Search results for: social mental models
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 16909

Search results for: social mental models

6739 Teaching during the Pandemic Using a Feminist Pedagogy: Classroom Conversations and Practices

Authors: T. Northcut, A. Rai, N. Perkins

Abstract:

Background: The COVID-19 pandemic has had a serious impact on academia in general and social work education in particular, changing permanently the way in which we approach educating students. The new reality of the pandemic coupled with the much-needed focus on racism across the country inspired and required educators to get creative with their teaching styles in order to disrupt the power imbalance in the classroom and attend to the multiple layers of needs of diverse students in precarious sociological and economic circumstances. This paper highlights research examining educators with distinctive positionalities and approaches to classroom instruction who use feminist and antiracist pedagogies while adapting to online teaching during the pandemic. Despite being feminist scholars, whose ideologies developed during different waves of feminism, our commitment to having student-led classrooms, liberation, and equity of all, and striving for social change, unified our feminist teaching pedagogies as well as provided interpersonal support. Methodology: Following a narrative qualitative inquiry methodology, the five authors of this paper came together to discuss our pedagogical styles and underlying values using Zoom in a series of six conversations. Narrative inquiry is an appropriate method to use when researchers are bound by common stories or personal experiences. The use of feminist pedagogy in the classroom before and during the pandemic guided the discussions. After six sessions, we reached the point of data saturation. All data from the dialogic process was recorded and transcribed. We used in vivo, narrative, and descriptive coding for the data analytic process. Results: Analysis of the data revealed several themes, which included (1) the influence of our positionalities as an intersection of race, sexual orientation, gender, and years of teaching experience in the classroom, (2) the meaning and variations between different liberatory pedagogical approaches, (3) the tensions between these approaches and institutional policies and practices, (4) the role of self-reflection in everyday teaching, (5) the distinctions between theory and practice and its utility for students, and (6) the challenges of applying a feminist-centered pedagogical approach during the pandemic while utilizing an online platform. As a collective, we discussed several challenges that limited the use of our feminist pedagogical approaches due to instruction through Zoom.

Keywords: feminist, pedagogy, COVID, zoom

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6738 Reinforcement Learning Optimization: Unraveling Trends and Advancements in Metaheuristic Algorithms

Authors: Rahul Paul, Kedar Nath Das

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The field of machine learning (ML) is experiencing rapid development, resulting in a multitude of theoretical advancements and extensive practical implementations across various disciplines. The objective of ML is to facilitate the ability of machines to perform cognitive tasks by leveraging knowledge gained from prior experiences and effectively addressing complex problems, even in situations that deviate from previously encountered instances. Reinforcement Learning (RL) has emerged as a prominent subfield within ML and has gained considerable attention in recent times from researchers. This surge in interest can be attributed to the practical applications of RL, the increasing availability of data, and the rapid advancements in computing power. At the same time, optimization algorithms play a pivotal role in the field of ML and have attracted considerable interest from researchers. A multitude of proposals have been put forth to address optimization problems or improve optimization techniques within the domain of ML. The necessity of a thorough examination and implementation of optimization algorithms within the context of ML is of utmost importance in order to provide guidance for the advancement of research in both optimization and ML. This article provides a comprehensive overview of the application of metaheuristic evolutionary optimization algorithms in conjunction with RL to address a diverse range of scientific challenges. Furthermore, this article delves into the various challenges and unresolved issues pertaining to the optimization of RL models.

Keywords: machine learning, reinforcement learning, loss function, evolutionary optimization techniques

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6737 Data-Driven Analysis of Velocity Gradient Dynamics Using Neural Network

Authors: Nishant Parashar, Sawan S. Sinha, Balaji Srinivasan

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We perform an investigation of the unclosed terms in the evolution equation of the velocity gradient tensor (VGT) in compressible decaying turbulent flow. Velocity gradients in a compressible turbulent flow field influence several important nonlinear turbulent processes like cascading and intermittency. In an attempt to understand the dynamics of the velocity gradients various researchers have tried to model the unclosed terms in the evolution equation of the VGT. The existing models proposed for these unclosed terms have limited applicability. This is mainly attributable to the complex structure of the higher order gradient terms appearing in the evolution equation of VGT. We investigate these higher order gradients using the data from direct numerical simulation (DNS) of compressible decaying isotropic turbulent flow. The gas kinetic method aided with weighted essentially non-oscillatory scheme (WENO) based flow- reconstruction is employed to generate DNS data. By applying neural-network to the DNS data, we map the structure of the unclosed higher order gradient terms in the evolution of the equation of the VGT with VGT itself. We validate our findings by performing alignment based study of the unclosed higher order gradient terms obtained using the neural network with the strain rate eigenvectors.

Keywords: compressible turbulence, neural network, velocity gradient tensor, direct numerical simulation

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6736 Locket Application

Authors: Farah Al-Fityani, Aljohara Alsowail, Shatha Bindawood, Heba Balrbeah

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Locket is a popular app that lets users share spontaneous photos with a close circle of friends. The app offers a unique way to stay connected with loved ones by allowing users to see glimpses of their day through photos displayed on a widget on their home screen. This summary outlines the process of developing an app like Locket, highlighting the importance of user privacy and security. It also details the findings of a study on user engagement with the Locket app, revealing positive sentiment towards its features and concept but also identifying areas for improvement. Overall, the summary portrays Locket as a successful app that is changing the way people connect on social media.

