Search results for: fluid collection

Authors: Lauren B. Birney

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This project focuses upon the expansion of the existing "Curriculum and Community Enterprise for the Restoration of New York Harbor in New York City Public Schools" NSF EHR DRL 1440869, NSF EHR DRL 1839656 and NSF EHR DRL 1759006. This project is recognized locally as “Curriculum and Community Enterprise for Restoration Science,” or CCERS. CCERS is a comprehensive model of ecological restoration-based STEM education for urban public-school students. Following an accelerated rollout, CCERS is now being implemented in 120+ Title 1 funded NYC Department of Education middle schools, led by two cohorts of 250 teachers, serving more than 11,000 students in total. Initial results and baseline data suggest that the CCERS model, with the Billion Oyster Project (BOP) as its local restoration ecology-based STEM curriculum, is having profound impacts on students, teachers, school leaders, and the broader community of CCERS participants and stakeholders. Students and teachers report being receptive to the CCERS model and deeply engaged in the initial phase of curriculum development, citizen science data collection, and student-centered, problem-based STEM learning. The BOP CCERS Digital Platform will serve as the central technology hub for all research, data, data analysis, resources, materials and student data to promote global interactions between communities, Research conducted included qualitative and quantitative data analysis. We continue to work internally on making edits and changes to accommodate a dynamic society. The STEM Collaboratory NYC® at Pace University New York City continues to act as the prime institution for the BOP CCERS project since the project’s inception in 2014. The project continues to strive to provide opportunities in STEM for underrepresented and underserved populations in New York City. The replicable model serves as an opportunity for other entities to create this type of collaboration within their own communities and ignite a community to come together and address the notable issue. Providing opportunities for young students to engage in community initiatives allows for a more cohesive set of stakeholders, ability for young people to network and provide additional resources for those students in need of additional support, resources and structure. The project has planted more than 47 million oysters across 12 acres and 15 reef sites, with the help of more than 8,000 students and 10,000 volunteers. Additional enhancements and features on the BOP CCERS Digital Platform will continue over the next three years through funding provided by the National Science Foundation, NSF DRL EHR 1759006/1839656 Principal Investigator Dr. Lauren Birney, Professor Pace University. Early results from the data indicate that the new version of the Platform is creating traction both nationally and internationally among community stakeholders and constituents. This project continues to focus on new collaborative partners that will support underrepresented students in STEM Education. The advanced Digital Platform will allow for us connect with other countries and networks on a larger Global scale.

Keywords: STEM education, environmental restoration science, technology, citizen science

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Authors: Ashok Kumar, Parveen Parveen

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India is bestowed with an extremely high population of plant species with medicinal value and even has two biodiversity hotspots. Indian systems of medicine including Ayurveda, Siddha and Unani have historically been serving humankind across the world since time immemorial. About 1500 plant species have well been documented in Ayurvedic Nighantus as official medicinal plants. Additionally, several hundred species of plants are being routinely used as medicines by local people especially tribes living in and around forests. The natural resources for medicinal plants have unscientifically been over-exploited forcing rapid depletion in their genetic diversity. Moreover, renewed global interest in herbal medicines may even lead to additional depletion of medicinal plant wealth of the country, as about 95% collection of medicinal plants for pharmaceutical preparation is being carried out from natural forests. On the other hand, huge export market of medicinal and aromatic plants needs to be seriously tapped for enhancing inflow of foreign currency. Asparagus racemosus Willd., a member of family Liliaceae, is one of thirty-two plant species that have been identified as priority species for cultivation and conservation by the National Medicinal Plant Board (NMPB), Government of India. Though attention is being focused on standardization of agro-techniques and extraction methods, little has been designed on genetic improvement and selection of desired types with higher root production and saponin content, a basic ingredient of medicinal value. The saponin not only improves defense mechanisms and controls diabetes but the roots of this species promote secretion of breast milk, improved lost body weight and considered as an aphrodisiac. There is ample scope for genetic improvement of this species for enhancing productivity substantially, qualitatively and quantitatively. It is emphasized to select desired genotypes with sufficient genetic diversity for important economic traits. Hybridization between two genetically divergent genotypes could result in the synthesis of new F1 hybrids consisting of useful traits of both the parents. The evaluation of twenty seed sources of Asparagus racemosus assembled different geographical locations of India revelled high degree of variability for traits of economic importance. The maximum genotypic and phenotypic variance was observed for shoot height among shoot related traits and for root length among root related traits. The shoot height, genotypic variance, phenotypic variance, genotypic coefficient of variance, the phenotypic coefficient of variance was recorded to be 231.80, 3924.80, 61.26 and 1037.32, respectively, where those of the root length were 9.55, 16.80, 23.46 and 41.27, respectively. The maximum genetic advance and genetic gain were obtained for shoot height among shoot-related traits and root length among root-related traits. Index values were developed for all seed sources based on the four most important traits, and Panthnagar (Uttrakhand), Jodhpur (Rajasthan), Dehradun (Uttarakhand), Chandigarh (Punjab), Jammu (Jammu & Kashmir) and Solan (Himachal Pradesh) were found to be promising seed sources.

