Search results for: sequential causal inference
Commenced in January 2007
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Edition: International
Paper Count: 1079

Search results for: sequential causal inference

89 Soybean Seed Composition Prediction From Standing Crops Using Planet Scope Satellite Imagery and Machine Learning

Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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88 Nursing Preceptors' Perspectives of Assessment Competency

Authors: Watin Alkhelaiwi, Iseult Wilson, Marian Traynor, Katherine Rogers

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Clinical nursing education allows nursing students to gain essential knowledge from practice experience and develop nursing skills in a variety of clinical environments. Integrating theoretical knowledge and practical skills is made easier for nursing students by providing opportunities for practice in a clinical environment. Nursing competency is an essential capability required to fulfill nursing responsibilities. Effective mentoring in clinical settings helps nursing students develop the necessary competence and promotes the integration of theory and practice. Preceptors play a considerable role in clinical nursing education, including the supervision of nursing students undergoing a rigorous clinical practicum. Preceptors are also involved in the clinical assessment of nursing students’ competency. The assessment of nursing students’ competence by professional practitioners is essential to investigate whether nurses have developed an adequate level of competence to deliver safe nursing care. Competency assessment remains challenging among nursing educators and preceptors, particularly owing to the complexity of the process. Consistency in terms of assessment methods and tools and valid and reliable assessment tools for measuring competence in clinical practice are lacking. Nurse preceptors must assess students’ competencies to prepare them for future professional responsibilities. Preceptors encounter difficulties in the assessment of competency owing to the nature of the assessment process, lack of standardised assessment tools, and a demanding clinical environment. The purpose of the study is to examine nursing preceptors’ experiences of assessing nursing interns’ competency in Saudi Arabia. There are three objectives in this study; the first objective is to examine the preceptors’ view of the Saudi assessment tool in relation to preceptorship, assessment, the assessment tool, the nursing curriculum, and the grading system. The second and third objectives are to examine preceptors’ view of "competency'' in nursing and their interpretations of the concept of competency and to assess the implications of the research in relation to the Saudi 2030 vision. The study uses an exploratory sequential mixed-methods design that involves a two-phase project: a qualitative focus group study is conducted in phase 1, and a quantitative study- a descriptive cross-sectional design (online survey) is conducted in phase 2. The results will inform the preceptors’ view of the Saudi assessment tool in relation to specific areas, including preceptorship and how the preceptors are prepared to be assessors, and assessment and assessment tools through identifying the appropriateness of the instrument for clinical practice. The results will also inform the challenges and difficulties that face the preceptors. These results will be analysed thematically for the focus group interview data, and SPSS software will be used for the analysis of the online survey data.

Keywords: clinical assessment tools, clinical competence, competency assessment, mentor, nursing, nurses, preceptor

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87 Estimation of Level of Pesticide in Recurrent Pregnancy Loss and Its Correlation with Paraoxanase1 Gene in North Indian Population

Authors: Apurva Singh, S. P. Jaiswar, Apala Priyadarshini, Akancha Pandey

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Objective: The aim of this study is to find the association of PON1 gene polymorphism with pesticides In RPL subjects. Background: Recurrent pregnancy loss (RPL) is defined as three or more sequential abortions before the 20th week of gestation. Pesticides and its derivatives (organochlorine and organophosphate) are proposed to accommodate a ruler chemical for RPL in the sub-humid region of India. The paraoxonase-1 enzyme (PON1) plays an important role in the toxicity of some organophosphate pesticides, with low PON1 activity being associated with higher pesticide sensitivity Methodology: This is a case-control study done in Department of Obstetrics & Gynaecology & Department of Biochemistry, K.G.M.U, Lucknow, India. The subjects were enrolled after fulfilling the inclusion & exclusion criteria. Inclusion criteria: Cases- Subject having two or more spontaneous abortions & Control- Healthy female having one or more alive child was selected. Exclusion criteria: Cases & Control- Subject having the following disease will be excluded from the study Diabetes mellitus, Hypertension, Tuberculosis, Immunocompromised patients, any endocrine disorder and genital, colon or breast cancer any other malignancies. Blood samples were collected in EDTA tubes from cases & healthy control women & genomic DNA was extracted by phenol-chloroform method. The estimation of pesticides residue from blood was done by HPLC. Biochemical estimation was also performed. Genotyping of PON1 gene polymorphism was performed by RFLP. Statistical analysis of the data was performed using the SPSS16.3 software. Results: A sum of total 14 pesticides (12 organochlorine and 2 organophosphate) selected on the basis of their persistent nature and consumption rate. The significant level of pesticide (ppb) estimated by the Mann whiney test and it was found to be significant at higher level of β-HCH (p:0.04), γ-HCH (p:0.001), δ-HCH (p: 0.002), chloropyrifos (p:0.001), pp-DDD (p:0.001) and fenvalrate (p: 0.001) in case group compare to its control. The level of antioxidant enzymes were found to be significantly decreased among the cases. Wild homozygous TT was more frequent and prevalent among control groups. However, heterozygous group (Tt) was more in cases than control groups (CI-0.3-1.3) (p=0.06). Conclusion: Higher levels of pesticides with endocrine disrupting potential in cases indicate the possible role of these compounds as one of the causes of recurrent pregnancy loss. Possibly, increased pesticide level appears to indicate increased levels of oxidative damage that has been associated with the possible cause of Recurrent Miscarriage, it may reflect indirect evidence of toxicity rather than the direct cause. Since both factors are reported to increase risk, individuals with higher levels of these 'Toxic compounds' especially in 'high-risk genotypes' might be more susceptible to recurrent pregnancy loss.

Keywords: paraoxonase, pesticides, PON1, RPL

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86 Integrations of the Instructional System Design for Students Learning Achievement Motives and Science Attitudes with Stem Educational Model on Stoichiometry Issue in Chemistry Classes with Different Genders

Authors: Tiptunya Duangsri, Panwilai Chomchid, Natchanok Jansawang

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This research study was to investigate of education decisions must be made which a part of it should be passed on to future generations as obligatory for all members of a chemistry class for students who will prepare themselves for a special position. The descriptions of instructional design were provided and the recent criticisms are discussed. This research study to an outline of an integrative framework for the description of information and the instructional design model give structure to negotiate a semblance of conscious understanding. The aims of this study are to describe the instructional design model for comparisons between students’ genders of their effects on STEM educational learning achievement motives to their science attitudes and logical thinking abilities with a sample size of 18 students at the 11th grade level with the cluster random sampling technique in Mahawichanukul School were designed. The chemistry learning environment was administered with the STEM education method. To build up the 5-instrument lesson instructional plan issues were instructed innovations, the 30-item Logical Thinking Test (LTT) on 5 scales, namely; Inference, Recognition of Assumptions, Deduction, Interpretation and Evaluation scales was used. Students’ responses of their perceptions with the Test Of Chemistry-Related Attitude (TOCRA) were assessed of their attitude in science toward chemistry. The validity from Index Objective Congruence value (IOC) checked by five expert specialist educator in two chemistry classroom targets in STEM education, the E1/E2 process were equaled evidence of 84.05/81.42 which results based on criteria are higher than of 80/80 standard level with the IOC from the expert educators. Comparisons between students’ learning achievement motives with STEM educational model on stoichiometry issue in chemistry classes with different genders were differentiated at evidence level of .05, significantly. Associations between students’ learning achievement motives on their posttest outcomes and logical thinking abilities, the predictive efficiency (R2) values indicate that 69% and 70% of the variances in different male and female student groups of their logical thinking abilities. The predictive efficiency (R2) values indicate that 73%; and 74% of the variances in different male and female student groups of their science attitudes toward chemistry were associated. Statistically significant on students’ perceptions of their chemistry learning classroom environment and their science attitude toward chemistry when using the MCI and TOCRA, the predictive efficiency (R2) values indicated that 72% and 74% of the variances in different male and female student groups of their chemistry classroom climate, consequently. Suggestions that supporting chemistry or science teachers from science, technology, engineering and mathematics (STEM) in addressing complex teaching and learning issues related instructional design to develop, teach, and assess traditional are important strategies with a focus on STEM education instructional method.