Keywords: locket, app, machine learning, connect

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6735 Metalorganic Chemical Vapor Deposition Overgrowth on the Bragg Grating for Gallium Nitride Based Distributed Feedback Laser

Authors: Junze Li, M. Li

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Laser diodes fabricated from the III-nitride material system are emerging solutions for the next generation telecommunication systems and optical clocks based on Ca at 397nm, Rb at 420.2nm and Yb at 398.9nm combined 556 nm. Most of the applications require single longitudinal optical mode lasers, with very narrow linewidth and compact size, such as communication systems and laser cooling. In this case, the GaN based distributed feedback (DFB) laser diode is one of the most effective candidates with gratings are known to operate with narrow spectra as well as high power and efficiency. Given the wavelength range, the period of the first-order diffraction grating is under 100 nm, and the realization of such gratings is technically difficult due to the narrow line width and the high quality nitride overgrowth based on the Bragg grating. Some groups have reported GaN DFB lasers with high order distributed feedback surface gratings, which avoids the overgrowth. However, generally the strength of coupling is lower than that with Bragg grating embedded into the waveguide within the GaN laser structure by two-step-epitaxy. Therefore, the overgrowth on the grating technology need to be studied and optimized. Here we propose to fabricate the fine step shape structure of first-order grating by the nanoimprint combined inductively coupled plasma (ICP) dry etching, then carry out overgrowth high quality AlGaN film by metalorganic chemical vapor deposition (MOCVD). Then a series of gratings with different period, depths and duty ratios are designed and fabricated to study the influence of grating structure to the nano-heteroepitaxy. Moreover, we observe the nucleation and growth process by step-by-step growth to study the growth mode for nitride overgrowth on grating, under the condition that the grating period is larger than the mental migration length on the surface. The AFM images demonstrate that a smooth surface of AlGaN film is achieved with an average roughness of 0.20 nm over 3 × 3 μm2. The full width at half maximums (FWHMs) of the (002) reflections in the XRD rocking curves are 278 arcsec for the AlGaN film, and the component of the Al within the film is 8% according to the XRD mapping measurement, which is in accordance with design values. By observing the samples with growth time changing from 200s, 400s to 600s, the growth model is summarized as the follow steps: initially, the nucleation is evenly distributed on the grating structure, as the migration length of Al atoms is low; then, AlGaN growth alone with the grating top surface; finally, the AlGaN film formed by lateral growth. This work contributed to carrying out GaN DFB laser by fabricating grating and overgrowth on the nano-grating patterned substrate by wafer scale, moreover, growth dynamics had been analyzed as well.

Keywords: DFB laser, MOCVD, nanoepitaxy, III-niitride

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6734 Higher Freshwater Fish and Sea Fish Intake Is Inversely Associated with Liver Cancer in Patients with Hepatitis B

Authors: Maomao Cao

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Background and aims While the association between higher consumption of fish and lower liver cancer risk has been confirmed, however, the association between specific fish intake and liver cancer risk remains unknown. We aimed to identify the association between specific fish consumption and the risk of liver cancer. Methods: Based on a community-based seropositive hepatitis B cohort involving 18404 individuals, face to face interview was conducted by a standardized questionnaire to acquire baseline information. Three common fish types in this study were analyzed, including freshwater fish, sea fish, and small fish (shrimp, crab, conch, and shell). All participants received liver cancer screening, and possible cases were identified by CT or MRI. Multivariable logistic models were applied to estimate the odds ratio (OR) and 95% confidence intervals (CI). Multivariate multiple imputations were utilized to impute observations with missing values. Results: 179 liver cancer cases were identified. Consumption of freshwater fish and sea fish at least once a week had a strong inverse association with liver cancer risk compared with the lowest intake level, with an adjusted OR of 0.53 (95% CI, 0.38-0.75) and 0.38 (95% CI, 0.19-0.73), respectively. This inverse association was also observed after the imputation. There was no statistically significant association between intake of small fish and liver cancer risk (OR=0.58, 95%, CI 0.32-1.08). Conclusions: Our findings suggest that consumption of freshwater fish and sea fish at least once a week could reduce liver cancer risk.

Keywords: cross-sectional study, fish intake, liver cancer, risk factor

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6733 A Community-Engaged Approach to Examining Health Outcomes Potentially Related to Exposure to Environmental Contaminants in Yuma, Arizona

Authors: Julie A. Baldwin, Robert T. Trotter, Mark Remiker, C. Loren Buck, Amanda Aguirre, Trudie Milner, Emma Torres, Frank A. von Hippel

Abstract:

Introduction: In the past, there have been concerns about contaminants in the water sources in Yuma, Arizona, including the Colorado River. Prolonged exposure to contaminants, such as perchlorate and heavy metals, can lead to deleterious health effects in humans. This project examined the association between the concentration of environmental contaminants and patient health outcomes in Yuma residents, using a community-engaged approach to data collection. Methods: A community-engaged design allowed community partners and researchers to establish joint research goals, recruit participants, collect data, and formulate strategies for dissemination of findings. Key informant interviews were conducted to evaluate adherence to models of community-based research. Results: The training needs, roles, and expectations of community partners varied based on available resources, prior research experience, and perceived research challenges and ways to address them. Conclusions: Leveraging community-engaged approaches for studies of environmental contamination in marginalized communities can expedite recruitment efforts and stimulate action that can lead to improved community health.