Keywords: asparagus, genetic, genotypes, variance

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Authors: Sun-Hee Lee, Amanda Kraley

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The “MeToo” movement is a social movement against sexual abuse and harassment. Though the hashtag went viral in 2017 following different cultural flashpoints in different countries, the initial response was quiet in South Korea. This radically changed in January 2018, when a high-ranking senior prosecutor, Seo Ji-hyun, gave a televised interview discussing being sexually assaulted by a colleague. Acknowledging public anger, particularly among women, on the long-existing problems of sexual harassment and abuse, the South Korean media have focused on several high-profile cases. Analyzing the media representation of these cases is a window into the evolving South Korean discourse around “MeToo.” This study presents a linguistic analysis of “MeToo” discourse in South Korea by utilizing a corpus-based approach. The term corpus (pl. corpora) is used to refer to electronic language data, that is, any collection of recorded instances of spoken or written language. A “MeToo” corpus has been collected by extracting newspaper articles containing the keyword “MeToo” from BIGKinds, big data analysis, and service and Nexis Uni, an online academic database search engine, to conduct this language analysis. The corpus analysis explores how Korean media represent accusers and the accused, victims and perpetrators. The extracted data includes 5,885 articles from four broadsheet newspapers (Chosun, JoongAng, Hangyore, and Kyunghyang) and 88 articles from two Korea-based English newspapers (Korea Times and Korea Herald) between January 2017 and November 2020. The information includes basic data analysis with respect to keyword frequency and network analysis and adds refined examinations of select corpus samples through naming strategies, semantic relations, and pragmatic properties. Along with the exponential increase of the number of articles containing the keyword “MeToo” from 104 articles in 2017 to 3,546 articles in 2018, the network and keyword analysis highlights ‘US,’ ‘Harvey Weinstein’, and ‘Hollywood,’ as keywords for 2017, with articles in 2018 highlighting ‘Seo Ji-Hyun, ‘politics,’ ‘President Moon,’ ‘An Ui-Jeong, ‘Lee Yoon-taek’ (the names of perpetrators), and ‘(Korean) society.’ This outcome demonstrates the shift of media focus from international affairs to domestic cases. Another crucial finding is that word ‘defamation’ is widely distributed in the “MeToo” corpus. This relates to the South Korean legal system, in which a person who defames another by publicly alleging information detrimental to their reputation—factual or fabricated—is punishable by law (Article 307 of the Criminal Act of Korea). If the defamation occurs on the internet, it is subject to aggravated punishment under the Act on Promotion of Information and Communications Network Utilization and Information Protection. These laws, in particular, have been used against accusers who have publicly come forward in the wake of “MeToo” in South Korea, adding an extra dimension of risk. This corpus analysis of “MeToo” newspaper articles contributes to the analysis of the media representation of the “MeToo” movement and sheds light on the shifting landscape of gender relations in the public sphere in South Korea.

