Search results for: tomato yield prediction

Authors: Christina Drosou, Konstantina E. Kyriakopoulou, Andreas Bimpilas, Dimitrios Tsimogiannis, Magdalini C. Krokida

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Rationale: Agiorgitiko is one of the most widely-grown and commercially well-established red wine varieties in Greece. Each year viticulture industry produces a large amount of waste consisting of grape skins and seeds (pomace) during a short period. Grapes contain polyphenolic compounds which are partially transferred to wine during winemaking. Therefore, winery wastes could be an alternative cheap source for obtaining such compounds with important antioxidant activity. Specifically, red grape waste contains anthocyanins and flavonols which are characterized by multiple biological activities, including cardioprotective, anti-inflammatory, anti-carcinogenic, antiviral and antibacterial properties attributed mainly to their antioxidant activity. Ultrasound assisted extraction (UAE) is considered an effective way to recover phenolic compounds, since it combines the advantage of mechanical effect with low temperature. Moreover, green solvents can be used in order to recover extracts intended for used in the food and nutraceutical industry. Apart from the extraction, pre-treatment process like drying can play an important role on the preservation of the grape pomace and the enhancement of its antioxidant capacity. Objective: The aim of this study is to recover natural extracts from winery waste with high antioxidant capacity using green solvents so they can be exploited and utilized as enhancers in food or nutraceuticals. Methods: Agiorgitiko grape pomace was dehydrated by air drying (AD) and accelerated solar drying (ASD) in order to explore the effect of the pre-treatment on the recovery of bioactive compounds. UAE was applied in untreated and dried samples using water and water: ethanol (1:1) as solvents. The total antioxidant potential and phenolic content of the extracts was determined using the 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging assay and Folin-Ciocalteu method, respectively. Finally, the profile of anthocyanins and flavonols was specified using HPLC-DAD analysis. The efficiency of processes was determined in terms of extraction yield, antioxidant activity, phenolic content and the anthocyanins and flavovols profile. Results & Discussion: The experiments indicated that the pre-treatment was essential for the recovery of highly nutritious compounds from the pomace as long as the extracts samples showed higher phenolic content and antioxidant capacity. Water: ethanol (1:1) was considered a more effective solvent on the recovery of phenolic compounds. Moreover, ASD grape pomace extracted with the solvent system exhibited the highest antioxidant activity (IC50=0.36±0.01mg/mL) and phenolic content (TPC=172.68±0.01mgGAE/g dry extract), followed by AD and untreated pomace. The major compounds recovered were malvidin3-O-glucoside and quercetin3-O-glucoside according to the HPLC analysis. Conclusions: Winery waste can be exploited for the recovery of nutritious compounds using green solvents such as water or ethanol. The pretreatment of the pomace can significantly affect the concentration of phenolic compounds, while UAE is considered a highly effective extraction process.

Keywords: agiorgitico grape pomace, antioxidants, phenolic compounds, ultrasound assisted extraction

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Authors: Prescilla Lambert, Christophe Roos, Mounim Lebrini

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For several years, the Caribbean islands and West Africa have had to deal with the massive arrival of the brown seaweed Sargassum. Overall, this macroalgae, which constitutes a habitat for a great diversity of marine organisms, is also an additional stress factor for the marine environment (e.g., coral reefs). In addition, the accumulation followed by the significant decomposition of the Sargassum spp. biomass on the coast leads to the release of toxic gases (H₂S and NH₃), which calls into question the functioning of the economic, health and tourist life of the island and the other interested territories. Originally, these algae are formed by the eutrophication of the oceans accentuated by global warming. Unfortunately, scientists predict a significant recurrence of these Sargassum strandings for years to come. It is therefore more than necessary to find solutions by putting in place a sustainable management plan for this phenomenon. Martinique, a small island in the Caribbean arc, is one of the many areas impacted by Sargassum seaweed strandings. Since 2011, there has been a constant increase in the degradation of the materials present in this region, largely due to toxic/corrosive gases released by the algae decomposition. In order to protect the structures and the vulnerable building materials while limiting the use of synthetic/petroleum based molecules as much as possible, research is being conducted on molecules of natural origin. Thus, thanks to the chemical composition, which comprise molecules with interesting properties, algae such as Sargassum could potentially help to solve many issues. Therefore, this study focuses on the green extraction and characterization of molecules from the species Sargassum fluitans and Sargassum natans present in Martinique. The secondary metabolites found in these extracts showed variability in yield rates due to local climatic conditions. The tests carried out shed light on the anticorrosive and antibacterial potential of the algae. These extracts can thus be described as natural inhibitors. The effect of variation in inhibitor concentrations was tested in electrochemistry using electrochemical impedance spectroscopy and polarization curves. The analysis of electrochemical results obtained by direct immersion in the extracts and self-assembled molecular layers (SAMs) for Sargassum fluitans III, Sargassum natans I and VIII species was conclusive in acid and alkaline environments. The excellent results obtained reveal an inhibitory efficacy of 88% at 50mg/L for the crude extract of Sargassum fluitans III and efficacies greater than 97% for the chemical families of Sargassum fluitans III. Similarly, microbiological tests also suggest a bactericidal character. Results for Sargassum fluitans III crude extract show a minimum inhibitory concentration (MIC) of 0.005 mg/mL on Gram-negative bacteria and a MIC greater than 0.6 mg/mL on Gram-positive bacteria. These results make it possible to consider the management of local and international issues while valuing a biomass rich in biodegradable molecules. The next step in this study will therefore be the evaluation of the toxicity of Sargassum spp..

Keywords: Sargassum, secondary metabolites, anticorrosive, antibacterial, natural inhibitors

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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Authors: Meitham Amereh, Mohsen Akbari, Ben Nadler

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Cancer has been recognized as one of the most challenging problems in biology and medicine. Aggressive tumors are a lethal type of cancers characterized by high genomic instability, rapid progression, invasiveness, and therapeutic resistance. Their behavior involves complicated molecular biology and consequential dynamics. Although tremendous effort has been devoted to developing therapeutic approaches, there is still a huge need for new insights into the dark aspects of tumors. As one of the key requirements in better understanding the complex behavior of tumors, mathematical modeling and continuum physics, in particular, play a pivotal role. Mathematical modeling can provide a quantitative prediction on biological processes and help interpret complicated physiological interactions in tumors microenvironment. The pathophysiology of aggressive tumors is strongly affected by the extracellular cues such as stresses produced by mechanical forces between the tumor and the host tissue. During the tumor progression, the growing mass displaces the surrounding extracellular matrix (ECM), and due to the level of tissue stiffness, stress accumulates inside the tumor. The produced stress can influence the tumor by breaking adherent junctions. During this process, the tumor stops the rapid proliferation and begins to remodel its shape to preserve the homeostatic equilibrium state. To reach this, the tumor, in turn, upregulates epithelial to mesenchymal transit-inducing transcription factors (EMT-TFs). These EMT-TFs are involved in various signaling cascades, which are often associated with tumor invasiveness and malignancy. In this work, we modeled the tumor as a growing hyperplastic mass and investigated the effects of mechanical stress from surrounding ECM on tumor invasion. The invasion is modeled as volume-preserving inelastic evolution. In this framework, principal balance laws are considered for tumor mass, linear momentum, and diffusion of nutrients. Also, mechanical interactions between the tumor and ECM is modeled using Ciarlet constitutive strain energy function, and dissipation inequality is utilized to model the volumetric growth rate. System parameters, such as rate of nutrient uptake and cell proliferation, are obtained experimentally. To validate the model, human Glioblastoma multiforme (hGBM) tumor spheroids were incorporated inside Matrigel/Alginate composite hydrogel and was injected into a microfluidic chip to mimic the tumor’s natural microenvironment. The invasion structure was analyzed by imaging the spheroid over time. Also, the expression of transcriptional factors involved in invasion was measured by immune-staining the tumor. The volumetric growth, stress distribution, and inelastic evolution of tumors were predicted by the model. Results showed that the level of invasion is in direct correlation with the level of predicted stress within the tumor. Moreover, the invasion length measured by fluorescent imaging was shown to be related to the inelastic evolution of tumors obtained by the model.