Keywords: community engaged research, environmental contaminants, underserved populations, health equity

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6732 In Search of Commonalities in the Determinants of Child Sex Ratios in India and People's of Republic of China

Authors: Suddhasil Siddhanta, Debasish Nandy

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Child sex ratios pattern in the Asian Population is highly masculine mainly due to birth masculinity and gender bias in child mortality. The vast and the growing literature of female deficit in world population points out the diffusion of child sex ratio pattern in many Asian as well as neighboring European countries. However, little attention has been given to understand the common factors in different demographics in explaining child sex ratio pattern. Such a scholarship is extremely important as level of gender inequity is different in different country set up. Our paper tries to explain the major structural commonalities in the child masculinity pattern in two demographic billionaires - India and China. The analysis reveals that apart from geographical diffusion of sex selection technology, patrilocal social structure, as proxied by households with more than one generation in China and proportion of population aged 65 years and above in India, can explain significant variation of missing girl child in these two countries. Even after controlling for individual capacity building factors like educational attainment, or work force participation, the measure of social stratification is coming out to be the major determinant of child sex ratio variation. Other socio economic factors that perform much well are the agency building factors of the females, like changing pattern of marriage customs which is proxied by divorce and remarriage ratio for china and percentage of female marrying at or after the age of 20 years in India and the female workforce participation. Proportion of minorities in socio-religious composition of the population and gender bias in scholastic attainment in both these counties are also found to be significant in modeling child sex ratio variations. All these significant common factors associated with child sex ratio point toward the one single most important factor: the historical evolution of patriarchy and its contemporary perpetuation in both the countries. It seems that prohibition of sex selection might not be sufficient to combat the peculiar skewness of excessive maleness in child population in both these countries. Demand sided policies is therefore utmost important to root out the gender bias in child sex ratios.

Keywords: child sex ratios, gender bias, structural factors, prosperity, patrilocality

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6731 A Semantic E-Learning and E-Assessment System of Learners

Authors: Wiem Ben Khalifa, Dalila Souilem, Mahmoud Neji

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The evolutions of Social Web and Semantic Web lead us to ask ourselves about the way of supporting the personalization of learning by means of intelligent filtering of educational resources published in the digital networks. We recommend personalized courses of learning articulated around a first educational course defined upstream. Resuming the context and the stakes in the personalization, we also suggest anchoring the personalization of learning in a community of interest within a group of learners enrolled in the same training. This reflection is supported by the display of an active and semantic system of learning dedicated to the constitution of personalized to measure courses and in the due time.

Keywords: Semantic Web, semantic system, ontology, evaluation, e-learning

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6730 Explaining the Relationship between Religiosity and Resilience

Authors: Rita Phillips, Mark Burgess, Maga Berlinski

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Although the positive impact of religiosity on well-being, health, and life-coping abilities is well known, up to date research has failed to provide scientific evidence for the relationship reasons. Therefore the present study took a qualitative approach by examining how religiosity interacts in coping with emotionally distressful situations, for which wedding preparations are an example. Wedding preparations, related to the experience of ambiguous emotions, can be the reason for phases of high distress. Although being per-se religious ceremonies, they are also socially-scripted and characterized by people’s striving for personally meaningful celebrations. The negotiation of these many influences can evoke conflicts. To reveal components of religiosity which contribute to stress-resolution, eight biographic-narrative interviews with recently married spouses were conducted. Participants were from different nationalities and Catholic deep-belief communities in order to determine factors independent from national-culture and social-subgroup. The audio-tape recorded, transcribed and translated interviews were analyzed by Interpretative Phenomenological Analysis. Opposing previous research on wedding-related conflicts but in-line with the quantitative account on the relation between stress-resilience and religiosity, the present study found participants reporting very low levels of distress and ambiguity. Although similar areas of potential conflicts were revealed, deep-belief Christians seemed to handle them in a different way. Participants freed themselves from own and others’ rigor mundane expectations by their spiritual preparation and the focus on a divine instance. This evoked a feeling of perceived closeness to God and of unconditional love, resulting in acceptance of oneself and others. Through relativizing mundane goods, participants perceived absolute freedom. Thus belief did not supplement coping strategies, previously defined in the literature, but substituted them. The paper implies that in explaining the connection between stress-resilience and religiosity, one’s perception and experience of unconditional love might outweigh other social or personal factors. However, further qualitative investigations are needed to fully explain the phenomenon.

Keywords: deep-belief, religiosity, resilience, wedding

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6729 Customized Design of Amorphous Solids by Generative Deep Learning

Authors: Yinghui Shang, Ziqing Zhou, Rong Han, Hang Wang, Xiaodi Liu, Yong Yang

Abstract:

The design of advanced amorphous solids, such as metallic glasses, with targeted properties through artificial intelligence signifies a paradigmatic shift in physical metallurgy and materials technology. Here, we developed a machine-learning architecture that facilitates the generation of metallic glasses with targeted multifunctional properties. Our architecture integrates the state-of-the-art unsupervised generative adversarial network model with supervised models, allowing the incorporation of general prior knowledge derived from thousands of data points across a vast range of alloy compositions, into the creation of data points for a specific type of composition, which overcame the common issue of data scarcity typically encountered in the design of a given type of metallic glasses. Using our generative model, we have successfully designed copper-based metallic glasses, which display exceptionally high hardness or a remarkably low modulus. Notably, our architecture can not only explore uncharted regions in the targeted compositional space but also permits self-improvement after experimentally validated data points are added to the initial dataset for subsequent cycles of data generation, hence paving the way for the customized design of amorphous solids without human intervention.

Keywords: metallic glass, artificial intelligence, mechanical property, automated generation

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6728 Behavioral Stages of Change in Calorie Balanced Dietary Intake; Effects of Decisional Balance and Self–Efficacy in Obese and Overweight Women

Authors: Abdmohammad Mousavi, Mohsen Shams, Mehdi Akbartabar Toori, Ali Mousavizadeh, Mohammad Ali Morowatisharifabad

Abstract:

Introduction: The effectiveness of Transtheoretical Model constructs on dietary behavior change has been subject to questions by some studies. The objective of this study was to determine the relationship between self–efficacy and decisional balance as mediator variables and transfer obese and overweight women among the stages of behavior change of calorie balanced dietary intake. Method: In this cross-sectional study, 448 obese and overweight 20-44 years old women were selected from three health centers in Yasuj, a city in south west of Iran. Anthropometric data were measured using standard techniques. Demographic, stages of change, self-efficacy and decisional balance data were collected by questionnaires and analyzed using One–Way ANOVA and Generalized Linear Models tests. Results: Demographic and anthropometric variables were not different significantly in different stages of change related to calorie intake except the pre-high school level of education (P=.047, OR=502, 95% CI= .255 ~ .990). Mean scores of Self-efficacy ( F(4.425)= 27.09, P= .000), decisional balance (F(4.394), P= .004), and pros (F(4.430)=5.33, P=000) were different significantly in five stages of change. However, the cons did not show a significant change in this regard (F(4.400)=1.83, P=.123). Discussion: Women movement through the stages of changes for calorie intake behavior can be predicted by self efficacy, decisional balance and pros.