Keywords: corpus linguistics, MeToo, newspapers, South Korea

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Authors: Monica Arnaudo, Monika Topel, Bjorn Laumert

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Within the Swedish context, the current trend of relatively low electricity prices promotes the electrification of the energy infrastructure. The residential heating sector takes part in this transition by proposing a switch from a centralized district heating system towards a distributed heat pumps-based setting. When it comes to urban environments, two issues arise. The first, seen from an electricity-sector perspective, is related to the fact that existing networks are limited with regards to their installed capacities. Additional electric loads, such as heat pumps, can cause severe overloads on crucial network elements. The second, seen from a heating-sector perspective, has to do with the fact that the indoor comfort conditions can become difficult to handle when the operation of the heat pumps is limited by a risk of overloading on the distribution grid. Furthermore, the uncertainty of the electricity market prices in the future introduces an additional variable. This study aims at assessing the extent to which distributed heat pumps can penetrate an existing heat energy network while respecting the technical limitations of the electricity grid and the thermal comfort levels in the buildings. In order to account for the multi-disciplinary nature of this research question, a cosimulation modeling approach was adopted. In this way, each energy technology is modeled in its customized simulation environment. As part of the cosimulation methodology: a steady-state power flow analysis in pandapower was used for modeling the electrical distribution grid, a thermal balance model of a reference building was implemented in EnergyPlus to account for space heating and a fluid-cycle model of a heat pump was implemented in JModelica to account for the actual heating technology. With the models set in place, different scenarios based on forecasted electricity market prices were developed both for present and future conditions of Hammarby Sjöstad, a neighborhood located in the south-east of Stockholm (Sweden). For each scenario, the technical and the comfort conditions were assessed. Additionally, the average cost of heat generation was estimated in terms of levelized cost of heat. This indicator enables a techno-economic comparison study among the different scenarios. In order to evaluate the levelized cost of heat, a yearly performance simulation of the energy infrastructure was implemented. The scenarios related to the current electricity prices show that distributed heat pumps can replace the district heating system by covering up to 30% of the heating demand. By lowering of 2°C, the minimum accepted indoor temperature of the apartments, this level of penetration can increase up to 40%. Within the future scenarios, if the electricity prices will increase, as most likely expected within the next decade, the penetration of distributed heat pumps can be limited to 15%. In terms of levelized cost of heat, a residential heat pump technology becomes competitive only within a scenario of decreasing electricity prices. In this case, a district heating system is characterized by an average cost of heat generation 7% higher compared to a distributed heat pumps option.

Keywords: cosimulation, distributed heat pumps, district heating, electrical distribution grid, integrated energy systems

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Authors: Yu-Mei Hsueh, Wei-Jen Chen, Yung-Kai Huang, Cheng-Shiuan Tsai, Kuo-Cheng Yeh

