Search results for: genetically diverse

Authors: Frances Turner

Abstract:

Gloves are significant physical objects, being one of the oldest forms of dress. Glove culture is part of every facet of life; its extraordinary history encompasses practicality, and symbolism reflecting a wide range of social practices. The survival of not only the gloves but associated articles enables the possibility to analyse real lives, however so far this area has been largely neglected. Limited information is available to students, researchers, or those involved with the design and making of gloves. There are several museums and independent collectors in England that hold collections of gloves (some from as early as 16th century), machinery, tools, designs and patterns, marketing materials and significant archives which demonstrate the rich heritage of English glove design and manufacturing, being of national significance and worthy of international interest. Through a research glove network which now exists thanks to research grant funding, there is potential for the holders of glove collections to make connections and explore links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English glove industry. The network takes an interdisciplinary approach to bring together interested parties from academia, museums and manufacturing, with expert knowledge of the production, collections, conservation and display of English leather gloves. Academics from diverse arts and humanities disciplines benefit from the opportunities to share research and discuss ideas with network members from non-academic contexts including museums and heritage organisations, industry, and contemporary designers. The fragmented collections when considered in entirety provide an overview of English glove making since earliest times and those who wore them. This paper makes connections and explores links between these resources to promote a stronger understanding of the significance, breadth and heritage of the English Glove industry. The following areas are explored: current content and status of the individual museum collections, potential links, sharing of information histories, social and cultural and relationship to history of fashion design, manufacturing and materials, approaches to maintenance and conservation, access to the collections and strategies for future understanding of their national significance. The facilitation of knowledge exchange and exploration of the collections through the network informs organisations’ future strategies for the maintenance, access and conservation of their collections. By involving industry in the network, it is possible to ensure a contemporary perspective on glove-making in addition to the input from heritage partners. The slow fashion movement and awareness of artisan craft and how these can be preserved and adopted for glove and accessory design is addressed. Artisan leather glove making was a skilled and significant industry in England that has now declined to the point where there is little production remaining utilising the specialist skills that have hardly changed since earliest times. This heritage will be identified and preserved for future generations of the rich cultural history of gloves may be lost.

Keywords: artisan glove-making skills, English leather gloves, glove culture, the glove network

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Authors: Piotr Romaniuk, Krzysztof Kaczmarek, Adam Szromek

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Background: A number of approaches to assess the performance of health system have been proposed so far. Nonetheless, they lack a consensus regarding the key components of assessment procedure and criteria of evaluation. The WHO and OECD have developed methods of assessing health system to counteract the underlying issues, but they are not free of controversies and did not manage to produce a commonly accepted consensus. The aim of the study: On the basis of WHO and OECD approaches we decided to develop own methodology to assess the performance of health systems in Central and Eastern European countries. We have applied the method to compare the effects of health systems reforms in 20 countries of the region, in order to evaluate the dynamic of changes in terms of health system outcomes.Methods: Data was collected from a 25-year time period after the fall of communism, subsetted into different post-reform stages. Datasets collected from individual countries underwent one-, two- or multi-dimensional statistical analyses, and the Synthetic Measure of health system Outcomes (SMO) was calculated, on the basis of the method of zeroed unitarization. A map of dynamics of changes over time across the region was constructed. Results: When making a comparative analysis of the tested group in terms of the average SMO value throughout the analyzed period, we noticed some differences, although the gaps between individual countries were small. The countries with the highest SMO were the Czech Republic, Estonia, Poland, Hungary and Slovenia, while the lowest was in Ukraine, Russia, Moldova, Georgia, Albania, and Armenia. Countries differ in terms of the range of SMO value changes throughout the analyzed period. The dynamics of change is high in the case of Estonia and Latvia, moderate in the case of Poland, Hungary, Czech Republic, Croatia, Russia and Moldova, and small when it comes to Belarus, Ukraine, Macedonia, Lithuania, and Georgia. This information reveals fluctuation dynamics of the measured value in time, yet it does not necessarily mean that in such a dynamic range an improvement appears in a given country. In reality, some of the countries moved from on the scale with different effects. Albania decreased the level of health system outcomes while Armenia and Georgia made progress, but lost distance to leaders in the region. On the other hand, Latvia and Estonia showed the most dynamic progress in improving the outcomes. Conclusions: Countries that have decided to implement comprehensive health reform have achieved a positive result in terms of further improvements in health system efficiency levels. Besides, a higher level of efficiency during the initial transition period generally positively determined the subsequent value of the efficiency index value, but not the dynamics of change. The paths of health system outcomes improvement are highly diverse between different countries. The instrument we propose constitutes a useful tool to evaluate the effectiveness of reform processes in post-communist countries, but more studies are needed to identify factors that may determine results obtained by individual countries, as well as to eliminate the limitations of methodology we applied.

Keywords: health system outcomes, health reforms, health system assessment, health system evaluation

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Authors: S. Delgado, C. Cerrada, R. S. Gómez

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This research introduces an approach to voxelizing the surfaces of triangular meshes with efficiency and accuracy. Our method leverages parallel equidistant scan-lines and introduces a Gap Detection technique to address the limitations of existing approaches. We present a comprehensive study showcasing the method's effectiveness, scalability, and versatility in different scenarios. Voxelization is a fundamental process in computer graphics and simulations, playing a pivotal role in applications ranging from scientific visualization to virtual reality. Our algorithm focuses on enhancing the voxelization process, especially for complex models and high resolutions. One of the major challenges in voxelization in the Graphics Processing Unit (GPU) is the high cost of discovering the same voxels multiple times. These repeated voxels incur in costly memory operations with no useful information. Our scan-line-based method ensures that each voxel is detected exactly once when processing the triangle, enhancing performance without compromising the quality of the voxelization. The heart of our approach lies in the use of parallel, equidistant scan-lines to traverse the interiors of triangles. This minimizes redundant memory operations and avoids revisiting the same voxels, resulting in a significant performance boost. Moreover, our method's computational efficiency is complemented by its simplicity and portability. Written as a single compute shader in Graphics Library Shader Language (GLSL), it is highly adaptable to various rendering pipelines and hardware configurations. To validate our method, we conducted extensive experiments on a diverse set of models from the Stanford repository. Our results demonstrate not only the algorithm's efficiency, but also its ability to produce 26 tunnel free accurate voxelizations. The Gap Detection technique successfully identifies and addresses gaps, ensuring consistent and visually pleasing voxelized surfaces. Furthermore, we introduce the Slope Consistency Value metric, quantifying the alignment of each triangle with its primary axis. This metric provides insights into the impact of triangle orientation on scan-line based voxelization methods. It also aids in understanding how the Gap Detection technique effectively improves results by targeting specific areas where simple scan-line-based methods might fail. Our research contributes to the field of voxelization by offering a robust and efficient approach that overcomes the limitations of existing methods. The Gap Detection technique fills a critical gap in the voxelization process. By addressing these gaps, our algorithm enhances the visual quality and accuracy of voxelized models, making it valuable for a wide range of applications. In conclusion, "Closing the Gap: Efficient Voxelization with Equidistant Scan-lines and Gap Detection" presents an effective solution to the challenges of voxelization. Our research combines computational efficiency, accuracy, and innovative techniques to elevate the quality of voxelized surfaces. With its adaptable nature and valuable innovations, this technique could have a positive influence on computer graphics and visualization.

Keywords: voxelization, GPU acceleration, computer graphics, compute shaders

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Authors: Ann P. Daunic, Nancy Corbett

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Background and Significance: Researchers emphasize the role that motivation, self-esteem, and self-regulation play in children’s early adjustment to the school culture, including skills such as identifying their own feelings and understanding the feelings of others. As social-emotional growth, academic learning, and successful integration within culture and society are inextricably connected, the Social-Emotional Learning Foundations (SELF) curriculum was designed to integrate social-emotional learning (SEL) instruction within early literacy instruction (specifically, reading) for Kindergarten and first-grade students at risk for emotional and behavioral difficulties. Storybook reading is a typically occurring activity in the primary grades; thus SELF provides an intervention that is both theoretically and practically sound. Methodology: The researchers will report on findings from the first two years of a three-year study funded by the US Department of Education’s Institute of Education Sciences to evaluate the effects of the SELF curriculum versus “business as usual” (BAU). SELF promotes the development of self-regulation by incorporating instructional strategies that support children’s use of SEL related vocabulary, self-talk, and critical thinking. The curriculum consists of a carefully coordinated set of materials and pedagogy designed specifically for primary grade children at early risk for emotional and behavioral difficulties. SELF lessons (approximately 50 at each grade level) are organized around 17 SEL topics within five critical competencies. SELF combines whole-group (the first in each topic) and small-group lessons (the 2nd and 3rd in each topic) to maximize opportunities for teacher modeling and language interactions. The researchers hypothesize that SELF offers a feasible and substantial opportunity within the classroom setting to provide a small-group social-emotional learning intervention integrated with K-1 literacy-related instruction. Participating target students (N = 876) were identified by their teachers as potentially at risk for emotional or behavioral issues. These students were selected from 122 Kindergarten and 100 first grade classrooms across diverse school districts in a southern state in the US. To measure the effectiveness of the SELF intervention, the researchers asked teachers to complete assessments related to social-emotional learning and adjustment to the school culture. A social-emotional learning related vocabulary assessment was administered directly to target students receiving small-group instruction. Data were analyzed using a 3-level MANOVA model with full information maximum likelihood to estimate coefficients and test hypotheses. Major Findings: SELF had significant positive effects on vocabulary, knowledge, and skills associated with social-emotional competencies, as evidenced by results from the measures administered. Effect sizes ranged from 0.41 for group (SELF vs. BAU) differences in vocabulary development to 0.68 for group differences in SEL related knowledge. Conclusion: Findings from two years of data collection indicate that SELF improved outcomes related to social-emotional learning and adjustment to the school culture. This study thus supports the integration of SEL with literacy instruction as a feasible and effective strategy to improve outcomes for K-1 students at risk for emotional and behavioral difficulties.