Keywords: development, the instructional design model, students learning achievement motives, science attitudes with STEM educational model, stoichiometry issue, chemistry classes, genders

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85 Leadership and Management Strategies of Sports Administrator in Asia

Authors: Mark Christian Inductivo Siwa, Jesrelle Ormoc Bontuyan

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This study was conducted in selected tertiary schools in selected universities in Asian countries such as Philippines, Thailand, and China, which are the top performing countries in Southeast Asian Games or SEA Games and Asian School Games (ASG), also known as the Youth SEA Games and Asian Games. The respondents of the study are sports administrators/directors and coaches in selected Southeast Asian countries such as Philippines, Thailand, and in Asia which is China. This study has generated a progressive sports operational model of Sports Leadership and Management in Selected Universities in Asia. This study utilized mixed-method research. It is a methodology for conducting research that involves collecting, analyzing and integrating quantitative (e.g., experiments, surveys) and qualitative (e.g., focus groups, interviews) research. This approach to research is used to provide integration for a better understanding of the research problem than either of each alone. This study particularly employed the explanatory sequential design of mixed methods, which involved two phases: the quantitative phase, which involves the collection and analysis of quantitative data, followed by the qualitative phase, which involves the collection and analysis of qualitative data. This study will prioritize the quantitative data and the findings will be followed up during the interpretation phase in the qualitative data of the study. The qualitative data help explain or build upon initial quantitative results. In phase I, the researcher began with the collection and analysis of the quantitative data. His investigation gave greater emphasis on the quantitative methods, particularly employed surveys with the coaches and sports directors of the three selected universities in Asia. In Phase II, the researcher subsequently collected and analyzed the qualitative data obtained through an interview with the sports directors to follow from or connect to the results of the quantitative phase. This study followed the data analysis spiral so that the researcher could follow – up or explain the quantitative results. The researcher engaged in the process of moving in analytic circles. Based on the school's mission and vision, the sports leadership and management consistently followed the key factors to take into account when leading the organization and managing the process in sports leadership and management when formulating objectives/goals, budget, equipment care and maintenance, facilities, training matrix, and consideration. Also, sports management demonstrates the need for development in terms of the upkeep and care of equipment as well as athlete funding. The development of goals or sports management goals, sports facilities and equipment, as well as improvements in demonstrating training and consideration, and incentives, should also include a maintenance plan. The study concluded with a progressive sports operational model that was created based on the result of the study.

Keywords: sports leadership and management, formulating objectives, budget, equipment care and maintenance, training, consideration, incentives, progressive sports operational model

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84 Conceptualization and Assessment of Key Competencies for Children in Preschools: A Case Study in Southwest China

Authors: Yumei Han, Naiqing Song, Xiaoping Yang, Yuping Han

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This study explores the conceptualization of key competencies that children are expected to develop in three year preschools (age 3-6) and the assessment practices of such key competencies in China. Assessment of children development has been put into the central place of early childhood education quality evaluation system in China. In the context of students key competencies development centered education reform in China, defining and selecting key competencies of children in preschools are of great significance in that they would lay a solid foundation for children’s lifelong learning path, and they would lead to curriculum and instruction reform, teacher development reform as well as quality evaluation reform in the early childhood education area. Based on sense making theory and framework, this study adopted multiple stakeholders’ (early childhood educators, parents, evaluation administrators, scholars in the early childhood education field) perspectives and grass root voices to conceptualize and operationalize key competencies for children in preschools in Southwest China. On the ground of children development theories, Chinese and international literature related to children development and key competencies, and key competencies frameworks by UNESCO, OECD and other nations, the authors designed a two-phase sequential mixed method study to address three main questions: (a) How is early childhood key competency defined or labeled from literature and from different stakeholders’ views? (b) Based on the definitions explicated in the literature and the surveys on different stakeholders, what domains and components are regarded to constitute the key competency framework of children in three-year preschools in China? (c) How have early childhood key competencies been assessed and measured, and how such assessment and measurement contribute to enhancing early childhood development quality? On the first phase, a series of focus group surveys were conducted among different types of stakeholders around the research questions. Moreover, on the second phase, based on the coding of the participants’ answers, together with literature synthesis findings, a questionnaire survey was designed and conducted to select most commonly expected components of preschool children’s key competencies. Semi-structured open questions were also included in the questionnaire for the participants to add on competencies beyond the checklist. Rudimentary findings show agreeable concerns on the significance and necessity of conceptualization and assessment of key competencies for children in preschools, and a key competencies framework composed of 7 domains and 25 indicators was constructed. Meanwhile, the findings also show issues in the current assessment practices of children’s competencies, such as lack of effective assessment tools, lack of teacher capacity in applying the tools to evaluating children and advancing children development accordingly. Finally, the authors put forth suggestions and implications for China and international communities in terms of restructuring early childhood key competencies framework, and promoting child development centered reform in early childhood education quality evaluation and development.

Keywords: assessment, conceptualization, early childhood education quality in China, key competencies

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83 The Psychological and Subjective Well-being of Ethiopian adults: Correlates, Explanations, and Cross-Cultural Constructions

Authors: Kassahun Tilahun

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The purpose of the study was two-fold: to examine the socio-demographic and psychological predictors of well-being and formulate a socio-culturally sound approach explaining the meaning and experience of psychological well-being among Ethiopian adults. Ryan and Deci’s Self-Determination Theory was duly considered as a theoretical framework of the study. The study followed a sequential explanatory mixed method design. Both quantitative and qualitative data were obtained, via scales and open-ended questionnaires, from 438 civil servants working in Addis Ababa. 30 interviews were also conducted to gain further information. An in-depth analysis of the reliability and validity of instruments was made before employing them to the main study. The results showed that adults were better off in both their scores of psychological and subjective well-being. Besides, adults’ well-being was found to be quite a function of their gender, age, marital status, educational level and household income. Males had a healthier psychological well-being status than females, where as females were better in their subjective well-being. A significant difference in psychological well-being was also observed between emerging and young adults, in favor of the young; and between cohabitated and married adults, married being advantageous. A significant difference in subjective well-being measures was also noticed among single, cohabitated and married adults, in favor of the married adults in all measures. The finding revealed that happiness level of adults decrease as their educational status increases while the reverse is true to psychological well-being. Besides, as adults’ household income boosts, so do their psychological well-being and satisfaction in life. The regression analysis also produced significant independent contributions of household income to overall well-being of adults. As such, subjective well-being was significantly predicted by dummy variable of sex and marital status. Likewise, the agreeableness, conscientiousness, neuroticism and openness dimensions of personality were notable significant predictors of adults’ psychological well-being where as extraversion and agreeableness were significant predictors of their subjective well-being. Religiosity was also a significant predictor of adults’ psychological well-being. Besides, adults’ well-being was significantly predicted by the interaction between conscientiousness and religiosity. From goal pursuit dimensions, attainment of extrinsic life goals was a significant predictor of both psychological and subjective well-being. Importance and attainment of intrinsic life goals also significantly predicts adults’ psychological well-being. Finally, the subjective well-being of adults was significantly predicted by environmental mastery, positive relations with others, self-acceptance and overall psychological well-being scores of adults. The thematic analysis identified five major categories of themes, which are essential in explaining the psychological well-being of Ethiopian adults. These were; socio-cultural harmony, social cohesion, security, competence and accomplishment, and the self. Detailed discussion on the rational for including these themes was made and appropriate implications were proposed. Researchers are encouraged to expand the findings of this research and in turn develop a suitable approach taping the psychological well-being of adults living in countries like Ethiopia.

Keywords: psychological well-being, subjective well-being, adulthood, Ethiopia

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82 Developmental Relationships between Alcohol Problems and Internalising Symptoms in a Longitudinal Sample of College Students

Authors: Lina E. Homman, Alexis C. Edwards, Seung Bin Cho, Danielle M. Dick, Kenneth S. Kendler

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Research supports an association between alcohol problems and internalising symptoms, but the understanding of how the two phenotypes relate to each other is poor. It has been hypothesized that the relationship between the phenotypes is causal; however investigations in regards to direction are inconsistent. Clarity of the relationship between the two phenotypes may be provided by investigating the phenotypes developmental inter-relationships longitudinally. The objective of the study was to investigate a) changes in alcohol problems and internalising symptoms in college students across time and b) the direction of effect of growth between alcohol problems and internalising symptoms from late adolescent to emerging adulthood c) possible gender differences. The present study adds to the knowledge of comorbidity of alcohol problems and internalising symptoms by examining a longitudinal sample of college students and by examining the simultaneous development of the symptoms. A sample of college students is of particular interest as symptoms of both phenotypes often have their onset around this age. A longitudinal sample of college students from a large, urban, public university in the United States was used. Data was collected over a time period of 2 years at 3 time points. Latent growth models were applied to examine growth trajectories. Parallel process growth models were used to assess whether initial level and rate of change of one symptom affected the initial level and rate of change of the second symptom. Possible effects of gender and ethnicity were investigated. Alcohol problems significantly increased over time, whereas internalizing symptoms remained relatively stable. The two phenotypes were significantly correlated in each wave, correlations were stronger among males. Initial level of alcohol problems was significantly positively correlated with initial level of internalising symptoms. Rate of change of alcohol problems positively predicted rate of change of internalising symptoms for females but not for males. Rate of change of internalising symptoms did not predict rate of change of alcohol problems for either gender. Participants of Black and Asian ethnicities indicated significantly lower levels of alcohol problems and a lower increase of internalising symptoms across time, compared to White participants. Participants of Black ethnicity also reported significantly lower levels of internalising symptoms compared to White participants. The present findings provide additional support for a positive relationship between alcohol problems and internalising symptoms in youth. Our findings indicated that both internalising symptoms and alcohol problems increased throughout the sample and that the phenotypes were correlated. The findings mainly implied a bi-directional relationship between the phenotypes in terms of significant associations between initial levels as well as rate of change. No direction of causality was indicated in males but significant results were found in females where alcohol problems acted as the main driver for the comorbidity of alcohol problems and internalising symptoms; alcohol may have more detrimental effects in females than in males. Importantly, our study examined a population-based longitudinal sample of college students, revealing that the observed relationships are not limited to individuals with clinically diagnosed mental health or substance use problems.