Keywords: transtheoretical model, stages of change, self efficacy, decisional balance, calorie intake, women

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6727 Correlation of Unsuited and Suited 5ᵗʰ Female Hybrid III Anthropometric Test Device Model under Multi-Axial Simulated Orion Abort and Landing Conditions

Authors: Christian J. Kennett, Mark A. Baldwin

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As several companies are working towards returning American astronauts back to space on US-made spacecraft, NASA developed a human flight certification-by-test and analysis approach due to the cost-prohibitive nature of extensive testing. This process relies heavily on the quality of analytical models to accurately predict crew injury potential specific to each spacecraft and under dynamic environments not tested. As the prime contractor on the Orion spacecraft, Lockheed Martin was tasked with quantifying the correlation of analytical anthropometric test devices (ATDs), also known as crash test dummies, against test measurements under representative impact conditions. Multiple dynamic impact sled tests were conducted to characterize Hybrid III 5th ATD lumbar, head, and neck responses with and without a modified shuttle-era advanced crew escape suit (ACES) under simulated Orion landing and abort conditions. Each ATD was restrained via a 5-point harness in a mockup Orion seat fixed to a dynamic impact sled at the Wright Patterson Air Force Base (WPAFB) Biodynamics Laboratory in the horizontal impact accelerator (HIA). ATDs were subject to multiple impact magnitudes, half-sine pulse rise times, and XZ - ‘eyeballs out/down’ or Z-axis ‘eyeballs down’ orientations for landing or an X-axis ‘eyeballs in’ orientation for abort. Several helmet constraint devices were evaluated during suited testing. Unique finite element models (FEMs) were developed of the unsuited and suited sled test configurations using an analytical 5th ATD model developed by LSTC (Livermore, CA) and deformable representations of the seat, suit, helmet constraint countermeasures, and body restraints. Explicit FE analyses were conducted using the non-linear solver LS-DYNA. Head linear and rotational acceleration, head rotational velocity, upper neck force and moment, and lumbar force time histories were compared between test and analysis using the enhanced error assessment of response time histories (EEARTH) composite score index. The EEARTH rating paired with the correlation and analysis (CORA) corridor rating provided a composite ISO score that was used to asses model correlation accuracy. NASA occupant protection subject matter experts established an ISO score of 0.5 or greater as the minimum expectation for correlating analytical and experimental ATD responses. Unsuited 5th ATD head X, Z, and resultant linear accelerations, head Y rotational accelerations and velocities, neck X and Z forces, and lumbar Z forces all showed consistent ISO scores above 0.5 in the XZ impact orientation, regardless of peak g-level or rise time. Upper neck Y moments were near or above the 0.5 score for most of the XZ cases. Similar trends were found in the XZ and Z-axis suited tests despite the addition of several different countermeasures for restraining the helmet. For the X-axis ‘eyeballs in’ loading direction, only resultant head linear acceleration and lumbar Z-axis force produced ISO scores above 0.5 whether unsuited or suited. The analytical LSTC 5th ATD model showed good correlation across multiple head, neck, and lumbar responses in both the unsuited and suited configurations when loaded in the XZ ‘eyeballs out/down’ direction. Upper neck moments were consistently the most difficult to predict, regardless of impact direction or test configuration.

Keywords: impact biomechanics, manned spaceflight, model correlation, multi-axial loading

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6726 Experimental Study on the Variation of Young's Modulus of Hollow Clay Brick Obtained from Static and Dynamic Tests

Authors: M. Aboudalle, Le Btth, M. Sari, F. Meftah

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In parallel with the appearance of new materials, brick masonry had and still has an essential part of the construction market today, with new technical challenges in designing bricks to meet additional requirements. Being used in structural applications, predicting the performance of clay brick masonry allows a significant cost reduction, in terms of practical experimentation. The behavior of masonry walls depends on the behavior of their elementary components, such as bricks, joints, and coatings. Therefore, it is necessary to consider it at different scales (from the scale of the intrinsic material to the real scale of the wall) and then to develop appropriate models, using numerical simulations. The work presented in this paper focuses on the mechanical characterization of the terracotta material at ambient temperature. As a result, the static Young’s modulus obtained from the flexural test shows different values in comparison with the compression test, as well as with the dynamic Young’s modulus obtained from the Impulse excitation of vibration test. Moreover, the Young's modulus varies according to the direction in which samples are extracted, where the values in the extrusion direction diverge from the ones in the orthogonal directions. Based on these results, hollow bricks can be considered as transversely isotropic bimodulus material.

Keywords: bimodulus material, hollow clay brick, ımpulse excitation of vibration, transversely isotropic material, young’s modulus

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6725 Recommendations Using Online Water Quality Sensors for Chlorinated Drinking Water Monitoring at Drinking Water Distribution Systems Exposed to Glyphosate

Authors: Angela Maria Fasnacht

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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.

Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive

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6724 Quantification of Glucosinolates in Turnip Greens and Turnip Tops by Near-Infrared Spectroscopy

Authors: S. Obregon-Cano, R. Moreno-Rojas, E. Cartea-Gonzalez, A. De Haro-Bailon

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The potential of near-infrared spectroscopy (NIRS) for screening the total glucosinolate (t-GSL) content, and also, the aliphatic glucosinolates gluconapin (GNA), progoitrin (PRO) and glucobrassicanapin (GBN) in turnip greens and turnip tops was assessed. This crop is grown for edible leaves and stems for human consumption. The reference values for glucosinolates, as they were obtained by high performance liquid chromatography on the vegetable samples, were regressed against different spectral transformations by modified partial least-squares (MPLS) regression (calibration set of samples n= 350). The resulting models were satisfactory, with calibration coefficient values from 0.72 (GBN) to 0.98 (tGSL). The predictive ability of the equations obtained was tested using a set of samples (n=70) independent of the calibration set. The determination coefficients and prediction errors (SEP) obtained in the external validation were: GNA=0.94 (SEP=3.49); PRO=0.41 (SEP=1.08); GBN=0.55 (SEP=0.60); tGSL=0.96 (SEP=3.28). These results show that the equations developed for total glucosinolates, as well as for gluconapin can be used for screening these compounds in the leaves and stems of this species. In addition, the progoitrin and glucobrassicanapin equations obtained can be used to identify those samples with high, medium and low contents. The calibration equations obtained were accurate enough for a fast, non-destructive and reliable analysis of the content in GNA and tGSL directly from NIR spectra. The equations for PRO and GBN can be employed to identify samples with high, medium and low contents.

Keywords: brassica rapa, glucosinolates, gluconapin, NIRS, turnip greens

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6723 Public Health Campaign to Eradicate Hepatitis C Virus during the Covid-19 Emergency in the North-East of Italy

Authors: Emanuela Zilli, Antonio Madia, Milvia Marchiori, Paola Anello, Chiara Cabbia, Emanuela Velo, Delia Campagnolo, Michele Scomazzon, Emanuela Salvatico, S. Tikvina, Antonio Miotti

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Hepatitis C is an inflammation of the liver caused by the hepatitis C virus (HCV). Antiviral medicines can cure more than 95% of cases of hepatitis C infection, but access to diagnosis and treatment remains low. The ULSS 6 Euganea – Health Trust has implemented a campaign to eradicate hepatitis C in the province of Padua (North-East of Italy), which can be subdivided into three areas: North (300.000 inhabitants), Centre (400.000) and South (300.000). In September 2021, the project was launched in the Northern area; a set of brochures was distributed in outpatient services, general practitioners’ clinics and offices, community pharmacy services, social health districts, and through social networks. The Hepatology Service contacted 460 patients selected by the Clinical Laboratory (positivity for HCV antibodies): 83 patients (18.0%) had been already cured of HCV infection, missing or deceased; 377 patients (82.0%) met the criteria to be eligible for HCV eradication therapy and were therefore included in a Day Service specific agenda and followed by a multidisciplinary team of healthcare professionals, with a dedicated telephone line. Haemato-chemical tests, general medical check-ups and ultrasound tests with fibroscan were performed. Patients were tested for Sars-CoV-2 positivity; those not yet vaccinated against Covid-19 were encouraged to complete the vaccination scheme. All 377 patients (100%) received HCV eradication therapy at the community pharmacy service; a detailed explanation of how to take their medication was provided. At the end of the first phase, Covid-19 vaccination rate was 100% (377/377), including patients already vaccinated and new-vaccinated. Check-up appointments were arranged after 2 or 3 months, according to the treatment plan. The awareness campaign and the organization of HCV eradication therapy service by ULSS 6 Euganea are proving to be effective; the project is now going to be applied to Central and Southern areas of the province (1.132 patients).

Keywords: public health, HCV-eradication, Covid-19 emergency, health communication strategies

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6722 An Examination of Factors Leading to Knowledge-Sharing Behavior of Sri Lankan Bankers

Authors: Eranga N. Somaratna, Pradeep Dharmadasa

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In the current competitive environment, the factors leading to organization success are not limited to the investment of capital, labor, and raw material, but in the ability of knowledge innovation from all the members of an organization. However, knowledge on its own cannot provide organizations with its promised benefits unless it is shared, as organizations are increasingly experiencing unsuccessful knowledge sharing efforts. In such a backdrop and due to the dearth of research in this area in the South Asian context, the study set forth to develop an understanding of the factors that influence knowledge-sharing behavior within an organizational framework, using widely accepted social psychology theories. The purpose of the article is to discover the determinants of knowledge-sharing intention and actual knowledge sharing behaviors of bank employees in Sri Lanka using an aggregate model. Knowledge sharing intentions are widely discussed in literature through the application of Ajzen’s Theory of planned behavior (TPB) and Theory of Social Capital (SCT) separately. Both the theories are rich to explain knowledge sharing intention of workers with limitations. The study, therefore, combines the TPB with SCT in developing its conceptual model. Data were collected through a self-administrated paper-based questionnaire of 199 bank managers from 6 public and private banks of Sri Lanka and analyzed the suggested research model using Structural Equation Modelling (SEM). The study supported six of the nine hypotheses, where Attitudes toward Knowledge Sharing Behavior, Perceived Behavioral Control, Trust, Anticipated Reciprocal Relationships and Actual Knowledge Sharing Behavior were supported while Organizational Climate, Sense of Self-Worth and Anticipated Extrinsic Rewards were not, in determining knowledge sharing intentions. Furthermore, the study investigated the effect of demographic factors of bankers (age, gender, position, education, and experiences) to the actual knowledge sharing behavior. However, findings should be confirmed using a larger sample, as well as through cross-sectional studies. The results highlight the need for theoreticians to combined TPB and SCT in understanding knowledge workers’ intentions and actual behavior; and for practitioners to focus on the perceptions and needs of the individual knowledge worker and the need to cultivate a culture of sharing knowledge in the organization for their mutual benefit.