Keywords: cancer, invasion, mathematical modeling, microfluidic chip, tumor spheroids

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Authors: Marcus Goh Tian Xi, Alicia Chua Si Wen, Eunice Gan Ghee Wu, Helen Bound, Lee Liang Ying, Albert Lee

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The Map of Dialogical Inquiry provides a conceptual look at the underlying nature of future-oriented skills. According to the Map, learning is learner-oriented, with conversational time shifted from teachers to learners, who play a strong role in deciding what and how they learn. For example, in courses operating on the principles of Dialogical Inquiry, learners were able to leave the classroom with a deeper understanding of the topic, broader exposure to differing perspectives, and stronger critical thinking capabilities, compared to traditional approaches to teaching. Despite its contributions to learning, the Map is grounded in a qualitative approach both in its development and its application for providing feedback to learners and educators. Studies hinge on openended responses by Map users, which can be time consuming and resource intensive. The present research is motivated by this gap in practicality by aiming to develop and validate a quantitative measure of the Map. In addition, a quantifiable measure may also strengthen applicability by making learning experiences trackable and comparable. The Map outlines eight learning aspects that learners should holistically engage. This research focuses on the Analysing aspect of learning. According to the Map, Analysing has four key components: liking or engaging in logic, using interpretative lenses, seeking patterns, and critiquing and deconstructing. Existing scales of constructs (e.g., critical thinking, rationality) related to these components were identified so that the current scale could adapt items from. Specifically, items were phrased beginning with an “I”, followed by an action phrase, to fulfil the purpose of assessing learners' engagement with Analysing either in general or in classroom contexts. Paralleling standard scale development procedure, the 26-item Analysing scale was administered to 330 participants alongside existing scales with varying levels of association to Analysing, to establish construct validity. Subsequently, the scale was refined and its dimensionality, reliability, and validity were determined. Confirmatory factor analysis (CFA) revealed if scale items loaded onto the four factors corresponding to the components of Analysing. To refine the scale, items were systematically removed via an iterative procedure, according to their factor loadings and results of likelihood ratio tests at each step. Eight items were removed this way. The Analysing scale is better conceptualised as unidimensional, rather than comprising the four components identified by the Map, for three reasons: 1) the covariance matrix of the model specified for the CFA was not positive definite, 2) correlations among the four factors were high, and 3) exploratory factor analyses did not yield an easily interpretable factor structure of Analysing. Regarding validity, since the Analysing scale had higher correlations with conceptually similar scales than conceptually distinct scales, with minor exceptions, construct validity was largely established. Overall, satisfactory reliability and validity of the scale suggest that the current procedure can result in a valid and easy-touse measure for each aspect of the Map.

Keywords: analytical thinking, dialogical inquiry, education, lifelong learning, pedagogy, scale development

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Authors: Jungyeol Hong, Dongjoo Park

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The urban transit system is a critical part of a solution to the economic, energy, and environmental challenges. Furthermore, it ultimately contributes the improvement of people’s quality of lives. For taking these kinds of advantages, the city of Seoul has tried to construct an integrated transit system including both subway and buses. The effort led to the fact that approximately 6.9 million citizens use the integrated transit system every day for their trips. Diagnosing the current transit network is a significant task to provide more convenient and pleasant transit environment. Therefore, the critical objective of this study is to establish a methodological framework for the analysis of an integrated bus-subway network and to examine the relationship between subway ridership and parameters such as network topology measures, bus demand, and a variety of commercial business facilities. Regarding a statistical approach to estimate subway ridership at a station level, many previous studies relied on Ordinary Least Square regression, but there was lack of studies considering the endogeneity issues which might show in the subway ridership prediction model. This study focused on both discovering the impacts of integrated transit network topology measures and endogenous effect of bus demand on subway ridership. It could ultimately contribute to developing more accurate subway ridership estimation accounting for its statistical bias. The spatial scope of the study covers Seoul city in South Korea, and it includes 243 subway stations and 10,120 bus stops with the temporal scope set during twenty-four hours with one-hour interval time panels each. The subway and bus ridership information in detail was collected from the Seoul Smart Card data in 2015 and 2016. First, integrated subway-bus network topology measures which have characteristics regarding connectivity, centrality, transitivity, and reciprocity were estimated based on the complex network theory. The results of integrated transit network topology analysis were compared to subway-only network topology. Also, the non-recursive approach which is Three-Stage Least Square was applied to develop the daily subway ridership model as capturing the endogeneity between bus and subway demands. Independent variables included roadway geometry, commercial business characteristics, social-economic characteristics, safety index, transit facility attributes, and dummies for seasons and time zone. Consequently, it was found that network topology measures were significant size effect. Especially, centrality measures showed that the elasticity was a change of 4.88% for closeness centrality, 24.48% for betweenness centrality while the elasticity of bus ridership was 8.85%. Moreover, it was proved that bus demand and subway ridership were endogenous in a non-recursive manner as showing that predicted bus ridership and predicted subway ridership is statistically significant in OLS regression models. Therefore, it shows that three-stage least square model appears to be a plausible model for efficient subway ridership estimation. It is expected that the proposed approach provides a reliable guideline that can be used as part of the spectrum of tools for evaluating a city-wide integrated transit network.

Keywords: integrated transit system, network topology measures, three-stage least squared, endogeneity, subway ridership

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Shawn Baker-Garcia, Janna O. Schaeffer

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As the global and national communities and governments strive to address ongoing and evolving threats to humanity and pervasive or emerging “shared” global priorities on environmental, economic, political, and security, it is more urgent than ever before to understand each other, communicate effectively with one another, identify models of cooperation that yield improved, mutually reinforcing outcomes across and within cultures. It is within the backdrop of this reality that the presentation examines whether cultural training as we have approached it in recent decades is sufficiently meeting our current needs and what changes may be applied to foster better and more productive and sustainable intercultural interactions. Domestic and global relations face multiple challenges to peaceable cooperation. The last two years, in particular, have been defined by a travel-restricted COVID-19 pandemic yielding increased intercultural interactions over virtual platforms, polarized politics dividing nations and regions, and the commensurate rise in weaponized social and traditional media communication. These societal and cultural fissures are noticeably challenging our collective and individual abilities to constructively interact both at home and abroad. It is within this pressure cooker environment that the authors believe it is time to reexamine existing and broadly accepted inter- and cross- cultural training approaches and concepts to determine their level of effectiveness in setting conditions for optimal human understanding and relationships both in the national and international context. In order to better understand the amount and the type of intercultural training practitioners professionally engaging in international partnership building have received throughout their careers and its perceived effectiveness, a survey was designed and distributed to US and international professionals presently engaged in the fields of diplomacy, military, academia, and international business. The survey questions were deigned to address the two primary research questions investigators posed in this exploratory study. Research questions aimed to examine practitioners’ view of the role and effectiveness of current and traditional cultural training and education as a means to fostering improved communication, interactions, understanding, and cooperation among inter, cross, or multi-cultural communities or efforts.Responses were then collected and analyzed for themes present in the participants’ reflections. In their responses, the practitioners identified the areas of improvement and desired outcomes in regards to intercultural training and awareness raising curricular approaches. They also raised issues directly and indirectly pertaining to the role of foreign language proficiency in intercultural interactions and a need for a solid grasp on cultural and regional issues (regional expertise) to facilitate such an interaction. Respondents indicated knowledge, skills, abilities, and capabilities that the participants were not trained on but learned through ad hoc personal and professional intercultural interactions, which they found most valuable and wished they had acquired prior to the intercultural experience.

Keywords: cultural training, improved communication, intercultural competence, international cooperation

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Authors: Ntandazo Dlatu, Benjamin Longo-Mbenza, Andre Renzaho, Ruffin Appalata, Yolande Yvonne Valeria Matoumona Mavoungou, Mbenza Ben Longo, Kenneth Ekoru, Blaise Makoso, Gedeon Longo Longo

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Background: The gap between complexities related to the integration of Tuberculosis /HIV control and evidence-based knowledge motivated the initiation of the study. Therefore, the objective of this study was to explore correlations between national TB management guidelines, multiple deprivation indexes, quantiles, components and levels of Tuberculosis control programme using mathematical modeling in rural O.R. Tambo District Health Facilities, South Africa. Methods: The study design used mixed secondary data analysis and cross-sectional analysis between 2009 and 2013 across O.R Tambo District, Eastern Cape, South Africa using univariate/ bivariate analysis, linear multiple regression models, and multivariate discriminant analysis. Health inequalities indicators and component of an impediment to the tuberculosis control programme were evaluated. Results: In total, 62 400 records for TB notification were analyzed for the period 2009-2013. There was a significant but negative between Financial Year Expenditure (r= -0.894; P= 0.041) Seropositive HIV status(r= -0.979; P= 0.004), Population Density (r = -0.881; P= 0.048) and the number of TB defaulter in all TB cases. It was shown unsuccessful control of TB management program through correlations between numbers of new PTB smear positive, TB defaulter new smear-positive, TB failure all TB, Pulmonary Tuberculosis case finding index and deprivation-concentration-dispersion index. It was shown successful TB program control through significant and negative associations between declining numbers of death in co-infection of HIV and TB, TB deaths all TB and SMIAD gradient/ deprivation-concentration-dispersion index. The multivariate linear model was summarized by unadjusted r of 96%, adjusted R2 of 95 %, Standard Error of estimate of 0.110, R2 changed of 0.959 and significance for variance change for P=0.004 to explain the prediction of TB defaulter in all TB with equation y= 8.558-0.979 x number of HIV seropositive. After adjusting for confounding factors (PTB case finding the index, TB defaulter new smear-positive, TB death in all TB, TB defaulter all TB, and TB failure in all TB). The HIV and TB death, as well as new PTB smear positive, were identified as the most important, significant, and independent indicator to discriminate most deprived deprivation index far from other deprivation quintiles 2-5 using discriminant analysis. Conclusion: Elimination of poverty such as overcrowding, lack of sanitation and environment of highest burden of HIV might end the TB threat in O.R Tambo District, Eastern Cape, South Africa. Furthermore, ongoing adequate budget comprehensive, holistic and collaborative initiative towards Sustainable Developmental Goals (SDGs) is necessary for complete elimination of TB in poor O.R Tambo District.

