Search results for: fault detection and identification
Commenced in January 2007
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Edition: International
Paper Count: 6281

Search results for: fault detection and identification

1151 Cytotoxicity of 13 South African Macrofungal Species and Mechanism/s of Action against Cancer Cell Lines

Authors: Gerhardt Boukes, Maryna Van De Venter, Sharlene Govender

Abstract:

Macrofungi have been used for the past two thousand years in Asian countries, and more recently in Western countries, for their medicinal properties. Biological activities include antimicrobial, antioxidant, anti-inflammatory, antidiabetic, anticancer and immunomodulatory to name a few. Several biologically active compounds have been identified and isolated. Macrofungal research in Africa is poorly documented and to the best of our knowledge non-existent. South Africa has a rich macrofungal biodiversity, which includes endemic and exotic macrofungal species. Ethanolic extracts of 13 macrofungal species, including mushrooms, bracket fungi and puffballs, were prepared and screened for cytotoxicity against a panel of seven cell lines, including A549 (human lung adenocarcinoma), HeLa (human cervical adenocarcinoma), HT-29 (human colorectal adenocarcinoma), MCF7 (human breast adenocarcinoma), MIA PaCa-2 (human pancreatic ductal adenocarcinoma), PC-3 (human prostate adenocarcinoma) and Vero (African green monkey kidney epithelial) cells using MTT. Cell lines were chosen according to the most prevalent cancer types affecting males and females in South Africa and globally, and the mutations they contain. Preliminary results have shown that three of the macrofungal genera, i.e. Fomitopsis, Gymnopilus and Pycnoporus, have shown cytotoxic activity, ranging between IC50 ~20 and 200 µg/mL. The molecular mechanism of action contributing to cell death investigated and being investigated include apoptosis (i.e. DNA cell cycle arrest, caspase-3 activation and mitochondrial membrane potential), autophagy (i.e. acridine orange and LC3B staining) and ER stress (i.e. thioflavin T staining and caspase-12) in the presence of melphalan, chloroquine and thapsigargin/tuncamycin as positive controls, respectively. The genus, Pycnoporus, has shown the best cytotoxicity of the three macrofungal genera. Future work will focus on the identification and isolation of novel active compounds and elucidating the mechanism/s of action.

Keywords: cancer, cytotoxicity, macrofungi, mechanism/s of action

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1150 Threat Modeling Methodology for Supporting Industrial Control Systems Device Manufacturers and System Integrators

Authors: Raluca Ana Maria Viziteu, Anna Prudnikova

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Industrial control systems (ICS) have received much attention in recent years due to the convergence of information technology (IT) and operational technology (OT) that has increased the interdependence of safety and security issues to be considered. These issues require ICS-tailored solutions. That led to the need to creation of a methodology for supporting ICS device manufacturers and system integrators in carrying out threat modeling of embedded ICS devices in a way that guarantees the quality of the identified threats and minimizes subjectivity in the threat identification process. To research, the possibility of creating such a methodology, a set of existing standards, regulations, papers, and publications related to threat modeling in the ICS sector and other sectors was reviewed to identify various existing methodologies and methods used in threat modeling. Furthermore, the most popular ones were tested in an exploratory phase on a specific PLC device. The outcome of this exploratory phase has been used as a basis for defining specific characteristics of ICS embedded devices and their deployment scenarios, identifying the factors that introduce subjectivity in the threat modeling process of such devices, and defining metrics for evaluating the minimum quality requirements of identified threats associated to the deployment of the devices in existing infrastructures. Furthermore, the threat modeling methodology was created based on the previous steps' results. The usability of the methodology was evaluated through a set of standardized threat modeling requirements and a standardized comparison method for threat modeling methodologies. The outcomes of these verification methods confirm that the methodology is effective. The full paper includes the outcome of research on different threat modeling methodologies that can be used in OT, their comparison, and the results of implementing each of them in practice on a PLC device. This research is further used to build a threat modeling methodology tailored to OT environments; a detailed description is included. Moreover, the paper includes results of the evaluation of created methodology based on a set of parameters specifically created to rate threat modeling methodologies.

Keywords: device manufacturers, embedded devices, industrial control systems, threat modeling

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1149 Training to Evaluate Creative Activity in a Training Context, Analysis of a Learner Evaluation Model

Authors: Massy Guillaume

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Introduction: The implementation of creativity in educational policies or curricula raises several issues, including the evaluation of creativity and the means to do so. This doctoral research focuses on the appropriation and transposition of creativity assessment models by future teachers. Our objective is to identify the elements of the models that are most transferable to practice in order to improve their implementation in the students' curriculum while seeking to create a new model for assessing creativity in the school environment. Methods: In order to meet our objective, this preliminary quantitative exploratory study by questionnaire was conducted at two points in the participants' training: at the beginning of the training module and throughout the practical work. The population is composed of 40 people of diverse origins with an average age of 26 (s:8,623) years. In order to be as close as possible to our research objective and to test our questionnaires, we set up a pre-test phase during the spring semester of 2022. Results: The results presented focus on aspects of the OECD Creative Competencies Assessment Model. Overall, 72% of participants support the model's focus on skill levels as appropriate for the school context. More specifically, the data indicate that the separation of production and process in the rubric facilitates observation by the assessor. From the point of view of transposing the grid into teaching practice, the participants emphasised that production is easier to plan and observe in students than in the process. This difference is reinforced by a lack of knowledge about certain concepts such as innovation or risktaking in schools. Finally, the qualitative results indicate that the addition of multiple levels of competencies to the OECD rubric would allow for better implementation in the classroom. Conclusion: The identification by the students of the elements allowing the evaluation of creativity in the school environment generates an innovative approach to the training contents. These first data, from the test phase of our research, demonstrate the difficulty that exists between the implementation of an evaluation model in a training program and its potential transposition by future teachers.

