Search results for: evolutional triangle similarity

Authors: Quentin Lobbe, David Chavalarias, Alexandre Delanoe

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The ICT revolution has given birth to an unprecedented world of digital traces and has impacted a wide number of knowledge-driven domains such as science, education or policy making. Nowadays, we are daily fueled by unlimited flows of articles, blogs, messages, tweets, etc. The internet itself can thus be considered as an unsteady hyper-textual environment where websites emerge and expand every day. But there are structures inside knowledge. A given text can always be studied in relation to others or in light of a specific socio-cultural context. By way of their textual traces, human beings are calling each other out: hypertext citations, retweets, vocabulary similarity, etc. We are in fact the architects of a giant web of elements of knowledge whose structures and shapes convey their own information. The global shapes of these digital traces represent a source of collective knowledge and the question of their visualization remains an opened challenge. How can we explore, browse and interact with such shapes? In order to navigate across these growing constellations of words and texts, interdisciplinary innovations are emerging at the crossroad between fields of social and computational sciences. In particular, complex systems approaches make it now possible to reconstruct the hidden structures of textual knowledge by means of multi-scale objects of research such as semantic maps and phylomemies. The phylomemy reconstruction is a generic method related to the co-word analysis framework. Phylomemies aim to reveal the temporal dynamics of large corpora of textual contents by performing inter-temporal matching on extracted knowledge domains in order to identify their conceptual lineages. This study aims to address the question of visualizing the global shapes of online political discussions related to the French presidential and legislative elections of 2017. We aim to build phylomemies on top of a dedicated collection of thousands of French political tweets enriched with archived contemporary news web articles. Our goal is to reconstruct the temporal evolution of online debates fueled by each political community during the elections. To that end, we want to introduce an iterative data exploration methodology implemented and tested within the free software Gargantext. There we combine synchronic and diachronic axis of visualization to reveal the dynamics of our corpora of tweets and web pages as well as their inner syntagmatic and paradigmatic relationships. In doing so, we aim to provide researchers with innovative methodological means to explore online semantic landscapes in a collaborative and reflective way.

Keywords: online political debate, French election, hyper-text, phylomemy

Procedia PDF Downloads 155

Authors: Soumava Boral, Sanjay K. Chaturvedi, Ian Howard, Kristoffer McKee, V. N. A. Naikan

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Due to strict regulations from government to enhance the possibilities of sustainability practices in industries, and noting the advances in sustainable manufacturing practices, it is necessary that the associated processes are also sustainable. Maintenance of large scale and complex machines is a pivotal task to maintain the uninterrupted flow of manufacturing processes. Appropriate maintenance practices can prolong the lifetime of machines, and prevent associated breakdowns, which subsequently reduces different cost heads. Selection of the best maintenance strategies for such machines are considered as a burdensome task, as they require the consideration of multiple technical criteria, complex mathematical calculations, previous fault data, maintenance records, etc. In the era of the fourth industrial revolution, organizations are rapidly changing their way of business, and they are giving their utmost importance to sensor technologies, artificial intelligence, data analytics, automations, etc. In this work, the effectiveness of several maintenance strategies (e.g., preventive, failure-based, reliability centered, condition based, total productive maintenance, etc.) related to a large scale and complex gearbox, operating in a steel processing plant is evaluated in terms of economic, social, environmental and technical criteria. As it is not possible to obtain/describe some criteria by exact numerical values, these criteria are evaluated linguistically by cross-functional experts. Fuzzy sets are potential soft-computing technique, which has been useful to deal with linguistic data and to provide inferences in many complex situations. To prioritize different maintenance practices based on the identified sustainable criteria, multi-criteria decision making (MCDM) approaches can be considered as potential tools. Multi-Attributive Ideal Real Comparative Analysis (MAIRCA) is a recent addition in the MCDM family and has proven its superiority over some well-known MCDM approaches, like TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and ELECTRE (ELimination Et Choix Traduisant la REalité). It has a simple but robust mathematical approach, which is easy to comprehend. On the other side, due to some inherent drawbacks of Intuitionistic Fuzzy Sets (IFS) and Pythagorean Fuzzy Sets (PFS), recently, the use of Fermatean Fuzzy Sets (FFSs) has been proposed. In this work, we propose the novel concept of FF-MAIRCA. We obtain the weights of the criteria by experts’ evaluation and use them to prioritize the different maintenance practices according to their suitability by FF-MAIRCA approach. Finally, a sensitivity analysis is carried out to highlight the robustness of the approach.

Keywords: Fermatean fuzzy sets, Fermatean fuzzy MAIRCA, maintenance strategy selection, sustainable manufacturing, MCDM

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Authors: Nigar Kantarci Carsibasi

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Coarse-grained elastic network models, namely Gaussian network model (GNM) and Anisotropic network model (ANM), are utilized in order to investigate the fluctuation dynamics of Murine Double Minute 2 (MDM2), which is the native inhibitor of p53. Conformational dynamics of MDM2 are elucidated in unbound, p53 bound, and non-peptide small molecule inhibitor bound forms. With this, it is aimed to gain insights about the alterations brought to global dynamics of MDM2 by native peptide inhibitor p53, and two small molecule inhibitors (HDM201 and NVP-CGM097) that are undergoing clinical stages in cancer studies. MDM2 undergoes significant conformational changes upon inhibitor binding, carrying pieces of evidence of induced-fit mechanism. Small molecule inhibitors examined in this work exhibit similar fluctuation dynamics and characteristic mode shapes with p53 when complexed with MDM2, which would shed light on the design of novel small molecule inhibitors for cancer therapy. The results showed that residues Phe 19, Trp 23, Leu 26 reside in the minima of slowest modes of p53, pointing to the accepted three-finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct regions are identified in MDM2, for which significant conformational changes are observed upon binding. Regions I (residues 50-77) and III (residues 90-105) correspond to the binding interface of MDM2, including (α2, L2, and α4), which are stabilized during complex formation. Region II (residues 77-90) exhibits a large amplitude motion, being highly flexible, both in the absence and presence of p53 or other inhibitors. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 domains, clearly distinguishing the kinetically hot regions. Mode shape analysis revealed that the α4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states for proper penetration and binding of p53 and inhibitors, which points to the induced-fit mechanism of p53 binding. P53 interacts with α2 and α4 in a synchronized manner. Collective modes are shifted upon inhibitor binding, i.e., second mode characteristic motion in MDM2-p53 complex is observed in the first mode of apo MDM2; however, apo and bound MDM2 exhibits similar features in the softest modes pointing to pre-existing modes facilitating the ligand binding. Although much higher amplitude motions are attained in the presence of non-peptide small molecule inhibitor molecules as compared to p53, they demonstrate close similarity. Hence, NVP-CGM097 and HDM201 succeed in mimicking the p53 behavior well. Elucidating how drug candidates alter the MDM2 global and conformational dynamics would shed light on the rational design of novel anticancer drugs.

Keywords: cancer, drug design, elastic network model, MDM2

Procedia PDF Downloads 101

Authors: Sami Alanazi

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Teamwork practices have been recognized as a significant strategy to improve patient safety, quality of care, and staff and patient satisfaction in healthcare settings, particularly within the emergency department (ED). The EDs depend heavily on teams of interdisciplinary healthcare staff to carry out their operational goals and core business of providing care to the serious illness and injured. The ED is also recognized as a high-risk area in relation to service demand and the potential for human error. Few studies have considered the perceptions and experiences of the ED staff (physicians, nurses, allied health professionals, and administration staff) about the practice of teamwork, especially in Saudi Arabia (SA), and no studies have been conducted to explore the practices of teamwork in the EDs. Aim: To explore the practices of teamwork from the perspectives and experiences of staff (physicians, nurses, allied health professionals, and administration staff) when interacting with each other in the admission areas in the ED of a public hospital in the Northern Border region of SA. Method: A qualitative case study design was utilized, drawing on two methods for the data collection, comprising of semi-structured interviews (n=22) with physicians (6), nurses (10), allied health professionals (3), and administrative members (3) working in the ED of a hospital in the Northern Border region of SA. The second method is non-participant direct observation. All data were analyzed using thematic analysis. Findings: The main themes that emerged from the analysis were as follows: the meaningful of teamwork, reasons of teamwork, the ED environmental factors, the organizational factors, the value of communication, leadership, teamwork skills in the ED, team members' behaviors, multicultural teamwork, and patients and families behaviors theme. Discussion: Working in the ED environment played a major role in affecting work performance as well as team dynamics. However, Communication, time management, fast-paced performance, multitasking, motivation, leadership, and stress management were highlighted by the participants as fundamental skills that have a major impact on team members and patients in the ED. It was found that the behaviors of the team members impacted the team dynamics as well as ED health services. Behaviors such as disputes among team members, conflict, cooperation, uncooperative members, neglect, and emotions of the members. Besides that, the behaviors of the patients and their accompanies had a direct impact on the team and the quality of the services. In addition, the differences in the cultures have separated the team members and created undesirable gaps such the gender segregation, national origin discrimination, and similarity and different in interests. Conclusion: Effective teamwork, in the context of the emergency department, was recognized as an essential element to obtain the quality of care as well as improve staff satisfaction.