Keywords: alcohol, comorbidity, internalising symptoms, longitudinal modelling

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81 Elevated Celiac Antibodies and Abnormal Duodenal Biopsies Associated with IBD Markers: Possible Role of Altered Gut Permeability and Inflammation in Gluten Related Disorders

Authors: Manav Sabharwal, Ruda Rai Md, Candace Parker, James Ridley

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Wheat is one of the most commonly consumed grains worldwide, which contains gluten. Nowadays, gluten intake is considered to be a trigger for GRDs, including Celiac disease (CD), a common genetic disease affecting 1% of the US population, non-celiac gluten sensitivity (NCGS) and wheat allergy. NCGS is being recognized as an acquired gluten-sensitive enteropathy that is prevalent across age, ethnic and geographic groups. The cause of this entity is not fully understood, and recent studies suggest that it is more common in participants with irritable bowel syndrome (IBS), with iron deficiency anemia, symptoms of fatigue, and has considerable overlap in symptoms with IBS and Crohn’s disease. However, these studies were lacking in availability of complete serologies, imaging tests and/or pan-endoscopy. We performed a prospective study of 745 adult patients who presented to an outpatient clinic for evaluation of chronic upper gastro-intestinal symptoms and subsequently underwent an upper endoscopic (EGD) examination as standard of care. Evaluation comprised of comprehensive celiac antibody panel, inflammatory bowel disease (IBD) serologic markers, duodenal biopsies and Small Bowel Video Capsule Endoscopy (VCE), when available. At least 6 biopsy specimens were obtained from the duodenum and proximal jejunum during EGD, and CD3+ Intraepithelial lymphocytes (IELs) and villous architecture were evaluated by a single experienced pathologist, and VCE was performed by a single experienced gastroenterologist. Of the 745 patients undergoing EGD, 12% (93/745) patients showed elevated CD3+ IELs in the duodenal biopsies. 52% (387/745) completed a comprehensive CD panel and 7.2% (28/387) were positive for at least 1 CD antibody (Tissue transglutaminase (tTG), being the most common antibody in 65% (18/28)). Of these patients, 18% (5/28) showed increased duodenal CD3+ IELs, but 0% showed villous blunting or distortion to meet criteria for CD. Surprisingly, 43% (12/28) were positive for at 1 IBD serology (ASCA, ANCA or expanded IBD panel (LabCorp)). Of these 28 patients, 29% (8/28) underwent a SB VCE, of which 100 % (8/8) showed significant jejuno-ileal mucosal lesions diagnostic for IBD. Findings of abnormal CD antibodies (7.2%, 28/387) and increased CD3+ IELs on duodenal biopsy (12%, 93/745) were observed frequently in patients with UGI symptoms undergoing EGD in an outpatient clinic. None met criteria for CD, and a high proportion (43%, 12/28) showed evidence of overlap with IBD. This suggests a potential causal link of acquired GRDs to underlying inflammation and gut mucosal barrier disruption. Further studies to investigate a role for abnormal antigen presentation of dietary gluten to gut associated lymphoid tissue as a cause are justified. This may explain a high prevalence of GRDs in the population and correlation with IBS, IBD and other gut inflammatory disorders.

Keywords: celiac, gluten sensitive enteropathy, lymphocitic enteritis, IBS, IBD

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80 Choosing Mountains Over the Beach: Evaluating the Effect of Altitude on Covid Brain Severity and Treatment

Authors: Kennedy Zinn, Chris Anderson

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Chronic Covid syndrome (CCS) is a condition in which individuals who test positive for Covid-19 experience persistent symptoms after recovering from the virus. CCS affects every organ system, including the central nervous system. Neurological “long-haul” symptoms last from a few weeks to several months and include brain fog, chronic fatigue, dyspnea, mood dysregulation, and headaches. Data suggest that 10-30% of individuals testing positive for Covid-19 develop CCS. Current literature indicates a decreased quality of life in persistent symptoms. CCS is a pervasive and pernicious COVID-19 sequelae. More research is needed to understand risk factors, impact, and possible interventions. Research frequently cites cytokine storming as noteworthy etiology in CCS. Cytokine storming is a malfunctional immune response and facilitates multidimensional interconnected physiological responses. The most prominent responses include abnormal blood flow, hypoxia/hypoxemia, inflammation, and endothelial damage. Neurological impairments and pathogenesis in CCS parallel that of traumatic brain injury (TBI). Both exhibit impairments in memory, cognition, mood, sustained attention, and chronic fatigue. Evidence suggests abnormal blood flow, inflammation, and hypoxemia as shared causal factors. Cytokine storming is also typical in mTBI. The shared characteristics in symptoms and etiology suggest potential parallel routes of investigation that allow for better understanding of CCS. Research on the effect of altitude in mTBI varies. Literature finds decreased rates of concussions at higher altitudes. Other studies suggest that at a higher altitude, pre-existing mTBI symptoms are exacerbated. This may mean that in CCS, the geographical location where individuals live and the location where individuals experienced acute Covid-19 symptoms may influence the severity and risk of developing CCS. It also suggests that clinics which treat mTBI patients could also provide benefits for those with CCS. This study aims to examine the relationships between altitude and CCS as a risk factor and investigate the longevity and severity of symptoms in different altitudes. Existing patient data from a concussion clinic using fMRI scans and self-reported symptoms will be used for approximately 30 individuals with CCS symptoms. The association between acclimated altitude and CCS severity will be analyzed. Patients will be classified into low, medium, and high altitude groups and compared for differences on fMRI severity scores and self-reported measures. It is anticipated that individuals living in lower altitudes are at higher risk of developing more severe neuropsychological symptoms in CCS. It is also anticipated that a treatment approach for mTBI will also be beneficial to those with CCS.

Keywords: altitude, chronic covid syndrome, concussion, covid brain, EPIC treatment, fMRI, traumatic brain injury

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79 Functional Analysis of Variants Implicated in Hearing Loss in a Cohort from Argentina: From Molecular Diagnosis to Pre-Clinical Research

Authors: Paula I. Buonfiglio, Carlos David Bruque, Lucia Salatino, Vanesa Lotersztein, Sebastián Menazzi, Paola Plazas, Ana Belén Elgoyhen, Viviana Dalamón

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Hearing loss (HL) is the most prevalent sensorineural disorder affecting about 10% of the global population, with more than half due to genetic causes. About 1 in 500-1000 newborns present congenital HL. Most of the patients are non-syndromic with an autosomal recessive mode of inheritance. To date, more than 100 genes are related to HL. Therefore, the Whole-exome sequencing (WES) technique has become a cost-effective alternative approach for molecular diagnosis. Nevertheless, new challenges arise from the detection of novel variants, in particular missense changes, which can lead to a spectrum of genotype-to-phenotype correlations, which is not always straightforward. In this work, we aimed to identify the genetic causes of HL in isolated and familial cases by designing a multistep approach to analyze target genes related to hearing impairment. Moreover, we performed in silico and in vivo analyses in order to further study the effect of some of the novel variants identified in the hair cell function using the zebrafish model. A total of 650 patients were studied by Sanger Sequencing and Gap-PCR in GJB2 and GJB6 genes, respectively, diagnosing 15.5% of sporadic cases and 36% of familial ones. Overall, 50 different sequence variants were detected. Fifty of the undiagnosed patients with moderate HL were tested for deletions in STRC gene by Multiplex ligation-dependent probe amplification technique (MLPA), leading to 6% of diagnosis. After this initial screening, 50 families were selected to be analyzed by WES, achieving diagnosis in 44% of them. Half of the identified variants were novel. A missense variant in MYO6 gene detected in a family with postlingual HL was selected to be further analyzed. A protein modeling with AlphaFold2 software was performed, proving its pathogenic effect. In order to functionally validate this novel variant, a knockdown phenotype rescue assay in zebrafish was carried out. Injection of wild-type MYO6 mRNA in embryos rescued the phenotype, whereas using the mutant MYO6 mRNA (carrying c.2782C>A variant) had no effect. These results strongly suggest the deleterious effect of this variant on the mobility of stereocilia in zebrafish neuromasts, and hence on the auditory system. In the present work, we demonstrated that our algorithm is suitable for the sequential multigenic approach to HL in our cohort. These results highlight the importance of a combined strategy in order to identify candidate variants as well as the in silico and in vivo studies to analyze and prove their pathogenicity and accomplish a better understanding of the mechanisms underlying the physiopathology of the hearing impairment.