Keywords: Socio-cultural context for learning, social-emotional learning, social skills, vocabulary development

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Authors: Ved Vrat Verma, Rani Gupta, Manisha Goel

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γ-glutamyltranspeptidase (GGT: EC 2.3.2.2) is an N-terminal nucleophile hydrolase conserved in all three domains of life. GGT plays a key role in glutathione metabolism where it catalyzes the breakage of the γ-glutamyl bonds and transfer of γ-glutamyl group to water (hydrolytic activity) or amino acids or short peptides (transpeptidase activity). GGTs from bacteria, archaea, and eukaryotes (human, rat and mouse) are homologous proteins sharing >50% sequence similarity and conserved four layered αββα sandwich like three dimensional structural fold. These proteins though similar in their structure to each other, are quite diverse in their enzyme activity: some GGTs are better at hydrolysis reactions but poor in transpeptidase activity, whereas many others may show opposite behaviour. GGT is known to be involved in various diseases like asthma, parkinson, arthritis, and gastric cancer. Its inhibition prior to chemotherapy treatments has been shown to sensitize tumours to the treatment. Microbial GGT is known to be a virulence factor too, important for the colonization of bacteria in host. However, all known inhibitors (mimics of its native substrate, glutamate) are highly toxic because they interfere with other enzyme pathways. However, a few successful efforts have been reported previously in designing species specific inhibitors. We aim to leverage the diversity seen in GGT family (pathogen vs. eukaryotes) for designing specific inhibitors. Thus, in the present study, we have used DIVERGE software to identify sites in GGT proteins, which are crucial for the functional and structural divergence of these proteins. Since, type II divergence sites vary in clade specific manner, so type II divergent sites were our focus of interest throughout the study. Type II divergent sites were identified for pathogen vs. eukaryotes clusters and sites were marked on clade specific representative structures HpGGT (2QM6) and HmGGT (4ZCG) of pathogen and eukaryotes clade respectively. The crucial divergent sites within 15 A radii of the binding cavity were highlighted, and in-silico mutations were performed on these sites to delineate the role of these sites on the mechanism of catalysis and protein folding. Further, the amino acid network (AAN) analysis was also performed by Cytoscape to delineate assortative mixing for cavity divergent sites which could strengthen our hypothesis. Additionally, molecular dynamics simulations were performed for wild complexes and mutant complexes close to physiological conditions (pH 7.0, 0.1 M ionic strength and 1 atm pressure) and the role of putative divergence sites and structural integrities of the homologous proteins have been analysed. The dynamics data were scrutinized in terms of RMSD, RMSF, non-native H-bonds and salt bridges. The RMSD, RMSF fluctuations of proteins complexes are compared, and the changes at protein ligand binding sites were highlighted. The outcomes of our study highlighted some crucial divergent sites which could be used for novel inhibitors designing in a species-specific manner. Since, for drug development, it is challenging to design novel drug by targeting similar protein which exists in eukaryotes, so this study could set up an initial platform to overcome this challenge and help to deduce the more effective targets for novel drug discovery.

Keywords: γ-glutamyltranspeptidase, divergence, species-specific, drug design

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Authors: Yuliya Y. Gavrichenko

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Background and Aims: The increasing bacterial resistance to almost all the available antibiotics has encouraged scientists to search for alternative sources of antibacterial agents. Nowadays, it is known that many plant secondary metabolites have diverse biological activity. These compounds can be potentially active against human bacterial and viral infections. Extended research has been carried out to explore the use of the luminescent bacterial test as a rapid, accurate and inexpensive method to assess the antibacterial properties and to predict the biological activity spectra for plant origin substances. Method: Botanical material of fifteen species was collected from their natural and cultural habitats on the Crimean peninsula. The aqueous extracts of following plants were tested: Robinia pseudoacacia L., Sideritis comosa, Cotinus coggygria Scop., Thymus serpyllum L., Juglans regia L., Securigera varia L., Achillea millefolium L., Phlomis taurica, Corylus avellana L., Sambucus nigra L., Helichrysum arenarium L., Glycyrrhiza glabra L., Elytrigia repens L., Echium vulgare L., Conium maculatum L. The test was carried out using luminous strains of marine bacteria Photobacterium leiognathi, which was isolated from the Sea of Azov as well as four Escherichia coli MG1655 recombinant strains harbouring Vibrio fischeri luxCDABE genes. Results: The bactericidal capacity of plant extracts showed significant differences in the study. Cotinus coggygria, Phlomis taurica, Juglans regia L. proved to be the most toxic to P. leiognathi. (EC50 = 0.33 g dried plant/l). Glycyrrhiza glabra L., Robinia pseudoacacia L., Sideritis comosa and Helichrysum arenarium L. had moderate inhibitory effects (EC50 = 3.3 g dried plant/l). The rest of the aqueous extracts have decreased the luminescence of no more than 50% at the lowest concentration (16.5 g dried plant/l). Antibacterial activity of herbal extracts against constitutively luminescent E. coli MG1655 (pXen7-lux) strain was observed at approximately the same level as for P. leiognathi. Cotinus coggygria and Conium maculatum L. extracts have increased light emission in the mutant E. coli MG1655 (pFabA-lux) strain which is associated with cell membranes damage. Sideritis comosa, Phlomis taurica, Juglans regia induced SOS response in E. coli (pColD-lux) strain. Glycyrrhiza glabra L. induced protein damage response in E. coli MG1655 (pIbpA-lux) strain. Conclusion: The received results have shown that the plants’ extracts had nonspecific antimicrobial effects against both E. coli (pXen7-lux) and P. leiognathi biosensors. Mutagenic, cytotoxic and protein damage effects have been observed. In general, the bioluminescent inhibition test result correlated with the traditional use of screened plants. It leads to the following conclusion that whole-cell luminescent biosensors could be the indicator of overall plants antibacterial capacity. The results of the investigation have shown a possibility of bioluminescent method in medicine and pharmacy as an approach to research the antibacterial properties of medicinal plants.

Keywords: antibacterial property, bioluminescence, medicinal plants, whole-cell biosensors

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Authors: Kimberly Samaha

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In order to attract new types of investors into the emerging Bio-Economy, a new set of metrics and measurement system is needed to better quantify the environmental, social and economic impacts of circular zero-waste design. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. Lack of an economically-viable business model for bioenergy facilities has resulted in the continuation of idled and decommissioned plants. In particular, the forestry-based plants which have been an invaluable outlet for woody biomass surplus, forest health improvement, timber production enhancement, and especially reduction of wildfire risk. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. It proposes not only models for integration of forestry, aquaculture, and agriculture in cradle-to-cradle linkages of what have typically been linear systems, but the proposal also allows for the early measurement of the circularity and impact of resource use and investment risk mitigation, for these systems. Typically, life cycle analyses measure environmental impacts of different industrial production stages and are not integrated with indicators of material use circularity. This concept paper proposes the further development of a new set of metrics that would illustrate not only the typical life-cycle analysis (LCA), which shows the reduction in greenhouse gas (GHG) emissions, but also the zero-waste circularity measures of mass balance of the full value chain of the raw material and energy content/caloric value. These new measures quantify key impacts in making hyper-efficient use of natural resources and eliminating waste to landfills. The project utilized traditional LCA using the GREET model where the standalone biomass energy plant case was contrasted with the integration of a jet-fuel biorefinery. The methodology was then expanded to include combinations of co-hosts that optimize the life cycle of woody biomass from tree to energy, CO₂, heat and wood ash both from an energy/caloric value and for mass balance to include reuse of waste streams which are typically landfilled. The major findings of both a formal LCA study resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. If proven as a model, the expedited roll-out of these innovative scenarios can set a new standard for circular zero-waste projects that advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable bio-economy paradigm where waste streams become valuable inputs, supporting local and rural communities in simple, sustainable ways.