Keywords: teamwork, barrier, facilitator, emergencydepartment

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Authors: Moen Torill, Rismark Marit, Astrid M. Solvberg

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In Norway, every municipality shall provide an educational psychological service, EPS, to support kindergartens and schools in their work with children and youths with special needs. The EPS focus its work on individuals, aiming to identify special needs and to give advice to teachers and parents when they ask for it. In addition, the service also give priority to prevention and system intervention in kindergartens and schools. To master these big tasks university courses are established to support EPS counsellors' continuous learning. There is, however, a need for more in-depth and systematic knowledge on how they experience the courses they attend. In this study, EPS counsellors’ reflection logs during a particular course are investigated. The research question is: what are the content and priorities of the reflections that are communicated in the logs produced by the educational psychological counsellors during a post-graduate course? The investigated course is a credit course organized over a one-year period in two one-semester modules. The altogether 55 students enrolled in the course work as EPS counsellors in various municipalities across Norway. At the end of each day throughout the course period, the participants wrote reflection logs about what they had experienced during the day. The data material consists of 165 pages of typed text. The collaborating researchers studied the data material to ascertain, differentiate and understand the meaning of the content in each log. The analysis also involved the search for similarity in content and development of analytical categories that described the focus and primary concerns in each of the written logs. This involved constant 'critical and sustained discussions' for mutual construction of meaning between the co-researchers in the developing categories. The process is inspired by Grounded Theory. This means that the concepts developed during the analysis derived from the data material and not chosen prior to the investigation. The analysis revealed that the concept 'Useful' frequently appeared in the participants’ reflections and, as such, 'Useful' serves as a core category. The core category is described through three major categories: (1) knowledge sharing (concerning direct and indirect work with students with special needs) with colleagues is useful, (2) reflections on models and theoretical concepts (concerning students with special needs) are useful, (3) reflection on the role as EPS counsellor is useful. In all the categories, the notion of useful occurs in the participants’ emphasis on and acknowledgement of the immediate and direct link between the university course content and their daily work practice. Even if each category has an importance and value of its own, it is crucial that they are understood in connection with one another and as interwoven. It is the connectedness that gives the core category an overarching explanatory power. The knowledge from this study may be a relevant contribution when it comes to designing new courses that support continuing professional development for EPS counsellors, whether for post-graduate university courses or local courses at the EPS offices or whether in Norway or other countries in the world.

Keywords: constructing and circulating knowledge, educational-psychological counsellor, higher education, professional development

Procedia PDF Downloads 88

Authors: M. I. Tyletc, O. I. Podgornya, T. G. Shaposhnikova, S. V. Shabelnikov, A. G. Mittenberg, M. A. Daugavet

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Ascidiacea is the most numerous class of the Tunicata subtype. These chordates' distinctive feature of the anatomical structure is a tunic consisting of cellulose fibrils, protein molecules, and single cells. The mechanisms of the tunic formation are not known in detail; tunic formation could be used as the model system for studying the interaction of cells with the extracellular matrix. Our model species is the ascidian Styela rustica, which is prevalent in benthic communities of the White Sea. As previously shown, the tunic formation involves morula blood cells, which contain the major 48 kDa protein p48. P48 participation in the tunic formation was proved using antibodies against the protein. The nature of the protein and its function remains unknown. The current research aims to determine the amino acid sequence of p48, as well as to clarify its role in the tunic formation. The peptides that make up the p48 amino acid sequence were determined by mass spectrometry. A search for peptides in protein sequence databases identified sequences homologous to p48 in Styela clava, Styela plicata, and Styela canopus. Based on sequence alignment, their level of similarity was determined as 81-87%. The correspondent sequence of ascidian Styela canopus was used for further analysis. The Styela rustica p48 sequence begins with a signal peptide, which could indicate that the protein is secretory. This is consistent with experimentally obtained data: the contents of morula cells secreted in the tunic matrix. The isoelectric point of p48 is 9.77, which is consistent with the experimental results of acid electrophoresis of morula cell proteins. However, the molecular weight of the amino acid sequence of ascidian Styela canopus is 103 kDa, so p48 of Styela rustica is a shorter homolog. The search for conservative functional domains revealed the presence of two Ca-binding EGF-like domains, thrombospondin (TSP1) and tyrosinase domains. The p48 peptides determined by mass spectrometry fall into the region of the sequence corresponding to the last two domains and have amino acid substitutions as compared to Styela canopus homolog. The tyrosinase domain (pfam00264) is known to be part of the phenoloxidase enzyme, which participates in melanization processes and the immune response. The thrombospondin domain (smart00209) interacts with a wide range of proteins, and is involved in several biological processes, including coagulation, cell adhesion, modulation of intercellular and cell-matrix interactions, angiogenesis, wound healing and tissue remodeling. It can be assumed that the tyrosinase domain in p48 plays the role of the phenoloxidase enzyme, and TSP1 provides a link between the extracellular matrix and cell surface receptors, and may also be responsible for the repair of the tunic. The results obtained are consistent with experimental data on p48. The domain organization of protein suggests that p48 is an enzyme involved in the tunic tunning and is an important regulator of the organization of the extracellular matrix.

Keywords: ascidian, p48, thrombospondin, tyrosinase, tunic, tunning

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Authors: Michelle S. Pereira, Analice C. Azevedo, Julliane D. Medeiros, Ana Claudia S. Martins, Didier S. Castellano-Filho, Claudio G. Diniz, Vania L. Silva

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Vaginal microbiota is a complex ecosystem, composed by aerobic and anaerobic bacteria, living in a dynamic equilibrium. Lactobacillus spp. are predominant in vaginal ecosystem, and factors such as immunity and hormonal variations may lead to disruptions, resulting in proliferation of opportunistic pathogens. Bacterial vaginosis (BV) is a polymicrobial syndrome, caused by an increasing of anaerobic bacteria replacing Lactobacillus spp. Microorganisms such as Gardnerella vaginalis, Mycoplasma hominis, Mobiluncus spp., and Atopobium vaginae can be found in BV, which may also be associated to other infections such as by Human Papillomavirus (HPV). HPV is highly prevalent in sexually active women, and is considered a risk factor for development of cervical cancer. As long as few data is available on vaginal microbiota of women with HPV-associated cervical lesions, our objectives were to evaluate the diversity in vaginal ecosystem in these women. To all patients, clinical and socio-demographic data were collected after gynecological examination. This study was approved by the Ethics Committee from Federal University of Juiz de Fora, Minas Gerais, Brazil. Vaginal secretion and cervical scraping were collected. Gram-stained smears were evaluated to establish Nugent score for BV determination. Viral and bacterial DNA obtained was used as template for HPV genotyping (PCR) and bacterial fingerprint (REP-PCR). In total 31 patients were included (mean age 35 and 93.6% sexually active). The Nugent score showed that 38.7% were BV. From the medical records, Pap smear tests showed that 32.3% had low grade squamous epithelial lesion (LSIL), 29% had high grade squamous epithelial lesion (HSIL), 25.8% had atypical squamous cells of undetermined significance (ASC-US) and 12.9% with atypical squamous cells that would not exclude high-grade lesion (ASC-H). All participants were HPV+. HPV-16 was the most frequent (87.1%), followed by HPV-18 (61.3%). HPV-31, HPV-52 and HPV-58 were also detected. Coinfection HPV-16/HPV-18 was observed in 75%. In the 18-30 age group, HPV-16 was detected in 40%, and HPV-16/HPV-18 coinfection in 35%. HPV-16 was associated to 30% of ASC-H and 20% of HSIL patients. BV was observed in 50% of HPV-16+ participants and in 45% of HPV-16/HPV-18+. Fingerprints of bacterial communities showed clusters with low similarity suggesting high heterogeneity in vaginal microbiota within the sampled group. Overall, the data is worrisome once cervical-cancer highly risk-associated HPV-types were identified. The high microbial diversity observed may be related to the different levels of cellular lesions, and different physiological conditions of the participants (age, social behavior, education). Further prospective studies are needed to better address correlations and BV and microbial imbalance in vaginal ecosystems which would be related to the different cellular lesions in women with HPV infections. Supported by FAPEMIG, CNPq, CAPES, PPGCBIO/UFJF.