Keywords: tuberculosis, HIV/AIDS, success, failure, control program, health inequalities, South Africa

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Rishana Bilimoria, Selina Tang, Sajni Shah, Marianne Henien, Christopher Sproat

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Temporomandibular disorders (TMD) may affect up to a third of the general population, and there is evidence demonstrating the majority of Myofascial TMD cases improve after education and conservative measures. In 2015 our department implemented a modified care pathway for myofascial TMD patients in an attempt to improve the patient journey. This involved the use of an interactive group therapy approach to deliver education, reinforce conservative measures and promote self-management. Patient reported experience measures from the new group clinic revealed 71% patient satisfaction. This service is efficient in improving aspects of health status while reducing health-care costs and redistributing clinical time. Since its’ establishment, 52 hours of clinical time, resources and funding have been redirected effectively. This Quality Improvement Project was initiated because it was felt that this new service was being underutilised by our surgical teams. The ‘Plan-Do-Study-Act cycle’ (PDSA) framework was employed to analyse utilisation of the service: The ‘plan’ stage involved outlining our aims: to raise awareness amongst clinicians of the unified care pathway and to increase referral to this clinic. The ‘do’ stage involved collecting data from a sample of 96 patients over 4 month period to ascertain the proportion of Myofascial TMD patients who were correctly referred to the designated clinic. ‘Suitable’ patients who weren’t referred were identified. The ‘Study’ phase involved analysis of results, which revealed that 77% of suitable patients weren’t referred to the designated clinic. They were reviewed on other clinics, which are often overbooked, or managed by junior staff members. This correlated with our original prediction. Barriers to referral included: lack of awareness of the clinic, individual consultant treatment preferences and patient, reluctance to be referred to a ‘group’ clinic. The ‘Act’ stage involved presenting our findings to the team at a clinical governance meeting. This included demonstration of the clinical effectiveness of the care-pathway and explaining the referral route and criteria. In light of the evaluation results, it was decided to keep the group clinic and maximize utilisation. The second cycle of data collection following these changes revealed that of 66 Myofascial TMD patients over a 4 month period, only 9% of suitable patients were not seen via the designated pathway; therefore this QIP was successful in meeting the set objectives. Overall, employing the PDSA cycle in this QIP resulted in appropriate utilisation of the modified care pathway for patients with myofascial TMD in Guy’s Oral Surgery Department. In turn, this leads to high patient satisfaction with the service and effectively redirected 52 hours of clinical time. It permitted adoption of a collaborative working style with oral surgery colleagues to investigate problems, identify solutions, and collectively raise standards of clinical care to ensure we adopt a unified care pathway in secondary care management of Myofascial TMD patients.

Keywords: myofascial, quality Improvement, PDSA, TMD

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Authors: Inas Raafat, Azza El Bassiouny, Waldemar L. Olszewsky, Nagui E. Mikhail, Mona Nossier, Nora E. I. El-Bassiouni, Mona Zoheiry, Houda Abou Taleb, Noha Abd El-Aal, Ali Baioumy, Shimaa Attia

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Background: Orthotopic liver transplantation is an established treatment for patients with severe acute and end-stage chronic liver disease. The shortage of donor organs continues to be the rate-limiting factor for liver transplantation throughout the world. Hepatocyte transplantation is a promising treatment for several liver diseases and can, also, be used as a "bridge" to liver transplantation in cases of liver failure. Aim of the work: This study was designed to develop a highly efficient protocol for isolation and transplantation of hepatocytes in experimental Lewis rat model to provide satisfactory guidelines for future application on humans.Materials and Methods: Hepatocytes were isolated from the liver by double perfusion technique and bone marrow cells were isolated by centrifugation of shafts of tibia and femur of donor Lewis rats. Recipient rats were subjected to sub-lethal dose of irradiation 2 days before transplantation. In a laparotomy operation the spleen was injected by freshly isolated hepatocytes and bone marrow cells were injected intravenously. The animals were sacrificed 45 day latter and splenic sections were prepared and stained with H & E, PAS AFP and Prox1. Results: The data obtained from this study showed that the double perfusion technique is successful in separation of hepatocytes regarding cell number and viability. Also the method used for bone marrow cells separation gave excellent results regarding cell number and viability. Intrasplenic engraftment of hepatocytes and live tissue formation within the splenic tissue were found in 70% of cases. Hematoxylin and eosin stained splenic sections from 7 rats showed sheets and clusters of cells among the splenic tissues. Periodic Acid Schiff stained splenic sections from 7 rats showed clusters of hepatocytes with intensely stained pink cytoplasmic granules denoting the presence of glycogen. Splenic sections from 7 rats stained with anti-α-fetoprotein antibody showed brownish cytoplasmic staining of the hepatocytes denoting positive expression of AFP. Splenic sections from 7 rats stained with anti-Prox1 showed brownish nuclear staining of the hepatocytes denoting positive expression of Prox1 gene on these cells. Also, positive expression of Prox1 gene was detected on lymphocytes aggregations in the spleens. Conclusions: Isolation of liver cells by double perfusion technique using collagenase buffer is a reliable method that has a very satisfactory yield regarding cell number and viability. The intrasplenic route of transplantation of the freshly isolated liver cells in an immunocompromised model was found to give good results regarding cell engraftment and tissue formation. Further studies are needed to assess function of engrafted hepatocytes by measuring prothrombin time, serum albumin and bilirubin levels.

Keywords: Lewis rats, hepatocytes, BMCs, transplantation, AFP, Prox1

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Authors: Berengere Vire, Nicolas Salvetat, Yoann Lannay, Guillaume Marcellin, Siem Van Der Laan, Franck Molina, Dinah Weissmann

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Predicting suicidal behaviors is one of the most complex challenges of daily psychiatric practices. Today, suicide risk prediction using biological tools is not validated and is only based on subjective clinical reports of the at-risk individual. Therefore, there is a great need to identify biomarkers that would allow early identification of individuals at risk of suicide. Alterations of adenosine-to-inosine (A-to-I) RNA editing of neurotransmitter receptors and other proteins have been shown to be involved in etiology of different psychiatric disorders and linked to suicidal behavior. RNA editing is a co- or post-transcriptional process leading to a site-specific alteration in RNA sequences. It plays an important role in the epi transcriptomic regulation of RNA metabolism. On postmortem human brain tissue (prefrontal cortex) of depressed suicide victims, Alcediag found specific alterations of RNA editing activity on the mRNA coding for the serotonin 2C receptor (5-HT2cR). Additionally, an increase in expression levels of ADARs, the RNA editing enzymes, and modifications of RNA editing profiles of prime targets, such as phosphodiesterase 8A (PDE8A) mRNA, have also been observed. Interestingly, the PDE8A gene is located on chromosome 15q25.3, a genomic region that has recurrently been associated with the early-onset major depressive disorder (MDD). In the current study, we examined whether modifications in RNA editing profile of prime targets allow identifying disease-relevant blood biomarkers and evaluating suicide risk in patients. To address this question, we performed a clinical study to identify an RNA editing signature in blood of depressed patients with and without the history of suicide attempts. Patient’s samples were drawn in PAXgene tubes and analyzed on Alcediag’s proprietary RNA editing platform using next generation sequencing technology. In addition, gene expression analysis by quantitative PCR was performed. We generated a multivariate algorithm comprising various selected biomarkers to detect patients with a high risk to attempt suicide. We evaluated the diagnostic performance using the relative proportion of PDE8A mRNA editing at different sites and/or isoforms as well as the expression of PDE8A and the ADARs. The significance of these biomarkers for suicidality was evaluated using the area under the receiver-operating characteristic curve (AUC). The generated algorithm comprising the biomarkers was found to have strong diagnostic performances with high specificity and sensitivity. In conclusion, we developed tools to measure disease-specific biomarkers in blood samples of patients for identifying individuals at the greatest risk for future suicide attempts. This technology not only fosters patient management but is also suitable to predict the risk of drug-induced psychiatric side effects such as iatrogenic increase of suicidal ideas/behaviors.