Keywords: bio-economy, biomass energy, financing, metrics

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Authors: Solanki Ravirajsinh, Kudo Kuniaki, Sharma Ankit, Devi Sherine, Kuboshima Misaki, Tachi Shuntaro

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In software development life cycles, the absence of scalable CI/CD significantly impacts organizations, leading to increased overall maintenance costs, prolonged release delivery times, heightened manual efforts, and difficulties in meeting tight deadlines. Implementing CI/CD with standard serverless technologies using cloud services overcomes all the above-mentioned issues and helps organizations improve efficiency and faster delivery without the need to manage server maintenance and capacity. By integrating scalable CI/CD with scalable automation testing, productivity, quality, and agility are enhanced while reducing the need for repetitive work and manual efforts. Implementing scalable CI/CD for development using cloud services like ECS (Container Management Service), AWS Fargate, ECR (to store Docker images with all dependencies), Serverless Computing (serverless virtual machines), Cloud Log (for monitoring errors and logs), Security Groups (for inside/outside access to the application), Docker Containerization (Docker-based images and container techniques), Jenkins (CI/CD build management tool), and code management tools (GitHub, Bitbucket, AWS CodeCommit) can efficiently handle the demands of diverse development environments and are capable of accommodating dynamic workloads, increasing efficiency for faster delivery with good quality. CI/CD pipelines encourage collaboration among development, operations, and quality assurance teams by providing a centralized platform for automated testing, deployment, and monitoring. Scalable CI/CD streamlines the development process by automatically fetching the latest code from the repository every time the process starts, building the application based on the branches, testing the application using a scalable automation testing framework, and deploying the builds. Developers can focus more on writing code and less on managing infrastructure as it scales based on the need. Serverless CI/CD eliminates the need to manage and maintain traditional CI/CD infrastructure, such as servers and build agents, reducing operational overhead and allowing teams to allocate resources more efficiently. Scalable CI/CD adjusts the application's scale according to usage, thereby alleviating concerns about scalability, maintenance costs, and resource needs. Creating scalable automation testing using cloud services (ECR, ECS Fargate, Docker, EFS, Serverless Computing) helps organizations run more than 500 test cases in parallel, aiding in the detection of race conditions, performance issues, and reducing execution time. Scalable CI/CD offers flexibility, dynamically adjusting to varying workloads and demands, allowing teams to scale resources up or down as needed. It optimizes costs by only paying for the resources as they are used and increases reliability. Scalable CI/CD pipelines employ automated testing and validation processes to detect and prevent errors early in the development cycle.

Keywords: achieve parallel execution, cloud services, scalable automation testing, scalable continuous integration and deployment

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Authors: Soma Ghosh, Balaram Mohapatra, Pinaki Sar, Abhijeet Mukherjee

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Microbial role in arsenic (As) mobilization in the groundwater aquifers of Brahmaputra river basin (BRB) in India, severely threatened by high concentrations of As, remains largely unknown. The present study, therefore, is a molecular and ecophysiological characterization of an indigenous bacterium strain IIIJ3-1 isolated from As contaminated groundwater of BRB and application of this strain in several microcosm set ups differing in their organic carbon (OC) source and terminal electron acceptors (TEA), to understand its role in As dissolution under aerobic and anaerobic conditions. Strain IIIJ3-1 was found to be a new facultative anaerobic, gram-positive, endospore-forming strain capable of arsenite (As3+) oxidation and dissimilatory arsenate (As5+) reduction. The bacterium exhibited low genomic (G+C)% content (45 mol%). Although, its 16S rRNA gene sequence revealed a maximum similarity of 99% with Bacillus cereus ATCC 14579(T) but the DNA-DNA relatedness of their genomic DNAs was only 49.9%, which remains well below the value recommended to delimit different species. Abundance of fatty acids iC17:0, iC15:0 and menaquinone (MK) 7 though corroborates its taxonomic affiliation with B. cereus sensu-lato group, presence of hydroxy fatty acids (HFAs), C18:2, MK5 and MK6 marked its uniqueness. Besides being highly As resistant (MTC=10mM As3+, 350mM As5+), metabolically diverse, efficient aerobic As3+ oxidizer; it exhibited near complete dissimilatory reduction of As5+ (1 mM). Utilization of various carbon sources with As5+ as TEA revealed lactate to serve as the best electron donor. Aerobic biotransformation assay yielded a lower Km for As3+ oxidation than As5+ reduction. Arsenic homeostasis was found to be conferred by the presence of arr, arsB, aioB, and acr3(1) genes. Scanning electron microscopy (SEM) coupled with energy dispersive X-ray (EDX) analysis of this bacterium revealed reduction in cell size upon exposure to As and formation of As-rich electron opaque dots following growth with As3+. Incubation of this strain with sediment (sterilised) collected from BRB aquifers under varying OC, TEA and redox conditions revealed that the strain caused highest As mobilization from solid to aqueous phase under anaerobic condition with lactate and nitrate as electron donor and acceptor, respectively. Co-release of highest concentrations of oxalic acid, a well known bioweathering agent, considerable fold increase in viable cell counts and SEM-EDX and X-ray diffraction analysis of the sediment after incubation under this condition indicated that As release is consequent to microbial bioweathering of the minerals. Co-release of other elements statistically proves decoupled release of As with Fe and Zn. Principle component analysis also revealed prominent role of nitrate under aerobic and/or anaerobic condition in As release by strain IIIJ3-1. This study, therefore, is the first to isolate, characterize and reveal As mobilization property of a strain belonging to the Bacillus cereus sensu lato group isolated from highly As contaminated aquifers of Brahmaputra River Basin.

Keywords: anaerobic microcosm, arsenic rich electron opaque dots, Arsenic release, Bacillus strain IIIJ3-1

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Authors: Jae Won Lee, Kyung Hyun Min, Hong Jae Lee, Sang Cheon Lee

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To date, imaging techniques have attracted much attention in medicine because the detection of diseases at an early stage provides greater opportunities for successful treatment. Consequently, over the past few decades, diverse imaging modalities including magnetic resonance (MR), positron emission tomography, computed tomography, and ultrasound (US) have been developed and applied widely in the field of clinical diagnosis. However, each of the above-mentioned imaging modalities possesses unique strengths and intrinsic weaknesses, which limit their abilities to provide accurate information. Therefore, multimodal imaging systems may be a solution that can provide improved diagnostic performance. Among the current medical imaging modalities, US is a widely available real-time imaging modality. It has many advantages including safety, low cost and easy access for patients. However, its low spatial resolution precludes accurate discrimination of diseased region such as cancer sites. In contrast, MR has no tissue-penetrating limit and can provide images possessing exquisite soft tissue contrast and high spatial resolution. However, it cannot offer real-time images and needs a comparatively long imaging time. The characteristics of these imaging modalities may be considered complementary, and the modalities have been frequently combined for the clinical diagnostic process. Biominerals such as calcium carbonate (CaCO3) and calcium phosphate (CaP) exhibit pH-dependent dissolution behavior. They demonstrate pH-controlled drug release due to the dissolution of minerals in acidic pH conditions. In particular, the application of this mineralization technique to a US contrast agent has been reported recently. The CaCO3 mineral reacts with acids and decomposes to generate calcium dioxide (CO2) gas in an acidic environment. These gas-generating mineralized nanoparticles generated CO2 bubbles in the acidic environment of the tumor, thereby allowing for strong echogenic US imaging of tumor tissues. On the basis of this previous work, it was hypothesized that the loading of MR contrast agents into the CaCO3 mineralized nanoparticles may be a novel strategy in designing a contrast agent for dual imaging. Herein, CaCO3 mineralized nanoparticles that were capable of generating CO2 bubbles to trigger the release of entrapped MR contrast agents in response to tumoral acidic pH were developed for the purposes of US and MR dual-modality imaging of tumors. Gd2O3 nanoparticles were selected as an MR contrast agent. A key strategy employed in this study was to prepare Gd2O3 nanoparticle-loaded mineralized nanoparticles (Gd2O3-MNPs) using block copolymer-templated CaCO3 mineralization in the presence of calcium cations (Ca2+), carbonate anions (CO32-) and positively charged Gd2O3 nanoparticles. The CaCO3 core was considered suitable because it may effectively shield Gd2O3 nanoparticles from water molecules in the blood (pH 7.4) before decomposing to generate CO2 gas, triggering the release of Gd2O3 nanoparticles in tumor tissues (pH 6.4~7.4). The kinetics of CaCO3 dissolution and CO2 generation from the Gd2O3-MNPs were examined as a function of pH and pH-dependent in vitro magnetic relaxation; additionally, the echogenic properties were estimated to demonstrate the potential of the particles for the tumor-specific US and MR imaging.

Keywords: calcium carbonate, mineralization, ultrasound imaging, magnetic resonance imaging

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Authors: Frederick W. Gooding, Jr., Mark Beeman

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Nearly a century ago, the groundbreaking 1915 film ‘The Birth of a Nation’ popularized the way Hollywood made movies with its avant-garde, feature-length style. The movie's subjugating and demeaning depictions of African American women (and men) reflected popular racist beliefs held during the time of slavery and the early Jim Crow era. Although much has changed concerning race relations in the past century, American sociologist Patricia Hill Collins theorizes that the disparaging images of African American women originating in the era of plantation slavery are adaptable and endure as controlling images today. In this context, a comparative analysis of the successful contemporary film, ‘Bringing Down the House’ starring Queen Latifah is relevant as this 2004 film was designed to purposely defy and ridicule classic stereotypes of African American women. However, the film is still tied to the controlling images from the past, although in a modern hybrid form. Scholars of race and film have noted that the pervasive filmic imagery of the African American woman as the loyal mammy stereotype faded from the screen in the post-civil rights era in favor of more sexualized characters (i.e., the Jezebel trope). Analyzing scenes and dialogue through the lens of sociological and critical race theory, the troubling persistence of African American controlling images in film stubbornly emerge in a movie like ‘Bringing Down the House.’ Thus, these controlling images, like racism itself, can adapt to new social and economic conditions. Although the classic controlling images appeared in the first feature length film focusing on race relations a century ago, ‘The Birth of a Nation,’ this black and white rendition of the mammy figure was later updated in 1939 with the classic hit, ‘Gone with the Wind’ in living color. These popular controlling images have loomed quite large in the minds of international audiences, as ‘Gone with the Wind’ is still shown in American theaters currently, and experts at the British Film Institute in 2004 rated ‘Gone with the Wind’ as the number one movie of all time in UK movie history based upon the total number of actual viewings. Critical analysis of character patterns demonstrate that images that appear superficially benign contribute to a broader and quite persistent pattern of marginalization within the aggregate. This approach allows experts and viewers alike to detect more subtle and sophisticated strands of racial discrimination that are ‘hidden in plain sight’ despite numerous changes in the Hollywood industry that appear to be more voluminous and diverse than three or four decades ago. In contrast to white characters, non-white or minority characters are likely to be subtly compromised or marginalized relative to white characters if and when seen within mainstream movies, rather than be subjected to obvious and offensive racist tropes. The hybrid form of both the older Jezebel and Mammy stereotypes exhibited by lead actress Queen Latifah in ‘Bringing Down the House’ represents a more suave and sophisticated merging of past imagery ideas deemed problematic in the past as well as the present.