Keywords: human papillomavirus, bacterial vaginosis, bacterial diversity, cervical cancer

Procedia PDF Downloads 164

Authors: Sami Houry

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Complex systems exhibit universal characteristics as they near a tipping point. Among them are common generic early warning signals which precede critical transitions. These signals include: critical slowing down in which the rate of recovery from perturbations decreases over time; an increase in the variance of the state variable; an increase in the skewness of the state variable; an increase in the autocorrelations of the state variable; flickering between different states; and an increase in spatial correlations over time. The presence of the signals has management implications, as the identification of the signals near the tipping point could allow management to identify intervention points. Despite the applications of the generic early warning signals in various scientific fields, such as fisheries, ecology and finance, a review of literature did not identify any applications that address the program student withdrawal problem at the undergraduate distance universities. This area could benefit from the application of generic early warning signals as the program withdrawal rate amongst distance students is higher than the program withdrawal rate at face-to-face conventional universities. This research specifically assessed the generic early warning signals through an intensive case study of undergraduate program student withdrawal at a Canadian distance university. The university is non-cohort based due to its system of continuous course enrollment where students can enroll in a course at the beginning of every month. The assessment of the signals was achieved through the comparison of the incidences of generic early warning signals among students who withdrew or simply became inactive in their undergraduate program of study, the true positives, to the incidences of the generic early warning signals among graduates, the false positives. This was achieved through significance testing. Research findings showed support for the signal pertaining to the rise in flickering which is represented in the increase in the student’s non-pass rates prior to withdrawing from a program; moderate support for the signals of critical slowing down as reflected in the increase in the time a student spends in a course; and moderate support for the signals on increase in autocorrelation and increase in variance in the grade variable. The findings did not support the signal on the increase in skewness of the grade variable. The research also proposes a new signal based on the fractal-like characteristic of student behavior. The research also sought to extend knowledge by investigating whether the emergence of a program withdrawal status is self-similar or fractal-like at multiple levels of observation, specifically the program level and the course level. In other words, whether the act of withdrawal at the program level is also present at the course level. The findings moderately supported self-similarity as a potential signal. Overall, the assessment of the signals suggests that the signals, with the exception with the increase of skewness, could be utilized as a predictive management tool and potentially add one more tool, the fractal-like characteristic of withdrawal, as an additional signal in addressing the student program withdrawal problem.

Keywords: critical transitions, fractals, generic early warning signals, program student withdrawal

Procedia PDF Downloads 157

Authors: Ekaterina Malova

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Type 1 diabetes (T1D) is a chronic illness requiring immense lifestyle changes to reduce the chance of life-threatening complications. Moving to a college may be the first time for a young adult with T1D to take responsibility for all the aspects of their diabetes care. In addition, people with T1D constantly face stigmatization and discrimination as a result of their health condition, which puts additional pressure on young adults with T1D. Hence, omissions in diabetes self-care often occur during the time of transition to college when both the social and physical environment of young adults changes drastically and contribute to the fact that emerging young adults remain one of the age groups with the highest hemoglobin levels and poorest diabetes control. However, despite potential severe health risks caused by a lack of proper diabetes self-care, little is known about the experiences of emerging adults embarking on a higher education journey as this population. Thus, young adults with type 1 diabetes are a 'forgotten group,' meaning that their experiences are rarely addressed by researchers. Given that self-disclosure and information-seeking can be challenging for individuals with stigmatized illnesses, online platforms like YouTube have become a popular medium of self-disclosure and information-seeking for people living with T1D. Thus, this study aims to provide an analysis of experiences that college students with T1D choose to share with the general public online and explore the nature of information being communicated by college students with T1D to the online community in personal narratives posted on YouTube. A systematic approach was used to retrieve a video sample by searching YouTube with keywords 'type 1 diabetes' and 'college,' with results ordered by relevance. A total of 18 videos were saved. Video lengths ranged from 2 to 28 minutes. The data were coded using NVivo. Video transcripts were coded and analyzed utilizing the thematic analysis method. Three key themes emerged from thematic analysis: 1) Advice, 2) Personal experience, and 3) Things I wish everyone knew about T1D. In addition, Theme 1 was divided into subtopics to differentiate between the most common types of advice: 1) Overcoming stigma and b) Seeking social support. The identified themes indicate that two groups of the population can potentially benefit from watching students’ video testimonies: 1) lay public and 2) other students with T1D. Given that students in the videos reported a lack of T1D education in the lay public, such video narratives can serve important educational purposes and reduce health stigma, while perceived similarity and identification with students in the videos may facilitate the transition of health information to other individuals with T1D and positively affect their diabetes routine. Thus, online video narratives can potentially serve both educational and persuasive purposes, empowering students with T1D to stay in control of T1D while succeeding academically.

Keywords: type 1 diabetes, college students, health communication, transition period

Procedia PDF Downloads 128

Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Cinzia Russi, Chiyo Nishida

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Using data from online corpora (Spanish CREA, Italian CORIS), this paper examines the relatively understudied use of Spanish se and Italian si exemplified in (1) and (2), respectively. (1) El rojo es … el que se come a los demás. ‘The red (bottle) is the one that outshines/*eats the rest.’(2) … ebbe anche la saggezza di mangiarsi tutto il suo patrimonio. ‘… he even had the wisdom to squander/*eat all his estate.’ In these sentences, se/si accompanies the consumption verb comer/mangiare ‘to eat’, without which the sentences would not be interpreted appropriately. This se/si cannot readily be attributed to any of the multiple functions so far identified in the literature: reflexive, ergative, middle/passive, inherent, benefactive, and complete consumptive. In particular, this paper argues against the feasibility of a recent construction-based analysis of sentences like (1) and (2), which situates se/si within a prototype-based network of meanings all deriving from the central meaning of 'COMPLETE CONSUMPTION' (e.g., Alice se comió toda la torta/Alicesi è mangiata tutta la torta ‘John ate the whole cake’). Clearly, the empirical adequacy of such an account is undermined by the fact that the events depicted in the se/si-sentences at issue do not always entail complete consumption because they may lack an INCREMENTAL THEME, the distinguishing property of complete consumption. Alternatively, it is proposed that the sentences under analysis represent instances of verbal METAPHORICAL EXTENSION: se/si represents an explicit marker of this cognitive process, which has independently developed from the complete consumptive se/si, and the meaning extension is captured by the general tenets of Conceptual Metaphor Theory (CMT). Two conceptual domains, Source (DS) and target (DT), are related by similarity, assigning an appropriate metaphorical interpretation to DT. The domains paired here are comer/mangiare (DS) and comerse/mangiarsi (DT). The eating event (DS) involves (a) the physical process of xEATER grinding yFOOD-STUFF into pieces and swallowing it; and (b) the aspect of xEATER savoring yFOOD-STUFF and being nurtured by it. In the physical act of eating, xEATER has dominance and exercises his force over yFOOD-STUFF. This general sense of dominance and force is mapped onto DT and is manifested in the ways exemplified in (1) and (2), and many others. According to CMT, two other properties are observed in each pair of DS & DT. First, DS tends to be more physical and concrete and DT more abstract, and systematic mappings are established between constituent elements in DS and those in DT: xEATER corresponds to the element that destroys and yFOOD-STUFF to the element that is destroyed in DT, as exemplified in (1) and (2). Though the metaphorical extension marker se/si appears by far most frequently with comer/mangiare in the corpora, similar systematic mappings are observed in several other verb pairs, for example, jugar/giocare ‘to play (games)’ and jugarse/giocarsi ‘to jeopardize/risk (life, reputation, etc.)’, perder/perdere ‘to lose (an object)’ and perderse/perdersi ‘to miss out on (an event)’, etc. Thus, this study provides evidence that languages may indeed formally mark metaphor using means available to them.

Keywords: complete consumption value, conceptual metaphor, Italian si/Spanish se, metaphorical extension.

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Authors: Harpal Singh, Sakshi Batra

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The widespread and easy accesses to multimedia contents and possibility to make numerous copies without loss of significant fidelity have roused the requirement of digital rights management. Thus this problem can be effectively solved by Digital watermarking technology. This is a concept of embedding some sort of data or special pattern (watermark) in the multimedia content; this information will later prove ownership in case of a dispute, trace the marked document’s dissemination, identify a misappropriating person or simply inform user about the rights-holder. The primary motive of digital watermarking is to embed the data imperceptibly and robustly in the host information. Extensive counts of watermarking techniques have been developed to embed copyright marks or data in digital images, video, audio and other multimedia objects. With the development of digital video-based innovations, copyright dilemma for the multimedia industry increases. Video watermarking had been proposed in recent years to serve the issue of illicit copying and allocation of videos. It is the process of embedding copyright information in video bit streams. Practically video watermarking schemes have to address some serious challenges as compared to image watermarking schemes like real-time requirements in the video broadcasting, large volume of inherently redundant data between frames, the unbalance between the motion and motionless regions etc. and they are particularly vulnerable to attacks, for example, frame swapping, statistical analysis, rotation, noise, median and crop attacks. In this paper, an effective, robust and imperceptible video watermarking algorithm is proposed based on hybridization of powerful mathematical transforms; Fractional Fourier Transform (FrFT), Discrete Wavelet transforms (DWT) and Singular Value Decomposition (SVD) using redundant wavelet. This scheme utilizes various transforms for embedding watermarks on different layers by using Hybrid systems. For this purpose, the video frames are portioned into layers (RGB) and the watermark is being embedded in two forms in the video frames using SVD portioning of the watermark, and DWT sub-band decomposition of host video, to facilitate copyright safeguard as well as reliability. The FrFT orders are used as the encryption key that allows the watermarking method to be more robust against various attacks. The fidelity of the scheme is enhanced by introducing key generation and wavelet based key embedding watermarking scheme. Thus, for watermark embedding and extraction, same key is required. Therefore the key must be shared between the owner and the verifier via some safe network. This paper demonstrates the performance by considering different qualitative metrics namely Peak Signal to Noise ratio, Structure similarity index and correlation values and also apply some attacks to prove the robustness. The Experimental results are presented to demonstrate that the proposed scheme can withstand a variety of video processing attacks as well as imperceptibility.