Keywords: banks, employees behavior, knowledge management, knowledge sharing

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6721 Optimal Sortation Strategy for a Distribution Network in an E-Commerce Supply Chain

Authors: Pankhuri Dagaonkar, Charumani Singh, Poornima Krothapalli, Krishna Karthik

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The backbone of any retail e-commerce success story is a unique design of supply chain network, providing the business an unparalleled speed and scalability. Primary goal of the supply chain strategy is to meet customer expectation by offering fastest deliveries while keeping the cost minimal. Meeting this objective at the large market that India provides is the problem statement that we have targeted here. There are many models and optimization techniques focused on network design to identify the ideal facility location and size, optimizing cost and speed. In this paper we are presenting a tactical approach to optimize cost of an existing network for a predefined speed. We have considered both forward and reverse logistics of a retail e-commerce supply chain consisting of multiple fulfillment (warehouse) and delivery centers, which are connected via sortation nodes. The mathematical model presented here determines if the shipment from a node should get sorted directly for the last mile delivery center or it should travel as consolidated package to another node for further sortation (resort). The objective function minimizes the total cost by varying the resort percentages between nodes and provides the optimal resource allocation and number of sorts at each node.

Keywords: distribution strategy, mathematical model, network design, supply chain management

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6720 Establishing Econometric Modeling Equations for Lumpy Skin Disease Outbreaks in the Nile Delta of Egypt under Current Climate Conditions

Authors: Abdelgawad, Salah El-Tahawy

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This paper aimed to establish econometrical equation models for the Nile delta region in Egypt, which will represent a basement for future predictions of Lumpy skin disease outbreaks and its pathway in relation to climate change. Data of lumpy skin disease (LSD) outbreaks were collected from the cattle farms located in the provinces representing the Nile delta region during 1 January, 2015 to December, 2015. The obtained results indicated that there was a significant association between the degree of the LSD outbreaks and the investigated climate factors (temperature, wind speed, and humidity) and the outbreaks peaked during the months of June, July, and August and gradually decreased to the lowest rate in January, February, and December. The model obtained depicted that the increment of these climate factors were associated with evidently increment on LSD outbreaks on the Nile Delta of Egypt. The model validation process was done by the root mean square error (RMSE) and means bias (MB) which compared the number of LSD outbreaks expected with the number of observed outbreaks and estimated the confidence level of the model. The value of RMSE was 1.38% and MB was 99.50% confirming that this established model described the current association between the LSD outbreaks and the change on climate factors and also can be used as a base for predicting the of LSD outbreaks depending on the climatic change on the future.

Keywords: LSD, climate factors, Nile delta, modeling

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6719 [Keynote Talk]: The Challenges and Solutions for Developing Mobile Apps in a Small University

Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

Abstract:

As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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6718 Role of Vigilante in Crime Control in Bodija Market

Authors: Obadiah Nwabueze

Abstract:

Bodija market is classified as Central Business District (CBD) of Ibadan North Local Government Area of Oyo State (Nigeria) because of socio economic activities, so Crime is a peculiar social issue that causes insecurity. The law enforcement agencies tasked with crime prevention and control such as the Nigerian Police have insufficient manpower, and a resultant effect is the emergence of Vigilante groups as citizen’s response to crime control and prevention (self-help). The research design adopted for this study is a case study design exploring Vigilante activities in Bodija Market. The study utilizes both quantitative and qualitative approach, sources of data includes primary and secondary sources. A sample of 127 respondents randomly picked from the 4 sections of Bodija Market through questionnaire, comprising of 50 male and 77 females which alienates issues of gender bias in addition to the 4 in-depth interview, making a total of 131 respondents. Statistical package for Social Sciences (SPSS) was used. The descriptive statistics of simple frequency, percentage, charts and graphs were computed for the analysis. Finding in the study shows that the market vigilante is able to deter and disrupt criminal activities through strategic spiritual intelligence (SSI), use of charm and juju, physical presence in strategic locations vulnerable to crime occurrence. Findings in the study also show that vigilantes collaborate with the police by assisting them in surveillance, tracking down criminals, identifying black spots, acting as informants to the police, arrest and handover criminal to police. Their challenges include poor equipment, motivation, unhealthy rivalry between the vigilante and the police. The study recommends that the government should support vigilantes with logistics and training, including patrol vehicle and radio communication. The study also recommends the integration of the informal mechanism (juju and charm) of crime detection and prevention into the formal policing strategy, an office should be created in the force commands for use of SSI.

Keywords: central business district, CBD, charm, Juju, strategic spiritual intelligence, SSI

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6717 Machine Learning Algorithms for Rocket Propulsion

Authors: Rômulo Eustáquio Martins de Souza, Paulo Alexandre Rodrigues de Vasconcelos Figueiredo

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In recent years, there has been a surge in interest in applying artificial intelligence techniques, particularly machine learning algorithms. Machine learning is a data-analysis technique that automates the creation of analytical models, making it especially useful for designing complex situations. As a result, this technology aids in reducing human intervention while producing accurate results. This methodology is also extensively used in aerospace engineering since this is a field that encompasses several high-complexity operations, such as rocket propulsion. Rocket propulsion is a high-risk operation in which engine failure could result in the loss of life. As a result, it is critical to use computational methods capable of precisely representing the spacecraft's analytical model to guarantee its security and operation. Thus, this paper describes the use of machine learning algorithms for rocket propulsion to aid the realization that this technique is an efficient way to deal with challenging and restrictive aerospace engineering activities. The paper focuses on three machine-learning-aided rocket propulsion applications: set-point control of an expander-bleed rocket engine, supersonic retro-propulsion of a small-scale rocket, and leak detection and isolation on rocket engine data. This paper describes the data-driven methods used for each implementation in depth and presents the obtained results.