Keywords: African Americans, Hollywood film, hybrid, stereotypes

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Authors: Harry Einhorn

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This paper aims to explore the integration of Buddhism into educational settings with the goal of fostering the holistic development of children. By incorporating Buddhist principles and practices, educators can create a nurturing environment that cultivates wisdom, compassion, and ethical values in children. The teachings of Buddhism provide valuable insights into mindfulness, compassion, and critical thinking, which can be adapted and applied to educational curricula to enhance children's intellectual, emotional, and moral growth. One of the fundamental aspects of Buddhist philosophy that is particularly relevant to education is the concept of mindfulness. By introducing mindfulness practices, such as meditation and breathing exercises, children can learn to cultivate present-moment awareness, develop emotional resilience, and enhance their ability to concentrate and focus. These skills are essential for effective learning and can contribute to reducing stress and promoting overall well-being in children. Mindfulness practices can also teach children how to manage their emotions and thoughts, promoting self-regulation and creating a positive classroom environment. In addition to mindfulness, Buddhism emphasizes the cultivation of compassion and empathy toward all living beings. Integrating teachings on kindness, empathy, and ethical behavior into the educational framework can help children develop a deep sense of interconnectedness and social responsibility. By engaging children in activities that promote empathy and encourage acts of kindness, such as community service projects and cooperative learning, educators can foster the development of compassionate individuals who are actively engaged in creating a more harmonious and compassionate society. Moreover, Buddhist teachings encourage critical thinking and inquiry, which are crucial skills for intellectual development. By introducing children to fundamental Buddhist concepts such as impermanence, interdependence, and the nature of suffering, educators can engage them in philosophical reflections and broaden their perspectives on life. These teachings promote open-mindedness, curiosity, and a deeper understanding of the interconnectedness of all things. Through the exploration of these concepts, children can develop critical thinking skills and gain insights into the complexities of the world, enabling them to navigate challenges with wisdom and discernment. While integrating Buddhism into education requires sensitivity, cultural awareness, and respect for diverse beliefs and backgrounds, it holds great potential for nurturing the holistic development of children. By incorporating mindfulness practices, fostering compassion and empathy, and promoting critical thinking, Buddhism can contribute to the creation of a more compassionate, inclusive, and harmonious educational environment. This integration can shape well-rounded individuals who are equipped with the necessary skills and qualities to navigate the complexities of the modern world with wisdom, compassion, and resilience. In conclusion, the integration of Buddhism into education offers a valuable framework for cultivating wisdom, compassion, and ethical values in children. By incorporating mindfulness, compassion, and critical thinking into educational practices, educators can create a supportive environment that promotes children's holistic development. By nurturing these qualities, Buddhism can help shape individuals who are not only academically proficient but also morally and ethically responsible, contributing to a more compassionate and harmonious society.

Keywords: Buddhism, education, children, mindfulness

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Authors: Catherine S. Fichten, Tali Heiman, Mary Jorgensen, Mai Nhu Nguyen, Rhonda Amsel, Dorit Olenik-Shemesh

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The study examined Canadian and Israeli students' perceptions related to their intention to graduate from their program of studies. Canada and Israel are dissimilar in many ways that affect education, including language and alphabet. In addition, the postsecondary education systems differ. For example, in some parts of Canada (e.g., in Quebec, Canada’s 2nd largest province), students matriculate after 11 years of high school; in Israel, this typically occurs after 12 years. In addition, Quebec students attend two compulsory years of junior college before enrolling in a three-year university Bachelor program; in Israel students enroll in a three-year Bachelor program directly after matriculation. In addition, Israeli students typically enroll in the army shortly after high school graduation; in Canada, this is not the case. What the two countries do have in common is concern about the success of postsecondary students with disabilities. The present study was based on Ajzen’s Theory of Planned Behavior (TPB); the model suggests that behavior is influenced by Intention to carry it out. This, in turn, is predicted by the following correlated variables: Perceived Behavioral Control (i.e., ease or difficulty enacting the behavior - in this case graduation), Subjective Norms (i.e., perceived social/peer pressure from individuals important in the student’s life), and Attitude (i.e., positive or negative evaluation of graduation). A questionnaire was developed to test the TPB in previous Canadian studies and administered to 845 Canadian college students (755 nondisabled, 90 with LD/ADHD) who had completed at least one semester of studies) and to 660 Israeli university students enrolled in a Bachelor’s program (537 nondisabled, 123 with LD/ADHD). Because Israeli students were older than Canadian students we covaried age in SPSS-based ANOVA comparisons and included it in regression equations. Because females typically have better academic outcomes than males, gender was included in all analyses. ANOVA results indicate only a significant gender effect for Intention to graduate, with females having higher scores. Four stepwise regressions were conducted, with Intention to graduate as the predicted variable, and Gender and the three TPB predictors as independent variables (separate analyses for Israeli and Canadian samples with and without LD/ADHD). Results show that for samples with LD/ADHD, although Gender and Age were not significant predictors, the TPB predictors were, with all three TPB predictors being significant for the Canadian sample (i.e., Perceived Behavioral Control, Subjective Norms, Attitude, R2=.595), and two of the three (i.e., Perceived Behavioral Control, Subjective Norms) for the Israeli sample (R2=.528). For nondisabled students, the results for both countries show that all three TPB predictors were significant along with Gender: R2=.443 for Canada and R2=.332 for Israel; age was not significant. Our findings show that despite vast differences between our Canadian and Israeli samples, Intention to graduate was related to the three TPB predictors. This suggests that our TPB measure is valid for diverse samples and countries that it can be used as a quick, inexpensive way to predict graduation rates, and that strengthening the three predictor variables may result in higher graduation rates.

Keywords: disability, higher education, students, theory of planned behavior

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Authors: Sakshi Gupta, Kavita Sardana

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Management of a forest catchment involves diverse dimensions, multiple stakeholders, and conflicting interests, primarily due to the wide variety of valuable ecosystem services offered by it. Often, the coordination among different levels of formal institutions governing the catchment, local communities, as well as societal norms, taboos, customs and practices, happens to be amiss, leading to conflicting policy interventions which prove detrimental for such resources. In the case of Ala Catchment, which is a protected forest located at a distance of 9 km North-East of the town of Dalhousie, within district Chamba of Himachal Pradesh, India, and serves as one of the primary sources of public water supply for the downstream town of Dalhousie and nearby areas, several policy measures have been adopted for the restoration of the forest catchment, as well as for the improvement of public water supply. These catchment forest restoration measures include; the installation of a fence along the perimeter of the catchment, plantation of trees in the empty patches of the forest, construction of check dams, contour trenches, contour bunds, issuance of grazing permits, and installation of check posts to keep track of trespassers. While the measures adopted to address the acute shortage of public water supply in the Dalhousie region include; building and maintenance of large capacity water storage tanks, laying of pipelines, expanding public water distribution infrastructure to include water sources other than Ala Catchment Forest and introducing of five new water supply schemes for drinking water as well as irrigation. However, despite these policy measures, the degradation of the Ala catchment and acute shortage of water supply continue to distress the region. This study attempts to conduct an institutional analysis to assess the impact of policy measures for the restoration of the Ala Catchment in the Chamba district of Himachal Pradesh in India. For this purpose, the theoretical framework of Ostrom’s Institutional Assessment and Development (IAD) Framework was used. Snowball sampling was used to conduct private interviews and focused group discussions. A semi-structured questionnaire was administered to interview a total of 184 respondents across stakeholders from both formal and informal institutions. The central hypothesis of the study is that the interplay of formal and informal institutions facilitates the implementation of policy measures for ameliorating Ala Catchment, in turn improving the livelihood of people depending on this forest catchment for direct and indirect benefits. The findings of the study suggest that leakages in the successful implementation of policy measures occur at several nodes of decision-making, which adversely impact the catchment and the ecosystem services provided by it. Some of the key reasons diagnosed by the immediate analysis include; ad-hoc assignment of property rights, rise in tourist inflow increasing the pressures on water demand, illegal trespassing by local and nomadic pastoral communities for grazing and unlawful extraction of forest products, and rent-seeking by a few influential formal institutions. Consequently, it is indicated that the interplay of formal and informal institutions may be obscuring the consequentiality of the policy measures on the restoration of the catchment.