Keywords: diagnosis, genetics, hearing loss, in silico analysis, in vivo analysis, WES, zebrafish

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78 Recycling the Lanthanides from Permanent Magnets by Electrochemistry in Ionic Liquid

Authors: Celine Bonnaud, Isabelle Billard, Nicolas Papaiconomou, Eric Chainet

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Thanks to their high magnetization and low mass, permanent magnets (NdFeB and SmCo) have quickly became essential for new energies (wind turbines, electrical vehicles…). They contain large quantities of neodymium, samarium and dysprosium, that have been recently classified as critical elements and that therefore need to be recycled. Electrochemical processes including electrodissolution followed by electrodeposition are an elegant and environmentally friendly solution for the recycling of such lanthanides contained in permanent magnets. However, electrochemistry of the lanthanides is a real challenge as their standard potentials are highly negative (around -2.5V vs ENH). Consequently, non-aqueous solvents are required. Ionic liquids (IL) are novel electrolytes exhibiting physico-chemical properties that fulfill many requirements of the sustainable chemistry principles, such as extremely low volatility and non-flammability. Furthermore, their chemical and electrochemical properties (solvation of metallic ions, large electrochemical windows, etc.) render them very attractive media to implement alternative and sustainable processes in view of integrated processes. All experiments that will be presented were carried out using butyl-methylpyrrolidinium bis(trifluoromethanesulfonyl)imide. Linear sweep, cyclic voltammetry and potentiostatic electrochemical techniques were used. The reliability of electrochemical experiments, performed without glove box, for the classic three electrodes cell used in this study has been assessed. Deposits were obtained by chronoamperometry and were characterized by scanning electron microscopy and energy-dispersive X-ray spectroscopy. The IL cathodic behavior under different constraints (argon, nitrogen, oxygen atmosphere or water content) and using several electrode materials (Pt, Au, GC) shows that with argon gas flow and gold as a working electrode, the cathodic potential can reach the maximum value of -3V vs Fc+/Fc; thus allowing a possible reduction of lanthanides. On a gold working electrode, the reduction potential of samarium and neodymium was found to be -1.8V vs Fc+/Fc while that of dysprosium was -2.1V vs Fc+/Fc. The individual deposits obtained were found to be porous and presented some significant amounts of C, N, F, S and O atoms. Selective deposition of neodymium in presence of dysprosium was also studied and will be discussed. Next, metallic Sm, Nd and Dy electrodes were used in replacement of Au, which induced changes in the reduction potential values and the deposit structures of lanthanides. The individual corrosion potentials were also measured in order to determine the parameters influencing the electrodissolution of these metals. Finally, a full recycling process was investigated. Electrodissolution of a real permanent magnet sample was monitored kinetically. Then, the sequential electrodeposition of all lanthanides contained in the IL was investigated. Yields, quality of the deposits and consumption of chemicals will be discussed in depth, in view of the industrial feasibility of this process for real permanent magnets recycling.

Keywords: electrodeposition, electrodissolution, ionic liquids, lanthanides, rcycling

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77 Microgrid Design Under Optimal Control With Batch Reinforcement Learning

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

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Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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76 Examination of Indoor Air Quality of Naturally Ventilated Dwellings During Winters in Mega-City Kolkata

Authors: Tanya Kaur Bedi, Shankha Pratim Bhattacharya

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The US Environmental Protection Agency defines indoor air quality as “The air quality within and around buildings, especially as it relates to the health and comfort of building occupants”. According to the 2021 report by the Energy Policy Institute at Chicago, Indian residents, a country which is home to the highest levels of air pollution in the world, lose about 5.9 years from life expectancy due to poor air quality and yet has numerous dwellings dependent on natural ventilation. Currently the urban population spends 90% of the time indoors, this scenario raises a concern for occupant health and well-being. The built environment can affect health directly and indirectly through immediate or long-term exposure to indoor air pollutants. Health effects associated with indoor air pollutants include eye/nose/throat irritation, respiratory diseases, heart disease, and even cancer. This study attempts to demonstrate the causal relationship between the indoor air quality and its determining aspects. Detailed indoor air quality audits were conducted in residential buildings located in Kolkata, India in the months of December and January 2021. According to the air pollution knowledge assessment city program in India, Kolkata is also the second most polluted mega-city after Delhi. Although the air pollution levels are alarming year-long, the winter months are most crucial due to the unfavorable environmental conditions. While emissions remain typically constant throughout the year, cold air is denser and moves slower than warm air, trapping the pollution in place for much longer and consequently is breathed in at a higher rate than the summers. The air pollution monitoring period was selected considering environmental factors and major pollution contributors like traffic and road dust. This study focuses on the relationship between the built environment and the spatial-temporal distribution of air pollutants in and around it. The measured parameters include, temperature, relative humidity, air velocity, particulate matter, volatile organic compounds, formaldehyde, and benzene. A total of 56 rooms were audited, selectively targeting the most dominant middle-income group. The data-collection was conducted using a set of instruments positioned in the human breathing-zone. The study assesses indoor air quality based on factors determining natural ventilation and air pollution dispersion such as surrounding environment, dominant wind, openable window to floor area ratio, windward or leeward side openings, and natural ventilation type in the room: single side or cross-ventilation, floor height, residents cleaning habits, etc.

Keywords: indoor air quality, occupant health, urban housing, air pollution, natural ventilation, architecture, urban issues

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75 Exploring the Neural Correlates of Different Interaction Types: A Hyperscanning Investigation Using the Pattern Game

Authors: Beata Spilakova, Daniel J. Shaw, Radek Marecek, Milan Brazdil

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Hyperscanning affords a unique insight into the brain dynamics underlying human interaction by simultaneously scanning two or more individuals’ brain responses while they engage in dyadic exchange. This provides an opportunity to observe dynamic brain activations in all individuals participating in interaction, and possible interbrain effects among them. The present research aims to provide an experimental paradigm for hyperscanning research capable of delineating among different forms of interaction. Specifically, the goal was to distinguish between two dimensions: (1) interaction structure (concurrent vs. turn-based) and (2) goal structure (competition vs cooperation). Dual-fMRI was used to scan 22 pairs of participants - each pair matched on gender, age, education and handedness - as they played the Pattern Game. In this simple interactive task, one player attempts to recreate a pattern of tokens while the second player must either help (cooperation) or prevent the first achieving the pattern (competition). Each pair played the game iteratively, alternating their roles every round. The game was played in two consecutive sessions: first the players took sequential turns (turn-based), but in the second session they placed their tokens concurrently (concurrent). Conventional general linear model (GLM) analyses revealed activations throughout a diffuse collection of brain regions: The cooperative condition engaged medial prefrontal cortex (mPFC) and posterior cingulate cortex (PCC); in the competitive condition, significant activations were observed in frontal and prefrontal areas, insula cortices and the thalamus. Comparisons between the turn-based and concurrent conditions revealed greater precuneus engagement in the former. Interestingly, mPFC, PCC and insulae are linked repeatedly to social cognitive processes. Similarly, the thalamus is often associated with a cognitive empathy, thus its activation may reflect the need to predict the opponent’s upcoming moves. Frontal and prefrontal activation most likely represent the higher attentional and executive demands of the concurrent condition, whereby subjects must simultaneously observe their co-player and place his own tokens accordingly. The activation of precuneus in the turn-based condition may be linked to self-other distinction processes. Finally, by performing intra-pair correlations of brain responses we demonstrate condition-specific patterns of brain-to-brain coupling in mPFC and PCC. Moreover, the degree of synchronicity in these neural signals related to performance on the game. The present results, then, show that different types of interaction recruit different brain systems implicated in social cognition, and the degree of inter-player synchrony within these brain systems is related to nature of the social interaction.