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Prostate cancer occurs in men over the age of 50, and rank sixth of the top ten cancers in Taiwan, and the incidence increased gradually over the past decade in Taiwan. Arsenic is confirmed as a carcinogen by International Agency for Research on (IARC). Arsenic induces oxidative stress may be a risk factor for prostate cancer, but the mechanism is not clear. Selenium is an important antioxidant element. Whether the association between plasma selenium levels and risk of prostate cancer are modified by different genotype of selenoprotein is still unknown. Glutathione peroxidase, selenoprotein P (SEPP1) and 15 kDa selenoprotein (SEP 15) are selenoprotein and regulates selenium transport and the oxidation and reduction reaction. However, the association between gene polymorphisms of selenoprotein and prostate cancer is not yet clear. The aim of this study is to determine the relationship between plasma selenium, polymorphism of selenoprotein, urinary total arsenic concentration and prostate cancer. This study is a hospital-based case-control study. Three hundred twenty-two cases of prostate cancer and age (±5 years) 1:1 matched 322 control group were recruited from National Taiwan University Hospital, Taipei Medical University Hospital, and Wan Fang Hospital. Well-trained personnel carried out standardized personal interviews based on a structured questionnaire. Information collected included demographic and socioeconomic characteristics, lifestyle and disease history. Blood and urine samples were also collected at the same time. The Research Ethics Committee of National Taiwan University Hospital, Taipei, Taiwan, approved the study. All patients provided informed consent forms before sample and data collection. Buffy coat was to extract DNA, and the polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) was used to measure the genotypes of SEPP1 rs3797310, SEP15 rs5859, GPX1 rs1050450, GPX2 rs4902346, GPX3 rs4958872, and GPX4 rs2075710. Plasma concentrations of selenium were determined by inductively coupled plasma mass spectrometry (ICP-MS).Urinary arsenic species concentrations were measured by high-performance liquid chromatography links hydride generator and atomic absorption spectrometer (HPLC-HG-AAS). Subject with high education level compared to those with low educational level had a lower prostate cancer odds ratio (OR) Mainland Chinese and aboriginal people had a lower OR of prostate cancer compared to Fukien Taiwanese. After adjustment for age, educational level, subjects with GPX1 rs1050450 CT and TT genotype compared to the CC genotype have lower, OR of prostate cancer, the OR and 95% confidence interval (Cl) was 0.53 (0.31-0.90). SEPP1 rs3797310 CT+TT genotype compared to those with CC genotype had a marginally significantly lower OR of PC. The low levels of plasma selenium and the high urinary total arsenic concentrations had the high OR of prostate cancer in a significant dose-response manner, and SEPP1 rs3797310 genotype modified this joint association.

Keywords: prostate cancer, plasma selenium concentration, urinary total arsenic concentrations, glutathione peroxidase, selenoprotein P, selenoprotein 15, gene polymorphism

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Authors: Pomozova Kseniia, Gorlachev Gennadiy, Chernyaev Aleksandr, Golanov Andrey

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In clinical practice, and especially in stereotactic radiosurgery planning, the significance of diffusion-weighted imaging (DWI) is growing. This makes the existence of software capable of quickly processing and reliably visualizing diffusion data, as well as equipped with tools for their analysis in terms of different tasks. We are developing the «MRDiffusionImaging» software on the standard C++ language. The subject part has been moved to separate class libraries and can be used on various platforms. The user interface is Windows WPF (Windows Presentation Foundation), which is a technology for managing Windows applications with access to all components of the .NET 5 or .NET Framework platform ecosystem. One of the important features is the use of a declarative markup language, XAML (eXtensible Application Markup Language), with which you can conveniently create, initialize and set properties of objects with hierarchical relationships. Graphics are generated using the DirectX environment. The MRDiffusionImaging software package has been implemented for processing diffusion magnetic resonance imaging (dMRI), which allows loading and viewing images sorted by series. An algorithm for "masking" dMRI series based on T2-weighted images was developed using a deformable surface model to exclude tissues that are not related to the area of interest from the analysis. An algorithm of distortion correction using deformable image registration based on autocorrelation of local structure has been developed. Maximum voxel dimension was 1,03 ± 0,12 mm. In an elementary brain's volume, the diffusion tensor is geometrically interpreted using an ellipsoid, which is an isosurface of the probability density of a molecule's diffusion. For the first time, non-parametric intensity distributions, neighborhood correlations, and inhomogeneities are combined in one segmentation of white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) algorithm. A tool for calculating the coefficient of average diffusion and fractional anisotropy has been created, on the basis of which it is possible to build quantitative maps for solving various clinical problems. Functionality has been created that allows clustering and segmenting images to individualize the clinical volume of radiation treatment and further assess the response (Median Dice Score = 0.963 ± 0,137). White matter tracts of the brain were visualized using two algorithms: deterministic (fiber assignment by continuous tracking) and probabilistic using the Hough transform. The proposed algorithms test candidate curves in the voxel, assigning to each one a score computed from the diffusion data, and then selects the curves with the highest scores as the potential anatomical connections. White matter fibers were visualized using a Hough transform tractography algorithm. In the context of functional radiosurgery, it is possible to reduce the irradiation volume of the internal capsule receiving 12 Gy from 0,402 cc to 0,254 cc. The «MRDiffusionImaging» will improve the efficiency and accuracy of diagnostics and stereotactic radiotherapy of intracranial pathology. We develop software with integrated, intuitive support for processing, analysis, and inclusion in the process of radiotherapy planning and evaluating its results.