Keywords: creativity, evaluation, schooling, training

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1148 Novel Hole-Bar Standard Design and Inter-Comparison for Geometric Errors Identification on Machine-Tool

Authors: F. Viprey, H. Nouira, S. Lavernhe, C. Tournier

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Manufacturing of freeform parts may be achieved on 5-axis machine tools currently considered as a common means of production. In particular, the geometrical quality of the freeform parts depends on the accuracy of the multi-axis structural loop, which is composed of several component assemblies maintaining the relative positioning between the tool and the workpiece. Therefore, to reach high quality of the geometries of the freeform parts the geometric errors of the 5 axis machine should be evaluated and compensated, which leads one to master the deviations between the tool and the workpiece (volumetric accuracy). In this study, a novel hole-bar design was developed and used for the characterization of the geometric errors of a RRTTT 5-axis machine tool. The hole-bar standard design is made of Invar material, selected since it is less sensitive to thermal drift. The proposed design allows once to extract 3 intrinsic parameters: one linear positioning and two straightnesses. These parameters can be obtained by measuring the cylindricity of 12 holes (bores) and 11 cylinders located on a perpendicular plane. By mathematical analysis, twelve 3D points coordinates can be identified and correspond to the intersection of each hole axis with the least square plane passing through two perpendicular neighbour cylinders axes. The hole-bar was calibrated using a precision CMM at LNE traceable the SI meter definition. The reversal technique was applied in order to separate the error forms of the hole bar from the motion errors of the mechanical guiding systems. An inter-comparison was additionally conducted between four NMIs (National Metrology Institutes) within the EMRP IND62: JRP-TIM project. Afterwards, the hole-bar was integrated in RRTTT 5-axis machine tool to identify its volumetric errors. Measurements were carried out in real time and combine raw data acquired by the Renishaw RMP600 touch probe and the linear and rotary encoders. The geometric errors of the 5 axis machine were also evaluated by an accurate laser tracer interferometer system. The results were compared to those obtained with the hole bar.

Keywords: volumetric errors, CMM, 3D hole-bar, inter-comparison

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1147 Milling Simulations with a 3-DOF Flexible Planar Robot

Authors: Hoai Nam Huynh, Edouard Rivière-Lorphèvre, Olivier Verlinden

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Manufacturing technologies are becoming continuously more diversified over the years. The increasing use of robots for various applications such as assembling, painting, welding has also affected the field of machining. Machining robots can deal with larger workspaces than conventional machine-tools at a lower cost and thus represent a very promising alternative for machining applications. Furthermore, their inherent structure ensures them a great flexibility of motion to reach any location on the workpiece with the desired orientation. Nevertheless, machining robots suffer from a lack of stiffness at their joints restricting their use to applications involving low cutting forces especially finishing operations. Vibratory instabilities may also happen while machining and deteriorate the precision leading to scrap parts. Some researchers are therefore concerned with the identification of optimal parameters in robotic machining. This paper continues the development of a virtual robotic machining simulator in order to find optimized cutting parameters in terms of depth of cut or feed per tooth for example. The simulation environment combines an in-house milling routine (DyStaMill) achieving the computation of cutting forces and material removal with an in-house multibody library (EasyDyn) which is used to build a dynamic model of a 3-DOF planar robot with flexible links. The position of the robot end-effector submitted to milling forces is controlled through an inverse kinematics scheme while controlling the position of its joints separately. Each joint is actuated through a servomotor for which the transfer function has been computed in order to tune the corresponding controller. The output results feature the evolution of the cutting forces when the robot structure is deformable or not and the tracking errors of the end-effector. Illustrations of the resulting machined surfaces are also presented. The consideration of the links flexibility has highlighted an increase of the cutting forces magnitude. This proof of concept will aim to enrich the database of results in robotic machining for potential improvements in production.

Keywords: control, milling, multibody, robotic, simulation

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1146 The Integration Process of Non-EU Citizens in Luxembourg: From an Empirical Approach Toward a Theoretical Model

Authors: Angela Odero, Chrysoula Karathanasi, Michèle Baumann

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Integration of foreign communities has been a forefront issue in Luxembourg for some time now. The country’s continued progress depends largely on the successful integration of immigrants. The aim of our study was to analyze factors which intervene in the course of integration of Non-EU citizens through the discourse of Non-EU citizens residing in Luxembourg, who have signed the Welcome and Integration Contract (CAI). The two-year contract offers integration services to assist foreigners in getting settled in the country. Semi-structured focus group discussions with 50 volunteers were held in English, French, Spanish, Serbo-Croatian or Chinese. Participants were asked to talk about their integration experiences. Recorded then transcribed, the transcriptions were analyzed with the help of NVivo 10, a qualitative analysis software. A systematic and reiterative analysis of decomposing and reconstituting was realized through (1) the identification of predetermined categories (difficulties, challenges and integration needs) (2) initial coding – the grouping together of similar ideas (3) axial coding – the regrouping of items from the initial coding in new ways in order to create sub-categories and identify other core dimensions. Our results show that intervening factors include language acquisition, professional career and socio-cultural activities or events. Each of these factors constitutes different components whose weight shifts from person to person and from situation to situation. Connecting these three emergent factors are two elements essential to the success of the immigrant’s integration – the role of time and deliberate effort from the immigrants, the community, and the formal institutions charged with helping immigrants integrate. We propose a theoretical model where the factors described may be classified in terms of how they predispose, facilitate, and / or reinforce the process towards a successful integration. Measures currently in place propose one size fits all programs yet integrative measures which target the family unit and those customized to target groups based on their needs would work best.

Keywords: integration, integration services, non-eu citizens, qualitative analysis, third country nationals

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1145 A Damage Level Assessment Model for Extra High Voltage Transmission Towers

Authors: Huan-Chieh Chiu, Hung-Shuo Wu, Chien-Hao Wang, Yu-Cheng Yang, Ching-Ya Tseng, Joe-Air Jiang

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Power failure resulting from tower collapse due to violent seismic events might bring enormous and inestimable losses. The Chi-Chi earthquake, for example, strongly struck Taiwan and caused huge damage to the power system on September 21, 1999. Nearly 10% of extra high voltage (EHV) transmission towers were damaged in the earthquake. Therefore, seismic hazards of EHV transmission towers should be monitored and evaluated. The ultimate goal of this study is to establish a damage level assessment model for EHV transmission towers. The data of earthquakes provided by Taiwan Central Weather Bureau serve as a reference and then lay the foundation for earthquake simulations and analyses afterward. Some parameters related to the damage level of each point of an EHV tower are simulated and analyzed by the data from monitoring stations once an earthquake occurs. Through the Fourier transform, the seismic wave is then analyzed and transformed into different wave frequencies, and the data would be shown through a response spectrum. With this method, the seismic frequency which damages EHV towers the most is clearly identified. An estimation model is built to determine the damage level caused by a future seismic event. Finally, instead of relying on visual observation done by inspectors, the proposed model can provide a power company with the damage information of a transmission tower. Using the model, manpower required by visual observation can be reduced, and the accuracy of the damage level estimation can be substantially improved. Such a model is greatly useful for health and construction monitoring because of the advantages of long-term evaluation of structural characteristics and long-term damage detection.