Keywords: discrete wavelet transform, robustness, video watermarking, watermark

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Authors: Shankaran Sitarama

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New Product Development (NPD) is invariably a team effort and involves effective teamwork. NPD team has members from different disciplines coming together and working through the different phases all the way from conceptual design phase till the production and product roll out. Creativity and Innovation are some of the key factors of successful NPD. Team members going through the different phases of NPD interact and work closely yet challenge each other during the design phases to brainstorm on ideas and later converge to work together. These two traits require the teams to have a divergent and a convergent thinking simultaneously. There needs to be a good balance. The team dynamics invariably result in conflicts among team members. While some amount of conflict (ideational conflict) is desirable in NPD teams to be creative as a group, relational conflicts (or discords among members) could be detrimental to teamwork. Team communication truly reflect these tensions and team dynamics. In this research, team communication (emails) between the members of the NPD teams is considered for analysis. The email communication is processed through a semantic analysis algorithm (LSA) to analyze the content of communication and a semantic similarity analysis to arrive at a social network graph that depicts the communication amongst team members based on the content of communication. The amount of communication (content and not frequency of communication) defines the interaction strength between the members. Social network adjacency matrix is thus obtained for the team. Standard social network analysis techniques based on the Adjacency Matrix (AM) and Dichotomized Adjacency Matrix (DAM) based on network density yield network graphs and network metrics like centrality. The social network graphs are then rendered for visual representation using a Metric Multi-Dimensional Scaling (MMDS) algorithm for node placements and arcs connecting the nodes (representing team members) are drawn. The distance of the nodes in the placement represents the tie-strength between the members. Stronger tie-strengths render nodes closer. Overall visual representation of the social network graph provides a clear picture of the team’s interactions. This research reveals four distinct patterns of team interaction that are clearly identifiable in the visual representation of the social network graph and have a clearly defined computational scheme. The four computational patterns of team interaction defined are Central Member Pattern (CMP), Subgroup and Aloof member Pattern (SAP), Isolate Member Pattern (IMP), and Pendant Member Pattern (PMP). Each of these patterns has a team dynamics implication in terms of the conflict level in the team. For instance, Isolate member pattern, clearly points to a near break-down in communication with the member and hence a possible high conflict level, whereas the subgroup or aloof member pattern points to a non-uniform information flow in the team and some moderate level of conflict. These pattern classifications of teams are then compared and correlated to the real level of conflict in the teams as indicated by the team members through an elaborate self-evaluation, team reflection, feedback form and results show a good correlation.

Keywords: team dynamics, team communication, team interactions, social network analysis, sna, new product development, latent semantic analysis, LSA, NPD teams

Procedia PDF Downloads 35

Authors: Alvarez M., Chapela M. J., Balboa E., Rubianes D., Sinde E., Fernandez de Ana C., Rodríguez-Blanco A.

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The gut microbiota plays an important role as gut inflammation could contribute to colorectal cancer development; however, this role is still not fully understood, and tools able to prevent this progression are yet to be developed. The main objective of this study was to monitor the effects of a mushroom extracts formulation in gut microbial community composition of an Azoxymethane (AOM)/Dextran sodium sulfate (DSS) mice model of inflammation-linked carcinogenesis. For the in vivo study, 41 adult male mice of the C57BL / 6 strain were obtained. 36 of them have been induced in a state of colon carcinogenesis by a single intraperitoneal administration of AOM at a dose of 12.5 mg/kg; the control group animals received instead of the same volume of 0.9% saline. DSS is an extremely toxic polysaccharide sulfate that causes chronic inflammation of the colon mucosa, favoring the appearance of severe colitis and the production of tumors induced by AOM. Induction by AOM/DSS is an interesting platform for chemopreventive intervention studies. This time the model was used to monitor gut microbiota changes as a result of supplementation with a specific mushroom extracts formulation previously shown to have prebiotic activity. The animals have been divided into three groups: (i) Cancer + mushroom extracts formulation experimental group: to which the MicoDigest2.0 mushroom extracts formulation developed by Hifas da Terra S.L has been administered dissolved in drinking water at an estimated concentration of 100 mg / ml. (ii) Control group of animals with Cancer: to which normal water has been administered without any type of treatment. (iii) Control group of healthy animals: these are the animals that have not been induced cancer or have not received any treatment in drinking water. This treatment has been maintained for a period of 3 months, after which the animals were sacrificed to obtain tissues that were subsequently analyzed to verify the effects of the mushroom extract formulation. A microbiological analysis has been carried out to compare the microbial communities present in the intestines of the mice belonging to each of the study groups. For this, the methodology of massive sequencing by molecular analysis of the 16S gene has been used (Ion Torrent technology). Initially, DNA extraction and metagenomics libraries were prepared using the 16S Metagenomics kit, always following the manufacturer's instructions. This kit amplifies 7 of the 9 hypervariable regions of the 16S gene that will then be sequenced. Finally, the data obtained will be compared with a database that makes it possible to determine the degree of similarity of the sequences obtained with a wide range of bacterial genomes. Results obtained showed that, similarly to certain natural compounds preventing colorectal tumorigenesis, a mushroom formulation enriched the Firmicutes and Proteobacteria phyla and depleted Bacteroidetes. Therefore, it was demonstrated that the consumption of the mushroom extracts’ formulation developed could promote the recovery of the microbial balance that is disrupted in the mice model of carcinogenesis. More preclinical and clinical studies are needed to validate this promising approach.

Keywords: carcinogenesis, microbiota, mushroom extracts, inflammation

Procedia PDF Downloads 124

Authors: Elena Collino, Dario A. Ronzio, Goffredo Decimi, Maurizio Riva

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The rapid increase of renewable energy in Italy is led by wind and solar installations. The 2017 Italian energy strategy foresees a further development of these sustainable technologies, especially solar. This fact has resulted in new opportunities, challenges, and different problems to deal with. The growth of renewables allows to meet the European requirements regarding energy and environmental policy, but these types of sources are difficult to manage because they are intermittent and non-programmable. Operationally, these characteristics can lead to instability on the voltage profile and increasing uncertainty on energy reserve scheduling. The increasing renewable production must be considered with more and more attention especially by the Transmission System Operator (TSO). The TSO, in fact, every day provides orders on energy dispatch, once the market outcome has been determined, on extended areas, defined mainly on the basis of power transmission limitations. In Italy, six market zone are defined: Northern-Italy, Central-Northern Italy, Central-Southern Italy, Southern Italy, Sardinia, and Sicily. An accurate hourly renewable power forecasting for the day-ahead on these extended areas brings an improvement both in terms of dispatching and reserve management. In this study, an operational forecasting tool of the hourly solar output for the six Italian market zones is presented, and the performance is analysed. The implementation is carried out by means of a numerical weather prediction model, coupled with a statistical post-processing in order to derive the power forecast on the basis of the meteorological projection. The weather forecast is obtained from the limited area model RAMS on the Italian territory, initialized with IFS-ECMWF boundary conditions. The post-processing calculates the solar power production with the Analog Ensemble technique (AN). This statistical approach forecasts the production using a probability distribution of the measured production registered in the past when the weather scenario looked very similar to the forecasted one. The similarity is evaluated for the components of the solar radiation: global (GHI), diffuse (DIF) and direct normal (DNI) irradiation, together with the corresponding azimuth and zenith solar angles. These are, in fact, the main factors that affect the solar production. Considering that the AN performance is strictly related to the length and quality of the historical data a training period of more than one year has been used. The training set is made by historical Numerical Weather Prediction (NWP) forecasts at 12 UTC for the GHI, DIF and DNI variables over the Italian territory together with corresponding hourly measured production for each of the six zones. The AN technique makes it possible to estimate the aggregate solar production in the area, without information about the technologic characteristics of the all solar parks present in each area. Besides, this information is often only partially available. Every day, the hourly solar power forecast for the six Italian market zones is made publicly available through a website.