Keywords: data analysis, modeling, machine learning, aerospace, rocket propulsion

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6716 To Allow or to Forbid: Investigating How Europeans Reason about Endorsing Rights to Minorities: A Vignette Methodology Based Cross-Cultural Study

Authors: Silvia Miele, Patrice Rusconi, Harriet Tenenbaum

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An increasingly multi-ethnic Europe has been pushing citizens’ boundaries on who should be entitled and to what extent to practise their own diversity. Indeed, according to a Standard Eurobarometer survey conducted in 2017, immigration is seen by Europeans as the most serious issue facing the EU, and a third of respondents reported they do not feel comfortable interacting with migrants from outside the EU. Many of these come from Muslim countries, accounting for 4.9% of Europe population in 2016. However, the figure is projected to rise up to 14% by 2050. Additionally, political debates have increasingly focused on Muslim immigrants, who are frequently portrayed as difficult to integrate, while nationalist parties across Europe have fostered the idea of insuperable cultural differences, creating an atmosphere of hostility. Using a 3 X 3 X 2 between-subjects design, it was investigated how people reason about endorsing religious and non-religious rights to minorities. An online survey has been administered to university students of three different countries (Italy, Spain and the UK) via Qualtrics, presenting hypothetical scenarios through a vignette methodology. Each respondent has been randomly allocated to one of the three following conditions: Christian, Muslim or non-religious (vegan) target. Each condition entailed three questions about children self-determination rights to exercise some control over their own lives and 3 questions about children nurturance rights of care and protection. Moreover, participants have been required to further elaborate on their answers via free-text entries and have been asked about their contact and quality of contact with the three targets, and to self-report religious, national and ethnic identification. Answers have been recorded on a Likert scale of 1-5, 1 being "not at all", 5 being "very much". A two-way ANCOVA will be used to analyse answers to closed-ended questions, while free-text answers will be coded and data will be dichotomised based on Social Cognitive Domain Theory for four categories: moral, social conventional and psychological reasons, and analysed via ANCOVAs. This study’s findings aim to contribute to the implementation of educational interventions and speak to the introduction of governmental policies on human rights.

Keywords: children's rights, Europe, migration, minority

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6715 The Development of a Cyber Violence Measurement Tool for Youths: A Multi-Reporting of Ecological Factors

Authors: Jong-Hyo Park, Eunyoung Choi, Jae-Yeon Lim, Seon-Suk Lee, Yeong-Rong Koo, Ji-Ung Kwon, Kyung-Sung Kim, Jong-Ik Lee, Juhan Park, Hyun-Kyu Lee, Won-Kyoung Oh, Jisang Lee, Jiwon Choe

Abstract:

Due to COVID-19, cyber violence among youths has soared as they spend more time online than before. In contrast to the deepening concerns, measurement tools that can assess the vulnerability of cyber violence in individual youths still need to be supplemented. The measurement tools lack consideration of various factors related to cyber violence among youths. Most of the tools are self-report questionnaires, and these adolescents' self-report questionnaire forms can underestimate the harmful behavior and overestimate the damage experience. Therefore, this study aims to develop a multi-report measurement tool for youths that can reliably measure individuals' ecological factors related to cyber violence. The literature review explored factors related to cyber violence, and the questions were constructed. The face validity of the questions was confirmed by conducting focus group interviews. Exploratory and confirmatory factor analyses (N=671) were also conducted for statistical validation. This study developed a multi-report measurement tool for cyber violence with 161 questions, consisting of six domains: online behavior, cyber violence awareness, victimization-perpetration-witness experience, coping efficacy (individuals, peers, teachers, and parents), psychological characteristics, and pro-social capabilities. In addition to self-report from a youth respondent, this measurement tool includes peers, teachers, and parents reporting for the respondent. It is possible to reliably measure the ecological factors of individual youths who are vulnerable or highly resistant to cyber violence. In schools, teachers could refer to the measurement results for guiding students, better understanding their cyber violence conditions, and assessing their pro-social capabilities. With the measurement results, teachers and police officers could detect perpetrators or victims and intervene immediately. In addition, this measurement tool could analyze the effects of the prevention and intervention programs for cyber violence and draw appropriate suggestions.

Keywords: adolescents, cyber violence, cyber violence measurement tool, measurement tool, multi-report measurement tool, youths

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6714 Expectation-Confirmation Model of Information System Continuance: A Meta-Analysis

Authors: Hui-Min Lai, Chin-Pin Chen, Yung-Fu Chang

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The expectation-confirmation model (ECM) is one of the most widely used models for evaluating information system continuance, and this model has been extended to other study backgrounds, or expanded with other theoretical perspectives. However, combining ECM with other theories or investigating the background problem may produce some disparities, thus generating inaccurate conclusions. Habit is considered to be an important factor that influences the user’s continuance behavior. This paper thus critically examines seven pairs of relationships from the original ECM and the habit variable. A meta-analysis was used to tackle the development of ECM research over the last 10 years from a range of journals and conference papers published in 2005–2014. Forty-six journal articles and 19 conference papers were selected for analysis. The results confirm our prediction that a high effect size for the seven pairs of relationships was obtained (ranging from r=0.386 to r=0.588). Furthermore, a meta-analytic structural equation modeling was performed to simultaneously test all relationships. The results show that habit had a significant positive effect on continuance intention at p<=0.05 and that the six other pairs of relationships were significant at p<0.10. Based on the findings, we refined our original research model and an alternative model was proposed for understanding and predicting information system continuance. Some theoretical implications are also discussed.