Keywords: damage level monitoring, drift ratio, fragility curve, smart grid, transmission tower

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1144 The Computational Psycholinguistic Situational-Fuzzy Self-Controlled Brain and Mind System Under Uncertainty

Authors: Ben Khayut, Lina Fabri, Maya Avikhana

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The models of the modern Artificial Narrow Intelligence (ANI) cannot: a) independently and continuously function without of human intelligence, used for retraining and reprogramming the ANI’s models, and b) think, understand, be conscious, cognize, infer, and more in state of Uncertainty, and changes in situations, and environmental objects. To eliminate these shortcomings and build a new generation of Artificial Intelligence systems, the paper proposes a Conception, Model, and Method of Computational Psycholinguistic Cognitive Situational-Fuzzy Self-Controlled Brain and Mind System (CPCSFSCBMSUU) using a neural network as its computational memory, operating under uncertainty, and activating its functions by perception, identification of real objects, fuzzy situational control, forming images of these objects, modeling their psychological, linguistic, cognitive, and neural values of properties and features, the meanings of which are identified, interpreted, generated, and formed taking into account the identified subject area, using the data, information, knowledge, and images, accumulated in the Memory. The functioning of the CPCSFSCBMSUU is carried out by its subsystems of the: fuzzy situational control of all processes, computational perception, identifying of reactions and actions, Psycholinguistic Cognitive Fuzzy Logical Inference, Decision making, Reasoning, Systems Thinking, Planning, Awareness, Consciousness, Cognition, Intuition, Wisdom, analysis and processing of the psycholinguistic, subject, visual, signal, sound and other objects, accumulation and using the data, information and knowledge in the Memory, communication, and interaction with other computing systems, robots and humans in order of solving the joint tasks. To investigate the functional processes of the proposed system, the principles of Situational Control, Fuzzy Logic, Psycholinguistics, Informatics, and modern possibilities of Data Science were applied. The proposed self-controlled System of Brain and Mind is oriented on use as a plug-in in multilingual subject Applications.

Keywords: computational brain, mind, psycholinguistic, system, under uncertainty

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1143 Behavioral and EEG Reactions in Children during Recognition of Emotionally Colored Sentences That Describe the Choice Situation

Authors: Tuiana A. Aiusheeva, Sergey S. Tamozhnikov, Alexander E. Saprygin, Arina A. Antonenko, Valentina V. Stepanova, Natalia N. Tolstykh, Alexander N. Savostyanov

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Situation of choice is an important condition for the formation of essential character qualities of a child, such as being initiative, responsible, hard-working. We have studied the behavioral and EEG reactions in Russian schoolchildren during recognition of syntactic errors in emotionally colored sentences that describe the choice situation. Twenty healthy children (mean age 9,0±0,3 years, 12 boys, 8 girls) were examined. Forty sentences were selected for the experiment; the half of them contained a syntactic error. The experiment additionally had the hidden condition: 50% of the sentences described the children's own choice and were emotionally colored (positive or negative). The other 50% of the sentences described the forced-choice situation, also with positive or negative coloring. EEG were recorded during execution of error-recognition task. Reaction time and quality of syntactic error detection were chosen as behavioral measures. Event-related spectral perturbation (ERSP) was applied to characterize the oscillatory brain activity of children. There were two time-frequency intervals in EEG reactions: (1) 500-800 ms in the 3-7 Hz frequency range (theta synchronization) and (2) 500-1000 ms in the 8-12 Hz range (alpha desynchronization). We found out that behavioral and brain reactions in child brain during recognition of positive and negative sentences describing forced-choice situation did not have significant differences. Theta synchronization and alpha desynchronization were stronger during recognition of sentences with children's own choice, especially with negative coloring. Also, the quality and execution time of the task were higher for this types of sentences. The results of our study will be useful for improvement of teaching methods and diagnostics of children affective disorders.

Keywords: choice situation, electroencephalogram (EEG), emotionally colored sentences, schoolchildren

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1142 Prevalence of Mycobacterium Tuberculosis Infection and Rifampicin Resistance among Presumptive Tuberculosis Cases Visiting Tuberculosis Clinic of Adare General Hospital, Southern Ethiopia

Authors: Degineh Belachew Andarge, Tariku Lambiyo Anticho, Getamesay Mulatu Jara, Musa Mohammed Ali

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Introduction: Tuberculosis (TB) is a communicable chronic disease causedby Mycobacterium tuberculosis (MTB). About one-third of the world’s population is latently infected with MTB. TB is among the top 10 causes of mortality throughout the globe from a single pathogen. Objective: The aim of this study was to determine the prevalence of tuberculosis,rifampicin-resistant/multidrug-resistant Mycobacterium tuberculosis, and associated factors among presumptive tuberculosis cases attending the tuberculosis clinic of Adare General Hospital located in Hawassa city. Methods: A hospital-based cross-sectional study was conducted among 321 tuberculosis suspected patients from April toJuly 2018. Socio-demographic, environmental, and behavioral data were collected using a structured questionnaire. Sputumspecimens were analyzed using GeneXpert. Data entry was made using Epi info version 7 and analyzed by SPSS version 20. Logistic regression models were used to determine the risk factors. A p-value less than 0.05 was taken as a cut point. Results: In this study, the prevalence of Mycobacterium tuberculosis was 98 (30.5%) with 95% confidence interval (25.5–35.8), and the prevalence of rifampicin-resistant/multidrug-resistantMycobacterium tuberculosis among the 98 Mycobacteriumtuberculosis confirmed cases was 4 (4.1%). The prevalence of rifampicin-resistant/multidrug-resistant Mycobacterium tuberculosisamong the tuberculosis suspected patients was 1.24%. Participants who had a history of treatment with anti-tuberculosisdrugs were more likely to develop rifampicin-resistant/multidrug-resistant Mycobacterium tuberculosis. Conclusions: This study identified relatively high rifampicin-resistant/multidrug-resistant Mycobacterium tuberculosis amongtuberculosis suspected patients in the study area. Early detection of drug-resistant Mycobacterium tuberculosis should be givenenough attention to strengthen the management of tuberculosis cases and improve direct observation therapy short-course and eventually minimize the spread of rifampicin-resistant tuberculosis strain in the community.