Keywords: catchment forest restoration, institutional analysis and development framework, institutional interplay, protected forest, water supply management

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Authors: Maddalena Arigoni, Maria Luisa Ratto, Raffaele A. Calogero, Luca Alessandri

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The presence of tumor heterogeneity, where distinct cancer cells exhibit diverse morphological and phenotypic profiles, including gene expression, metabolism, and proliferation, poses challenges for molecular prognostic markers and patient classification for targeted therapies. Understanding the causes and progression of cancer requires research efforts aimed at characterizing heterogeneity, which can be facilitated by evolving single-cell sequencing technologies. However, analyzing single-cell data necessitates computational methods that often lack objective validation. Therefore, the establishment of benchmarking datasets is necessary to provide a controlled environment for validating bioinformatics tools in the field of single-cell oncology. Benchmarking bioinformatics tools for single-cell experiments can be costly due to the high expense involved. Therefore, datasets used for benchmarking are typically sourced from publicly available experiments, which often lack a comprehensive cell annotation. This limitation can affect the accuracy and effectiveness of such experiments as benchmarking tools. To address this issue, we introduce omics benchmark experiments designed to evaluate bioinformatics tools to depict the heterogeneity in single-cell tumor experiments. We conducted single-cell RNA sequencing on six lung cancer tumor cell lines that display resistant clones upon treatment of EGFR mutated tumors and are characterized by driver genes, namely ROS1, ALK, HER2, MET, KRAS, and BRAF. These driver genes are associated with downstream networks controlled by EGFR mutations, such as JAK-STAT, PI3K-AKT-mTOR, and MEK-ERK. The experiment also featured an EGFR-mutated cell line. Using 10XGenomics platform with cellplex technology, we analyzed the seven cell lines together with a pseudo-immunological microenvironment consisting of PBMC cells labeled with the Biolegend TotalSeq™-B Human Universal Cocktail (CITEseq). This technology allowed for independent labeling of each cell line and single-cell analysis of the pooled seven cell lines and the pseudo-microenvironment. The data generated from the aforementioned experiments are available as part of an online tool, which allows users to define cell heterogeneity and generates count tables as an output. The tool provides the cell line derivation for each cell and cell annotations for the pseudo-microenvironment based on CITEseq data by an experienced immunologist. Additionally, we created a range of pseudo-tumor tissues using different ratios of the aforementioned cells embedded in matrigel. These tissues were analyzed using 10XGenomics (FFPE samples) and Curio Bioscience (fresh frozen samples) platforms for spatial transcriptomics, further expanding the scope of our benchmark experiments. The benchmark experiments we conducted provide a unique opportunity to evaluate the performance of bioinformatics tools for detecting and characterizing tumor heterogeneity at the single-cell level. Overall, our experiments provide a controlled and standardized environment for assessing the accuracy and robustness of bioinformatics tools for studying tumor heterogeneity at the single-cell level, which can ultimately lead to more precise and effective cancer diagnosis and treatment.

Keywords: single cell omics, benchmark, spatial transcriptomics, CITEseq

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Authors: Shayan Mohajer Hamidi

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Federated Learning (FL) has emerged as a promising paradigm for training machine learning models on distributed data without the need for centralized data aggregation. In the realm of wireless communications, FL has the potential to leverage the vast amounts of data generated by wireless devices to improve model performance and enable intelligent applications. However, the fairness aspect of FL in wireless communications remains largely unexplored. This abstract presents an idea for fair federated learning in wireless communications, addressing the challenges of imbalanced data distribution, privacy preservation, and resource allocation. Firstly, the proposed approach aims to tackle the issue of imbalanced data distribution in wireless networks. In typical FL scenarios, the distribution of data across wireless devices can be highly skewed, resulting in unfair model updates. To address this, we propose a weighted aggregation strategy that assigns higher importance to devices with fewer samples during the aggregation process. By incorporating fairness-aware weighting mechanisms, the proposed approach ensures that each participating device's contribution is proportional to its data distribution, thereby mitigating the impact of data imbalance on model performance. Secondly, privacy preservation is a critical concern in federated learning, especially in wireless communications where sensitive user data is involved. The proposed approach incorporates privacy-enhancing techniques, such as differential privacy, to protect user privacy during the model training process. By adding carefully calibrated noise to the gradient updates, the proposed approach ensures that the privacy of individual devices is preserved without compromising the overall model accuracy. Moreover, the approach considers the heterogeneity of devices in terms of computational capabilities and energy constraints, allowing devices to adaptively adjust the level of privacy preservation to strike a balance between privacy and utility. Thirdly, efficient resource allocation is crucial for federated learning in wireless communications, as devices operate under limited bandwidth, energy, and computational resources. The proposed approach leverages optimization techniques to allocate resources effectively among the participating devices, considering factors such as data quality, network conditions, and device capabilities. By intelligently distributing the computational load, communication bandwidth, and energy consumption, the proposed approach minimizes resource wastage and ensures a fair and efficient FL process in wireless networks. To evaluate the performance of the proposed fair federated learning approach, extensive simulations and experiments will be conducted. The experiments will involve a diverse set of wireless devices, ranging from smartphones to Internet of Things (IoT) devices, operating in various scenarios with different data distributions and network conditions. The evaluation metrics will include model accuracy, fairness measures, privacy preservation, and resource utilization. The expected outcomes of this research include improved model performance, fair allocation of resources, enhanced privacy preservation, and a better understanding of the challenges and solutions for fair federated learning in wireless communications. The proposed approach has the potential to revolutionize wireless communication systems by enabling intelligent applications while addressing fairness concerns and preserving user privacy.

Keywords: federated learning, wireless communications, fairness, imbalanced data, privacy preservation, resource allocation, differential privacy, optimization

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Authors: Ma Chu Jui

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Culture plays a pivotal role in shaping societal responses to change and fostering adaptability. In the realm of healthcare provision, hospitals serve as dynamic settings molded by the cultural consciousness of healthcare professionals. This intricate interplay extends to their expectations of leadership, communication styles, and attitudes towards patient care. Recognizing the cultural inclinations of healthcare professionals becomes imperative in navigating this complex landscape. This study will utilize Hofstede's Value Survey Module 2013 (VSM 2013) as a comprehensive analytical tool. The targeted participants for this research are in-service nursing professionals with a tenure of at least three months, specifically employed in the nursing department of an Eastern hospital. This quantitative approach seeks to quantify diverse cultural tendencies among the targeted nursing professionals, elucidating not only abstract cultural concepts but also revealing their cultural inclinations across different dimensions. The study anticipates gathering between 400 to 500 responses, ensuring a robust dataset for a comprehensive analysis. The focused approach on nursing professionals within the Eastern hospital setting enhances the relevance and specificity of the cultural insights obtained. The research aims to contribute valuable knowledge to the understanding of cultural tendencies among in-service nursing personnel in the nursing department of this specific Eastern hospital. The VSM 2013 will be initially distributed to this specific group to collect responses, aiming to calculate scores on each of Hofstede's six cultural dimensions—Power Distance Index (PDI), Individualism vs. Collectivism (IDV), Uncertainty Avoidance Index (UAI), Masculinity vs. Femininity (MAS), Long-Term Orientation vs. Short-Term Normative Orientation (LTO), and Indulgence vs. Restraint (IVR). the study unveils a significant correlation between different cultural dimensions and healthcare professionals' tendencies in understanding leadership expectations through PDI, grasping behavioral patterns via IDV, acknowledging risk acceptance through UAI, and understanding their long-term and short-term behaviors through LTO. These tendencies extend to communication styles and attitudes towards patient care. These findings provide valuable insights into the nuanced interconnections between cultural factors and healthcare practices. Through a detailed analysis of the varying levels of these cultural dimensions, we gain a comprehensive understanding of the predominant inclinations among the majority of healthcare professionals. This nuanced perspective adds depth to our comprehension of how cultural values shape their approach to leadership, communication, and patient care, contributing to a more holistic understanding of the healthcare landscape. A profound comprehension of the cultural paradigms embraced by healthcare professionals holds transformative potential. Beyond a mere understanding, it acts as a catalyst for elevating the caliber of healthcare services. This heightened awareness fosters cohesive collaboration among healthcare teams, paving the way for the establishment of a unified healthcare ethos. By cultivating shared values, our study envisions a healthcare environment characterized by enhanced quality, improved teamwork, and ultimately, a more favorable and patient-centric healthcare landscape. In essence, our research underscores the critical role of cultural awareness in shaping the future of healthcare delivery.