Keywords: brain-to-brain coupling, hyperscanning, pattern game, social interaction

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74 Urban Stratification as a Basis for Analyzing Political Instability: Evidence from Syrian Cities

Authors: Munqeth Othman Agha

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The historical formation of urban centres in the eastern Arab world was shaped by rapid urbanization and sudden transformation from the age of the pre-industrial to a post-industrial economy, coupled with uneven development, informal urban expansion, and constant surges in unemployment and poverty rates. The city was stratified accordingly as overlapping layers of division and inequality that have been built on top of each other, creating complex horizontal and vertical divisions based on economic, social, political, and ethno-sectarian basis. This has been further exacerbated during the neoliberal era, which transferred the city into a sort of dual city that is inhabited by heterogeneous and often antagonistic social groups. Economic deprivation combined with a growing sense of marginalization and inequality across the city planted the seeds of political instability, outbreaking in 2011. Unlike other popular uprisings that occupy central squares, as in Egypt and Tunisia, the Syrian uprising in 2011 took place mainly within inner streets and neighborhood squares, mobilizing primarily on more or less upon the lines of stratification. This has emphasized the role of micro-urban and social settings in shaping mobilization and resistance tactics, which necessitates us to understand the way the city was stratified and place it at the center of the city-conflict nexus analysis. This research aims to understand to what extent pre-conflict urban stratification lines played a role in determining the different trajectories of three cities’ neighborhoods (Homs, Dara’a and Deir-ez-Zor). The main argument of the paper is that the way the Syrian city has been stratified creates various social groups within the city who have enjoyed different levels of accessibility to life chances, material resources and social statuses. This determines their relationship with other social groups in the city and, more importantly, their relationship with the state. The advent of a political opportunity will be depicted differently across the city’s different social groups according to their perceived interests and threats, which consequently leads to either political mobilization or demobilization. Several factors, including the type of social structures, built environment, and state response, determine the ability of social actors to transfer the repertoire of contention to collective action or transfer from social actors to political actors. The research uses urban stratification lines as the basis for understanding the different patterns of political upheavals in urban areas while explaining why neighborhoods with different social and urban environment settings had different abilities and capacities to mobilize, resist state repression and then descend into a military conflict. It particularly traces the transformation from social groups to social actors and political actors by applying the Explaining-outcome Process-Tracing method to depict the causal mechanisms that led to including or excluding different neighborhoods from each stage of the uprising, namely mobilization (M1), response (M2), and control (M3).

Keywords: urban stratification, syrian conflict, social movement, process tracing, divided city

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73 Social and Economic Aspects of Unlikely but Still Possible Welfare to Work Transitions from Long-Term Unemployed

Authors: Andreas Hirseland, Lukas Kerschbaumer

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In Germany, during the past years there constantly are about one million long term unemployed who did not benefit from the prospering labor market while most short term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long term unemployment thus turns into a main obstacle to regular employment, especially if accompanied by other impediments such as low level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. Almost two thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Hiring them is often considered as an investment too risky for employers. Therefore formal application schemes based on formal qualification certificates and vocational biographies might reduce employers’ risks but at the same time are not helpful for long-term unemployed and welfare recipients. The panel survey ‘Labor market and social security’ (PASS; ~15,000 respondents in ~10,000 households), carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency), shows that their chance to get back to work tends to fall to nil. Only 66 cases of such unlikely transitions could be observed. In a sequential explanatory mixed-method study, the very scarce ‘success stories’ of unlikely transitions from long term unemployment to work were explored by qualitative inquiry – in-depth interviews with a focus on biography accompanied by qualitative network techniques in order to get a more detailed insight of relevant actors involved in the processes which promote the transition from being a welfare recipient to work. There is strong evidence that sustainable transitions are influenced by biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation.

Keywords: against-all-odds, economic sociology, long-term unemployment, mixed-methods

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72 An Exploratory Factor and Cluster Analysis of the Willingness to Pay for Last Mile Delivery

Authors: Maximilian Engelhardt, Stephan Seeck

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The COVID-19 pandemic is accelerating the already growing field of e-commerce. The resulting urban freight transport volume leads to traffic and negative environmental impact. Furthermore, the service level of parcel logistics service provider is lacking far behind the expectations of consumer. These challenges can be solved by radically reorganize the urban last mile distribution structure: parcels could be consolidated in a micro hub within the inner city and delivered within time windows by cargo bike. This approach leads to a significant improvement of consumer satisfaction with their overall delivery experience. However, this approach also leads to significantly increased costs per parcel. While there is a relevant share of online shoppers that are willing to pay for such a delivery service there are no deeper insights about this target group available in the literature. Being aware of the importance of knowing target groups for businesses, the aim of this paper is to elaborate the most important factors that determine the willingness to pay for sustainable and service-oriented parcel delivery (factor analysis) and to derive customer segments (cluster analysis). In order to answer those questions, a data set is analyzed using quantitative methods of multivariate statistics. The data set was generated via an online survey in September and October 2020 within the five largest cities in Germany (n = 1.071). The data set contains socio-demographic, living-related and value-related variables, e.g. age, income, city, living situation and willingness to pay. In a prior work of the author, the data was analyzed applying descriptive and inference statistical methods that only provided limited insights regarding the above-mentioned research questions. The analysis in an exploratory way using factor and cluster analysis promise deeper insights of relevant influencing factors and segments for user behavior of the mentioned parcel delivery concept. The analysis model is built and implemented with help of the statistical software language R. The data analysis is currently performed and will be completed in December 2021. It is expected that the results will show the most relevant factors that are determining user behavior of sustainable and service-oriented parcel deliveries (e.g. age, current service experience, willingness to pay) and give deeper insights in characteristics that describe the segments that are more or less willing to pay for a better parcel delivery service. Based on the expected results, relevant implications and conclusions can be derived for startups that are about to change the way parcels are delivered: more customer-orientated by time window-delivery and parcel consolidation, more environmental-friendly by cargo bike. The results will give detailed insights regarding their target groups of parcel recipients. Further research can be conducted by exploring alternative revenue models (beyond the parcel recipient) that could compensate the additional costs, e.g. online-shops that increase their service-level or municipalities that reduce traffic on their streets.

Keywords: customer segmentation, e-commerce, last mile delivery, parcel service, urban logistics, willingness-to-pay

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71 Active Development of Tacit Knowledge: Knowledge Management, High Impact Practices and Experiential Learning

Authors: John Zanetich

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Due to their positive associations with student learning and retention, certain undergraduate opportunities are designated ‘high-impact.’ High-Impact Practices (HIPs) such as, learning communities, community based projects, research, internships, study abroad and culminating senior experience, share several traits bin common: they demand considerable time and effort, learning occurs outside of the classroom, and they require meaningful interactions between faculty and students, they encourage collaboration with diverse others, and they provide frequent and substantive feedback. As a result of experiential learning in these practices, participation in these practices can be life changing. High impact learning helps individuals locate tacit knowledge, and build mental models that support the accumulation of knowledge. On-going learning from experience and knowledge conversion provides the individual with a way to implicitly organize knowledge and share knowledge over a lifetime. Knowledge conversion is a knowledge management component which focuses on the explication of the tacit knowledge that exists in the minds of students and that knowledge which is embedded in the process and relationships of the classroom educational experience. Knowledge conversion is required when working with tacit knowledge and the demand for a learner to align deeply held beliefs with the cognitive dissonance created by new information. Knowledge conversion and tacit knowledge result from the fact that an individual's way of knowing, that is, their core belief structure, is considered generalized and tacit instead of explicit and specific. As a phenomenon, tacit knowledge is not readily available to the learner for explicit description unless evoked by an external source. The development of knowledge–related capabilities such as Aggressive Development of Tacit Knowledge (ADTK) can be used in experiential educational programs to enhance knowledge, foster behavioral change, improve decision making, and overall performance. ADTK allows the student in HIPs to use their existing knowledge in a way that allows them to evaluate and make any necessary modifications to their core construct of reality in order to amalgamate new information. Based on the Lewin/Schein Change Theory, the learner will reach for tacit knowledge as a stabilizing mechanism when they are challenged by new information that puts them slightly off balance. As in word association drills, the important concept is the first thought. The reactionary outpouring to an experience is the programmed or tacit memory and knowledge of their core belief structure. ADTK is a way to help teachers design their own methods and activities to unfreeze, create new learning, and then refreeze the core constructs upon which future learning in a subject area is built. This paper will explore the use of ADTK as a technique for knowledge conversion in the classroom in general and in HIP programs specifically. It will focus on knowledge conversion in curriculum development and propose the use of one-time educational experiences, multi-session experiences and sequential program experiences focusing on tacit knowledge in educational programs.