Keywords: Expectation-confirmation theory, Expectation-confirmation model, Meta-analysis, meta-analytic structural equation modeling.

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6713 A Model to Assess Sustainability Using Multi-Criteria Analysis and Geographic Information Systems: A Case Study

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

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

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

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6712 The Critical Velocity and Heat of Smoke Outflow in Z-shaped Passage Fires Under Weak Stack Effect

Authors: Zekun Li, Bart Merci, Miaocheng Weng, Fang Liu

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The Z-shaped passage, widely used in metro entrance/exit passageways, inclined mining laneways, and other applications, features steep slopes and a combination of horizontal and inclined sections. These characteristics lead to notable differences in airflow patterns and temperature distributions compared to conventional confined passages. In fires occurring within Z-shaped passages under natural ventilation with a weak stack effect, the induced airflow may be insufficient to fully confined smoke downstream of the fire source. This can cause smoke back-layering upstream, with the possibility of smoke escaping from the lower entrance located upstream of the fire. Consequently, not all the heat from the fire source contributes to the stack effect. This study combines theoretical analysis and fire simulations to examine the influence of various heat release rates (HRR), passage structures, and fire source locations on the induced airflow velocity driven by the stack effect. An empirical equation is proposed to quantify the strength of the stack effect under different conditions. Additionally, predictive models have been developed to determine the critical induced airflow and to estimate the heat of smoke escaping from the lower entrance of the passage.

Keywords: stack effect, critical velocity, heat outflow, numerical simulation

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6711 Design and Identification of Mycobacterium tuberculosis Glutamate Racemase (MurI) Inhibitors

Authors: Prasanthi Malapati, R. Reshma, Vijay Soni, Perumal Yogeeswari, Dharmarajan Sriram

Abstract:

In the present study, we attempted to develop Mycobacterium tuberculosis (Mtb) inhibitors by exploring the pharmaceutically underexploited enzyme targets which are majorly involved in cell wall biosynthesis of mycobacteria. For this purpose, glutamate racemase (coded by MurI gene) was selected. This enzyme racemize L-glutamate to D-glutamate required for the construction of peptidoglycan in the bacterial cell wall synthesis process. Furthermore this enzyme is neither expressed nor its product, D-glutamate is normally found in mammals, and hence designing inhibitors against this enzyme will not affect the host system as well act as potential antitubercular drugs. A library of BITS in house compounds were screened against Mtb MurI enzyme. Based on docking score, interactions and synthetic feasibility one hit lead was identified. Further optimization of lead was attempted and its derivatives were synthesized. Forty eight derivatives of 2-phenylbenzo[d]oxazole and 2-phenylbenzo[d]thiazole were synthesized and evaluated for Mtb MurI inhibition study, in vitro activities against Mtb, cytotoxicity against RAW 264.7 cell line. Chemical derivatization of the lead resulted in compounds NR-1213 AND NR-1124 as the potent M. tuberculosis glutamate racemase inhibitors with IC50 of 4-5µM which are remarkable and were found to be non-cytotoxic. Molecular dynamics, dormant models and cardiotoxicity studies of the most active molecules are in process.

Keywords: cell wall biosynthesis, dormancy, glutamate racemase, tuberculosis

Procedia PDF Downloads 273
6710 Attention and Memory in the Music Learning Process in Individuals with Visual Impairments

Authors: Lana Burmistrova

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Introduction: The influence of visual impairments on several cognitive processes used in the music learning process is an increasingly important area in special education and cognitive musicology. Many children have several visual impairments due to the refractive errors and irreversible inhibitors. However, based on the compensatory neuroplasticity and functional reorganization, congenitally blind (CB) and early blind (EB) individuals use several areas of the occipital lobe to perceive and process auditory and tactile information. CB individuals have greater memory capacity, memory reliability, and less false memory mechanisms are used while executing several tasks, they have better working memory (WM) and short-term memory (STM). Blind individuals use several strategies while executing tactile and working memory n-back tasks: verbalization strategy (mental recall), tactile strategy (tactile recall) and combined strategies. Methods and design: The aim of the pilot study was to substantiate similar tendencies while executing attention, memory and combined auditory tasks in blind and sighted individuals constructed for this study, and to investigate attention, memory and combined mechanisms used in the music learning process. For this study eight (n=8) blind and eight (n=8) sighted individuals aged 13-20 were chosen. All respondents had more than five years music performance and music learning experience. In the attention task, all respondents had to identify pitch changes in tonal and randomized melodic pairs. The memory task was based on the mismatch negativity (MMN) proportion theory: 80 percent standard (not changed) and 20 percent deviant (changed) stimuli (sequences). Every sequence was named (na-na, ra-ra, za-za) and several items (pencil, spoon, tealight) were assigned for each sequence. Respondents had to recall the sequences, to associate them with the item and to detect possible changes. While executing the combined task, all respondents had to focus attention on the pitch changes and had to detect and describe these during the recall. Results and conclusion: The results support specific features in CB and EB, and similarities between late blind (LB) and sighted individuals. While executing attention and memory tasks, it was possible to observe the tendency in CB and EB by using more precise execution tactics and usage of more advanced periodic memory, while focusing on auditory and tactile stimuli. While executing memory and combined tasks, CB and EB individuals used passive working memory to recall standard sequences, active working memory to recall deviant sequences and combined strategies. Based on the observation results, assessment of blind respondents and recording specifics, following attention and memory correlations were identified: reflective attention and STM, reflective attention and periodic memory, auditory attention and WM, tactile attention and WM, auditory tactile attention and STM. The results and the summary of findings highlight the attention and memory features used in the music learning process in the context of blindness, and the tendency of the several attention and memory types correlated based on the task, strategy and individual features.

Keywords: attention, blindness, memory, music learning, strategy

Procedia PDF Downloads 189