Keywords: diffusion-weighted imaging, medical imaging, stereotactic radiosurgery, tractography

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Authors: Sagar Saroha, Sawan S. Sinha, Sunil Lakshmipathy

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Reynolds averaged Navier-Stokes (RANS) model is the popular computational tool for prediction of turbulent flows. Being computationally less expensive as compared to direct numerical simulation (DNS), RANS has received wide acceptance in industry and research community as well. However, for high Reynolds number flows, the traditional RANS approach based on the Boussinesq hypothesis is incapacitated to capture all the essential flow characteristics, and thus, its performance is restricted in high Reynolds number flows of practical interest. RANS performance turns out to be inadequate in regimes like flow over curved surfaces, flows with rapid changes in the mean strain rate, duct flows involving secondary streamlines and three-dimensional separated flows. In the recent decade, partially averaged Navier-Stokes (PANS) methodology has gained acceptability among seamless bridging methods of turbulence- placed between DNS and RANS. PANS methodology, being a scale resolving bridging method, is inherently more suitable than RANS for simulating turbulent flows. The superior ability of PANS method has been demonstrated for some cases like swirling flows, high-speed mixing environment, and high Reynolds number turbulent flows. In our work, we intend to evaluate PANS in case of separated turbulent flows past bluff bodies -which is of broad aerodynamic research and industrial application. PANS equations, being derived from base RANS, continue to inherit the inadequacies from the parent RANS model based on linear eddy-viscosity model (LEVM) closure. To enhance PANS’ capabilities for simulating separated flows, the shortcomings of the LEVM closure need to be addressed. Inabilities of the LEVMs have inspired the development of non-linear eddy viscosity models (NLEVM). To explore the potential improvement in PANS performance, in our study we evaluate the PANS behavior in conjugation with NLEVM. Our work can be categorized into three significant steps: (i) Extraction of PANS version of NLEVM from RANS model, (ii) testing the model in the homogeneous turbulence environment and (iii) application and evaluation of the model in the canonical case of separated non-homogeneous flow field (flow past prismatic bodies and bodies of revolution at high Reynolds number). PANS version of NLEVM shall be derived and implemented in OpenFOAM -an open source solver. Homogeneous flows evaluation will comprise the study of the influence of the PANS’ filter-width control parameter on the turbulent stresses; the homogeneous analysis performed over typical velocity fields and asymptotic analysis of Reynolds stress tensor. Non-homogeneous flow case will include the study of mean integrated quantities and various instantaneous flow field features including wake structures. Performance of PANS + NLEVM shall be compared against the LEVM based PANS and LEVM based RANS. This assessment will contribute to significant improvement of the predictive ability of the computational fluid dynamics (CFD) tools in massively separated turbulent flows past bluff bodies.

Keywords: bridging methods of turbulence, high Re-CFD, non-linear PANS, separated turbulent flows

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Authors: Zylfi Shehu, Shpetim Madani, Bashkim Delia