Keywords: blood biomarker, next-generation-sequencing, RNA editing, suicide

Procedia PDF Downloads 258

Authors: Ola Hall, Ibrahim Wahab, Thorsteinn Rognvaldsson, Mattias Ohlsson

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The subfield of poverty and welfare estimation that applies machine learning tools and methods on satellite imagery is a nascent but rapidly growing one. This is in part driven by the sustainable development goal, whose overarching principle is that no region is left behind. Among other things, this requires that welfare levels can be accurately and rapidly estimated at different spatial scales and resolutions. Conventional tools of household surveys and interviews do not suffice in this regard. While they are useful for gaining a longitudinal understanding of the welfare levels of populations, they do not offer adequate spatial coverage for the accuracy that is needed, nor are their implementation sufficiently swift to gain an accurate insight into people and places. It is this void that satellite imagery fills. Previously, this was near-impossible to implement due to the sheer volume of data that needed processing. Recent advances in machine learning, especially the deep learning subtype, such as deep neural networks, have made this a rapidly growing area of scholarship. Despite their unprecedented levels of performance, such models lack transparency and explainability and thus have seen limited downstream applications as humans generally are apprehensive of techniques that are not inherently interpretable and trustworthy. While several studies have demonstrated the superhuman performance of AI models, none has directly compared the performance of such models and human readers in the domain of poverty studies. In the present study, we directly compare the performance of human readers and a DL model using different resolutions of satellite imagery to estimate the welfare levels of demographic and health survey clusters in Tanzania, using the wealth quintile ratings from the same survey as the ground truth data. The cluster-level imagery covers all 608 cluster locations, of which 428 were classified as rural. The imagery for the human readers was sourced from the Google Maps Platform at an ultra-high resolution of 0.6m per pixel at zoom level 18, while that of the machine learning model was sourced from the comparatively lower resolution Sentinel-2 10m per pixel data for the same cluster locations. Rank correlation coefficients of between 0.31 and 0.32 achieved by the human readers were much lower when compared to those attained by the machine learning model – 0.69-0.79. This superhuman performance by the model is even more significant given that it was trained on the relatively lower 10-meter resolution satellite data while the human readers estimated welfare levels from the higher 0.6m spatial resolution data from which key markers of poverty and slums – roofing and road quality – are discernible. It is important to note, however, that the human readers did not receive any training before ratings, and had this been done, their performance might have improved. The stellar performance of the model also comes with the inevitable shortfall relating to limited transparency and explainability. The findings have significant implications for attaining the objective of the current frontier of deep learning models in this domain of scholarship – eXplainable Artificial Intelligence through a collaborative rather than a comparative framework.

Keywords: poverty prediction, satellite imagery, human readers, machine learning, Tanzania

Procedia PDF Downloads 105

Authors: Jacques M. Berner, Lehlogonolo Maloma

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Context: Glyphosate, a widely used herbicide, has raised concerns about its impact on various crops. Amaranthus cruentus, an important grain crop species, is particularly susceptible to glyphosate. Understanding the specific disruptions caused by glyphosate on the photosynthetic process in Amaranthus cruentus is crucial for assessing its effects on crop productivity and ecological sustainability. Research Aim: This study aimed to investigate the dose-dependent impact of glyphosate on the photochemical efficiency of Amaranthus cruentus using the OJIP transient analysis. The goal was to assess the specific disruptions caused by glyphosate on key parameters of photosystem II. Methodology: The experiment was conducted in a controlled greenhouse environment. Amaranthus cruentus plants were exposed to different concentrations of glyphosate, including half, recommended, and double the recommended application rates. The photochemical efficiency of the plants was evaluated using non-invasive chlorophyll a fluorescence measurements and subsequent analysis of OJIP transients. Measurements were taken on 1-hour dark-adapted leaves using a Hansatech Handy PEA+ chlorophyll fluorimeter. Findings: The study's results demonstrated a significant reduction in the photochemical efficiency of Amaranthus cruentus following glyphosate treatment. The OJIP transients showed distinct alterations in the glyphosate-treated plants compared to the control group. These changes included a decrease in maximal fluorescence (FP) and a delay in the rise of the fluorescence signal, indicating impairment in the energy conversion process within the photosystem II. Glyphosate exposure also led to a substantial decrease in the maximum quantum yield efficiency of photosystem II (FV/FM) and the total performance index (PItotal), which reflects the overall photochemical efficiency of photosystem II. These reductions in photochemical efficiency were observed even at half the recommended dose of glyphosate. Theoretical Importance: The study provides valuable insights into the specific disruptions caused by glyphosate on the photochemical efficiency of Amaranthus cruentus. Data Collection and Analysis Procedures: Data collection involved non-invasive chlorophyll a fluorescence measurements using a chlorophyll fluorimeter on dark-adapted leaves. The OJIP transients were then analyzed to assess specific disruptions in key parameters of photosystem II. Statistical analysis was conducted to determine the significance of the differences observed between glyphosate-treated plants and the control group. Question Addressed: The study aimed to address the question of how glyphosate exposure affects the photochemical efficiency of Amaranthus cruentus, specifically examining disruptions in the photosynthetic electron transport chain and overall photochemical efficiency. Conclusion: The study demonstrates that glyphosate severely impairs the photochemical efficiency of Amaranthus cruentus, as indicated by the alterations in OJIP transients. Even at half the recommended dose, glyphosate caused significant reductions in photochemical efficiency. These findings highlight the detrimental effects of glyphosate on crop productivity and emphasize the need for further research to evaluate its long-term consequences and ecological implications in agriculture. The authors gratefully acknowledge the support from North-West University for making this research possible.

Keywords: glyphosate, amaranthus cruentus, ojip transient analysis, pitotal, photochemical efficiency, chlorophyll fluorescence, weeds

Procedia PDF Downloads 91

Authors: Zamira Sattinova, Tassybek Bekenov

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The article is devoted to modeling the technology of hot casting of beryllium oxide ceramics. The stages of ultrasonic activation of beryllium oxide slurry in the plant vessel to improve the rheological property, hot casting in the moulding cavity with cooling and solidification of the casting are described. Thermoplastic slurry (hereinafter referred to as slurry) shows the rheology of a non-Newtonian fluid with yield and plastic viscosity. Cooling-solidification of the slurry in the forming cavity occurs in the liquid, taking into account crystallization and solid state. In this work is the method of calculation of hot casting of the slurry using the method of effective molecular viscosity of viscoplastic fluid. It is shown that the slurry near the cooled wall is in a state of crystallization and plasticity, and the rest may still be in the liquid phase. Nonuniform distribution of temperature, density and concentration of kinetically free binder takes place along the cavity section. This leads to compensation of shrinkage by the influx of slurry from the liquid into the crystallization zones and plasticity of the castings. In the plasticity zone, the shrinkage determined by the concentration of kinetically free binder is compensated under the action of the pressure gradient. The solidification mechanism, as well as the mechanical behavior of the casting mass during casting, the rheological and thermophysical properties of the thermoplastic BeO slurry due to ultrasound exposure have not been well studied. Nevertheless, experimental data allow us to conclude that the effect of ultrasonic vibrations on the slurry mass leads to it: a change in structure, an increase in technological properties, a decrease in heterogeneity and a change in rheological properties. In the course of experiments, the effect of ultrasonic treatment and its duration on the change in viscosity and ultimate shear stress of the slurry depending on temperature (55-75℃) and the mass fraction of the binder (10 - 11.7%) have been studied. At the same time, changes in these properties before and after ultrasound exposure have been analyzed, as well as the nature of the flow in the system under study. The experience of operating the unit with ultrasonic impact has shown that at the same time, the casting capacity of the slurry increases by an average of 15%, and the viscosity decreases by more than half. Experimental study of physicochemical properties and phase change with simultaneous consideration of all factors affecting the quality of products in the process of continuous casting is labor-intensive. Therefore, an effective way to control the physical processes occurring in the formation of articles with predetermined properties and shapes is to simulate the process and determine its basic characteristics. The results of the calculations show the whole stage of hot casting of beryllium oxide slurry, taking into account the change in its state of aggregation. Ultrasonic treatment improves rheological properties and increases the fluidity of the slurry in the forming cavity. Calculations show the influence of velocity, temperature factors and structural data of the cavity on the cooling-solidification process of the casting. In the calculations, conditions for molding with shrinkage of the slurry by hot casting have been found, which makes it possible to obtain a solidifying product with a uniform beryllium oxide structure at the outlet of the cavity.

