conditions which are affected by adjacent and offshore developments. Equilibrium beach orientations were estimated with application of LitDrift by finding the beach orientations with null annual littoral transport at the 7 selected locations. The littoral transport calculation results were compared with beach erosion/accretion quantities estimated from the beach monitoring program (twice a year including bathymetric and topographical surveys). An innovative integral method was developed to outline the stable beach plan forms from the estimated equilibrium beach orientations, with predetermined minimum beach width. The optimal lengths for the composite groyne extensions were recommended based on the stable beach plan forms.

Keywords: composite groyne, equilibrium beach orientation, stable beach plan form, wave transformation matrix

Procedia PDF Downloads 228

Authors: Masoud Fathi Kazerouni, Jens Schlemper, Klaus-Dieter Kuhnert

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Green planet is one of the Earth’s names which is known as a terrestrial planet and also can be named the fifth largest planet of the solar system as another scientific interpretation. Plants do not have a constant and steady distribution all around the world, and even plant species’ variations are not the same in one specific region. Presence of plants is not only limited to one field like botany; they exist in different fields such as literature and mythology and they hold useful and inestimable historical records. No one can imagine the world without oxygen which is produced mostly by plants. Their influences become more manifest since no other live species can exist on earth without plants as they form the basic food staples too. Regulation of water cycle and oxygen production are the other roles of plants. The roles affect environment and climate. Plants are the main components of agricultural activities. Many countries benefit from these activities. Therefore, plants have impacts on political and economic situations and future of countries. Due to importance of plants and their roles, study of plants is essential in various fields. Consideration of their different applications leads to focus on details of them too. Automatic recognition of plants is a novel field to contribute other researches and future of studies. Moreover, plants can survive their life in different places and regions by means of adaptations. Therefore, adaptations are their special factors to help them in hard life situations. Weather condition is one of the parameters which affect plants life and their existence in one area. Recognition of plants in different weather conditions is a new window of research in the field. Only natural images are usable to consider weather conditions as new factors. Thus, it will be a generalized and useful system. In order to have a general system, distance from the camera to plants is considered as another factor. The other considered factor is change of light intensity in environment as it changes during the day. Adding these factors leads to a huge challenge to invent an accurate and secure system. Development of an efficient plant recognition system is essential and effective. One important component of plant is leaf which can be used to implement automatic systems for plant recognition without any human interface and interaction. Due to the nature of used images, characteristic investigation of plants is done. Leaves of plants are the first characteristics to select as trusty parts. Four different plant species are specified for the goal to classify them with an accurate system. The current paper is devoted to principal directions of the proposed methods and implemented system, image dataset, and results. The procedure of algorithm and classification is explained in details. First steps, feature detection and description of visual information, are outperformed by using Scale invariant feature transform (SIFT), HARRIS-SIFT, and FAST-SIFT methods. The accuracy of the implemented methods is computed. In addition to comparison, robustness and efficiency of results in different conditions are investigated and explained.

Keywords: SIFT combination, feature extraction, feature detection, natural images, natural plant recognition, HARRIS-SIFT, FAST-SIFT

Procedia PDF Downloads 247

Authors: Diana Mitova, Krassimir Mitrev

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To prepare the current generation for the future, education systems need to change. It implies a way of learning that meets the demands of the times and the environment in which we live. Productive interaction in the educational process implies an interactive learning environment and the possibility of personal development of learners based on communication and mutual dialogue, cooperation and good partnership in decision-making. Students need not only theoretical knowledge, but transferable skills that will help them to become inventors and entrepreneurs, to implement ideas. STEM education , is now a real necessity for the modern school. Through learning in a "learning company", students master examples from classroom practice, simulate real life situations, group activities and apply basic interactive learning strategies and techniques. The learning company is the subject of this study, reduced to entrepreneurship training in STEM - technologies that encourage students to think outside the traditional box. STEM learning focuses the teacher's efforts on modeling entrepreneurial thinking and behavior in students and helping them solve problems in the world of business and entrepreneurship. Learning based on the implementation of various STEM projects in extracurricular activities, experiential learning, and an interdisciplinary approach are means by which educators better connect the local community and private businesses. Learners learn to be creative, experiment and take risks and work in teams - the leading characteristics of any innovator and future entrepreneur. This article presents some European policies on STEM and entrepreneurship education. It also shares best practices for training company training , with the integration of STEM in the learning company training environment. The main results boil down to identifying some advantages and problems in STEM entrepreneurship education. The benefits of using integrative approaches to teach STEM within a training company are identified, as well as the positive effects of project-based learning in a training company using STEM. Best practices for teaching entrepreneurship through extracurricular activities using STEM within a training company are shared. The following research methods are applied in this research paper: Theoretical and comparative analysis of principles and policies of European Union countries and Bulgaria in the field of entrepreneurship education through a training company. Experiences in entrepreneurship education through extracurricular activities with STEM application within a training company are shared. A questionnaire survey to investigate the motivation of secondary vocational school students to learn entrepreneurship through a training company and their readiness to start their own business after completing their education. Within the framework of learning through a "learning company" with the integration of STEM, the activity of the teacher-facilitator includes the methods: counseling, supervising and advising students during work. The expectation is that students acquire the key competence "initiative and entrepreneurship" and that the cooperation between the vocational education system and the business in Bulgaria is more effective.