Keywords: analog ensemble, electricity market, PV forecast, solar energy

Procedia PDF Downloads 123

Authors: Hyppolite Aignon, Souleymane Yorou, Martin Ryberg, Anneli Svanholm

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Climate change and human actions cause the extinction of wild mushrooms. In Benin, the diversity of fungi is large and may still contain species new to science but the inventory effort remains low and focuses on particularly edible species (Russula, Lactarius, Lactifluus, and also Amanita). In addition, inventories have started recently and some groups of fungi are not sufficiently sampled, however, the degradation of fungal habitat continues to increase and some species are already disappearing. (Yorou and De Kesel, 2011), however, the degradation of fungi habitat continues to increase and some species may disappear without being known. This genus (Inocybe) overlooked has a worldwide distribution and includes more than 700 species with many undiscovered or poorly known species worldwide and particularly in tropical Africa. It is therefore important to orient the inventory to other genera or important families such as Inocybe (Fungi, Agaricales) in order to highlight their diversity and also to know their phylogenetic positions with a combined approach of gene regions. This study aims to evaluate the species richness and phylogenetic position of Inocybe species and affiliated taxa in West Africa. Thus, in North Benin, we visited the Forest Reserve of Ouémé Supérieur, the Okpara forest and the Alibori Supérieur Forest Reserve. In the center, we targeted the Forest Reserve of Toui-Kilibo. The surveys have been carried during the raining season in the study area meaning from June to October. A total of 24 taxa were collected, photographed and described. The DNA was extracted, the Polymerase Chain Reaction was carried out using primers (ITS1-F, ITS4-B) for Internal transcribed spacer (ITS), (LROR, LWRB, LR7, LR5) for nuclear ribosomal (LSU), (RPB2-f5F, RPB2-b6F, RPB2- b6R2, RPB2-b7R) for RNA polymerase II gene (RPB2) and sequenced. The ITS sequences of the 24 collections of Inocybaceae were edited in Staden and all the sequences were aligned and edited with Aliview v1.17. The sequences were examined by eye for sufficient similarity to be considered the same species. 13 different species were present in the collections. In addition, sequences similar to the ITS sequences of the thirteen final species were searched using BLAST. The nLSU and RPB2 markers for these species have been inserted in a complete alignment, where species from all major Inocybaceae clades as well as from all continents except Antarctica are present. Our new sequences for nLSU and RPB2 have been manually aligned in this dataset. Phylogenetic analysis was performed using the RAxML v7.2.6 maximum likelihood software. Bootstrap replications have been set to 100 and no partitioning of the dataset has been performed. The resulting tree was viewed and edited with FigTree v1.4.3. The preliminary tree resulting from the analysis of maximum likelihood shows us that these species coming from Benin are much diversified and are distributed in four different clades (Inosperma, Inocybe, Mallocybe and Pseudosperma) on the seven clades of Inocybaceae but the phylogeny position of 7 is currently known. This study marks the diversity of Inocybe in Benin and the investigations will continue and a protection plan will be developed in the coming years.

Keywords: Benin, diversity, Inocybe, phylogeny placement

Procedia PDF Downloads 111

Authors: M. D. Nirmani, K. L. N. Perera, G. H. Galhena

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Dengue has become one of the most important arbo-viral disease in all tropical and subtropical regions of the world. Aedes aegypti, is the principal vector of the virus, vary in both epidemiological and behavioral characteristics, which could be finely measured through DNA sequence comparison at their population level. Such knowledge in the population differences can assist in implementation of effective vector control strategies allowing to make estimates of the gene flow and adaptive genomic changes, which are important predictors of the spread of Wolbachia infection or insecticide resistance. As such, this study was undertaken to investigate the phylogenetic relationships of Ae. aegypti from Galle and Colombo, Sri Lanka, based on the ribosomal protein region which spans between two exons, in order to understand the geographical distribution of genetically distinct mosquito clades and its impact on mosquito control measures. A 320bp DNA region spanning from 681-930 bp, corresponding to the ribosomal protein, was sequenced in 62 Ae. aegypti larvae collected from Galle (N=30) and Colombo (N=32), Sri Lanka. The sequences were aligned using ClustalW and the haplotypes were determined with DnaSP 5.10. Phylogenetic relationships among haplotypes were constructed using the maximum likelihood method under Tamura 3 parameter model in MEGA 7.0.14 including three previously reported sequences of Australian (N=2) and Brazilian (N=1) Ae. aegypti. The bootstrap support was calculated using 1000 replicates and the tree was rooted using Aedes notoscriptus (GenBank accession No. KJ194101). Among all sequences, nineteen different haplotypes were found among which five haplotypes were shared between 80% of mosquitoes in the two populations. Seven haplotypes were unique to each of the population. Phylogenetic tree revealed two basal clades and a single derived clade. All observed haplotypes of the two Ae. aegypti populations were distributed in all the three clades, indicating a lack of genetic differentiation between populations. The Brazilian Ae. aegypti haplotype and one of the Australian haplotypes were grouped together with the Sri Lankan basal haplotype in the same basal clade, whereas the other Australian haplotype was found in the derived clade. Phylogram showed that Galle and Colombo Ae. aegypti populations are highly related to each other despite the large geographic distance (129 Km) indicating a substantial genetic similarity between them. This may have probably arisen from passive migration assisted by human travelling and trade through both land and water as the two areas are bordered by the sea. In addition, studied Sri Lankan mosquito populations were closely related to Australian and Brazilian samples. Probably this might have caused by shipping industry between the three countries as all of them are fully or partially enclosed by sea. For example, illegal fishing boats migrating to Australia by sea is perhaps a good mean of transportation of all life stages of mosquitoes from Sri Lanka. These findings indicate that extensive mosquito migrations occur between populations not only within the country, but also among other countries in the world which might be a main barrier to the successful vector control measures.

Keywords: Aedes aegypti, dengue control, extensive mosquito migration, haplotypes, phylogeny, ribosomal protein

Procedia PDF Downloads 153

Authors: Shubhangi Roy

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Relational Contracts (informal understandings not enforceable by law) are a common feature of most economies. However, their dominance is higher in developing countries. Such informality of economic sectors is often co-related to lower economic growth. The aim of this paper is to investigate whether informal arrangements i.e. relational contracts are a cause or symptom of lower levels of economic and/or institutional development. The methodology followed involves an initial survey of 150 test subjects in Northern India. The subjects are all members of occupations where they frequently transact ensuring uniformity in transaction volume. However, the subjects are from varied socio-economic backgrounds to ensure sufficient variance in transaction values allowing us to understand the relationship between the amount of money involved to the method of transaction used, if any. Questions asked are quantitative and qualitative with an aim to observe both the behavior and motivation behind such behavior. An overarching similarity observed during the survey across all subjects’ responses is that in an economy like India with pervasive corruption and delayed litigation, economy participants have created alternative social sanctions to deal with non-performers. In a society that functions predominantly on caste, class and gender classifications, these sanctions could, in fact, be more cumbersome for a potential rule-breaker than the legal ramifications. It, therefore, is a symptom of weak formal regulatory enforcement and dispute settlement mechanism. Additionally, the study bifurcates such informal arrangements into two separate systems - a) when it exists in addition to and augments a legal framework creating an efficient socio-legal equilibrium or; b) in conflict with the legal system in place. This categorization is an important step in regulating informal arrangements. Instead of considering the entire gamut of such arrangements as counter-development, it helps decision-makers understand when to dismantle (latter) and when to pivot around existing informal systems (former). The paper hypothesizes that those social arrangements that support the formal legal frameworks allow for cheaper enforcement of regulations with lower enforcement costs burden on the state mechanism. On the other hand, norms which contradict legal rules will undermine the formal framework. Law infringement, in presence of these norms, will have no impact on the reputation of the business or individual outside of the punishment imposed under the law. It is especially exacerbated in the Indian legal system where enforcement of penalties for non-performance of contracts is low. In such a situation, the social norm will be adhered to more strictly by the individuals rather than the legal norms. This greatly undermines the role of regulations. The paper concludes with recommendations that allow policy-makers and legal systems to encourage the former category of informal arrangements while discouraging norms that undermine legitimate policy objectives. Through this investigation, we will be able to expand our understanding of tools of market development beyond regulations. This will allow academics and policymakers to harness social norms for less disruptive and more lasting growth.