Keywords: tacit knowledge, knowledge management, college programs, experiential learning

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70 Functional Switching of Serratia marcescens Transcriptional Regulator from Activator to Inhibitor of Quorum Sensing by Exogenous Addition

Authors: Norihiro Kato, Yuriko Takayama

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Some gram-negative bacteria enable the simultaneous activation of gene expression involved in N-acylhomoserine lactone (AHL) dependent cell-to-cell communication system. Such regulatory system for the bacterial group behavior is termed as quorum sensing (QS) because a diffusible AHL signal can accumulate around the cell during the increase of the cell density and trigger activation of the sequential QS process. By blocking the QS, the expression of diverse genes related to infection, antibiotic production, and biofilm formation is inhibited. Conditioning of QS by regulation of the DNA-receptor-AHL interaction is a potential target for enhancing host defenses against pathogenicity. We focused on engineered application of transcriptional regulator SpnR produced in opportunistic human pathogen Serratia marcescens. The SpnR can interact with AHL signals at an N-terminal domain and also with a promoter region of a QS target gene at a C-terminal domain. As the initial process of the QS activation, the SpnR forms a complex with the AHL to enhance the expression of pig cluster; the SpnR normally acts as an activator for the expression of the QS-dependent gene. In this research, we attempt to artificially control QS by changing the role of SpnR. The QS-dependent prodigiosin production is expected to inhibit by externally added SpnR in the culture broth of AS-1 strain because the AHL concentration was kept below the threshold by AHL-SpnR complex formation. Maltose-binding protein (MBP)-tagged SpnR (MBP-SpnR) was overexpressed in Escherichia coli and purified using an affinity chromatography equipped with an amylose resin column. The specific interaction between AHL and MBP-SpnR was demonstrated by quartz crystal microbalance (QCM) sensor. AHL with amino end-group was coupled with COOH-terminated self-assembled monolayer prepared on a gold electrode of 27-MHz quartz crystal sensor using water-soluble carbodiimide. After the injection of MBP-SpnR into a cup-type sensor cell filled with the buffer solution, time course of resonant frequency change (ΔFs) was determined. A decrease of ΔFs clearly showed the uptake of MBP-SpnR onto the AHL-immobilized electrode. Furthermore, no binding affinity was observed after the heat-inactivation of MBP-SpnR at 80ºC. These results suggest that MBP-SpnR possesses a specific affinity for AHL. MBP-SpnR was added to the culture medium as an AHL trap to study inhibitory effects on intracellularly accumulated prodigiosin. With approximately 2 µM MBP-SpnR, the amount of prodigiosin induced was half that of the control without any additives. In conclusion, the function of SpnR could be switched by adding it to the cell culture. Exogenously added MBP-SpnR possesses high affinity for AHL derived from cells and acts as an inhibitor of AHL-mediated QS.

Keywords: intracellular signaling, microbial biotechnology, quorum sensing, transcriptional regulator

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69 Cobb Angle Measurement from Coronal X-Rays Using Artificial Neural Networks

Authors: Andrew N. Saylor, James R. Peters

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Scoliosis is a complex 3D deformity of the thoracic and lumbar spines, clinically diagnosed by measurement of a Cobb angle of 10 degrees or more on a coronal X-ray. The Cobb angle is the angle made by the lines drawn along the proximal and distal endplates of the respective proximal and distal vertebrae comprising the curve. Traditionally, Cobb angles are measured manually using either a marker, straight edge, and protractor or image measurement software. The task of measuring the Cobb angle can also be represented by a function taking the spine geometry rendered using X-ray imaging as input and returning the approximate angle. Although the form of such a function may be unknown, it can be approximated using artificial neural networks (ANNs). The performance of ANNs is affected by many factors, including the choice of activation function and network architecture; however, the effects of these parameters on the accuracy of scoliotic deformity measurements are poorly understood. Therefore, the objective of this study was to systematically investigate the effect of ANN architecture and activation function on Cobb angle measurement from the coronal X-rays of scoliotic subjects. The data set for this study consisted of 609 coronal chest X-rays of scoliotic subjects divided into 481 training images and 128 test images. These data, which included labeled Cobb angle measurements, were obtained from the SpineWeb online database. In order to normalize the input data, each image was resized using bi-linear interpolation to a size of 500 × 187 pixels, and the pixel intensities were scaled to be between 0 and 1. A fully connected (dense) ANN with a fixed cost function (mean squared error), batch size (10), and learning rate (0.01) was developed using Python Version 3.7.3 and TensorFlow 1.13.1. The activation functions (sigmoid, hyperbolic tangent [tanh], or rectified linear units [ReLU]), number of hidden layers (1, 3, 5, or 10), and number of neurons per layer (10, 100, or 1000) were varied systematically to generate a total of 36 network conditions. Stochastic gradient descent with early stopping was used to train each network. Three trials were run per condition, and the final mean squared errors and mean absolute errors were averaged to quantify the network response for each condition. The network that performed the best used ReLU neurons had three hidden layers, and 100 neurons per layer. The average mean squared error of this network was 222.28 ± 30 degrees2, and the average mean absolute error was 11.96 ± 0.64 degrees. It is also notable that while most of the networks performed similarly, the networks using ReLU neurons, 10 hidden layers, and 1000 neurons per layer, and those using Tanh neurons, one hidden layer, and 10 neurons per layer performed markedly worse with average mean squared errors greater than 400 degrees2 and average mean absolute errors greater than 16 degrees. From the results of this study, it can be seen that the choice of ANN architecture and activation function has a clear impact on Cobb angle inference from coronal X-rays of scoliotic subjects.

Keywords: scoliosis, artificial neural networks, cobb angle, medical imaging

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68 Artificial Intelligence in Management Simulators

Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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67 Distribution Routs Redesign through the Vehicle Problem Routing in Havana Distribution Center

Authors: Sonia P. Marrero Duran, Lilian Noya Dominguez, Lisandra Quintana Alvarez, Evert Martinez Perez, Ana Julia Acevedo Urquiaga

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Cuban business and economic policy are in the constant update as well as facing a client ever more knowledgeable and demanding. For that reason become fundamental for companies competitiveness through the optimization of its processes and services. One of the Cuban’s pillars, which has been sustained since the triumph of the Cuban Revolution back in 1959, is the free health service to all those who need it. This service is offered without any charge under the concept of preserving human life, but it implied costly management processes and logistics services to be able to supply the necessary medicines to all the units who provide health services. One of the key actors on the medicine supply chain is the Havana Distribution Center (HDC), which is responsible for the delivery of medicines in the province; as well as the acquisition of medicines from national and international producers and its subsequent transport to health care units and pharmacies in time, and with the required quality. This HDC also carries for all distribution centers in the country. Given the eminent need to create an actor in the supply chain that specializes in the medicines supply, the possibility of centralizing this operation in a logistics service provider is analyzed. Based on this decision, pharmacies operate as clients of the logistic service center whose main function is to centralize all logistics operations associated with the medicine supply chain. The HDC is precisely the logistic service provider in Havana and it is the center of this research. In 2017 the pharmacies had affectations in the availability of medicine due to deficiencies in the distribution routes. This is caused by the fact that they are not based on routing studies, besides the long distribution cycle. The distribution routs are fixed, attend only one type of customer and there respond to a territorial location by the municipality. Taking into consideration the above-mentioned problem, the objective of this research is to optimize the routes system in the Havana Distribution Center. To accomplish this objective, the techniques applied were document analysis, random sampling, statistical inference and tools such as Ishikawa diagram and the computerized software’s: ArcGis, Osmand y MapIfnfo. As a result, were analyzed four distribution alternatives; the actual rout, by customer type, by the municipality and the combination of the two last. It was demonstrated that the territorial location alternative does not take full advantage of the transportation capacities or the distance of the trips, which leads to elevated costs breaking whit the current ways of distribution and the currents characteristics of the clients. The principal finding of the investigation was the optimum option distribution rout is the 4th one that is formed by hospitals and the join of pharmacies, stomatology clinics, polyclinics and maternal and elderly homes. This solution breaks the territorial location by the municipality and permits different distribution cycles in dependence of medicine consumption and transport availability.

Keywords: computerized geographic software, distribution, distribution routs, vehicle problem routing (VPR)

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66 The Dynamics of a Droplet Spreading on a Steel Surface

Authors: Evgeniya Orlova, Dmitriy Feoktistov, Geniy Kuznetsov

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Spreading of a droplet over a solid substrate is a key phenomenon observed in the following engineering applications: thin film coating, oil extraction, inkjet printing, and spray cooling of heated surfaces. Droplet cooling systems are known to be more effective than film or rivulet cooling systems. It is caused by the greater evaporation surface area of droplets compared with the film of the same mass and wetting surface. And the greater surface area of droplets is connected with the curvature of the interface. Location of the droplets on the cooling surface influences on the heat transfer conditions. The close distance between the droplets provides intensive heat removal, but there is a possibility of their coalescence in the liquid film. The long distance leads to overheating of the local areas of the cooling surface and the occurrence of thermal stresses. To control the location of droplets is possible by changing the roughness, structure and chemical composition of the surface. Thus, control of spreading can be implemented. The most important characteristic of spreading of droplets on solid surfaces is a dynamic contact angle, which is a function of the contact line speed or capillary number. However, there is currently no universal equation, which would describe the relationship between these parameters. This paper presents the results of the experimental studies of water droplet spreading on metal substrates with different surface roughness. The effect of the droplet growth rate and the surface roughness on spreading characteristics was studied at low capillary numbers. The shadow method using high speed video cameras recording up to 10,000 frames per seconds was implemented. A droplet profile was analyzed by Axisymmetric Drop Shape Analyses techniques. According to change of the dynamic contact angle and the contact line speed three sequential spreading stages were observed: rapid increase in the dynamic contact angle; monotonous decrease in the contact angle and the contact line speed; and form of the equilibrium contact angle at constant contact line. At low droplet growth rate, the dynamic contact angle of the droplet spreading on the surfaces with the maximum roughness is found to increase throughout the spreading time. It is due to the fact that the friction force on such surfaces is significantly greater than the inertia force; and the contact line is pinned on microasperities of a relief. At high droplet growth rate the contact angle decreases during the second stage even on the surfaces with the maximum roughness, as in this case, the liquid does not fill the microcavities, and the droplet moves over the “air cushion”, i.e. the interface is a liquid/gas/solid system. Also at such growth rates pulsation of liquid flow was detected; and the droplet oscillates during the spreading. Thus, obtained results allow to conclude that it is possible to control spreading by using the surface roughness and the growth rate of droplets on surfaces as varied factors. Also, the research findings may be used for analyzing heat transfer in rivulet and drop cooling systems of high energy equipment.