Keywords: rifampicin resistance, mycobacterium tuberculosis, risk factors, prevalence of TB

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1141 Computer Modeling and Plant-Wide Dynamic Simulation for Industrial Flare Minimization

Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

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Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

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1140 Food Poisoning (Salmonellosis) as a Public Health Problem Through Consuming the Meat and Eggs of the Carrier Birds

Authors: M.Younus, M. Athar Khan, Asif Adrees

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The present research endeavour was made to investigate the Public Health impact of Salmonellosis through consuming the meat and eggs of the carrier’s birds and to see the prevalence of Salmonella enteritidis and Salmonella typhimurium from poultry feed, poultry meat, and poultry eggs and their role in the chain of transmission of salmonellae to human beings and causing food poisoning. The ultimate objective was to generate data to improve the quality of poultry products and human health awareness. Salmonellosis is one of the most wide spread food borne zoonoses in all the continents of the world. The etiological agents Salmonella enteritidis and Salmonella typhimurium not only produce the disease but during the convalescent phase (after the recovery of disease) remain carriers for indefinite period of time. The carrier state was not only the source of spread of disease with in the poultry but also caused typhoid fever in humans. The chain of transmission started from poultry feed to poultry meat and ultimately to humans as dead end hosts. In this experiment a total number of 200 samples of human stool and blood were collected randomly (100 samples of human stool and 100 samples of human blood) of 100 patients suspected from food poisoning patients from different hospitals of Lahore area for the identification of Salmonella enteritidis and Salmonella typhimurium through PCR method in order to see the public health impact of Salmonellosis through consuming the meat and eggs of the carrier birds. On the average 14 and 10 stool samples were found positive against Salmonella enteritidis and Salmonella typhimurium from each of the 25 patients from each hospital respectively in case of suspected food poisoning patients. Similarly on an average 5% and 6% blood samples were found positive from 25 patients of each hospital respectively. There was a significant difference (P< 0.05) in the sero positivity of stool and blood samples of suspected food poisoning patients as far as Salmonella enteritidis and Salmonella typhimurium was concerned. However there was no significant difference (P<0.05) between the hospitals.

Keywords: salmonella, zoonosis, food, transmission, eggs

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1139 Improving Cell Type Identification of Single Cell Data by Iterative Graph-Based Noise Filtering

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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1138 Milk Yield and Fingerprinting of Beta-Casein Precursor (CSN2) Gene in Some Saudi Camel Breeds

Authors: Amr A. El Hanafy, Yasser M. Saad, Saleh A. Alkarim, Hussein A. Almehdar, Elrashdy M. Redwan

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Camels are substantial providers of transport, milk, sport, meat, shelter, fuel, security and capital in many countries, particularly Saudi Arabia. Identification of animal breeds has progressed rapidly during the last decade. Advanced molecular techniques are playing a significant role in breeding or strain protection laws. On the other hand, fingerprinting of some molecular markers related to some productive traits in farm animals represents most important studies to our knowledge, which aim to conserve these local genetic resources, and to the genetic improvement of such local breeds by selective programs depending on gene markers. Milk records were taken two days in each week from female camels of Majahem, Safara, Wathaha, and Hamara breeds, respectively from different private farms in northern Jeddah, Riyadh and Alwagh governorates and average weekly yields were calculated. DNA sequencing for CSN2 gene was used for evaluating the genetic variations and calculating the genetic distance values among four Saudi camel populations which are Hamra(R), Safra(Y), Wadha(W) and Majaheim(M). In addition, this marker was analyzed for reconstructing the Neighbor joining tree among evaluating camel breeds. In respect to milk yield during winter season, result indicated that average weekly milk yield of Safara camel breed (30.05 Kg/week) is significantly (p < 0.05) lower than the other 3 breeds which ranged from 39.68 for Hamara to 42.42 Kg/week for Majahem, while there are not significant differences between these three breeds. The Neighbor Joining analysis that re-constructed based on DNA variations showed that samples are clustered into two unique clades. The first clade includes Y (from Y4 to Y18) and M (from M1, to M9). On the other hand, the second cluster is including all R (from R1 to R6) and W (from W1 to W6). The genetic distance values were equal 0.0068 (between the groups M&Y and R&W) and equal 0 (within each group).

Keywords: milk yield, beta-casein precursor (CSN2), Saudi camel, molecular markers

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1137 Detection of MspI Polymorphism and SNP of GH Gene in Some Camel Breeds Reared in Egypt

Authors: Sekena H. Abd El-Aziem, Heba A. M. Abd El-Kader, Sally S. Alam, Othman E. Othman

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Growth hormone (GH) is an anabolic hormone synthesized and secreted by the somatotroph cells of the anterior lobe of the pituitary gland in a circadian and pulsatile manner, the pattern of which plays an important role in postnatal longitudinal growth and development, tissue growth, lactation, reproduction as well as protein, lipid and carbohydrate metabolism. The aim of this study was to detect the genetic polymorphism of GH gene in five camel breeds reared in Egypt; Sudany, Somali, Mowaled, Maghrabi and Falahy, using PCR-RFLP technique. Also this work aimed to identify the single nucleotide polymorphism between different genotypes detected in these camel breeds. The amplified fragment of camel GH at 613-bp was digested with the restriction enzyme MspI and the result revealed the presence of three different genotypes; CC, CT and TT in tested breeds and significant differences were recorded in the genotype frequencies between these camel breeds. The result showed that the Maghrabi breed that is classified as a dual purpose camels had higher frequency for allele C (0.75) than those in the other tested four breeds. The sequence analysis declared the presence of a SNP (C→T) at position 264 in the amplified fragment which is responsible for the destruction of the restriction site C^CGG and consequently the appearance of two different alleles C and T. The nucleotide sequences of camel GH alleles T and C were submitted to nucleotide sequences database NCBI/Bankit/GenBank and have accession numbers: KP143517 and KP143518, respectively. It is concluded that only one SNP C→T was detected in GH gene among the five tested camel breeds reared in Egypt and this nucleotide substitution can be used as a marker for the genetic biodiversity between camel breeds reared in Egypt. Also, due to the possible association between allele C and higher growth rate, we can used it in MAS for camels and enter the camels possess this allele in breeding program as a way for enhancement of growth trait in camel breeds reared in Egypt.

Keywords: camel breeds in Egypt, GH, PCR-RFLP, SNPs

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1136 Principal Component Analysis Combined Machine Learning Techniques on Pharmaceutical Samples by Laser Induced Breakdown Spectroscopy

Authors: Kemal Efe Eseller, Göktuğ Yazici

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Laser-induced breakdown spectroscopy (LIBS) is a rapid optical atomic emission spectroscopy which is used for material identification and analysis with the advantages of in-situ analysis, elimination of intensive sample preparation, and micro-destructive properties for the material to be tested. LIBS delivers short pulses of laser beams onto the material in order to create plasma by excitation of the material to a certain threshold. The plasma characteristics, which consist of wavelength value and intensity amplitude, depends on the material and the experiment’s environment. In the present work, medicine samples’ spectrum profiles were obtained via LIBS. Medicine samples’ datasets include two different concentrations for both paracetamol based medicines, namely Aferin and Parafon. The spectrum data of the samples were preprocessed via filling outliers based on quartiles, smoothing spectra to eliminate noise and normalizing both wavelength and intensity axis. Statistical information was obtained and principal component analysis (PCA) was incorporated to both the preprocessed and raw datasets. The machine learning models were set based on two different train-test splits, which were 70% training – 30% test and 80% training – 20% test. Cross-validation was preferred to protect the models against overfitting; thus the sample amount is small. The machine learning results of preprocessed and raw datasets were subjected to comparison for both splits. This is the first time that all supervised machine learning classification algorithms; consisting of Decision Trees, Discriminant, naïve Bayes, Support Vector Machines (SVM), k-NN(k-Nearest Neighbor) Ensemble Learning and Neural Network algorithms; were incorporated to LIBS data of paracetamol based pharmaceutical samples, and their different concentrations on preprocessed and raw dataset in order to observe the effect of preprocessing.