Keywords: hot casting, thermoplastic slurry molding, shrinkage, beryllium oxide

Procedia PDF Downloads 23

Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

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Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of biomass platform, comprising a potential pool of hydrogen energy that stands as a new energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need of in-situ H2 production, which plays a key role in the hydrogenation reactions of biomass into higher value components. It is reported elsewhere in literature that catalytic decomposition of FA is usually performed in poorly designed setup using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. it work suggests an approach that integrates designing a novel catalyst featuring magnetic property with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H2 gas from FA. Using ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under inert medium. Through a novel approach, FA is charged into the reactor via high-pressure positive displacement pump at steady state conditions. The produced gas (H2+CO2) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The novelty of this work lies in designing a very responsive catalyst, pumping consistent amount of FA into a sealed reactor running at steady state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at lower temperature range (35-50°C) yielded more gas while the catalyst loading and Pd doping wt.% were found to be the most significant factors with a P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

Procedia PDF Downloads 52

Authors: Ganesh V., Asit Kumar Khanra

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An in-situ powder metallurgy technique was employed to create Ni-Al3Ni/Al3Ni2 core-shell-shaped aluminum-based intermetallic reinforced composites. The impact of Ni addition on the phase composition, microstructure, and mechanical characteristics of the Al-4Cu-xNi (x = 0, 2, 4, 6, 8, 10 wt.%) in relation to various sintering temperatures was investigated. Microstructure evolution was extensively examined using X-ray diffraction (XRD), scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), and transmission electron microscopy (TEM) techniques. Initially, under sintering conditions, the formation of "Single Core-Shell" structures was observed, consisting of Ni as the core with Al3Ni2 intermetallic, whereas samples sintered at 620°C exhibited both "Single Core-Shell" and "Double Core-Shell" structures containing Al3Ni2 and Al3Ni intermetallics formed between the Al matrix and Ni reinforcements. The composite achieved a high compressive yield strength of 198.13 MPa and ultimate strength of 410.68 MPa, with 24% total elongation for the sample containing 10 wt.% Ni. Additionally, there was a substantial increase in hardness, reaching 124.21 HV, which is 2.4 times higher than that of the base aluminum. Nanoindentation studies showed hardness values of 1.54, 4.65, 21.01, 13.16, 5.52, 6.27, and 8.39GPa corresponding to α-Al matrix, Ni, Al3Ni2, Ni and Al3Ni2 interface, Al3Ni, and their respective interfaces. Even at 200°C, it retained 54% of its room temperature strength (90.51 MPa). To investigate the deformation behavior of the composite material, experiments were conducted at deformation temperatures ranging from 300°C to 500°C, with strain rates varying from 0.0001s-1 to 0.1s-1. A sine-hyperbolic constitutive equation was developed to characterize the flow stress of the composite, which exhibited a significantly higher hot deformation activation energy of 231.44 kJ/mol compared to the self-diffusion of pure aluminum. The formation of Al2Cu intermetallics at grain boundaries and Al3Ni2/Al3Ni within the matrix hindered dislocation movement, leading to an increase in activation energy, which might have an adverse effect on high-temperature applications. Two models, the Strain-compensated Arrhenius model and the Artificial Neural Network (ANN) model, were developed to predict the composite's flow behavior. The ANN model outperformed the Strain-compensated Arrhenius model with a lower average absolute relative error of 2.266%, a smaller root means square error of 1.2488 MPa, and a higher correlation coefficient of 0.9997. Processing maps revealed that the optimal hot working conditions for the composite were in the temperature range of 420-500°C and strain rates between 0.0001s-1 and 0.001s-1. The changes in the composite microstructure were successfully correlated with the theory of processing maps, considering temperature and strain rate conditions. The uneven distribution in the shape and size of Core-shell/Al3Ni intermetallic compounds influenced the flow stress curves, leading to Dynamic Recrystallization (DRX), followed by partial Dynamic Recovery (DRV), and ultimately strain hardening. This composite material shows promise for applications in the automobile and aerospace industries.

Keywords: core-shell structure, hot deformation, intermetallic compounds, powder metallurgy

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Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

Procedia PDF Downloads 208

Authors: Nisha Sharma, Mili Kaur, Ashutosh Halder, Seema Kaushal, Manoj Kumar, Manish Jain

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Purpose: To investigate microRNAs (miRNA) as an epigenomic etiological factor in idiopathic non-obstructive azoospermia (NOA). In order to achieve the same, an association was seen between occupational exposure to radiation, thermal, and chemical factors and idiopathic cases of non-obstructive azoospermia, and later, testicular differential miRNA expression profiling was done in exposure group NOA cases. Method: It is a prospective study in which 200 apparent idiopathic male factor infertility cases, who have been advised to undergo testicular fine needle aspiration (FNA) evaluation, are recruited. A detailed occupational history was taken to understand the possible type of exposure due to the nature and duration of work. A total of 26 patients were excluded upon XY-FISH and Yq microdeletion tests due to the presence of genetic causes of infertility, 6 hypospermatogeneis (HS), six Sertoli cell-only syndrome (SCOS), and six normospermatogeneis patients testicular FNA samples were used for RNA isolation followed by small RNA sequencing and nCounter miRNA expression analysis. Differential miRNA expression profile of HS and SCOS patients was done. A web-based tool, miRNet, was used to predict the interacting compounds or chemicals using the shortlisted miRNAs with high fold change. The major limitation encountered in this study was the insufficient quantity of testicular FNA sample used for total RNA isolation, which resulted in a low yield and RNA integrity number (RIN) value. Therefore, the number of RNA samples admissible for differential miRNA expression analysis was very small in comparison to the total number of patients recruited. Results: Differential expression analysis revealed 69 down-regulated and 40 up-regulated miRNAs in HS and 66 down-regulated and 33 up-regulated miRNAs in SCOS in comparison to normospermatogenesis controls. The miRNA interaction analysis using the miRNet tool showed that the differential expression profiles of HS and SCOS patients were associated with arsenic trioxide, bisphenol-A, calcium sulphate, lithium, and cadmium. These compounds are reproductive toxins and might be responsible for miRNA-mediated epigenetic deregulation leading to NOA. The association between occupational risk factor exposure and the non-exposure group of NOA patients was not statistically significant, with ꭓ2 (3, N= 178) = 6.70, p= 0.082. The association between individual exposure groups (radiation, thermal, and chemical) and various sub-types of NOA is also not significant, with ꭓ2 (9, N= 178) = 15.06, p= 0.089. Functional analysis of HS and SCOS patients' miRNA profiles revealed some important miR-family members in terms of male fertility. The miR-181 family plays a role in the differentiation of spermatogonia and spermatocytes, as well as the transcriptional regulation of haploid germ cells. The miR-34 family is expressed in spermatocytes and round spermatids and is involved in the regulation of SSCs differentiation. Conclusion: The reproductive toxins might adopt the miRNA-mediated mechanism of disease development in idiopathic cases of NOA. Chemical compound induced; miRNA-mediated epigenetic deregulation can give a future perspective on the etiopathogenesis of the disease.

Keywords: microRNA, non-obstructive azoospermia (NOA), occupational exposure, hypospermatogenesis (HS), Sertoli cell only syndrome (SCOS)

Procedia PDF Downloads 87

Authors: Weili Jiang, Simon Cadavid Lopera, Klaus Drechsler

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Fuel cell vehicle has become the most competitive solution for the transportation sector in the hydrogen economy. Type IV pressure vessel is currently the most popular and widely developed technology for the on-board storage, based on their high reliability and relatively low cost. Due to the stringent requirement on mechanical performance, the pressure vessel is subject to great amount of composite material, a major cost driver for the hydrogen tanks. Evidently, the optimization of composite layup design shows great potential in reducing the overall material usage, yet requires comprehensive understanding on underlying mechanisms as well as the influence of different design parameters on mechanical performance. Given the type of materials and manufacturing processes by which the type IV pressure vessels are manufactured, the design and optimization are a nuanced subject. The manifold of stacking sequence and fiber orientation variation possibilities have an out-standing effect on vessel strength due to the anisotropic property of carbon fiber composites, which make the design space high dimensional. Each variation of design parameters requires computational resources. Using finite element analysis to evaluate different designs is the most common method, however, the model-ing, setup and simulation process can be very time consuming and result in high computational cost. For this reason, it is necessary to build a reliable automation scheme to set up and analyze the di-verse composite layups. In this research, the simulation process of different tank designs regarding various parameters is conducted and automatized in a commercial finite element analysis framework Abaqus. Worth mentioning, the modeling of the composite overwrap is automatically generated using an Abaqus-Python scripting interface. The prediction of the winding angle of each layer and corresponding thickness variation on dome region is the most crucial step of the modeling, which is calculated and implemented using analytical methods. Subsequently, these different composites layups are simulated as axisymmetric models to facilitate the computational complexity and reduce the calculation time. Finally, the results are evaluated and compared regarding the ultimate tank strength. By automatically modeling, evaluating and comparing various composites layups, this system is applicable for the optimization of the tanks structures. As mentioned above, the mechanical property of the pressure vessel is highly dependent on composites layup, which requires big amount of simulations. Consequently, to automatize the simulation process gains a rapid way to compare the various designs and provide an indication of the optimum one. Moreover, this automation process can also be operated for creating a data bank of layups and corresponding mechanical properties with few preliminary configuration steps for the further case analysis. Subsequently, using e.g. machine learning to gather the optimum by the data pool directly without the simulation process.