Keywords: contact line speed, droplet growth rate, dynamic contact angle, shadow system, spreading

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65 Iron Metabolism and Ferroptosis in Polycystic Ovary Syndrome: A Systematic Review and Meta-Analysis

Authors: Fangfang Wang, Tianjing Wang, Leyi Fu, Feng Yun, Ningning Xie, Jue Zhou, Fan Qu

Abstract:

Background: Ferroptosis, a recently discovered form of programmed cell death characterized by iron-dependent lipid peroxidation, may be linked to polycystic ovary syndrome (PCOS). Diseases marked by iron overload have been correlated with ferroptosis. Coincidently, investigations have revealed anomalies in iron metabolism among women with PCOS; however, there were inconsistencies in the evidence. Objective and Rationale: This review aimed to comprehensively explore the potential relationship between ferroptosis and PCOS by investigating the differences in iron metabolism among women with PCOS in comparison to a control group. Additionally, a narrative synthesis was provided on the past research status regarding the association between PCOS and ferroptosis. Methods: A systematic search of the literature was performed using PubMed, Embase, Web of Science from inception up to December 2022. Search terms relating to assisted PCOS, ferroptosis, and iron metabolism were used. PRISMA guidance was followed. RevMan 5.4 was utilized for conducting the meta-analysis, wherein the investigated outcomes included iron status (ferritin, iron, transferrin saturation) and a systemic iron-regulatory hormone (hepcidin). A narrative synthesis was performed to explore the correlation between PCOS and ferroptosis. Results: In the meta-analysis comprising a total of 16 studies, significant differences in serum ferritin levels between the PCOS group and the control group were observed (15 studies, standardized mean difference (SMD): 0.41, 95% CI: 0.22 to 0.59, P<0.01). This indicates elevated serum ferritin levels in PCOS patients compared to women without PCOS. The transferrin saturation in PCOS patients was significantly higher than that in the control group (3 studies, mean difference (MD): 4.39, 95% CI: 1.67 to 7.11, P<0.01). Regarding serum iron (6 studies, SMD: 0.05, 95% CI: -0.24 to 0.33, P=0.75) and serum hepcidin (4 studies, SMD: -0.44, 95% CI: -1.41 to 0.52, P=0.37), no statistically significant differences were observed between the PCOS group and the control group. Other studies have found that ferroptosis is involved in the occurrence and development of PCOS, offering valuable insights for guiding potential treatment measures and prognosis evaluation of PCOS. In addition, ferroptosis is involved in the miscarriage of PCOS-like rats; thus, controlling ferroptosis might improve pregnancy outcomes in PCOS. Conclusions: The observation of a significant elevation in serum ferritin and transferrin saturation levels in women with PCOS may suggest an underlying disturbance in iron metabolism, potentially inducing the activation of ferroptosis. Further research is imperative to elucidate the underlying pathophysiology, providing insights for potential preventive measures and therapeutic strategies. Limitation: There are some limitations as follows: First, due to limited extractable information, we excluded purely abstract publications and non-English publications. Second, the majority of original articles were case-control studies, making it difficult to determine the causal relationship between iron metabolism abnormalities and the onset of PCOS. Third, there is substantial heterogeneity in the definition of PCOS.

Keywords: polycystic ovary syndrome, ferroptosis, iron metabolism, systematic review and meta-analysis

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64 Inferring Influenza Epidemics in the Presence of Stratified Immunity

Authors: Hsiang-Yu Yuan, Marc Baguelin, Kin O. Kwok, Nimalan Arinaminpathy, Edwin Leeuwen, Steven Riley

Abstract:

Traditional syndromic surveillance for influenza has substantial public health value in characterizing epidemics. Because the relationship between syndromic incidence and the true infection events can vary from one population to another and from one year to another, recent studies rely on combining serological test results with syndromic data from traditional surveillance into epidemic models to make inference on epidemiological processes of influenza. However, despite the widespread availability of serological data, epidemic models have thus far not explicitly represented antibody titre levels and their correspondence with immunity. Most studies use dichotomized data with a threshold (Typically, a titre of 1:40 was used) to define individuals as likely recently infected and likely immune and further estimate the cumulative incidence. Underestimation of Influenza attack rate could be resulted from the dichotomized data. In order to improve the use of serosurveillance data, here, a refinement of the concept of the stratified immunity within an epidemic model for influenza transmission was proposed, such that all individual antibody titre levels were enumerated explicitly and mapped onto a variable scale of susceptibility in different age groups. Haemagglutination inhibition titres from 523 individuals and 465 individuals during pre- and post-pandemic phase of the 2009 pandemic in Hong Kong were collected. The model was fitted to serological data in age-structured population using Bayesian framework and was able to reproduce key features of the epidemics. The effects of age-specific antibody boosting and protection were explored in greater detail. RB was defined to be the effective reproductive number in the presence of stratified immunity and its temporal dynamics was compared to the traditional epidemic model using use dichotomized seropositivity data. Deviance Information Criterion (DIC) was used to measure the fitness of the model to serological data with different mechanisms of the serological response. The results demonstrated that the differential antibody response with age was present (ΔDIC = -7.0). The age-specific mixing patterns with children specific transmissibility, rather than pre-existing immunity, was most likely to explain the high serological attack rates in children and low serological attack rates in elderly (ΔDIC = -38.5). Our results suggested that the disease dynamics and herd immunity of a population could be described more accurately for influenza when the distribution of immunity was explicitly represented, rather than relying only on the dichotomous states 'susceptible' and 'immune' defined by the threshold titre (1:40) (ΔDIC = -11.5). During the outbreak, RB declined slowly from 1.22[1.16-1.28] in the first four months after 1st May. RB dropped rapidly below to 1 during September and October, which was consistent to the observed epidemic peak time in the late September. One of the most important challenges for infectious disease control is to monitor disease transmissibility in real time with statistics such as the effective reproduction number. Once early estimates of antibody boosting and protection are obtained, disease dynamics can be reconstructed, which are valuable for infectious disease prevention and control.

Keywords: effective reproductive number, epidemic model, influenza epidemic dynamics, stratified immunity

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63 Use of Proton Pump Inhibitors Medications during the First Years of Life and Late Complications

Authors: Kamelia Hamza

Abstract:

Background: Proton pump inhibitors (PPIs) are the most prescribed drug classes for pediatric gastroesophageal reflux disease (GERD).Many patients are treated with these drugs for atypical manifestations attributed to gastroesophageal reflux (GER), even in the absence of proved causal relationship. There is an impression of increase use of PPI's treatment for reflux in "clalit health services," the largest health organization in Israel. In the recent years, the medicine is given without restriction, it's not limited to pediatric gastroenterologists only, but pediatricians and family doctors. The objective of this study is to evaluate the hypothesis that exposure to PPIs during the first year of life is associated with an increased risk of developing late adverse diseases: pneumonia, asthma, AGE, IBD, celiac disease, allergic disorders, obesity, attention deficit hyperactivity disorders (ADHD), autism spectrum disorders (ASD). Methods: The study is a retrospective case-control cohort study based on a computerized database of Clalit Health Services (CHS). It includes 9844 children born between 2002-2018 and reported to complain of at least one of the symptoms (reflux/ spitting up, irritability, feeding difficulties, colics). The study population included the study group (n=4922) of children exposed to PPIs at any time prior to the first year of life and a control group (n=4922) child not exposed to PPIs who were matched to each case of the study group on age, race, socioeconomic status, and year of birth. The prevalence of late complications/diseases in the study group was compared with the prevalence of late complications/diseases diagnosis between 2002-2020 in the control group. Odds ratios and 95% confidence intervals were calculated by using logistic regression models. Results: We found that compared to the control group, children exposed to PPIs in the first year of life had an increased risk of developing several late complications/ disorders: pneumonia, asthma, various allergies (urticaria, allergic rhinitis, or allergic conjunctivitis) OR, inhalant allergies, and food allergies. In addition, they showed an increased risk of being diagnosed with ADHD or ASD, but children exposed to PPIs in the first year of life had decrease the risk of obesity by 17% (OR 0.825, 95%CI 0.697-0.976). Conclusions: We found significant associations between the use of PPIs during the first year of life and subsequent development of late complications/diseases such as respiratory diseases, allergy diseases, ADHD, and ASD. More studies are needed to prove causality and determine the mechanism behind the effect of PPIs and the development of late complications.