Keywords: machine learning, laser-induced breakdown spectroscopy, medicines, principal component analysis, preprocessing

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1135 Species Distribution and Incidence of Inducible Clindamycin Resistance in Coagulase-Negative Staphylococci Isolated from Blood Cultures of Patients with True Bacteremia in Turkey

Authors: Fatma Koksal Cakirlar, Murat Gunaydin, Nevri̇ye Gonullu, Nuri Kiraz

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During the last few decades, the increasing prevalence of methicillin resistant-CoNS isolates has become a common problem worldwide. Macrolide-lincosamide-streptogramin B (MLSB) antibiotics are effectively used for the treatment of CoNS infections. However, resistance to MLSB antibiotics is prevalent among staphylococci. The aim of this study is to determine species distribution and the incidence of inducible clindamycin resistance in CoNS isolates caused nosocomial bacteremia in our hospital. Between January 2014 and October 2015, a total of 484 coagulase-negative CoNS isolates were isolated from blood samples of patients with true bacteremia who were hospitalized in intensive care units and in other departments of Istanbul University Cerrahpasa Medical Hospital. Blood cultures were analyzed with the BACTEC 9120 system (Becton Dickinson, USA). The identification and antimicrobial resistance of isolates were determined by Phoenix automated system (BD Diagnostic Systems, Sparks, MD). Inducible clindamycin resistance was detected using D-test. The species distribution was as follows: Staphylococcus epidermidis 211 (43%), S. hominis 154 (32%), S. haemolyticus 69 (14%), S. capitis 28 (6%), S. saprophyticus 11 (2%), S. warnerii 7 (1%), S. schleiferi 5 (1%) and S. lugdunensis 1 (0.2%). Resistance to methicillin was detected in 74.6% of CoNS isolates. Methicillin resistance was highest in S.hemoliticus isolates (89%). Resistance rates of CoNS strains to the antibacterial agents, respectively, were as follows: ampicillin 77%, gentamicin 20%, erythromycin 71%, clindamycin 22%, trimethoprim-sulfamethoxazole 45%, ciprofloxacin 52%, tetracycline 34%, rifampicin 20%, daptomycin 0.2% and linezolid 0.2%. None of the strains were resistant to vancomycin and teicoplanin. Fifteen (3%) CoNS isolates were D-test positive, inducible MLSB resistance type (iMLSB-phenotype), 94 (19%) were constitutively resistant (cMLSB -phenotype), and 237 (46,76%) isolates were found D-test negative, indicating truly clindamycin-susceptible MS phenotype (M-phenotype resistance). The incidence of iMLSB-phenotypes was higher in S. epidermidis isolates (4,7%) compared to other CoNS isolates.

Keywords: bacteremia, inducible MLSB resistance phenotype, methicillin-resistant, staphylococci

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1134 Coronin 1C and miR-128A as Potential Diagnostic Biomarkers for Glioblastoma Multiform

Authors: Denis Mustafov, Emmanouil Karteris, Maria Braoudaki

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Glioblastoma multiform (GBM) is a heterogenous primary brain tumour that kills most affected patients. To the authors best knowledge, despite all research efforts there is no early diagnostic biomarker for GBM. MicroRNAs (miRNAs) are short non-coding RNA molecules which are deregulated in many cancers. The aim of this research was to determine miRNAs with a diagnostic impact and to potentially identify promising therapeutic targets for glioblastoma multiform. In silico analysis was performed to identify deregulated miRNAs with diagnostic relevance for glioblastoma. The expression profiles of the chosen miRNAs were then validated in vitro in the human glioblastoma cell lines A172 and U-87MG. Briefly, RNA extraction was carried out using the Trizol method, whilst miRNA extraction was performed using the mirVANA miRNA isolation kit. Quantitative Real-Time Polymerase Chain Reaction was performed to verify their expression. The presence of five target proteins within the A172 cell line was evaluated by Western blotting. The expression of the CORO1C protein within 32 GBM cases was examined via immunohistochemistry. The miRNAs identified in silico included miR-21-5p, miR-34a and miR-128a. These miRNAs were shown to target deregulated GBM genes, such as CDK6, E2F3, BMI1, JAG1, and CORO1C. miR-34a and miR-128a showed low expression profiles in comparison to a control miR-RNU-44 in both GBM cell lines suggesting tumour suppressor properties. Opposing, miR-21-5p demonstrated greater expression indicating that it could potentially function as an oncomiR. Western blotting revealed expression of all five proteins within the A172 cell line. In silico analysis also suggested that CORO1C is a target of miR-128a and miR-34a. Immunohistochemistry demonstrated that 75% of the GBM cases showed moderate to high expression of CORO1C protein. Greater understanding of the deregulated expression of miR-128a and the upregulation of CORO1C in GBM could potentially lead to the identification of a promising diagnostic biomarker signature for glioblastomas.

Keywords: non-coding RNAs, gene expression, brain tumours, immunohistochemistry

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1133 A Novel Study Contrasting Traditional Autopsy with Post-Mortem Computed Tomography in Falls Leading to Death

Authors: Balaji Devanathan, Gokul G., Abilash S., Abhishek Yadav, Sudhir K. Gupta

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Background: As an alternative to the traditional autopsy, a virtual autopsy is carried out using scanning and imaging technologies, mainly post-mortem computed tomography (PMCT). This facility aims to supplement traditional autopsy results and reduce or eliminate internal dissection in subsequent autopsies. For emotional and religious reasons, the deceased's relatives have historically disapproved such interior dissection. The non-invasive, objective, and preservative PMCT is what friends and family would rather have than a traditional autopsy. Additionally, it aids in the examination of the technologies and the benefits and drawbacks of each, demonstrating the significance of contemporary imaging in the field of forensic medicine. Results: One hundred falls resulting in fatalities was analysed by the writers. Before the autopsy, each case underwent a PMCT examination using a 16-slice Multi-Slice CT spiral scanner. By using specialised software, MPR and VR reconstructions were carried out following the capture of the raw images. The accurate detection of fractures in the skull, face bones, clavicle, scapula, and vertebra was better observed in comparison to a routine autopsy. The interpretation of pneumothorax, Pneumoperitoneum, pneumocephalus, and hemosiuns are much enhanced by PMCT than traditional autopsy. Conclusion. It is useful to visualise the skeletal damage in fall from height cases using a virtual autopsy based on PMCT. So, the ideal tool in traumatising patients is a virtual autopsy based on PMCT scans. When assessing trauma victims, PMCT should be viewed as an additional helpful tool to traditional autopsy. This is because it can identify additional bone fractures in body parts that are challenging to examine during autopsy, such as posterior regions, which helps the pathologist reconstruct the victim's life and determine the cause of death.