Keywords: hofstede's cultural, cultural dimensions, cultural values in healthcare, cultural awareness in nursing

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Authors: Melanie Grier, Adam Murry

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Objective: Worldwide, Indigenous Peoples experience underemployment and poverty at disproportionately higher rates than non-Indigenous people, despite similar rates of employment seeking. Euro-colonial conquest and genocidal assimilation policies are implicated as perpetuating poverty, which research consistently links to health and wellbeing disparities. Many of the contributors to poverty, such as inadequate income and lack of access to medical care, can be directly or indirectly linked to underemployment. Calls have been made to prioritize Indigenous perspectives in Industrial-Organizational (I/O) psychology research, yet the literature on Indigenous employment remains scarce. What does exist is disciplinarily diverse, topically scattered, and lacking evidence of community-based participatory research (CBPR) practices, a research project approach which prioritizes community leadership, partnership, and betterment and reduces the potential for harm. Due to the harmful colonial legacy of extractive scientific inquiry "on" rather than "with" Indigenous groups, Indigenous leaders and research funding agencies advocate for academic researchers to adopt reparative research methodologies such as CBPR to be used when studying issues pertaining to Indigenous Peoples or individuals. However, the frequency and consistency of CBPR implementation within scholarly discourse are unknown. Therefore, this project’s goal is two-fold: (1) to understand what comprises CBPR in Indigenous research and (2) to determine if CBPR has been historically used in Indigenous employment research. Method: Using a systematic literature review process, sixteen articles about CBPR use with Indigenous groups were selected, and content was analyzed to identify key components comprising CBPR usage. An Indigenous CBPR components framework was constructed and subsequently utilized to analyze the Indigenous employment empirical literature. A similar systematic literature review process was followed to search for relevant empirical articles on Indigenous employment. A total of 120 articles were identified in six global regions: Australia, New Zealand, Canada, America, the Pacific Islands, and Greenland/Norway. Each empirical study was procedurally examined and coded for criteria inclusion using content analysis directives. Results: Analysis revealed that, in total, CBPR elements were used 14% of the time in Indigenous employment research. Most studies (n=69; 58%) neglected to mention using any CBPR components, while just two studies discussed implementing all sixteen (2%). The most significant determinant of overall CBPR use was community member partnership (CP) in the research process. Studies from New Zealand were most likely to use CBPR components, followed by Canada, Australia, and America. While CBPR use did increase slowly over time, meaningful temporal trends were not found. Further, CBPR use did not directly correspond with the total number of topical articles published that year. Conclusions: Community-initiated and engaged research approaches must be better utilized in employment studies involving Indigenous Peoples. Future research efforts must be particularly attentive to community-driven objectives and research protocols, emphasizing specific areas of concern relevant to the field of I/O psychology, such as organizational support, recruitment, and selection.

Keywords: community-based participatory research, content analysis, employment, indigenous research, international, reconciliation, recruitment, reparative research, selection, systematic literature review

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Authors: D. Madhushanka, Y. Liu, H. C. Fernando

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Fires are one of the foremost factors of land surface disturbance in diverse ecosystems, causing soil erosion and land-cover changes and atmospheric effects affecting people's lives and properties. Generally, the severity of the fire is calculated as the Normalized Burn Ratio (NBR) index. This is performed manually by comparing two images obtained afterward. Then by using the bitemporal difference of the preprocessed satellite images, the dNBR is calculated. The burnt area is then classified as either unburnt (dNBR<0.1) or burnt (dNBR>= 0.1). Furthermore, Wildfire Severity Assessment (WSA) classifies burnt areas and unburnt areas using classification levels proposed by USGS and comprises seven classes. This procedure generates a burn severity report for the area chosen by the user manually. This study is carried out with the objective of producing an automated tool for the above-mentioned process, namely the World Wildfire Severity Assessment Tool (WWSAT). It is implemented in Google Earth Engine (GEE), which is a free cloud-computing platform for satellite data processing, with several data catalogs at different resolutions (notably Landsat, Sentinel-2, and MODIS) and planetary-scale analysis capabilities. Sentinel-2 MSI is chosen to obtain regular processes related to burnt area severity mapping using a medium spatial resolution sensor (15m). This tool uses machine learning classification techniques to identify burnt areas using NBR and to classify their severity over the user-selected extent and period automatically. Cloud coverage is one of the biggest concerns when fire severity mapping is performed. In WWSAT based on GEE, we present a fully automatic workflow to aggregate cloud-free Sentinel-2 images for both pre-fire and post-fire image compositing. The parallel processing capabilities and preloaded geospatial datasets of GEE facilitated the production of this tool. This tool consists of a Graphical User Interface (GUI) to make it user-friendly. The advantage of this tool is the ability to obtain burn area severity over a large extent and more extended temporal periods. Two case studies were carried out to demonstrate the performance of this tool. The Blue Mountain national park forest affected by the Australian fire season between 2019 and 2020 is used to describe the workflow of the WWSAT. This site detected more than 7809 km2, using Sentinel-2 data, giving an error below 6.5% when compared with the area detected on the field. Furthermore, 86.77% of the detected area was recognized as fully burnt out, of which high severity (17.29%), moderate-high severity (19.63%), moderate-low severity (22.35%), and low severity (27.51%). The Arapaho and Roosevelt National Forest Park, California, the USA, which is affected by the Cameron peak fire in 2020, is chosen for the second case study. It was found that around 983 km2 had burned out, of which high severity (2.73%), moderate-high severity (1.57%), moderate-low severity (1.18%), and low severity (5.45%). These spots also can be detected through the visual inspection made possible by cloud-free images generated by WWSAT. This tool is cost-effective in calculating the burnt area since satellite images are free and the cost of field surveys is avoided.

Keywords: burnt area, burnt severity, fires, google earth engine (GEE), sentinel-2

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

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Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: Antonella Falanga, Armando Cartenì

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Today, an unprecedented amount of data coming from several sources, including mobile devices, sensors, tracking systems, and online platforms, characterizes our lives. The term “big data” not only refers to the quantity of data but also to the variety and speed of data generation. These data hold valuable insights that, when extracted and analyzed, facilitate informed decision-making. The 4Vs of big data - velocity, volume, variety, and value - highlight essential aspects, showcasing the rapid generation, vast quantities, diverse sources, and potential value addition of these kinds of data. This surge of information has revolutionized many sectors, such as business for improving decision-making processes, healthcare for clinical record analysis and medical research, education for enhancing teaching methodologies, agriculture for optimizing crop management, finance for risk assessment and fraud detection, media and entertainment for personalized content recommendations, emergency for a real-time response during crisis/events, and also mobility for the urban planning and for the design/management of public and private transport services. Big data's pervasive impact enhances societal aspects, elevating the quality of life, service efficiency, and problem-solving capacities. However, during this transformative era, new challenges arise, including data quality, privacy, data security, cybersecurity, interoperability, the need for advanced infrastructures, and staff training. Within the transportation sector (the one investigated in this research), applications span planning, designing, and managing systems and mobility services. Among the most common big data applications within the transport sector are, for example, real-time traffic monitoring, bus/freight vehicle route optimization, vehicle maintenance, road safety and all the autonomous and connected vehicles applications. Benefits include a reduction in travel times, road accidents and pollutant emissions. Within these issues, the proper transport demand estimation is crucial for sustainable transportation planning. Evaluating the impact of sustainable mobility policies starts with a quantitative analysis of travel demand. Achieving transportation decarbonization goals hinges on precise estimations of demand for individual transport modes. Emerging technologies, offering substantial big data at lower costs than traditional methods, play a pivotal role in this context. Starting from these considerations, this study explores the usefulness impact of big data within transport demand estimation. This research focuses on leveraging (big) data collected during the COVID-19 pandemic to estimate the evolution of the mobility demand in Italy. Estimation results reveal in the post-COVID-19 era, more than 96 million national daily trips, about 2.6 trips per capita, with a mobile population of more than 37.6 million Italian travelers per day. Overall, this research allows us to conclude that big data better enhances rational decision-making for mobility demand estimation, which is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, cloud computing, decision-making, mobility demand, transportation

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Authors: Mapule Maema

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The paper aims to highlight the role that community activism has played in promoting social justice around housing issues in the Western Cape. The Western Cape is one of the largest spatially segregated provinces in South Africa which continues to exhibit grave inequalities between cities, townships and farms. These inequalities cut across intersectional issues such as, race, class, gender, and politics. The main challenges facing marginalized communities in the Western Cape include access to housing, land and basic services. This is not peculiar to only the Western Cape, the entire country is facing similar challenges however the Western Cape is seen as a fasted urbanizing province in the country due to tourism. Various social movements have been formed across the country to counter these challenges, however, this paper focuses on the resilience communities have fostered despite the myriad housing and spatial crisis they are faced with. The paper focuses on the Legal Resource’s Centre’s clients from an informal settlement called Imizamo Yethu based in Hout Bay Valley area. The 18 hectare settlement houses approximately 33600 people. On the 21st July 2017, Hout Bay experienced violent protests following an eviction order passed by the City of Cape Town. The protest was characterized by tensions within the community regarding the super-blocking initiative which aims to establish roads in informal settlements to ensure basic services. Residents against the process argued that there were no proper consultations done to educate them on what this process entailed. Public participation is one of the objectives the municipalities aim to promote however it remains a great challenge. In order to highlight the experiences of the LRC clients in relation to what motivated their involvement in the movement, how it felt their participation, and aspirations, the paper will employ qualitative research methods. Qualitative research methods enable the researcher to get a deeper and nuanced understanding of the social world in the eyes of those who experienced it. It is a flexible methodology that enables one to also understand social processes and the significance they generate. Data will be collected through the use of the World Cafe as a focus group method. The World Café is a simple, effective and flexible format for hosting group dialogue. The steps taken when setting up a World Café includes the following: setting the context (why you are bringing people together and what you want to achieve), create hospitality space (make participants feel at home and free to discuss issues), explore questions that matter, connect diverse perspectives (the opportunity to actively contribute your thinking), listen together for patterns and insights, share collective discoveries and learnings. Secondary data will be used to augment the data collected. Stories of impact will be drawn from the exercises. This paper will contribute to the discourse of sustainable housing and urban development and the research outputs will be disseminated to the public for learning.