Keywords: acid suppressing medications, proton pump inhibitors, histamine 2 blocker, late complications, gastroesophageal reflux, gastroesophageal reflux disease, acute gastroenteritis, community acquired pneumonia, asthma, allergic diseases, obesity, inflammatory bowel diseases, ulcerative colitis, crohn disease, attention deficit hyperactivity disorders, autism spectrum disorders

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62 A Comparative Study on South-East Asian Leading Container Ports: Jawaharlal Nehru Port Trust, Chennai, Singapore, Dubai, and Colombo Ports

Authors: Jonardan Koner, Avinash Purandare

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In today’s globalized world international business is a very key area for the country's growth. Some of the strategic areas for holding up a country’s international business to grow are in the areas of connecting Ports, Road Network, and Rail Network. India’s International Business is booming both in Exports as well as Imports. Ports play a very central part in the growth of international trade and ensuring competitive ports is of critical importance. India has a long coastline which is a big asset for the country as it has given the opportunity for development of a large number of major and minor ports which will contribute to the maritime trades’ development. The National Economic Development of India requires a well-functioning seaport system. To know the comparative strength of Indian ports over South-east Asian similar ports, the study is considering the objectives of (I) to identify the key parameters of an international mega container port, (II) to compare the five selected container ports (JNPT, Chennai, Singapore, Dubai, and Colombo Ports) according to user of the ports and iii) to measure the growth of selected five container ports’ throughput over time and their comparison. The study is based on both primary and secondary databases. The linear time trend analysis is done to show the trend in quantum of exports, imports and total goods/services handled by individual ports over the years. The comparative trend analysis is done for the selected five ports of cargo traffic handled in terms of Tonnage (weight) and number of containers (TEU’s). The comparative trend analysis is done between containerized and non-containerized cargo traffic in the five selected five ports. The primary data analysis is done comprising of comparative analysis of factor ratings through bar diagrams, statistical inference of factor ratings for the selected five ports, consolidated comparative line charts of factor rating for the selected five ports, consolidated comparative bar charts of factor ratings of the selected five ports and the distribution of ratings (frequency terms). The linear regression model is used to forecast the container capacities required for JNPT Port and Chennai Port by the year 2030. Multiple regression analysis is carried out to measure the impact of selected 34 explanatory variables on the ‘Overall Performance of the Port’ for each of the selected five ports. The research outcome is of high significance to the stakeholders of Indian container handling ports. Indian container port of JNPT and Chennai are benchmarked against international ports such as Singapore, Dubai, and Colombo Ports which are the competing ports in the neighbouring region. The study has analysed the feedback ratings for the selected 35 factors regarding physical infrastructure and services rendered to the port users. This feedback would provide valuable data for carrying out improvements in the facilities provided to the port users. These installations would help the ports’ users to carry out their work in more efficient manner.

Keywords: throughput, twenty equivalent units, TEUs, cargo traffic, shipping lines, freight forwarders

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61 Species Profiling of Scarab Beetles with the Help of Light Trap in Western Himalayan Region of Uttarakhand

Authors: Ajay Kumar Pandey

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White grub (Coleoptera: Scarabaeidae), locally known as Kurmula, Pagra, Chinchu, is a major destructive pest in western Himalayan region of Uttarakhand state of India. Various crops like cereals (up land paddy, wheat, and barley), vegetables (capsicum, cabbage, tomato, cauliflower, carrot etc) and some pulse (like pigeon pea, green gram, black gram) are grown with limited availability of primary resources. Among the various limitations in successful cultivation of these crops, white grub has been proved a major constraint in for all crops grown in hilly area. The losses incurred due to white grubs are huge in case of commercial crops like sugarcane, groundnut, potato, maize and upland rice. Moreover, it has been proved major constraint in potato production in mid and higher hills of India. Adults emerge in May-June following the onset of monsoon and thereafter defoliate the apple, apricot, plum, and walnut during night while 2nd and 3rd instar grubs feed on live roots of cultivated as well as non cultivated crops from August to January. Survey was conducted in hilly (Pauri and Tehri) as well as plain area (Haridwar district) of Uttarakhand state. Collection of beetle was done from various locations from August to September of five consecutive years with the help of light trap and directly from host plant. The grub was also collected by excavating one square meter area from different locations and reared in laboratory to find out adult. During the collection, the diseased or dead cadaver were also collected and brought in the laboratory and identified the causal organisms. Total 25 species of white grub was identified out of which Holotrichia longipennis, Anomala dimidiata, Holotrichia lineatopennis, Maladera insanabilis, Brahmina sp. make complex problem in different area of Uttarakhand where they cause severe damage to various crops. During the survey, it was observed that white grubs beetles have variation in preference of host plant, even in choice of fruit and leaves of host plant. It was observed that, a white grub species, which identified as Lepidiota mansueta Burmeister., was causing severe havoc to sugarcane crop grown in major sugarcane growing belt of Haridwar district. The study also revealed that Bacillus cereus, Beauveria bassiana, Metarhizium anisopliae, Steinernema, Heterorhabditis are major disease causing agents in immature stage of white grub under rain-fed condition of Uttarakhand which caused 15.55 to 21.63 percent natural mortality of grubs with an average of 18.91 percent. However, among the microorganisms, B. cereus found to be significantly more efficient (7.03 percent mortality) then the entomopathogenic fungi (3.80 percent mortality) and nematodes (3.20 percent mortality).

Keywords: Lepidiota, profiling, Uttarakhand, whitegrub

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60 Influence of Temperature and Immersion on the Behavior of a Polymer Composite

Authors: Quentin C.P. Bourgogne, Vanessa Bouchart, Pierre Chevrier, Emmanuel Dattoli

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This study presents an experimental and theoretical work conducted on a PolyPhenylene Sulfide reinforced with 40%wt of short glass fibers (PPS GF40) and its matrix. Thermoplastics are widely used in the automotive industry to lightweight automotive parts. The replacement of metallic parts by thermoplastics is reaching under-the-hood parts, near the engine. In this area, the parts are subjected to high temperatures and are immersed in cooling liquid. This liquid is composed of water and glycol and can affect the mechanical properties of the composite. The aim of this work was thus to quantify the evolution of mechanical properties of the thermoplastic composite, as a function of temperature and liquid aging effects, in order to develop a reliable design of parts. An experimental campaign in the tensile mode was carried out at different temperatures and for various glycol proportions in the cooling liquid, for monotonic and cyclic loadings on a neat and a reinforced PPS. The results of these tests allowed to highlight some of the main physical phenomena occurring during these solicitations under tough hydro-thermal conditions. Indeed, the performed tests showed that temperature and liquid cooling aging can affect the mechanical behavior of the material in several ways. The more the cooling liquid contains water, the more the mechanical behavior is affected. It was observed that PPS showed a higher sensitivity to absorption than to chemical aggressiveness of the cooling liquid, explaining this dominant sensitivity. Two kinds of behaviors were noted: an elasto-plastic type under the glass transition temperature and a visco-pseudo-plastic one above it. It was also shown that viscosity is the leading phenomenon above the glass transition temperature for the PPS and could also be important under this temperature, mostly under cyclic conditions and when the stress rate is low. Finally, it was observed that soliciting this composite at high temperatures is decreasing the advantages of the presence of fibers. A new phenomenological model was then built to take into account these experimental observations. This new model allowed the prediction of the evolution of mechanical properties as a function of the loading environment, with a reduced number of parameters compared to precedent studies. It was also shown that the presented approach enables the description and the prediction of the mechanical response with very good accuracy (2% of average error at worst), over a wide range of hydrothermal conditions. A temperature-humidity equivalence principle was underlined for the PPS, allowing the consideration of aging effects within the proposed model. Then, a limit of improvement of the reachable accuracy was determinate for all models using this set of data by the application of an artificial intelligence-based model allowing a comparison between artificial intelligence-based models and phenomenological based ones.

Keywords: aging, analytical modeling, mechanical testing, polymer matrix composites, sequential model, thermomechanical

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