Keywords: PMCT, fall from height, autopsy, fracture

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1132 Jagiellonian-PET: A Novel TOF-PET Detector Based on Plastic Scintillators

Authors: P. Moskal, T. Bednarski, P. Bialas, E. Czerwinski, A. Gajos, A. Gruntowski, D. Kaminska, L. Kaplon, G. Korcyl, P. Kowalski, T. Kozik, W. Krzemien, E. Kubicz, Sz. Niedzwiecki, M. Palka, L. Raczynski, Z. Rudy, P. Salabura, N. G. Sharma, M. Silarski, A. Slomski, J. Smyrski, A. Strzelecki, A. Wieczorek, W. Wislicki, M. Zielinski, N. Zon

Abstract:

A new concept and results of the performance tests of the TOF-PET detection system developed at the Jagiellonian University will be presented. The novelty of the concept lies in employing long strips of polymer scintillators instead of crystals as detectors of annihilation quanta, and in using predominantly the timing of signals instead of their amplitudes for the reconstruction of Lines-of-Response. The diagnostic chamber consists of plastic scintillator strips readout by pairs of photo multipliers arranged axially around a cylindrical surface. To take advantage of the superior timing properties of plastic scintillators the signals are probed in the voltage domain with the accuracy of 20 ps by a newly developed electronics, and the data are collected by the novel trigger-less and reconfigurable data acquisition system. The hit-position and hit-time are reconstructed by the dedicated reconstruction methods based on the compressing sensing theory and the library of synchronized model signals. The solutions are subject to twelve patent applications. So far a time-of-flight resolution of ~120 ps (sigma) was achieved for a double-strip prototype with 30 cm field-of-view (FOV). It is by more than a factor of two better than TOF resolution achievable in current TOF-PET modalities and at the same time the FOV of 30 cm long prototype is significantly larger with respect to typical commercial PET devices. The Jagiellonian PET (J-PET) detector with plastic scintillators arranged axially possesses also another advantage. Its diagnostic chamber is free of any electronic devices and magnetic materials thus giving unique possibilities of combining J-PET with CT and J-PET with MRI for scanning the same part of a patient at the same time with both methods.

Keywords: PET-CT, PET-MRI, TOF-PET, scintillator

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1131 Enhanced Photocatalytic H₂ Production from H₂S on Metal Modified Cds-Zns Semiconductors

Authors: Maali-Amel Mersel, Lajos Fodor, Otto Horvath

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Photocatalytic H₂ production by H₂S decomposition is regarded to be an environmentally friendly process to produce carbon-free energy through direct solar energy conversion. For this purpose, sulphide-based materials, as photocatalysts, were widely used due to their excellent solar spectrum responses and high photocatalytic activity. The loading of proper co-catalysts that are based on cheap and earth-abundant materials on those semiconductors was shown to play an important role in the improvement of their efficiency. In this research, CdS-ZnS composite was studied because of its controllable band gap and excellent performance for H₂ evolution under visible light irradiation. The effects of the modification of this photocatalyst with different types of materials and the influence of the preparation parameters on its H₂ production activity were investigated. The CdS-ZnS composite with an enhanced photocatalytic activity for H₂ production was synthesized from ammine complexes. Two types of modification were used: compounds of Ni-group metals (NiS, PdS, and Pt) were applied as co-catalyst on the surface of CdS-ZnS semiconductor, while NiS, MnS, CoS, Ag₂S, and CuS were used as a dopant in the bulk of the catalyst. It was found that 0.1% of noble metals didn’t remarkably influence the photocatalytic activity, while the modification with 0.5% of NiS was shown to be more efficient in the bulk than on the surface. The modification with other types of metals results in a decrease of the rate of H₂ production, while the co-doping seems to be more promising. The preparation parameters (such as the amount of ammonia to form the ammine complexes, the order of the preparation steps together with the hydrothermal treatment) were also found to highly influence the rate of H₂ production. SEM, EDS and DRS analyses were made to reveal the structure of the most efficient photocatalysts. Moreover, the detection of the conduction band electron on the surface of the catalyst was also investigated. The excellent photoactivity of the CdS-ZnS catalysts with and without modification encourages further investigations to enhance the hydrogen generation by optimization of the reaction conditions.

Keywords: H₂S, photoactivity, photocatalytic H₂ production, CdS-ZnS

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1130 3D Modeling Approach for Cultural Heritage Structures: The Case of Virgin of Loreto Chapel in Cusco, Peru

Authors: Rony Reátegui, Cesar Chácara, Benjamin Castañeda, Rafael Aguilar

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Nowadays, heritage building information modeling (HBIM) is considered an efficient tool to represent and manage information of cultural heritage (CH). The basis of this tool relies on a 3D model generally obtained from a cloud-to-BIM procedure. There are different methods to create an HBIM model that goes from manual modeling based on the point cloud to the automatic detection of shapes and the creation of objects. The selection of these methods depends on the desired level of development (LOD), level of information (LOI), grade of generation (GOG), as well as on the availability of commercial software. This paper presents the 3D modeling of a stone masonry chapel using Recap Pro, Revit, and Dynamo interface following a three-step methodology. The first step consists of the manual modeling of simple structural (e.g., regular walls, columns, floors, wall openings, etc.) and architectural (e.g., cornices, moldings, and other minor details) elements using the point cloud as reference. Then, Dynamo is used for generative modeling of complex structural elements such as vaults, infills, and domes. Finally, semantic information (e.g., materials, typology, state of conservation, etc.) and pathologies are added within the HBIM model as text parameters and generic models families, respectively. The application of this methodology allows the documentation of CH following a relatively simple to apply process that ensures adequate LOD, LOI, and GOG levels. In addition, the easy implementation of the method as well as the fact of using only one BIM software with its respective plugin for the scan-to-BIM modeling process means that this methodology can be adopted by a larger number of users with intermediate knowledge and limited resources since the BIM software used has a free student license.