Keywords: type IV pressure vessels, carbon composites, finite element analy-sis, automation of simulation process

Procedia PDF Downloads 135

Authors: Natalia C. E. S. Nascimento, Mercia L. Oliveira, Fernando R. A. Lima, Leonardo T. C. do Nascimento, Marina B. Silveira, Brigida G. A. Schirmer, Andrea V. Ferreira, Carlos Malamut, Juliana B. da Silva

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Tissue hypoxia is a common characteristic of solid tumors leading to decreased sensitivity to radiotherapy and chemotherapy. In the clinical context, tumor hypoxia assessment employing the positron emission tomography (PET) tracer ¹⁸F-fluoromisonidazole ([¹⁸F]FMISO) is helpful for physicians for planning and therapy adjusting. The aim of this work was to implement the synthesis of 18F-FMISO in a TRACERlab® MXFDG module and also to establish the quality control procedure. [¹⁸F]FMISO was synthesized at Centro de Desenvolvimento da Tecnologia Nuclear (CDTN/CNEN/Brazil) using an automated synthesizer (TRACERlab® MXFDG, GE) adapted for the production of [¹⁸F]FMISO. The FMISO chemical standard was purchased from ABX. 18O- enriched water was acquired from Center of Molecular Research. Reagent kits containing eluent solution, acetonitrile, ethanol, 2.0 M HCl solution, buffer solution, water for injections and [¹⁸F]FMISO precursor (dissolved in 2 ml acetonitrile) were purchased from ABX. The [¹⁸F]FMISO samples were purified by Solid Phase Extraction method. The quality requirements of [¹⁸F]FMISO are established in the European Pharmacopeia. According to that reference, quality control of [¹⁸F]FMISO should include appearance, pH, radionuclidic identity and purity, radiochemical identity and purity, chemical purity, residual solvents, bacterial endotoxins, and sterility. The duration of the synthesis process was 53 min, with radiochemical yield of (37.00 ± 0.01) % and the specific activity was more than 70 GBq/µmol. The syntheses were reproducible and showed satisfactory results. In relation to the quality control analysis, the samples were clear and colorless at pH 6.0. The spectrum emission, measured by using a High-Purity Germanium Detector (HPGe), presented a single peak at 511 keV and the half-life, determined by the decay method in an activimeter, was (111.0 ± 0.5) min, indicating no presence of radioactive contaminants, besides the desirable radionuclide (¹⁸F). The samples showed concentration of tetrabutylammonium (TBA) < 50μg/mL, assessed by visual comparison to TBA standard applied in the same thin layer chromatographic plate. Radiochemical purity was determined by high performance liquid chromatography (HPLC) and the results were 100%. Regarding the residual solvents tested, ethanol and acetonitrile presented concentration lower than 10% and 0.04%, respectively. Healthy female mice were injected via lateral tail vein with [¹⁸F]FMISO, microPET imaging studies (15 min) were performed after 2 h post injection (p.i), and the biodistribution was analyzed in five-time points (30, 60, 90, 120 and 180 min) after injection. Subsequently, organs/tissues were assayed for radioactivity with a gamma counter. All parameters of quality control test were in agreement to quality criteria confirming that [¹⁸F]FMISO was suitable for use in non-clinical and clinical trials, following the legal requirements for the production of new radiopharmaceuticals in Brazil.

Keywords: automatic radiosynthesis, hypoxic tumors, pharmacopeia, positron emitters, quality requirements

Procedia PDF Downloads 193

Authors: Sabrina Neururer, Marco Schweitzer, Werner Hackl, Bernhard Tilg, Patrick Raudaschl, Andreas Huber, Bernhard Pfeifer

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History and the current outbreak of Covid-19 have shown the deadly potential of infectious diseases. However, infectious diseases also have a serious impact on areas other than health and healthcare, such as the economy or social life. These areas are strongly codependent. Therefore, disease control measures, such as social distancing, quarantines, curfews, or lockdowns, have to be adopted in a very considerate manner. Infectious disease modeling can support policy and decision-makers with adequate information regarding the dynamics of the pandemic and therefore assist in planning and enforcing appropriate measures that will prevent the healthcare system from collapsing. In this work, an agent-based simulation package named “survival” for simulating infectious diseases is presented. A special focus is put on SARS-Cov-2. The presented simulation package was used in Austria to model the SARS-Cov-2 outbreak from the beginning of 2020. Agent-based modeling is a relatively recent modeling approach. Since our world is getting more and more complex, the complexity of the underlying systems is also increasing. The development of tools and frameworks and increasing computational power advance the application of agent-based models. For parametrizing the presented model, different data sources, such as known infections, wastewater virus load, blood donor antibodies, circulating virus variants and the used capacity for hospitalization, as well as the availability of medical materials like ventilators, were integrated with a database system and used. The simulation result of the model was used for predicting the dynamics and the possible outcomes and was used by the health authorities to decide on the measures to be taken in order to control the pandemic situation. The survival package was implemented in the programming language Java and the analytics were performed with R Studio. During the first run in March 2020, the simulation showed that without measures other than individual personal behavior and appropriate medication, the death toll would have been about 27 million people worldwide within the first year. The model predicted the hospitalization rates (standard and intensive care) for Tyrol and South Tyrol with an accuracy of about 1.5% average error. They were calculated to provide 10-days forecasts. The state government and the hospitals were provided with the 10-days models to support their decision-making. This ensured that standard care was maintained for as long as possible without restrictions. Furthermore, various measures were estimated and thereafter enforced. Among other things, communities were quarantined based on the calculations while, in accordance with the calculations, the curfews for the entire population were reduced. With this framework, which is used in the national crisis team of the Austrian province of Tyrol, a very accurate model could be created on the federal state level as well as on the district and municipal level, which was able to provide decision-makers with a solid information basis. This framework can be transferred to various infectious diseases and thus can be used as a basis for future monitoring.

Keywords: modelling, simulation, agent-based, SARS-Cov-2, COVID-19

Procedia PDF Downloads 174

Authors: Dagmara A. Niedziela, Mark P. Murphy, Orla M. Keane, Finola C. Leonard

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Staphylococcus aureus is the most frequent cause of clinical and subclinical bovine mastitis in Ireland. Mastitis caused by S. aureus is often chronic and tends to recur after antibiotic treatment. This may be due to several virulence factors, including attributes that enable the bacterium to internalize into bovine mammary epithelial cells, where it may evade antibiotic treatment, or evade the host immune response. Four bovine-adapted lineages (CC71, CC97, CC151 and ST136) were identified among a collection of Irish S. aureus mastitis isolates. Genotypic variation of mastitis-causing strains may contribute to different presentations of the disease, including differences in milk somatic cell count (SCC), the main method of mastitis detection. The objective of this study was to investigate the influence of bacterial strain and lineage on host immune response, by employing cell culture methods in vitro as well as an in vivo infection model. Twelve bovine adapted S. aureus strains were examined for internalization into bovine mammary epithelial cells (bMEC) and their ability to induce an immune response from bMEC (using qPCR and ELISA). In vitro studies found differences in a variety of virulence traits between the lineages. Strains from lineages CC97 and CC71 internalized more efficiently into bovine mammary epithelial cells (bMEC) than CC151 and ST136. CC97 strains also induced immune genes in bMEC more strongly than strains from the other 3 lineages. One strain each of CC151 and CC97 that differed in their ability to cause an immune response in bMEC were selected on the basis of the above in vitro experiments. Fourteen first-lactation Holstein-Friesian cows were purchased from 2 farms on the basis of low SCC (less than 50 000 cells/ml) and infection free status. Seven cows were infected with 1.73 x 102 c.f.u. of the CC97 strain (Group 1) and another seven with 5.83 x 102 c.f.u. of the CC151 strain (Group 2). The contralateral quarter of each cow was inoculated with PBS (vehicle). Clinical signs of infection (temperature, milk and udder appearance, milk yield) were monitored for 30 days. Blood and milk samples were taken to determine bacterial counts in milk, SCC, white blood cell populations and cytokines. Differences in disease presentation in vivo between groups were observed, with two animals from Group 2 developing clinical mastitis and requiring antibiotic treatment, while one animal from Group 1 did not develop an infection for the duration of the study. Fever (temperature > 39.5⁰C) was observed in 3 animals from Group 2 and in none from Group 1. Significant differences in SCC and bacterial load between groups were observed in the initial stages of infection (week 1). Data is also being collected on cytokines and chemokines secreted during the course of infection. The results of this study suggest that a strain from lineage CC151 may cause more severe clinical mastitis, while a strain from lineage CC97 may cause mild, subclinical mastitis. Diversity between strains of S. aureus may therefore influence the clinical presentation of mastitis, which in turn may influence disease detection and treatment needs.