Keywords: STEM, entrepreneurship, training company, extracurricular activities

Procedia PDF Downloads 77

Authors: C.Ardil

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Open Science translates the understanding and application of various theories and practices in open science philosophy, systems, paradigms and epistemology. Open Science originates with the premise that universal scientific knowledge is a product of a collective scholarly and social collaboration involving all stakeholders and knowledge belongs to the global society. Scientific outputs generated by public research are a public good that should be available to all at no cost and without barriers or restrictions. Open Science has the potential to increase the quality, impact and benefits of science and to accelerate advancement of knowledge by making it more reliable, more efficient and accurate, better understandable by society and responsive to societal challenges, and has the potential to enable growth and innovation through reuse of scientific results by all stakeholders at all levels of society, and ultimately contribute to growth and competitiveness of global society. Open Science is a global movement to improve accessibility to and reusability of research practices and outputs. In its broadest definition, it encompasses open access to publications, open research data and methods, open source, open educational resources, open evaluation, and citizen science. The implementation of open science provides an excellent opportunity to renegotiate the social roles and responsibilities of publicly funded research and to rethink the science system as a whole. Open Science is the practice of science in such a way that others can collaborate and contribute, where research data, lab notes and other research processes are freely available, under terms that enable reuse, redistribution and reproduction of the research and its underlying data and methods. Open Science represents a novel systematic approach to the scientific process, shifting from the standard practices of publishing research results in scientific publications towards sharing and using all available knowledge at an earlier stage in the research process, based on cooperative work and diffusing scholarly knowledge with no barriers and restrictions. Open Science refers to efforts to make the primary outputs of publicly funded research results (publications and the research data) publicly accessible in digital format with no limitations. Open Science is about extending the principles of openness to the whole research cycle, fostering, sharing and collaboration as early as possible, thus entailing a systemic change to the way science and research is done. Open Science is the ongoing transition in how open research is carried out, disseminated, deployed, and transformed to make scholarly research more open, global, collaborative, creative and closer to society. Open Science involves various movements aiming to remove the barriers for sharing any kind of output, resources, methods or tools, at any stage of the research process. Open Science embraces open access to publications, research data, source software, collaboration, peer review, notebooks, educational resources, monographs, citizen science, or research crowdfunding. The recognition and adoption of open science practices, including open science policies that increase open access to scientific literature and encourage data and code sharing, is increasing in the open science philosophy. Revolutionary open science policies are motivated by ethical, moral or utilitarian arguments, such as the right to access digital research literature for open source research or science data accumulation, research indicators, transparency in the field of academic practice, and reproducibility. Open science philosophy is adopted primarily to demonstrate the benefits of open science practices. Researchers use open science applications for their own advantage in order to get more offers, increase citations, attract media attention, potential collaborators, career opportunities, donations and funding opportunities. In open science philosophy, open data findings are evidence that open science practices provide significant benefits to researchers in scientific research creation, collaboration, communication, and evaluation according to more traditional closed science practices. Open science considers concerns such as the rigor of peer review, common research facts such as financing and career development, and the sacrifice of author rights. Therefore, researchers are recommended to implement open science research within the framework of existing academic evaluation and incentives. As a result, open science research issues are addressed in the areas of publishing, financing, collaboration, resource management and sharing, career development, discussion of open science questions and conclusions.

Keywords: Open Science, Open Science Philosophy, Open Science Research, Open Science Data