Keywords: distribution of income, emerging economies, relational contracts, sample survey, social norms

Procedia PDF Downloads 135

Authors: Zhao Gao, Eran Edirisinghe

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The production of an accurate sketch of a suspect based on a verbal description obtained from a witness is an essential task for most criminal investigations. The criminal investigation system employs specifically trained professional artists to manually draw a facial image of the suspect according to the descriptions of an eyewitness for subsequent identification. Within the advancement of Deep Learning, Recurrent Neural Networks (RNN) have shown great promise in Natural Language Processing (NLP) tasks. Additionally, Generative Adversarial Networks (GAN) have also proven to be very effective in image generation. In this study, a trained GAN conditioned on textual features such as keywords automatically encoded from a verbal description of a human face using an RNN is used to generate photo-realistic facial images for criminal investigations. The intention of the proposed system is to map corresponding features into text generated from verbal descriptions. With this, it becomes possible to generate many reasonably accurate alternatives to which the witness can use to hopefully identify a suspect from. This reduces subjectivity in decision making both by the eyewitness and the artist while giving an opportunity for the witness to evaluate and reconsider decisions. Furthermore, the proposed approach benefits law enforcement agencies by reducing the time taken to physically draw each potential sketch, thus increasing response times and mitigating potentially malicious human intervention. With publically available 'CelebFaces Attributes Dataset' (CelebA) and additionally providing verbal description as training data, the proposed architecture is able to effectively produce facial structures from given text. Word Embeddings are learnt by applying the RNN architecture in order to perform semantic parsing, the output of which is fed into the GAN for synthesizing photo-realistic images. Rather than the grid search method, a metaheuristic search based on genetic algorithms is applied to evolve the network with the intent of achieving optimal hyperparameters in a fraction the time of a typical brute force approach. With the exception of the ‘CelebA’ training database, further novel test cases are supplied to the network for evaluation. Witness reports detailing criminals from Interpol or other law enforcement agencies are sampled on the network. Using the descriptions provided, samples are generated and compared with the ground truth images of a criminal in order to calculate the similarities. Two factors are used for performance evaluation: The Structural Similarity Index (SSIM) and the Peak Signal-to-Noise Ratio (PSNR). A high percentile output from this performance matrix should attribute to demonstrating the accuracy, in hope of proving that the proposed approach can be an effective tool for law enforcement agencies. The proposed approach to criminal facial image generation has potential to increase the ratio of criminal cases that can be ultimately resolved using eyewitness information gathering.

Keywords: RNN, GAN, NLP, facial composition, criminal investigation

Procedia PDF Downloads 135

Authors: Elizaveta S. Prokofyeva, Svetlana V. Maltseva, Roman D. Zaitsev

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Rapidly evolving modern data analysis technologies in healthcare play a large role in understanding the operation of the system and its characteristics. Nowadays, one of the key tasks in urban healthcare is to optimize the resource allocation. Thus, the application of data analysis in medical institutions to solve optimization problems determines the significance of this study. The purpose of this research was to establish the dependence between the indicators of the effectiveness of the medical institution and its resources. Hospital discharges by diagnosis; hospital days of in-patients and in-patient average length of stay were selected as the performance indicators and the demand of the medical facility. The hospital beds by type of care, medical technology (magnetic resonance tomography, gamma cameras, angiographic complexes and lithotripters) and physicians characterized the resource provision of medical institutions for the developed models. The data source for the research was an open database of the statistical service Eurostat. The choice of the source is due to the fact that the databases contain complete and open information necessary for research tasks in the field of public health. In addition, the statistical database has a user-friendly interface that allows you to quickly build analytical reports. The study provides information on 28 European for the period from 2007 to 2016. For all countries included in the study, with the most accurate and complete data for the period under review, predictive models were developed based on historical panel data. An attempt to improve the quality and the interpretation of the models was made by cluster analysis of the investigated set of countries. The main idea was to assess the similarity of the joint behavior of the variables throughout the time period under consideration to identify groups of similar countries and to construct the separate regression models for them. Therefore, the original time series were used as the objects of clustering. The hierarchical agglomerate algorithm k-medoids was used. The sampled objects were used as the centers of the clusters obtained, since determining the centroid when working with time series involves additional difficulties. The number of clusters used the silhouette coefficient. After the cluster analysis it was possible to significantly improve the predictive power of the models: for example, in the one of the clusters, MAPE error was only 0,82%, which makes it possible to conclude that this forecast is highly reliable in the short term. The obtained predicted values of the developed models have a relatively low level of error and can be used to make decisions on the resource provision of the hospital by medical personnel. The research displays the strong dependencies between the demand for the medical services and the modern medical equipment variable, which highlights the importance of the technological component for the successful development of the medical facility. Currently, data analysis has a huge potential, which allows to significantly improving health services. Medical institutions that are the first to introduce these technologies will certainly have a competitive advantage.

Keywords: data analysis, demand modeling, healthcare, medical facilities

Procedia PDF Downloads 112

Authors: Tomasz Stenzel, Daria Dziewulska, Ewa Łukaszuk, Joy Custer, Simona Kraberger, Arvind Varsani

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Viral diseases, especially those leading to impairment of the immune system, are among the most important problems in avian pathology. However, there is not much data available on this subject other than commercial poultry bird species. Recently, increasing attention has been paid to racing pigeons, which have been refined for many years in terms of their ability to return to their place of origin. Currently, these birds are used for races at distances from 100 to 1000 km, and winning pigeons are highly valuable. The rearing system of racing pigeons contradicts the principles of biosecurity, as birds originating from various breeding facilities are commonly transported and reared in “One Loft Race” (OLR) facilities. This favors the spread of multiple infections and provides conditions for the development of novel variants of various pathogens through recombination. One of the most significant viruses occurring in this avian species is the pigeon circovirus (PiCV), which is detected in ca. 70% of pigeons. Circoviruses are characterized by vast genetic diversity which is due to, among other things, the recombination phenomenon. It consists of an exchange of fragments of genetic material among various strains of the virus during the infection of one organism. The rate and intensity of the development of PiCV recombinants have not been determined so far. For this reason, an experiment was performed to investigate the frequency of development of novel PiCV recombinants in racing pigeons kept in OLR-type conditions. 15 racing pigeons originating from 5 different breeding facilities, subclinically infected with various PiCV strains, were housed in one room for eight weeks, which was supposed to mimic the conditions of OLR rearing. Blood and swab samples were collected from birds every seven days to recover complete PiCV genomes that were amplified through Rolling Circle Amplification (RCA), cloned, sequenced, and subjected to bioinformatic analyses aimed at determining the genetic diversity and the dynamics of recombination phenomenon among the viruses. In addition, virus shedding rate/level of viremia, expression of the IFN-γ and interferon-related genes, and anti-PiCV antibodies were determined to enable the complete analysis of the course of infection in the flock. Initial results have shown that 336 full PiCV genomes were obtained, exhibiting nucleotide similarity ranging from 86.6 to 100%, and 8 of those were recombinants originating from viruses of different lofts of origin. The first recombinant appeared after seven days of experiment, but most of the recombinants appeared after 14 and 21 days of joint housing. The level of viremia and virus shedding was the highest in the 2nd week of the experiment and gradually decreased to the end of the experiment, which partially corresponded with Mx 1 gene expression and antibody dynamics. The results have shown that the OLR pigeon-rearing system could play a significant role in spreading infectious agents such as circoviruses and contributing to PiCV evolution through recombination. Therefore, it is worth considering whether a popular gambling game such as pigeon racing is sensible from both animal welfare and epidemiological point of view.

Keywords: pigeon circovirus, recombination, evolution, one loft race

Procedia PDF Downloads 46

Authors: Ana L. M. Pavan, Guilherme Giacomini, Allan F. F. Alves, Marcela De Oliveira, Fernando A. B. Neto, Maria E. D. Rosa, Andre P. Trindade, Diana R. De Pina

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Mammography is a worldwide image modality used to diagnose breast cancer, even in asymptomatic women. Due to its large availability, mammograms can be used to measure breast density and to predict cancer development. Women with increased mammographic density have a four- to sixfold increase in their risk of developing breast cancer. Therefore, studies have been made to accurately quantify mammographic breast density. In clinical routine, radiologists perform image evaluations through BIRADS (Breast Imaging Reporting and Data System) assessment. However, this method has inter and intraindividual variability. An automatic objective method to measure breast density could relieve radiologist’s workload by providing a first aid opinion. However, pectoral muscle is a high density tissue, with similar characteristics of fibroglandular tissues. It is consequently hard to automatically quantify mammographic breast density. Therefore, a pre-processing is needed to segment the pectoral muscle which may erroneously be quantified as fibroglandular tissue. The aim of this work was to develop an automatic algorithm to segment and extract pectoral muscle in digital mammograms. The database consisted of thirty medio-lateral oblique incidence digital mammography from São Paulo Medical School. This study was developed with ethical approval from the authors’ institutions and national review panels under protocol number 3720-2010. An algorithm was developed, in Matlab® platform, for the pre-processing of images. The algorithm uses image processing tools to automatically segment and extract the pectoral muscle of mammograms. Firstly, it was applied thresholding technique to remove non-biological information from image. Then, the Hough transform is applied, to find the limit of the pectoral muscle, followed by active contour method. Seed of active contour is applied in the limit of pectoral muscle found by Hough transform. An experienced radiologist also manually performed the pectoral muscle segmentation. Both methods, manual and automatic, were compared using the Jaccard index and Bland-Altman statistics. The comparison between manual and the developed automatic method presented a Jaccard similarity coefficient greater than 90% for all analyzed images, showing the efficiency and accuracy of segmentation of the proposed method. The Bland-Altman statistics compared both methods in relation to area (mm²) of segmented pectoral muscle. The statistic showed data within the 95% confidence interval, enhancing the accuracy of segmentation compared to the manual method. Thus, the method proved to be accurate and robust, segmenting rapidly and freely from intra and inter-observer variability. It is concluded that the proposed method may be used reliably to segment pectoral muscle in digital mammography in clinical routine. The segmentation of the pectoral muscle is very important for further quantifications of fibroglandular tissue volume present in the breast.