Keywords: Bovine mastitis, host immune response, host-pathogen interactions, Staphylococcus aureus

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Authors: Ayman Hijazi, Witold Kwapinski, J. J. Leahy

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Finding a sustainable alternative energy to fossil fuel is an urgent need as various environmental challenges in the world arise. Therefore, formic acid (FA) decomposition has been an attractive field that lies at the center of the biomass platform, comprising a potential pool of hydrogen energy that stands as a distinct energy vector. Liquid FA features considerable volumetric energy density of 6.4 MJ/L and a specific energy density of 5.3 MJ/Kg that qualifies it in the prime seat as an energy source for transportation infrastructure. Additionally, the increasing research interest in FA decomposition is driven by the need for in-situ H₂ production, which plays a key role in the hydrogenation reactions of biomass into higher-value components. It is reported elsewhere in the literature that catalytic decomposition of FA is usually performed in poorly designed setups using simple glassware under magnetic stirring, thus demanding further energy investment to retain the used catalyst. Our work suggests an approach that integrates designing a distinct catalyst featuring magnetic properties with a robust setup that minimizes experimental & measurement discrepancies. One of the most prominent active species for the dehydrogenation/hydrogenation of biomass compounds is palladium. Accordingly, we investigate the potential of engrafting palladium metal onto functionalized magnetic nanoparticles as a heterogeneous catalyst to favor the production of CO-free H₂ gas from FA. Using an ordinary magnet to collect the spent catalyst renders core-shell magnetic nanoparticles as the backbone of the process. Catalytic experiments were performed in a jacketed batch reactor equipped with an overhead stirrer under an inert medium. Through a distinct approach, FA is charged into the reactor via a high-pressure positive displacement pump at steady-state conditions. The produced gas (H₂+CO₂) was measured by connecting the gas outlet to a measuring system based on the amount of the displaced water. The uniqueness of this work lies in designing a very responsive catalyst, pumping a consistent amount of FA into a sealed reactor running at steady-state mild temperatures, and continuous gas measurement, along with collecting the used catalyst without the need for centrifugation. Catalyst characterization using TEM, XRD, SEM, and CHN elemental analyzer provided us with details of catalyst preparation and facilitated new venues to alter the nanostructure of the catalyst framework. Consequently, the introduction of amine groups has led to appreciable improvements in terms of dispersion of the doped metals and eventually attaining nearly complete conversion (100%) of FA after 7 hours. The relative importance of the process parameters such as temperature (35-85°C), stirring speed (150-450rpm), catalyst loading (50-200mgr.), and Pd doping ratio (0.75-1.80wt.%) on gas yield was assessed by a Taguchi design-of-experiment based model. Experimental results showed that operating at a lower temperature range (35-50°C) yielded more gas, while the catalyst loading and Pd doping wt.% were found to be the most significant factors with P-values 0.026 & 0.031, respectively.

Keywords: formic acid decomposition, green catalysis, hydrogen, mesoporous silica, process optimization, nanoparticles

Procedia PDF Downloads 56

Authors: Maria Ledinskaya

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This paper is part case study and part literature review. It seeks to introduce Agile, Lean, and Hybrid project management concepts from business, software development, and manufacturing fields to museum conservation by looking at their practical application on a recent conservation project at the Sainsbury Centre for Visual Arts. The author outlines the advantages of leaner and more agile conservation practices in today’s faster, less certain, and more budget-conscious museum climate where traditional project structures are no longer as relevant or effective. The Morris Collection Conservation Project was carried out in 2019-2021 in Norwich, UK, and concerned the remedial conservation of around 150 Abstract Constructivist artworks bequeathed to the Sainsbury Centre by private collectors Michael and Joyce Morris. It was a medium-sized conservation project of moderate complexity, planned and delivered in an environment with multiple known unknowns – unresearched collection, unknown conditions and materials, unconfirmed budget. The project was later impacted by the COVID-19 pandemic, introducing indeterminate lockdowns, budget cuts, staff changes, and the need to accommodate social distancing and remote communications. The author, then a staff conservator at the Sainsbury Centre who acted as project manager on the Morris Project, presents an incremental, iterative, and value-based approach to managing a conservation project in an uncertain environment. The paper examines the project from the point of view of Traditional, Agile, Lean, and Hybrid project management. The author argues that most academic writing on project management in conservation has focussed on a Traditional plan-driven approach – also known as Waterfall project management – which has significant drawbacks in today’s museum environment due to its over-reliance on prediction-based planning and its low tolerance to change. In the last 20 years, alternative Agile, Lean and Hybrid approaches to project management have been widely adopted in software development, manufacturing, and other industries, although their recognition in the museum sector has been slow. Using examples from the Morris Project, the author introduces key principles and tools of Agile, Lean, and Hybrid project management and presents a series of arguments on the effectiveness of these alternative methodologies in museum conservation, including the ethical and practical challenges to their implementation. These project management approaches are discussed in the context of consequentialist, relativist, and utilitarian developments in contemporary conservation ethics. Although not intentionally planned as such, the Morris Project had a number of Agile and Lean features which were instrumental to its successful delivery. These key features are identified as distributed decision-making, a co-located cross-disciplinary team, servant leadership, focus on value-added work, flexible planning done in shorter sprint cycles, light documentation, and emphasis on reducing procedural, financial, and logistical waste. Overall, the author’s findings point in favour of a hybrid model, which combines traditional and alternative project processes and tools to suit the specific needs of the project.

Keywords: agile project management, conservation, hybrid project management, lean project management, waterfall project management

Procedia PDF Downloads 71

Authors: Sonika Sharma, Mohan G. Vairale, Sibnarayan Datta, Soumya Chatterjee, Dharmendra Dubey, Rajesh Prasad, Raghvendra Budhauliya, Bidisha Das, Vijay Veer

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Bacteriophages are viruses that parasitize specific bacteria and multiply in metabolising host bacteria. Bacteriophages hunt for a single or a subset of bacterial species, making them potential antibacterial agents. Utilizing the ability of phages to control bacterial populations has several applications from medical to the fields of agriculture, aquaculture and the food industry. However, harnessing phage based techniques in wastewater treatments to improve quality of effluent and sludge release into the environment is a potential area for R&D application. Phage mediated bactericidal effect in any wastewater treatment process has many controlling factors that lead to treatment performance. In laboratory conditions, titer of bacteriophages (coliphages) isolated from effluent water of a specially designed anaerobic digester of human night soil (DRDO Biotoilet) was successfully increased with a modified protocol of the classical double layer agar technique. Enrichment of the same was carried out and efficacy of the phage enriched medium was evaluated at different conditions (specific media, temperature, storage conditions). Growth optimization study was carried out on different media like soybean casein digest medium (Tryptone soya medium), Luria-Bertani medium, phage deca broth medium and MNA medium (Modified nutrient medium). Further, temperature-phage yield relationship was also observed at three different temperatures 27˚C, 37˚C and 44˚C at laboratory condition. Results showed the higher activity of coliphage 27˚C and at 37˚C. Further, addition of divalent ions (10mM MgCl2, 5mM CaCl2) and 5% glycerol resulted in a significant increase in phage titer. Besides this, effect of antibiotics addition like ampicillin and kanamycin at different concentration on plaque formation was analysed and reported that ampicillin at a concentration of 1mg/ml ampicillin stimulates phage infection and results in more number of plaques. Experiments to test viability of phage showed that it can remain active for 6 months at 4˚C in fresh tryptone soya broth supplemented with fresh culture of coliforms (early log phase). The application of bacteriophages (especially coliphages) for treatment of effluent of human faecal matter contaminated effluent water is unique. This environment-friendly treatment system not only reduces the pathogenic coliforms, but also decreases the competition between nuisance bacteria and functionally important microbial populations. Therefore, the phage based cocktail to treat fecal pathogenic bacteria present in black water has many implication in wastewater treatment processes including ‘DRDO Biotoilet’, which is an ecofriendly appropriate and affordable human faecal matter treatment technology for different climates and situations.