Keywords: cloud-to-BIM, cultural heritage, generative modeling, HBIM, parametric modeling, Revit

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1129 Effect of Climate Variability on Children Health Outcomes in Rural Uganda

Authors: Emily Injete Amondo, Alisher Mirzabaev, Emmanuel Rukundo

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Children in rural farming households are often vulnerable to a multitude of risks, including health risks associated with climate change and variability. Cognizant of this, this study empirically traced the relationship between climate variability and nutritional health outcomes in rural children while identifying the cause-and-effect transmission mechanisms. We combined four waves of the rich Uganda National Panel Survey (UNPS), part of the World Bank Living Standards Measurement Studies (LSMS) for the period 2009-2014, with long-term and high-frequency rainfall and temperature datasets. Self-reported drought and flood shock variables were further used in separate regressions for triangulation purposes and robustness checks. Panel fixed effects regressions were applied in the empirical analysis, accounting for a variety of causal identification issues. The results showed significant negative outcomes for children’s anthropometric measurements due to the impacts of moderate and extreme droughts, extreme wet spells, and heatwaves. On the contrary, moderate wet spells were positively linked with nutritional measures. Agricultural production and child diarrhea were the main transmission channels, with heatwaves, droughts, and high rainfall variability negatively affecting crop output. The probability of diarrhea was positively related to increases in temperature and dry spells. Results further revealed that children in households who engaged in ex-ante or anticipatory risk-reducing strategies such as savings had better health outcomes as opposed to those engaged in ex-post coping such as involuntary change of diet. These results highlight the importance of adaptation in smoothing the harmful effects of climate variability on the health of rural households and children in Uganda.

Keywords: extreme weather events, undernutrition, diarrhea, agricultural production, gridded weather data

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1128 3D Microscopy, Image Processing, and Analysis of Lymphangiogenesis in Biological Models

Authors: Thomas Louis, Irina Primac, Florent Morfoisse, Tania Durre, Silvia Blacher, Agnes Noel

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In vitro and in vivo lymphangiogenesis assays are essential for the identification of potential lymphangiogenic agents and the screening of pharmacological inhibitors. In the present study, we analyse three biological models: in vitro lymphatic endothelial cell spheroids, in vivo ear sponge assay, and in vivo lymph node colonisation by tumour cells. These assays provide suitable 3D models to test pro- and anti-lymphangiogenic factors or drugs. 3D images were acquired by confocal laser scanning and light sheet fluorescence microscopy. Virtual scan microscopy followed by 3D reconstruction by image aligning methods was also used to obtain 3D images of whole large sponge and ganglion samples. 3D reconstruction, image segmentation, skeletonisation, and other image processing algorithms are described. Fixed and time-lapse imaging techniques are used to analyse lymphatic endothelial cell spheroids behaviour. The study of cell spatial distribution in spheroid models enables to detect interactions between cells and to identify invasion hierarchy and guidance patterns. Global measurements such as volume, length, and density of lymphatic vessels are measured in both in vivo models. Branching density and tortuosity evaluation are also proposed to determine structure complexity. Those properties combined with vessel spatial distribution are evaluated in order to determine lymphangiogenesis extent. Lymphatic endothelial cell invasion and lymphangiogenesis were evaluated under various experimental conditions. The comparison of these conditions enables to identify lymphangiogenic agents and to better comprehend their roles in the lymphangiogenesis process. The proposed methodology is validated by its application on the three presented models.

Keywords: 3D image segmentation, 3D image skeletonisation, cell invasion, confocal microscopy, ear sponges, light sheet microscopy, lymph nodes, lymphangiogenesis, spheroids

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1127 Road Accident Blackspot Analysis: Development of Decision Criteria for Accident Blackspot Safety Strategies

Authors: Tania Viju, Bimal P., Naseer M. A.

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This study aims to develop a conceptual framework for the decision support system (DSS), that helps the decision-makers to dynamically choose appropriate safety measures for each identified accident blackspot. An accident blackspot is a segment of road where the frequency of accident occurrence is disproportionately greater than other sections on roadways. According to a report by the World Bank, India accounts for the highest, that is, eleven percent of the global death in road accidents with just one percent of the world’s vehicles. Hence in 2015, the Ministry of Road Transport and Highways of India gave prime importance to the rectification of accident blackspots. To enhance road traffic safety and reduce the traffic accident rate, effectively identifying and rectifying accident blackspots is of great importance. This study helps to understand and evaluate the existing methods in accident blackspot identification and prediction that are used around the world and their application in Indian roadways. The decision support system, with the help of IoT, ICT and smart systems, acts as a management and planning tool for the government for employing efficient and cost-effective rectification strategies. In order to develop a decision criterion, several factors in terms of quantitative as well as qualitative data that influence the safety conditions of the road are analyzed. Factors include past accident severity data, occurrence time, light, weather and road conditions, visibility, driver conditions, junction type, land use, road markings and signs, road geometry, etc. The framework conceptualizes decision-making by classifying blackspot stretches based on factors like accident occurrence time, different climatic and road conditions and suggesting mitigation measures based on these identified factors. The decision support system will help the public administration dynamically manage and plan the necessary safety interventions required to enhance the safety of the road network.

Keywords: decision support system, dynamic management, road accident blackspots, road safety

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1126 Between Hope and Despair: Exploring Experiences and Belonging of Return Migrants and Their Children in Albania

Authors: Elida Cena

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Return migration is receiving increased attention as the phenomenon challenges assumptions of natural ‘homecomings’. This talk outlines preliminary findings from an ongoing PhD study which explores return migration of Albanian migrants (aged 30-50 years) and their children (aged 7-18 years). Participants (n=51) were purposively recruited from two Albanian cities with divergent social and economic conditions, and the majority had returned from Greece following the recent economic downturn in that country. Qualitative data were collected through in-depth interviews with respondents aged 13 years and above, and were augmented with focus groups and family case studies. Data collection for case studies was aided by photo elicitation, interviews and participatory techniques (drawing) were employed for children aged 7-12 years. Through a multidisciplinary perspective, findings will uncover experiences of migrants and children upon return, the quest to identify with the originating country and create a sense of belongingness. Narrative analysis reveals that the abrupt return was associated with ambivalent feelings and disillusionment about their (re)settlement for both younger and older participants. Faced with unexpected realities and lack of opportunities, particularly for the children of migrants, Albania is viewed as a ‘transit country’, a temporary solution to escape the crisis in the destination country and move to a more developed western country. Adult return migrants articulate lack of employment and insecurity for the future. Apart from school difficulties, children experience isolation and social exclusion, marked by stigmatized labelling from other peers which exacerbates their belonging. Such mobilities have had deeper effects in complicating family relationships as influenced by many disintegration factors. Feelings of alienation and being emigrant for the second time were common in participants' accounts. Findings concerning the difficulties of individuals (re)connecting with their ethnic background and the impact on their identities are discussed in relation to the literature on return migration and identification.