Keywords: active contour, fibroglandular tissue, hough transform, pectoral muscle

Procedia PDF Downloads 321

Authors: V. Mantey, N. Findlay, I. Maddox

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The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

Procedia PDF Downloads 147

Authors: Chao-Yang Huang, Rwey-Hua Cherng, Chung-Lin Fu, Yuan-Lung Lo

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Solar energy is one of the replaceable choices to reduce the CO2 emission produced by conventional power plants in the modern society. As an island which is frequently visited by strong typhoons and earthquakes, it is an urgent issue for Taiwan to make an effort in revising the local regulations to strengthen the safety design of photovoltaic systems. Currently, the Taiwanese code for wind resistant design of structures does not have a clear explanation on photovoltaic systems, especially when the systems are arranged in arrayed format. Furthermore, when the arrayed photovoltaic system is mounted on the rooftop, the approaching flow is significantly altered by the building and led to different pressure pattern in the different area of the photovoltaic system. In this study, L-shape arrayed photovoltaic system is mounted on the ground of the wind tunnel and then mounted on the building rooftop. The system is consisted of 60 PV models. Each panel model is equivalent to a full size of 3.0 m in depth and 10.0 m in length. Six pressure taps are installed on the upper surface of the panel model and the other six are on the bottom surface to measure the net pressures. Wind attack angle is varied from 0° to 360° in a 10° interval for the worst concern due to wind direction. The sampling rate of the pressure scanning system is set as high enough to precisely estimate the peak pressure and at least 20 samples are recorded for good ensemble average stability. Each sample is equivalent to 10-minute time length in full scale. All the scale factors, including timescale, length scale, and velocity scale, are properly verified by similarity rules in low wind speed wind tunnel environment. The purpose of L-shape arrayed system is for the understanding the pressure characteristics at the corner area. Extreme value analysis is applied to obtain the design pressure coefficient for each net pressure. The commonly utilized Cook-and-Mayne coefficient, 78%, is set to the target non-exceedance probability for design pressure coefficients under Gumbel distribution. Best linear unbiased estimator method is utilized for the Gumbel parameter identification. Careful time moving averaging method is also concerned in data processing. Results show that when the arrayed photovoltaic system is mounted on the ground, the first row of the panels reveals stronger positive pressure than that mounted on the rooftop. Due to the flow separation occurring at the building edge, the first row of the panels on the rooftop is most in negative pressures; the last row, on the other hand, shows positive pressures because of the flow reattachment. Different areas also have different pressure patterns, which corresponds well to the regulations in ASCE7-16 describing the area division for design values. Several minor observations are found according to parametric studies, such as rooftop edge effect, parapet effect, building aspect effect, row interval effect, and so on. General comments are then made for the proposal of regulation revision in Taiwanese code.

Keywords: aerodynamic force coefficient, ground-mounted, roof-mounted, wind tunnel test, photovoltaic

Procedia PDF Downloads 97

Authors: Ewa Szarek-Gwiazda, Agata Z. Wojtal, Agnieszka Pociecha, Andrzej Kownacki, Dariusz Ciszewski

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Mining of metal ores is one of the largest sources of heavy metals, which deteriorate aquatic systems. The response of organisms to environmental changes can be well recorded in sediments of the affected water bodies and may be reconstructed basing on analyses of organisms remains. The present study aimed at response of diatoms, Cladocera and Chronomidae communities to impact of Zn-Pb mine water discharge recorded in sediment cores of small subsidence ponds on the Chechło River floodplain (Silesia–Krakow Region, southern Poland). We hypothesis various response of the above groups to high metal concentrations (Cd, Pb, Zn, and Cu). The investigated ponds were formed either during the peak of the ore exploitation (DOWN) or after mining cessation (UP). Currently, the concentrations of dissolved metals (in µg g-1) in water reached up to 0.53 for Cd, 7.3 for Pb and up to 47.1 for Zn. All the sediment cores from subsidence ponds were heavily polluted with Cd 6.7–612 μg g−1, Pb 0.1–10.2 mg g−1, and Zn 0.5–23.1 mg g−1. Core sediments varied also in respect to pH 5.8-7.1 and concentrations of organic matter (5.7-39.8%). The impact of high metal concentrations was expressed by the occurrence of metal tolerant taxa like diatoms – Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii; Cladocera – Chydorus sphaericus (dominated in cores from all ponds), and Chironomidae – Chironomus and Cricotopus especially in the DOWN ponds. Statistical analysis exhibited a negative impact of metals on some taxa of diatoms and Cladocera, but only on Polypedilum sp. from Chironomidae. Abundance of such diatoms like Gomphonema utae, Staurosirella pinnata, Eunotia bilunaris, and Cladocera like Alona, Chydorus, Graptoleberis, and Pleuroxus decreased with increasing Pb concentration. However, the occurrence or dominance of more sensitive species of diatoms and Cladocera indicates their adaptation to higher metal loads, which was facilitated by neutral pH and slightly alkaline waters. Diatom assemblages were generally resistant to Zn, Pb, Cu, and Cd pollution as indicated by their large similarity to populations from non-contaminated waters. Comparison with reference objects clearly indicates the dominance of Achnanthidium minutissimum, Staurosira venter, and Fragilaria gracilis in very diverse assemblages of unpolluted waters. The distribution of the Cladocera and Chironomidae taxa depended on the habitat type. The DOWN ponds with stagnant water and overgrown with macrophytes were more suitable for Cladocerans (14 taxa, higher diversity) than the UP ponds with river water flowing through their centre and with a small share of macrophytes (8 taxa). The Chironominae, mainly Chironomus and Microspectra, were abundant in cores from the UP ponds with muddy bottom. Inversely, the density of Orthocladiinae, especially genus Cricotopus, were related to the organic matter content and dominated in cores from the DOWN ponds. The presence of diatoms like Nitzschia amphibia, Sellaphora nigri, and Surirella brebisonii var. kuetzingii, Cladocerans Bosmina longirostris, Chydorus sphaericus, littoral cladocerans, Alona affinis, A. rectangularis as well as Chironomidae Chironomus sp. (UP ponds) and Psecrotanypus varius (DOWN ponds) indicate the influence of the water trophy on their distribution.

Keywords: Chironomidae, cladocerans, diatoms, metals, Zn-Pb mine, sediment cores, subsidence ponds

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Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Dominic Sagar

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Manchester ‘King Cotton’, the first truly industrial city of the nineteenth century, passing on the baton to Detroit ‘Motor City’, is the first truly modern city. We are exploring the tales of the two cities, their rise and fall and subsequent post-industrial decline, their transitions and transformations, whilst alongside paralleling their corresponding, commercial, cultural, industrial and even agricultural, artistic and musical transactions and connections. The paper will briefly contextualize how technologies of the industrial age and modern age have been instrumental in the development of these cities and other similar cities including New York. However, the main focus of the study will be the present and more importantly the future, how globalisation and the advancements of digital technologies and industries have shaped the cities developments from AlanTuring and the making of the first programmable computer to the effect of digitalisation and digital initiatives. Manchester now has a thriving creative digital infrastructure of Digilabs, FabLabs, MadLabs and hubs, the study will reference the Smart Project and the Manchester Digital Development Association whilst paralleling similar digital and creative industrial initiatives now starting to happen in Detroit. The paper will explore other topics including the need to allow for zones of experimentation, areas to play, think and create in order develop and instigate new initiatives and ideas of production, carrying on the tradition of influential inventions throughout the history of these key cities. Other topics will be briefly touched on, such as urban farming, citing the Biospheric foundation in Manchester and other similar projects in Detroit. However, the main thread will focus on the music industries and how they are contributing to the regeneration of cities. Musically and artistically, Manchester and Detroit have been closely connected by the flow and transmission of information and transfer of ideas via ‘cars and trains and boats and planes’ through to the new ‘super highway’. From Detroit to Manchester often via New York and Liverpool and back again, these musical and artistic connections and flows have greatly affected and influenced both cities and the advancement of technology are still connecting the cities. In summary two hugely important industrial cities, subsequently both experienced massive decline in fortunes, having had their large industrial hearts ripped out, ravaged leaving dying industrial carcasses and car crashes of despair, dereliction, desolation and post-industrial wastelands vacated by a massive exodus of the cities’ inhabitants. To examine the affinity, similarity and differences between Manchester & Detroit, from their industrial importance to their post-industrial decline and their current transmutations, transformations, transient transgressions, cities in transition; contrasting how they have dealt with these problems and how they can learn from each other. With a view to framing these topics with regard to how various communities have shaped these cities and the creative industries and design [the new cotton/car manufacturing industries] are reinventing post-industrial cities, to speculate on future development of these themes in relation to Globalisation, digitalisation and how cities can function to develop solutions to communal living in cities of the future.