Keywords: community activism, influence, social justice, development

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Authors: Shashi Mehta, Krishan Kumar Yadav

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This paper presents an overview of issues pertaining to the conservation of the natural environment and factors affecting the coexistence of the forest, wildlife and people. As forests and wildlife together create the basis for economic, cultural and recreational spaces for overall well-being and life-support systems, the adverse impacts of increasing consumerism are only too evident. The IUCN predicts extinction of 41% of all amphibians and 26% of mammals. The major causes behind this threatened extinction are Deforestation, Dysfunctional governance, Climate Change, Pollution and Cataclysmic phenomena. Thus the intrinsic relationship between natural resources and wildlife needs to be understood in totality, not only for the eco-system but for humanity at large. To demonstrate this, forest areas in the Aravalis- the oldest mountain ranges of Asia—falling in the States of Haryana and Rajasthan, have been taken up for study. The Aravalis are characterized by extreme climatic conditions and dry deciduous forest cover on intermittent scattered hills. Extending across the districts of Gurgaon, Faridabad, Mewat, Mahendergarh, Rewari and Bhiwani, these ranges - with village common land on which the entire economy of the rural settlements depends - fall in the state of Haryana. Aravali ranges with diverse fauna and flora near Alwar town of state of Rajasthan also form part of NCR. Once, rich in biodiversity, the Aravalis played an important role in the sustainable co-existence of forest and people. However, with the advent of industrialization and unregulated urbanization, these ranges are facing deforestation, degradation and denudation. The causes are twofold, i.e. the need of the poor and the greed of the rich. People living in and around the Aravalis are mainly poor and eke out a living by rearing live-stock. With shrinking commons, they depend entirely upon these hills for grazing, fuel, NTFP, medicinal plants and even drinking water. But at the same time, the pressure of indiscriminate urbanization and industrialization in these hills fulfils the demands of the rich and powerful in collusion with Government agencies. The functionaries of federal and State Governments play largely a negative role supporting commercial interests. Additionally, planting of a non- indigenous species like prosopis juliflora across the ranges has resulted in the extinction of almost all the indigenous species. The wildlife in the area is also threatened because of the lack of safe corridors and suitable habitat. In this scenario, the participatory role of different stakeholders such as NGOs, civil society and local community in the management of forests becomes crucial not only for conservation but also for the economic wellbeing of the local people. Exclusion of villagers from protection and conservation efforts - be it designing, implementing or monitoring and evaluating could prove counterproductive. A strategy needs to be evolved, wherein Government agencies be made responsible by putting relevant legislation in place along with nurturing and promoting the traditional wisdom and ethics of local communities in the protection and conservation of forests and wild life in the Aravali ranges of States of Haryana and Rajasthan of the National Capital Region, Delhi.

Keywords: deforestation, ecosystem, governance, urbanization

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Authors: Soheila Sadeghi

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Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

Procedia PDF Downloads 59

Authors: Walid A. Alkeridy, Arwa Aljasser, Khalid Mohammed Alayed, Saad Alsaad, Amani S. Alqahtani, Claire Ann Lim, Sultan H. Alamri, Doaa Zainhom Mekkawy, Mohammed Al-Sofiani

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Introduction: The history of publicly funded Home Health Care (HHC) service in Saudi Arabia dates back to 1991. The first HC program was launched to provide palliative home care services for patients with terminal cancer. Thereafter, more programs launched across Saudi Arabia most remarkably was launching the national program for HHC by the Ministry Of Health (MOH) in 2008. The national HHC MOH program is mainly providing long-term care home care services for over 40,000 Saudi citizens. The scope of the HHC service program provided by the Saudi MOH is quite diverse, ranging from basic nursing care to specialized care programs, e.g., home peritoneal dialysis, home ventilation, home infusion therapy, etc. Objectives: The primary aim of our study is to report the prevalence of chronic conditions among Saudi people receiving long-term HHC services. Secondary aims include identifying the predictors of mortality among individuals receiving long-term HHC services and studying the association between frailty and poor health outcomes among HHC users. Methods: We conducted a retrospective and cross-sectional data collection from participants receiving HHC services at King Saud University Medical City, Riyadh, Saudi Arabia. Data were collected from electronic health records (EHR), patient charts, and interviewing caregivers from the year 2019 to 2022. We assessed functional performance by Katz's activity of daily living and the Bristol Activity of Daily Living Scale (BADLS). A trained health care provider assessed frailty using the Clinical Frailty Scale (CFS). Mortality was assessed by reviewing the death certificates if patients were hospitalized through discharge status ascertainment from EHR. Results: The mean age for deceased individuals in HHC was 78.3 years. Over twenty percent of individuals receiving HHC services were readmitted to the hospital. The following variables were statistically significant between deceased and alive individuals receiving HHC services; clinical frailty scale, the total number of comorbid conditions, and functional performance based on the KATZ activity of daily living scale and the BADLS. We found that the strongest predictors for mortality were pressure ulcers which had an odds ratio of 3.75 and p-value of < 0.0001, and the clinical frailty scale, which had an odds ratio of 1.69 and p-value of 0.002, using multivariate regression analysis. In conclusion, our study found that pressure ulcers and frailty are the strongest predictors of mortality for individuals receiving home health care services. Moreover, we found a high rate of annual readmission for individuals enrolled in HHC, which requires further analysis to understand the possible contributing factors for the increased rate of hospital readmission and develop strategies to address them. Future studies should focus on designing quality improvement projects aimed at improving the quality of life for individuals receiving HHC services, especially those who have pressure ulcers at the end of life.

Keywords: homecare, Saudi, prevalence, chronic

Procedia PDF Downloads 118

Authors: Hamza Saeed, Khurram Iqbal Ahmad Khan

Abstract:

Effective information management is crucial for any construction project and its success. Primary areas of information generation are either the construction site or the design office. There are different types of information required at different stages of construction involving various stakeholders creating complexity. There is a need for effective management of information flows to reduce uncertainty creating complexity. Nature provides a unique perspective in terms of dealing with complexity, in particular, information complexity. System dynamics methodology provides tools and techniques to address complexity. It involves modeling and simulation techniques that help address complexity. Nature has been dealing with complex systems since its creation 4.5 billion years ago. It has perfected its system by evolution, resilience towards sudden changes, and extinction of unadaptable and outdated species that are no longer fit for the environment. Nature has been accommodating the changing factors and handling complexity forever. Humans have started to look at their natural counterparts for inspiration and solutions for their problems. This brings forth the possibility of using a biomimetics approach to improve the management practices used in the construction sector. Ants inhabit different habitats. Cataglyphis and Pogonomyrmex live in deserts, Leafcutter ants reside in rainforests, and Pharaoh ants are native to urban developments of tropical areas. Detailed studies have been done on fifty species out of fourteen thousand discovered. They provide the opportunity to study the interactions in diverse environments to generate collective behavior. Animals evolve to better adapt to their environment. The collective behavior of ants emerges from feedback through interactions among individuals, based on a combination of three basic factors: The patchiness of resources in time and space, operating cost, environmental stability, and the threat of rupture. If resources appear in patches through time and space, the response is accelerating and non-linear, and if resources are scattered, the response follows a linear pattern. If the acquisition of energy through food is faster than energy spent to get it, the default is to continue with an activity unless it is halted for some reason. If the energy spent is rather higher than getting it, the default changes to stay put unless activated. Finally, if the environment is stable and the threat of rupture is low, the activation and amplification rate is slow but steady. Otherwise, it is fast and sporadic. To further study the effects and to eliminate the environmental bias, the behavior of four different ant species were studied, namely Red Harvester ants (Pogonomyrmex Barbatus), Argentine ants (Linepithema Humile), Turtle ants (Cephalotes Goniodontus), Leafcutter ants (Genus: Atta). This study aims to improve the information system in the construction sector by providing a guideline inspired by nature with a systems-thinking approach, using system dynamics as a tool. Identified factors and their interdependencies were analyzed in the form of a causal loop diagram (CLD), and construction industry professionals were interviewed based on the developed CLD, which was validated with significance response. These factors and interdependencies in the natural system corresponds with the man-made systems, providing a guideline for effective use and flow of information.