Keywords: return migration, belonging, identity, disintegration, integration

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1125 Effect of Chemical Modification of Functional Groups on Copper(II) Biosorption by Brown Marine Macroalgae Ascophyllum nodosum

Authors: Luciana P. Mazur, Tatiana A. Pozdniakova, Rui A. R. Boaventura, Vitor J. P. Vilar

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The principal mechanism of metal ions sequestration by brown algae involves the formation of complexes between the metal ion and functional groups present on the cell wall of the biological material. To understand the role of functional groups on copper(II) uptake by Ascophyllum nodosum, some functional groups were chemically modified. The esterification of carboxylic groups was carried out by suspending the biomass in a methanol/HCl solution under stirring for 48 h and the blocking of the sulfonic groups was performed by repeating the same procedure for 4 cycles of 48 h. The methylation of amines was conducted by suspending the biomass in a formaldehyde/formic acid solution under shaking for 6 h and the chemical modification of sulfhydryl groups on the biomass surface was achieved using dithiodipyridine for 1 h. Equilibrium sorption studies for Cu2+ using the raw and esterified algae were performed at pH 2.0 and 4.0. The experiments were performed using an initial copper concentration of 300 mg/L and algae dose of 1.0 g/L. After reaching the equilibrium, the metal in solution was quantified by atomic absorption spectrometry. The biological material was analyzed by Fourier Transform Infrared Spectroscopy and Potentiometric Titration techniques for functional groups identification and quantification, respectively. The results using unmodified algae showed that the maximum copper uptake capacity at pH 4.0 and 2.0 was 1.17 and 0.52 mmol/g, respectively. At acidic pH values most carboxyl groups are protonated and copper sorption suffered a significant reduction of 56%. Blocking the carboxylic, sulfonic, amines and sulfhydryl functional groups, copper uptake decreased by 24/26%, 69/81%, 1/23% and 40/27% at pH 2.0/4.0, respectively, when compared to the unmodified biomass. It was possible to conclude that the carboxylic and sulfonic groups are the main functional groups responsible for copper binding (>80%). This result is supported by the fact that the adsorption capacity is directly related to the presence of carboxylic groups of the alginate polymer, and the second most abundant acidic functional group in brown algae is the sulfonic acid of fucoidan that contributes, to a lower extent, to heavy metal binding, particularly at low pH.

Keywords: biosorption, brown marine macroalgae, copper, ion-exchange

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1124 Management of High Conservation Value Forests (HCVF) in Peninsular Malaysia as Part of Sustainable Forest Management Practices

Authors: Abu Samah Abdul Khalim, Hamzah Khali Aziz

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Tropical forests in Malaysia safeguard enormous biological diversity while providing crucial benefits and services for the sustainable development of human communities. They are highly significant globally, both for their diverse and threatened species and as representative unique ecosystems. In order to promote the conservation and sustainable management of forest in this country, the Forestry Department (FD) is using ITTO guidelines on managing the forest under the Sustainable Forest Management practice (SFM). The fundamental principles of SFM are the sustained provision of products, goods and services; economic viability, social acceptability and the minimization of environmental/ecological impacts. With increased awareness and recognition of the importance of tropical forests and biodiversity in the global environment, efforts have been made to classify forests and natural areas with unique values or properties in a universally accepted scale. In line with that the concept of High Conservation Value Forest (HCVF) first used by the Forest Stewardship Council (FSC) in 1999, has been adopted and included as Principle ‘9’ in the Malaysia Criteria and Indicators for Forest Management Certification (MC&I 2002). The MC&I 2002 is a standard used for assessing forest management practices of the Forest Management Unit (FMU) level for purpose of certification. The key to the concept of HCVF is identification of HCVs of the forest. This paper highlighted initiative taken by the Forestry Department Peninsular Malaysia in establishing and managing HCVF areas within the Permanent Forest Reserves (PFE). To date almost all states forestry department in Peninsular Malaysia have established HCVFs in their respective states under different categories. Among others, the establishments of HCVF in this country are related to the importance of conserving biological diversity of the flora in the natural forest in particular endemic and threatened species such as Shorea bentongensis. As such it is anticipated that by taking this important initiatives, it will promote the conservation of biological diversity in the PFE of Peninsular Malaysia in line with the Sustainable Forest Management practice.

Keywords: high conservation value forest, sustainable forest management, forest management certification, Peninsular Malaysia

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1123 Impacts of Urbanization on Forest and Agriculture Areas in Savannakhet Province, Lao People's Democratic Republic

Authors: Chittana Phompila

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The current increased population pushes increasing demands for natural resources and living space. In Laos, urban areas have been expanding rapidly in recent years. The rapid urbanization can have negative impacts on landscapes, including forest and agriculture lands. The primary objective of this research were to map current urban areas in a large city in Savannakhet province, in Laos, 2) to compare changes in urbanization between 1990 and 2018, and 3) to estimate forest and agriculture areas lost due to expansions of urban areas during the last over twenty years within study area. Landsat 8 data was used and existing GIS data was collected including spatial data on rivers, lakes, roads, vegetated areas and other land use/land covers). GIS data was obtained from the government sectors. Object based classification (OBC) approach was applied in ECognition for image processing and analysis of urban area using. Historical data from other Landsat instruments (Landsat 5 and 7) were used to allow us comparing changes in urbanization in 1990, 2000, 2010 and 2018 in this study area. Only three main land cover classes were focused and classified, namely forest, agriculture and urban areas. Change detection approach was applied to illustrate changes in built-up areas in these periods. Our study shows that the overall accuracy of map was 95% assessed, kappa~ 0.8. It is found that that there is an ineffective control over forest and land-use conversions from forests and agriculture to urban areas in many main cities across the province. A large area of agriculture and forest has been decreased due to this conversion. Uncontrolled urban expansion and inappropriate land use planning can lead to creating a pressure in our resource utilisation. As consequence, it can lead to food insecurity and national economic downturn in a long term.

Keywords: urbanisation, forest cover, agriculture areas, Landsat 8 imagery

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1122 Efficient Video Compression Technique Using Convolutional Neural Networks and Generative Adversarial Network

Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

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