Keywords: cultural capital, digital developments, musical initiatives, zones of experimentation

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Authors: Asma Ben Hmidene, Mizuho Hanaki, Kazuma Murakami, Kazuhiro Irie, Hiroko Isoda, Hideyuki Shigemori

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Type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD) are characterized as a peripheral metabolic disorder and a degenerative disease of the central nervous system, respectively. It is now widely recognized that T2DM and AD share many pathophysiological features including glucose metabolism, increased oxidative stress and amyloid aggregation. Amyloid beta (Aβ) is the components of the amyloid deposits in the AD brain and while the component of the amyloidogenic peptide deposit in the pancreatic islets of Langerhans is identified as human islet amyloid polypeptide (hIAPP). These two proteins are originated from the amyloid precursor protein and have a high sequence similarity. Although the amino acid sequences of amyloidogenic proteins are diverse, they all adopt a similar structure in aggregates called cross-beta-spine. Add at that, extensive studies in the past years have found that like Aβ1-42, IAPP forms early intermediate assemblies as spherical oligomers, implicating that these oligomers possess a common folding pattern or conformation. These similarities can be used in the search for effective pharmacotherapy for DM, since potent therapeutic agents such as antioxidants with a catechol moiety, proved to inhibit Aβ aggregation, may play a key role in the inhibit the aggregation of hIAPP treatment of patients with DM. Tamarix gallica is one of the halophyte species having a powerful antioxidant system. Although it was traditionally used for the treatment of various liver metabolic disorders, there is no report about the use of this plant for the treatment or prevention of T2DM and AD. Therefore, the aim of this work is to investigate their protective effect towards T2DM and AD by isolation and identification of α-glucosidase inhibitors, with antioxidant potential, that play an important role in the glucose metabolism in diabetic patient, as well as, the polymerization of hIAPP and Aβ aggregation inhibitors. Structure-activity relationship study was conducted for both assays. And as for α-glucosidase inhibitors, their mechanism of action and their synergistic potential when applied with a very low concentration of acarbose were also suggesting that they can be used not only as α-glucosidase inhibitors but also be combined with established α-glucosidase inhibitors to reduce their adverse effect. The antioxidant potential of the purified substances was evaluated by DPPH and SOD assays. Th-T assay using 42-mer amyloid β-protein (Aβ42) for AD and hIAPP which is a 37-residue peptide secreted by the pancreatic β –cells for T2DM and Transmission electronic microscopy (TEM) were conducted to evaluate the amyloid aggragation of the actives substances. For α-glucosidase, p-NPG and glucose oxidase assays were performed for determining the inhibition potential and structure-activity relationship study. The Enzyme kinetic protocol was used to study the mechanism of action. From this research, it was concluded that polyphenols playing a role in the glucose metabolism and oxidative stress can also inhibit the amyloid aggregation, and that substances with a catechol and glucuronide moieties inhibiting amyloid-β aggregation, might be used to inhibit the aggregation of hIAPP.

Keywords: α-glucosidase inhibitors, amyloid aggregation inhibition, mechanism of action, polyphenols, structure activity relationship, synergistic potential, tamarix gallica

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Authors: Raptis Sotirios

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Health and social care (HSc) services planning and scheduling are facing unprecedented challenges due to the pandemic pressure and also suffer from unplanned spending that is negatively impacted by the global financial crisis. Data-driven can help to improve policies, plan and design services provision schedules using algorithms assist healthcare managers’ to face unexpected demands using fewer resources. The paper discusses services packing using statistical significance tests and machine learning (ML) to evaluate demands similarity and coupling. This is achieved by predicting the range of the demand (class) using ML methods such as CART, random forests (RF), and logistic regression (LGR). The significance tests Chi-Squared test and Student test are used on data over a 39 years span for which HSc services data exist for services delivered in Scotland. The demands are probabilistically associated through statistical hypotheses that assume that the target service’s demands are statistically dependent on other demands as a NULL hypothesis. This linkage can be confirmed or not by the data. Complementarily, ML methods are used to linearly predict the above target demands from the statistically found associations and extend the linear dependence of the target’s demand to independent demands forming, thus groups of services. Statistical tests confirm ML couplings making the prediction also statistically meaningful and prove that a target service can be matched reliably to other services, and ML shows these indicated relationships can also be linear ones. Zero paddings were used for missing years records and illustrated better such relationships both for limited years and in the entire span offering long term data visualizations while limited years groups explained how well patients numbers can be related in short periods or can change over time as opposed to behaviors across more years. The prediction performance of the associations is measured using Receiver Operating Characteristic(ROC) AUC and ACC metrics as well as the statistical tests, Chi-Squared and Student. Co-plots and comparison tables for RF, CART, and LGR as well as p-values and Information Exchange(IE), are provided showing the specific behavior of the ML and of the statistical tests and the behavior using different learning ratios. The impact of k-NN and cross-correlation and C-Means first groupings is also studied over limited years and the entire span. It was found that CART was generally behind RF and LGR, but in some interesting cases, LGR reached an AUC=0 falling below CART, while the ACC was as high as 0.912, showing that ML methods can be confused padding or by data irregularities or outliers. On average, 3 linear predictors were sufficient, LGR was found competing RF well, and CART followed with the same performance at higher learning ratios. Services were packed only if when significance level(p-value) of their association coefficient was more than 0.05. Social factors relationships were observed between home care services and treatment of old people, birth weights, alcoholism, drug abuse, and emergency admissions. The work found that different HSc services can be well packed as plans of limited years, across various services sectors, learning configurations, as confirmed using statistical hypotheses.

Keywords: class, cohorts, data frames, grouping, prediction, prob-ability, services

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Authors: Yi H. Wong, Li L. Chan, Chee O. Leong, Stephen Ambu, Joon W. Mak, Priyadashi S. Sahu

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Background: Acanthamoeba is a free-living opportunistic protist which is ubiquitously distributed in the environment. Virulent Acanthamoeba can cause fatal encephalitis in immunocompromised patients and potential blinding keratitis in immunocompetent contact lens wearers. Approximately 24 species have been identified but only the A. castellanii, A. polyphaga and A. culbertsoni are commonly associated with human infections. Until to date, the precise molecular basis for Acanthamoeba pathogenesis remains unclear. Previous studies reported that Acanthamoeba virulence can be diminished through prolonged axenic culture but revived through serial mouse passages. As no clear explanation on this reversible pathogenesis is established, hereby, we postulate that the epigenetic regulators, DNA-methyltransferases (DNMT) and histone-deacetylases (HDAC), could possibly be involved in granting the virulence plasticity of Acanthamoeba spp. Methods: Four rounds of mouse passages were conducted to revive the virulence potential of the virulence-attenuated Acanthamoeba castellanii strain (ATCC 50492). Briefly, each mouse (n=6/group) was inoculated intraperitoneally with Acanthamoebae cells (2x 105 trophozoites/mouse) and incubated for 2 months. Acanthamoebae cells were isolated from infected mouse organs by culture method and subjected to subsequent mouse passage. In vitro cytopathic, encystment and gelatinolytic assays were conducted to evaluate the virulence characteristics of Acanthamoebae isolates for each passage. PCR primers which targeted on the 2 members (DNMT1 and DNMT2) and 5 members (HDAC1 to 5) of the DNMT and HDAC gene families respectively were custom designed. Quantitative real-time PCR (qPCR) was performed to detect and quantify the relative expression of the two gene families in each Acanthamoeba isolates. Beta-tubulin of A. castellanii (Genbank accession no: XP_004353728) was included as housekeeping gene for data normalisation. PCR mixtures were also analyzed by electrophoresis for amplicons detection. All statistical analyses were performed using the paired one-tailed Student’s t test. Results: Our pathogenicity tests showed that the virulence-reactivated Acanthamoeba had a higher degree of cytopathic effect on vero cells, a better resistance to encystment challenge and a higher gelatinolytic activity which was catalysed by serine protease. qPCR assay showed that DNMT1 expression was significantly higher in the virulence-reactivated compared to the virulence-attenuated Acanthamoeba strain (p ≤ 0.01). The specificity of primers which targeted on DNMT1 was confirmed by sequence analysis of PCR amplicons, which showed a 97% similarity to the published DNA-methyltransferase gene of A. castellanii (GenBank accession no: XM_004332804.1). Out of the five primer pairs which targeted on the HDAC family genes, only HDAC4 expression was significantly difference between the two variant strains. In contrast to DNMT1, HDAC4 expression was much higher in the virulence-attenuated Acanthamoeba strain. Conclusion: Our mouse passages had successfully restored the virulence of the attenuated strain. Our findings suggested that DNA-methyltransferase (DNMT1) and histone deacetylase (HDAC4) expressions are associated with virulence potential of Acanthamoeba spp.

Keywords: acanthamoeba, DNA-methyltransferase, histone deacetylase, virulence-associated proteins

Procedia PDF Downloads 258