Procedia PDF Downloads 107

Authors: Zhuang Ma, Zihan Zhang, Yu Li

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Environmental concerns from stakeholders (e.g., governments & customers) have pushed firms to integrate environmental management systems into business processes such as R&D, manufacturing, and marketing. Environmental systems include managing environmental risks and pollution control (e.g., air pollution control, waste-water treatment, noise control, energy recycling & solid waste treatment) through raw material management, the elimination and reduction of contaminants, recycling, and reuse in firms' operational processes. Despite increasing studies on firms' proactive adoption of environmental management, their focus is primarily on large corporations operating in developed economies. Investigations in the environmental management efforts of small and medium-sized enterprises (SMEs) are scarce. This is problematic for SMEs because, unlike large corporations, SMEs have limited awareness, resources, capabilities to adapt their operational routines to address environmental impacts. The purpose of this study is to explore how SMEs develop organizational capabilities through interactions with business partners (e.g., environmental management specialists & customers). Drawing on the resource-based view (RBV) and an organizational capabilities perspective, this study investigates the interactively developed capabilities that allow SMEs to adopt environmental management systems. Using an exploratory approach, the study includes 12 semi-structured interviews with senior managers from four SMEs, two environmental management specialists, and two customers in the pharmaceutical sector in Chongqing, China. Findings of this study include four key organizational capabilities: 1) ‘dynamic marketing’ capability, which allows SMEs to recoup the investments in environmental management systems by developing environmentally friendly products to address customers' ever-changing needs; 2) ‘process improvement’ capability, which allows SMEs to select and adopt the latest technologies from biology, chemistry, new material, and new energy sectors into the production system for improved environmental performance and cost-reductions; and 3) ‘relationship management’ capability which allows SMEs to improve corporate image among the public, social media, government agencies, and customers, who in turn help SMEs to overcome their competitive disadvantages. These interactively developed capabilities help SMEs to address larger competitors' foothold in the local market, reduce market constraints, and exploit competitive advantages in other regions (e.g., Guangdong & Jiangsu) of China. These findings extend the RBV and organizational capabilities perspective; that is, SMEs can develop the essential resources and capabilities required for environmental management through interactions with upstream and downstream business partners. While a limited number of studies did highlight the importance of interactions among SMEs, customers, suppliers, NGOs, industrial associations, and consulting firms, they failed to explore the specific capabilities developed through these interactions. Additionally, the findings can explain how a proactive adoption of environmental management systems could help some SMEs to overcome the institutional and market restraints on their products, thereby springboarding into larger, more environmentally demanding, yet more profitable markets compared with their existing market.

Keywords: capabilities, environmental management systems, interactions, SMEs

Procedia PDF Downloads 143

Authors: Ruth Goldschmidt, Vyacheslav Kalchenko, Lilah Agemy, Rachel Elmoalem, Avigdor Scherz

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Vascular Targeted Photodynamic therapy (VTP) is a new modality for selective cancer treatment that leads to the complete tumor ablation. A photosensitizer, a bacteriochlorophyll derivative in our case, is first administered to the patient and followed by the illumination of the tumor area, by a near-IR laser for its photoactivation. The photoactivated drug releases reactive oxygen species (ROS) in the circulation, which reacts with blood cells and the endothelium leading to the occlusion of the blood vasculature. If the blood vessels are only partially closed, the tumor may recover, and cancer cells could survive. On the other hand, excessive treatment may lead to toxicity of healthy tissues nearby. Simultaneous VTP monitoring and image processing independent of the photoexcitation laser has not yet been reported, to our knowledge. Here we present a method for blood flow monitoring, using a real-time laser speckle imaging (RTLSI) in the tumor during VTP. We have synthesized over the years a library of bacteriochlorophyll derivatives, among them WST11 and STL-6014. Both are water soluble derivatives that are retained in the blood vasculature through their partial binding to HSA. WST11 has been approved in Mexico for VTP treatment of prostate cancer at a certain drug dose, and time/intensity of illumination. Application to other bacteriochlorophyll derivatives or other cancers may require different treatment parameters (such as light/drug administration). VTP parameters for STL-6014 are still under study. This new derivative mainly differs from WST11 by its lack of the central Palladium, and its conjugation to an Arg-Gly-Asp (RGD) sequence. RGD is a tumor-specific ligand that is used for targeting the necrotic tumor domains through its affinity to αVβ3 integrin receptors. This enables the study of cell-targeted VTP. We developed a special RTLSI module, based on Labview software environment for data processing. The new module enables to acquire raw laser speckle images and calculate the values of the laser temporal statistics of time-integrated speckles in real time, without additional off-line processing. Using RTLSI, we could monitor the tumor’s blood flow following VTP in a CT26 colon carcinoma ear model. VTP with WST11 induced an immediate slow down of the blood flow within the tumor and a complete final flow arrest, after some sporadic reperfusions. If the irradiation continued further, the blood flow stopped also in the blood vessels of the surrounding healthy tissue. This emphasizes the significance of light dose control. Using our RTLSI system, we could prevent any additional healthy tissue damage by controlling the illumination time and restrict blood flow arrest within the tumor only. In addition, we found that VTP with STL-6014 was the most effective when the photoactivation was conducted 4h post-injection, in terms of tumor ablation success in-vivo and blood vessel flow arrest. In conclusion, RTSLI application should allow to optimize VTP efficacy vs. toxicity in both the preclinical and clinical arenas.

Keywords: blood vessel occlusion, cancer treatment, photodynamic therapy, real time imaging

Procedia PDF Downloads 198

Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

Procedia PDF Downloads 112