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Context: The study focuses on the interest and engagement of high school students in Tirana, Albania, in physical activity, sports, and foreign languages. It acknowledges the numerous physiological benefits of physical activity, such as cardiovascular health and improved mood. It also recognizes the importance of physical activity in childhood and adolescence for proper skeletal development and long-term health. Research Aim: The main purpose of the study is to investigate and analyze the preferences and interests of male and female high school students in Tirana regarding their functional development, physical activity, sports participation, and choice of foreign languages. The aim is to provide insights for the students and teachers to guide future objectives and improve the quality of physical education. Methodology: The study employed a survey-based approach, targeting both male and female students in public high schools in Tirana. A total of 410 students aged 15 to 19 years old, participated in the study. The data collected from the survey were processed using Excel and presented through tables and graphs. Findings: The results revealed that team sports were more favored by the students, with football being the preferred choice among males, while basketball and volleyball were more popular among females. Additionally, English was found to be the most preferred foreign language, selected by a higher percentage of females (38.57%) compared to males (16.90%). German followed as the second preferred language. Theoretical Importance: This study contributes to the understanding of students' interests in physical activity, sports, and foreign languages in Tirana's high schools. The findings highlight the need to focus on specific sports and languages to cater to students' preferences and guide future educational objectives. It also emphasizes the importance of physical education in promoting students' overall well-being and highlights potential areas for policy and program improvement. Data Collection and Analysis Procedures: The study collected data through surveys administered to high school students in Tirana. The survey responses were processed and analyzed using Excel, and the findings were presented through tables and graphs. The data analysis allowed for the identification of preferences and trends among male and female students, providing valuable insights for future decision-making. Question Addressed: The study aimed to address the question of high school students' interest in physical activity, sports, and foreign languages. It sought to understand the preferences and choices made by students in Tirana and investigate factors such as gender, family income, and accessibility to extracurricular sports activities. Conclusion: The study revealed that high school students in Tirana show a preference for team sports, with football being the most favored among males and basketball and volleyball among females. English was found to be the most preferred foreign language. The findings provide important insights for educators and policymakers to enhance physical education programs and consider students' preferences and interests to foster a more effective learning environment. The study also emphasizes the importance of physical activity and sports in promoting students' physical and mental well-being.

Keywords: female, male, foreign languages, sports, physical education, high school students

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Authors: Zakia Fatima, Liu Lu, Donghao Li

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The analysis of biological fluid metabolites holds significant importance in various areas, such as medical research, food science, and public health. Investigating the levels and distribution of nutrients and their metabolites in biological samples allows researchers and healthcare professionals to determine nutritional status, find hypovitaminosis or hypervitaminosis, and monitor the effectiveness of interventions such as dietary supplementation. Moreover, analysis of nutrient metabolites provides insight into their metabolism, bioavailability, and physiological processes, aiding in the clarification of their health roles. Hence, the exploration of a distinct, efficient, eco-friendly, and simpler methodology is of great importance to evaluate the metabolic content of complex biological samples. In this work, a green and rapid analytical method based on an automated online two-dimensional microscale carbon fiber/activated carbon fiber fractionation system and time-of-flight mass spectrometry (2DμCFs-TOF-MS) was used to evaluate metabolites of urine samples after oral administration of food supplements. The automated 2DμCFs instrument consisted of a microcolumn system with bare carbon fibers and modified carbon fiber coatings. Carbon fibers and modified carbon fibers exhibit different surface characteristics and retain different compounds accordingly. Three kinds of mobile-phase solvents were used to elute the compounds of varied chemical heterogeneities. The 2DμCFs separation system has the ability to effectively separate different compounds based on their polarity and solubility characteristics. No complicated sample preparation method was used prior to analysis, which makes the strategy more eco-friendly, practical, and faster than traditional analysis methods. For optimum analysis results, mobile phase composition, flow rate, and sample diluent were optimized. Water-soluble vitamins, fat-soluble vitamins, and amino acids, as well as 22 vitamin metabolites and 11 vitamin metabolic pathway-related metabolites, were found in urine samples. All water-soluble vitamins except vitamin B12 and vitamin B9 were detected in urine samples. However, no fat-soluble vitamin was detected, and only one metabolite of Vitamin A was found. The comparison with a blank urine sample showed a considerable difference in metabolite content. For example, vitamin metabolites and three related metabolites were not detected in blank urine. The complete single-run screening was carried out in 5.5 minutes with the minimum consumption of toxic organic solvent (0.5 ml). The analytical method was evaluated in terms of greenness, with an analytical greenness (AGREE) score of 0.72. The method’s practicality has been investigated using the Blue Applicability Grade Index (BAGI) tool, obtaining a score of 77. The findings in this work illustrated that the 2DµCFs-TOF-MS approach could emerge as a fast, sustainable, practical, high-throughput, and promising analytical tool for screening and accurate detection of various metabolites, pharmaceuticals, and ingredients in dietary supplements as well as biological fluids.