Keywords: biomimetics, complex systems, construction management, information management, system dynamics

Procedia PDF Downloads 137

Authors: Jose A. C. Venancio, Alexandrino J. M. Goncalves, Anabela Marto, Nuno C. S. Rodrigues, Rita M. T. Ascenso

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Nowadays, it is common to find people who are concerned about getting away from the everyday life routine, looking forward to outcome well-being and pleasant emotions. Trying to disconnect themselves from the usual places of work and residence, they pursue different places, such as tourist destinations, aiming to have unexpected experiences. In order to make this exploration process easier, cities and tourism agencies seek new opportunities and solutions, creating routes with diverse cultural landmarks, including natural landscapes and historic buildings. These offers frequently aspire to the preservation of the local patrimony. In nature and wildlife, birdwatching is an activity that has been increasing, both in cities and in the countryside. This activity seeks to find, observe and identify the diversity of birds that live permanently or temporarily in these places, and it is usually supported by birdwatching guides. Leiria (Portugal) is a well-known city, presenting several historical and natural landmarks, like the Lis river and the castle where King D. Dinis lived in the 13th century. Along the Lis River, a conservation process was carried out and a pedestrian route was created (Polis project). This is considered an excellent spot for birdwatching, especially for the gray heron (Ardea cinerea) and for the kingfisher (Alcedo atthis). There is also a route through the city, from the riverside to the castle, which encloses a characterized variety of species, such as the barn swallow (Hirundo rustica), known for passing through different seasons of the year. Birdwatching is sometimes a difficult task since it is not always possible to see all bird species that inhabit a given place. For this reason, a need to create a technological solution was found to ease this activity. This project aims to encourage people to learn about the various species of birds that live along the Lis River and to promote the preservation of nature in a conscious way. This work is being conducted in collaboration with Leiria Municipal Council and with the Environmental Interpretation Centre. It intends to show the majesty of the Lis River, a place visited daily by several people, such as children and families, who use it for didactic and recreational activities. We are developing a mobile multi-platform application (Guard@Lis) that allows bird species to be observed along a given route, using representative digital 3D models through the integration of augmented reality technologies. Guard@Lis displays a route with points of interest for birdwatching and a list of species for each point of interest, along with scientific information, images and sounds for every species. For some birds, to ensure their observation, the user can watch them in loco, in their real and natural environment, with their mobile device by means of augmented reality, giving the sensation of presence of these birds, even if they cannot be seen in that place at that moment. The augmented reality feature is being developed with Vuforia SDK, using a hybrid approach to recognition and tracking processes, combining marks and geolocation techniques. This application proposes routes and notifies users with alerts for the possibility of viewing models of augmented reality birds. The final Guard@Lis prototype will be tested by volunteers in-situ.

Keywords: augmented reality, birdwatching route, mobile application, nature tourism, watch birds using augmented reality

Procedia PDF Downloads 177

Authors: Mohosina Jabin Toma, Gerald Tembrevilla, Marina Milner-Bolotin

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Science education in Bangladesh is losing its appeal at an alarming rate due to the lack of science laboratory equipment, excessive teacher-student ratio, and outdated teaching strategies. Research-based educational technologies aim to address some of the problems faced by teachers who have limited access to laboratory resources, like many Bangladeshi teachers. Physics Education Technology (PhET) research team has been developing science and mathematics interactive simulations to help students develop deeper conceptual understanding. Still, PhET simulations are rarely used in Bangladesh. The purpose of this study is to explore Bangladeshi teachers’ challenges in learning to implement PhET-enhanced pedagogies and examine teachers’ views on PhET’s pedagogical opportunities in secondary science education. Since it is a new technology for Bangladesh, seven workshops on PhET were conducted in Dhaka city for 129 in-service and pre-service teachers in the winter of 2023 prior to data collection. This study followed an explanatory mixed method approach that included a pre-and post-workshop survey and five semi-structured interviews. Teachers participated in the workshops voluntarily and shared their experiences at the end. Teachers’ challenges were also identified from workshop discussions and observations. The interviews took place three to four weeks after the workshop and shed light on teachers’ experiences of using PhET in actual classroom settings. The results suggest that teachers had difficulty handling new technology; hence, they recommended preparing a booklet and Bengali YouTube videos on PhET to assist them in overcoming their struggles. Teachers also faced challenges in using any inquiry-based learning approach due to the content-loaded curriculum and exam-oriented education system, as well as limited experience with inquiry-based education. The short duration of classes makes it difficult for them to design PhET activities. Furthermore, considering limited access to computers and the internet in school, teachers think PhET simulations can bring positive changes if used in homework activities. Teachers also think they lack pedagogical skills and sound content knowledge to take full advantage of PhET. They highly appreciated the workshops and proposed that the government designs some teacher training modules on how to incorporate PhET simulations. Despite all the challenges, teachers believe PhET can enhance student learning, ensure student engagement and increase student interest in STEM Education. Considering the lack of science laboratory equipment, teachers recognized the potential of PhET as a supplement to hands-on activities for secondary science education in Bangladesh. They believed that if PhET develops more curriculum-relevant sims, it will bring revolutionary changes to how Bangladeshi students learn science. All the participating teachers in this study came from two organizations, and all the workshops took place in urban areas; therefore, the findings cannot be generalized to all secondary science teachers. A nationwide study is required to include teachers from diverse backgrounds. A further study can shed light on how building a professional learning community can lessen teachers’ challenges in incorporating PhET-enhanced pedagogy in their teaching.

Keywords: educational technology, inquiry-based learning, PhET interactive simulations, PhET-enhanced pedagogies, science education, science laboratory equipment, teacher professional development

Procedia PDF Downloads 95

Authors: Rupak Kumar Sarma, Ratul Saikia

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Macrophytes encompass major functional group in eutrophic wetland ecosystems. As a key functional element of freshwater lakes, they play a crucial role in regulating various wetland biogeochemical cycles, as well as maintain the biodiversity at the ecosystem level. The high carbon-rich underground biomass of macrophyte populations may harbour diverse microbial community having significant potential in maintaining different biogeochemical cycles. The present investigation was designed to study the macrophyte-microbe interaction in coupled nitrification and denitrification, considering Deepor Beel Lake (a Ramsar conservation site) of North East India as a model eutrophic system. Highly eutrophic sites of Deepor Beel were selected based on sediment oxygen demand and inorganic phosphorus and nitrogen (P&N) concentration. Sediment redox potential and depth of the lake was chosen as the benchmark for collecting the plant and sediment samples. The average highest depth in winter (January 2016) and summer (July 2016) were recorded as 20ft (6.096m) and 35ft (10.668m) respectively. Both sampling depth and sampling seasons had the distinct effect on variation in macrophyte community composition. Overall, the dominant macrophytic populations in the lake were Nymphaea alba, Hydrilla verticillata, Utricularia flexuosa, Vallisneria spiralis, Najas indica, Monochoria hastaefolia, Trapa bispinosa, Ipomea fistulosa, Hygrorhiza aristata, Polygonum hydropiper, Eichhornia crassipes and Euryale ferox. There was a distinct correlation in the variation of major sediment physicochemical parameters with change in macrophyte community compositions. Quantitative estimation revealed an almost even accumulation of nitrate and nitrite in the sediment samples dominated by the plant species Eichhornia crassipes, Nymphaea alba, Hydrilla verticillata, Vallisneria spiralis, Euryale ferox and Monochoria hastaefolia, which might have signified a stable nitrification and denitrification process in the sites dominated by the selected aquatic plants. This was further examined by a systematic analysis of microbial populations through culture dependent and independent approach. Culture-dependent bacterial community study revealed the higher population of nitrifiers and denitrifiers in the sediment samples dominated by the six macrophyte species. However, culture-independent study with bacterial 16S rDNA V3-V4 metagenome sequencing revealed the overall similar type of bacterial phylum in all the sediment samples collected during the study. Thus, there might be the possibility of uneven distribution of nitrifying and denitrifying molecular markers among the sediment samples collected during the investigation. The diversity and abundance of the nitrifying and denitrifying molecular markers in the sediment samples are under investigation. Thus, the role of different aquatic plant functional types in microorganism mediated nitrogen cycle coupling could be screened out further from the present initial investigation.

Keywords: denitrification, macrophyte, metagenome, microorganism, nitrification

Procedia PDF Downloads 174

Authors: Shanhua Hu

Abstract:

Social media as a critical propagandizing form of film, video games, and digital products has received substantial research attention, but there exists several critical barriers such as: (1) few studies exploring the internal and external connections of a product as part of the multimodal context that gives rise to readability and commercial return; (2) the lack of study of multimodal analysis in product’s official account of game publishers and its impact on users’ behaviors including purchase intention, social media engagement, and playing time; (3) no standardized ecologically-valid, game type-varying data can be used to study the complexity of official account’s postings within a time period. This proposed research helps to tackle these limitations in order to develop a model of readability study that is more ecologically valid, robust, and thorough. To accomplish this objective, this paper provides a more diverse dataset comprising different visual elements and messages collected from the official Twitter accounts of the Top 20 best-selling games of 2021. Video game companies target potential users through social media, a popular approach is to set up an official account to maintain exposure. Typically, major game publishers would create an official account on Twitter months before the game's release date to update on the game's development, announce collaborations, and reveal spoilers. Analyses of tweets from those official Twitter accounts would assist publishers and marketers in identifying how to efficiently and precisely deploy advertising to increase game sales. The purpose of this research is to determine how official game accounts use Twitter to attract new customers, specifically which types of messages are most effective at increasing sales. The dataset includes the number of days until the actual release date on Twitter posts, the readability of the post (Flesch Reading Ease Score, FRES), the number of emojis used, the number of hashtags, the number of followers of the mentioned users, the categorization of the posts (i.e., spoilers, collaborations, promotions), and the number of video views. The timeline of Twitter postings from official accounts will be compared to the history of pre-orders and sales figures to determine the potential impact of social media posts. This study aims to determine how the above-mentioned characteristics of official accounts' Twitter postings influence the sales of the game and to examine the possible causes of this influence. The outcome will provide researchers with a list of potential aspects that could influence people's judgments in limited-word posts. With the increased average online time, users would adapt more quickly than before in online information exchange and readings, such as the word to use sentence length, and the use of emojis or hashtags. The study on the promotion of official game accounts will not only enable publishers to create more effective promotion techniques in the future but also provide ideas for future research on the influence of social media posts with a limited number of words on consumers' purchasing decisions. Future research can focus on more specific linguistic aspects, such as precise word choice in advertising.

Keywords: engagement, official account, promotion, twitter, video game

Procedia PDF Downloads 76