Keywords: wastewater, microbes, virus, biotoilet, phage viability

Procedia PDF Downloads 436

Authors: Laverne Seales

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When most people think of Panama, they immediately think of the Canal; however, the construction and the people who made it possible are often omitted and seldom acknowledged. The reality is that the construction of this waterway was achieved through forced migration and discriminatory practices toward people of African descent, specifically black people from the Caribbean. From the colonial period to the opening and subsequent operation of the Panama Canal by the United States, this paper goes through the rich layers of Panamanian history to examine the life of Afro-Caribbeans and their descendants in Panama. It also considers the role of the United States in Panama; it explores how the United States in Panama forged a racially complex country that made the integration of Afro-Caribbeans and their descendants difficult. After laying a historical foundation, the exploration of Afro-Caribbean people and Panamanians of Afro-Caribbean descent are analyzed through Afro-Panamanian writer Carlos Guillermo ‘Cubena’ Wilson's novels, short stories, and poetry. This study focuses on how Cubena addresses racism, discrimination, inequality, and social justice issues towards Afro-Caribbeans and their descendants who traveled to Panama to construct the Canal. Content analysis methodology can yield several significant contributions, and analyzing Carlos Guillermo Wilson's literature under this framework allows us to consider social commentary and critique of Panamanian society. It identifies the social issues and concerns of Afro-Caribbeans and people of Afro-Caribbean descent, such as inequality, corruption, racism, political oppression, and cultural identity. Analysis methodology allows us to explore how Cubena's literature engages with questions of cultural identity and belonging in Panamanian society. By examining themes related to race, ethnicity, language, and heritage, this research uncovers the complexities of Panamanian cultural identity, allowing us to interrogate power dynamics and social hierarchies in Panamanian society. Analyzing the portrayal of different social groups, institutions, and power structures helps uncover how power is wielded, contested, and resisted; Cubena's fictional world allows us to see how it functions in Panama. Content analysis methodology also provides for critiquing political systems and governance in Panama. By examining the representation and presentation of political figures, institutions, and events in Cubena's literature, we uncover his commentary on corruption, authoritarianism, governance, and the role of the United States in Panama. Content analysis highlights how Wilson's literature amplifies the voices and experiences of marginalized individuals and communities in Panamanian society. By centering the narratives of Afro-Panamanians and other marginalized groups, this researcher uncovers Cubena's commitment to social justice and inclusion in his writing and helps the reader engage with historical narratives and collective memory in Panama. Overall, analyzing Carlos Guillermo ‘Cubena’ Wilson's literature as a platform for social commentary and critique of Panamanian society using content analysis methodology provides valuable insights into the cultural, social, and political dimensions of Afro-Panamanians during and after the construction of the Panama Canal.

Keywords: Afro-Caribbean, Panama Canal, race, Afro-Panamanian, identity, history

Procedia PDF Downloads 44

Authors: Laith F. Gulli, Nicole M. Mallory

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The undertaking to develop a psychometric instrument is monumental. Understanding the relationship between variables and events is important in structural and exploratory design of psychometric instruments. Considering this, we describe a method used to group, pair and combine multiple Philosophical Assumption statements that assisted in development of a 13 item psychometric screening instrument. We abbreviated our Philosophical Assumptions (PA)s and added parameters, which were then condensed and mathematically modeled in a specific process. This model produced clusters of combinatorics which was utilized in design and development for 1) information retrieval and categorization 2) item development and 3) estimation of interactions among variables and likelihood of events. The psychometric screening instrument measured Knowledge, Assessment (education) and Beliefs (KAB) of New Addictions Research (NAR), which we called KABNAR. We obtained an overall internal consistency for the seven Likert belief items as measured by Cronbach’s α of .81 in the final study of 40 Clinicians, calculated by SPSS 14.0.1 for Windows. We constructed the instrument to begin with demographic items (degree/addictions certifications) for identification of target populations that practiced within Outpatient Substance Abuse Counseling (OSAC) settings. We then devised education items, beliefs items (seven items) and a modifiable “barrier from learning” item that consisted of six “choose any” choices. We also conceptualized a close relationship between identifying various degrees and certifications held by Outpatient Substance Abuse Therapists (OSAT) (the demographics domain) and all aspects of their education related to EB-NAR (past and present education and desired future training). We placed a descriptive (PA)1tx in both demographic and education domains to trace relationships of therapist education within these two domains. The two perceptions domains B1/b1 and B2/b2 represented different but interrelated perceptions from the therapist perspective. The belief items measured therapist perceptions concerning EB-NAR and therapist perceptions using EB-NAR during the beginning of outpatient addictions counseling. The (PA)s were written in simple words and descriptively accurate and concise. We then devised a list of parameters and appropriately matched them to each PA and devised descriptive parametric (PA)s in a domain categorized information grid. Descriptive parametric (PA)s were reduced to simple mathematical symbols. This made it easy to utilize parametric (PA)s into algorithms, combinatorics and clusters to develop larger information grids. By using matching combinatorics we took paired demographic and education domains with a subscript of 1 and matched them to the column with each B domain with subscript 1. Our algorithmic matching formed larger information grids with organized clusters in columns and rows. We repeated the process using different demographic, education and belief domains and devised multiple information grids with different parametric clusters and geometric arrays. We found benefit combining clusters by different geometric arrays, which enabled us to trace parametric variables and concepts. We were able to understand potential differences between dependent and independent variables and trace relationships of maximum likelihoods.

Keywords: psychometric, parametric, domains, grids, therapists

Procedia PDF Downloads 278

Authors: Francesco Pandolfi, Georgios Baltzopoulos, Iunio Iervolino

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The impact of extreme winds on industrial assets and the built environment is gaining increasing attention from stakeholders, including the corporate insurance industry. This has led to a progressively more in-depth study of building vulnerability and fragility to wind. Wind vulnerability models are used in probabilistic risk assessment to relate a loss metric to an intensity measure of the natural event, usually a gust or a mean wind speed. In fact, vulnerability models can be integrated with the wind hazard, which consists of associating a probability to each intensity level in a time interval (e.g., by means of return periods) to provide an assessment of future losses due to extreme wind. This has also given impulse to the world- and regional-scale wind hazard studies.Another approach often adopted for the probabilistic description of building vulnerability to the wind is the use of fragility functions, which provide the conditional probability that selected building components will exceed certain damage states, given wind intensity. In fact, in wind engineering literature, it is more common to find structural system- or component-level fragility functions rather than wind vulnerability models for an entire building. Loss assessment based on component fragilities requires some logical combination rules that define the building’s damage state given the damage state of each component and the availability of a consequence model that provides the losses associated with each damage state. When risk calculations are based on numerical simulation of a structure’s behavior during extreme wind scenarios, the interaction of component fragilities is intertwined with the computational procedure. However, simulation-based approaches are usually computationally demanding and case-specific. In this context, the present work introduces the ExtReMe wind risk assESsment prototype Software, ERMESS, which is being developed at the University of Naples Federico II. ERMESS is a wind risk assessment tool for insurance applications to industrial facilities, collecting a wide assortment of available wind vulnerability models and fragility functions to facilitate their incorporation into risk calculations based on in-built or user-defined wind hazard data. This software implements an alternative method for building-specific risk assessment based on existing component-level fragility functions and on a number of simplifying assumptions for their interactions. The applicability of this alternative procedure is explored by means of an illustrative proof-of-concept example, which considers four main building components, namely: the roof covering, roof structure, envelope wall and envelope openings. The application shows that, despite the simplifying assumptions, the procedure can yield risk evaluations that are comparable to those obtained via more rigorous building-level simulation-based methods, at least in the considered example. The advantage of this approach is shown to lie in the fact that a database of building component fragility curves can be put to use for the development of new wind vulnerability models to cover building typologies not yet adequately covered by existing works and whose rigorous development is usually beyond the budget of portfolio-related industrial applications.

Keywords: component wind fragility, probabilistic risk assessment, vulnerability model, wind-induced losses

Procedia PDF Downloads 181