Keywords: metabolite analysis, sustainability, carbon fibers, urine.

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Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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Authors: Luciano Tarantino

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Gas gangrene is a rare, severe infection with a very high mortality rate caused by Clostridium species. The infection causes a non-suppurative localized producing gas lesion from which harmful toxins that impair the inflammatory response cause vessel damage and multiple organ failure. Gas gangrene of the liver is very rare and develops suddenly, often as a complication of abdominal surgery and liver transplantation. The present paper deals with a case of gas gangrene of the liver that occurred after percutaneous MW ablation of hepatocellular carcinoma, resulting in progressive liver necrosis and multi-organ failure in spite of specific antibiotics administration. The patient was successfully treated with percutaneous Radiofrequency ablation. Case report: Female, 76 years old, Child A class cirrhosis, treated with synchronous insertion of 3 MW antennae for large HCC (5.5 cm) in the VIII segment. 24 hours after treatment, the patient was asymptomatic and left the hospital . 2 days later, she complained of fever, weakness, abdominal swelling, and pain. Abdominal US detected a 2.3 cm in size gas-containing area, eccentric within the large (7 cm) ablated area. The patient was promptly hospitalized with the diagnosis of anaerobic liver abscess and started antibiotic therapy with Imipenem/cilastatine+metronidazole+teicoplanine. On the fourth day, the patient was moved to the ICU because of dyspnea, congestive heart failure, atrial fibrillation, right pleural effusion, ascites, and renal failure. Blood tests demonstrated severe leukopenia and neutropenia, anemia, increased creatinine and blood nitrogen, high-level FDP, and high INR. Blood cultures were negative. At US, unenhanced CT, and CEUS, a progressive enlargement of the infected liver lesion was observed. Percutaneous drainage was attempted, but only drops of non-suppurative brownish material could be obtained. Pleural and peritoneal drainages gave serosanguineous muddy fluid. The Surgeon and the Anesthesiologist excluded any indication of surgical resection because of the high perioperative mortality risk. Therefore, we asked for the informed consent of the patient and her relatives to treat the gangrenous liver lesion by percutaneous Ablation. Under conscious sedation, percutaneous RFA of GG was performed by double insertion of 3 cool-tip needles (Covidien LDT, USA ) into the infected area. The procedure was well tolerated by the patient. A dramatic improvement in the patient's condition was observed in the subsequent 24 hours and thereafter. Fever and dyspnea disappeared. Normalization of blood tests, including creatinine, was observed within 4 days. Heart performance improved, 10 days after the RFA the patient left the hospital and was followed-up with weekly as an outpatient for 2 months and every two months thereafter. At 18 months follow-up, the patient is well compensated (Child-Pugh class B7), without any peritoneal or pleural effusion and without any HCC recurrence at imaging (US every 3 months, CT every 6 months). Percutaneous RFA could be a valuable therapy of focal GG of the liver in patients non-responder to antibiotics and when surgery and liver transplantation are not feasible. A fast and early indication is needed in case of rapid worsening of patient's conditions.

Keywords: liver tumor ablation, interventional ultrasound, liver infection, gas gangrene, radiofrequency ablation

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Authors: Irakli Javakhishvili, Tamara Tsutsunava, Giorgi Beridze

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The Caucasus is a component of the Mediterranean collision belt. The Dizi series is situated within the Greater Caucasian region of the Caucasus and crops out in the core of the Svaneti anticlinorium. The series was formed in the continental slope conditions on the southern passive margin of the small ocean basin. The Dizi series crops out on about 560 square km with the thickness 2000-2200 m. The rocks are faunally dated from the Devonian to the Triassic inclusive. The series is composed of terrigenous phyllitic schists, sandstones, quartzite aleurolites and lenses and interlayers of marbleized limestones. During the early Cimmerian orogeny, they underwent regional metamorphism of chlorite-sericite subfacies of greenschist facies. Typical minerals of metapelites are chlorite, sericite, augite, quartz, and tourmaline, but of basic rocks - actinolite, fibrolite, prehnite, calcite, and chlorite are developed. Into the Dizi series, polyphase intrusions of gabbros, diorites, quartz-diorites, syenite-diorites, syenites, and granitoids are intruded. Their K-Ar age dating (176-165Ma) points out that their formation corresponds to the Bathonian orogeny. The Dizi series is well-studied geologically, but very complicated processes of its regional and contact metamorphisms are insufficiently investigated. The aim of the authors was a detailed study of contact metamorphism processes of the series rocks. Investigations were accomplished applying the following methodologies: finding of key sections, a collection of material, microscopic study of samples, microprobe and structural analysis of minerals and X-ray determination of elements. The Dizi series rocks formed under the influence of the Bathonian magmatites on metapelites and carbonate-enriched rocks. They are represented by quartz, biotite, sericite, graphite, andalusite, muscovite, plagioclase, corundum, cordierite, clinopyroxene, hornblende, cummingtonite, actinolite, and tremolite bearing hornfels, marbles, and skarns. The contact metamorphism aureole reaches 350 meters. Biotite is developed only in contact-metamorphosed rocks and is a rather informative index mineral. In metapelites, biotite is formed as a result of the reaction between phengite, chlorite, and leucoxene, but in basites, it replaces actinolite or actinolite-hornblende. To study the compositional regularities of biotites, they were investigated from both - metapelites and metabasites. In total, biotite from the basites is characterized by an increased of titanium in contrast to biotite from metapelites. Biotites from metapelites are distinguished by an increased amount of aluminum. In biotites an increased amount of titanium and aluminum is observed as they approximate the contact, while their magnesia content decreases. Metapelite biotites are characterized by an increased amount of alumina in aluminum octahedrals, in contrast to biotite of the basites. In biotites of metapelites, the amount of tetrahedric aluminum is 28–34%, octahedral - 15–26%, and in basites tetrahedral aluminum is 28–33%, and octahedral 7–21%. As a result of the study of minerals, including biotite, from the contact-metamorphosed rocks of the Dizi series three exocontact zones with corresponding mineral assemblages were identified. It was established that contact metamorphism in the aureole of the Dizi series intrusions is going on at a significantly higher temperature and lower pressure than the regional metamorphism preceding the contact metamorphism.

Keywords: biotite, contact metamorphism, Dizi series, the Greater Caucasus

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Authors: Saul Ngarava, Leocadia Zhou, Nomakhaya Monde

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Water crises have the fourth most significant societal impact after weapons of mass destruction, climate change, and extreme weather conditions, ahead of natural disasters. Intricacies between women and water are central to achieving the 2030 Sustainable Development Goals (SDGs). The majority of the 1.2 billion poor people worldwide, with two-thirds being women, and mostly located in Sub Sahara Africa (SSA) and South Asia, do not have access to safe and reliable sources of water. There exist gendered differences in water security based on the division of labour associating women with water. Globally, women and girls are responsible for water collection in 80% of the households which have no water on their premises. Women spend 16 million hours a day collecting water, while men and children spend 6 million and 4 million per day, respectively, which is time foregone in the pursuit of other livelihood activities. Due to their proximity and activities concerning water, women are vulnerable to water insecurity through exposures to water-borne diseases, fatigue from physically carrying water, and exposure to sexual and physical harassment, amongst others. Proximity to treated water and their wellbeing also has an effect on their sensitivity and adaptive capacity to water insecurity. The great distances, difficult terrain and heavy lifting expose women to vulnerabilities of water insecurity. However, few studies have quantified the vulnerabilities and burdens on women, with a few taking a phenomenological qualitative approach. Vulnerability studies have also been scanty in the water security realm, with most studies taking linear forms of either quantifying exposures, sensitivities or adaptive capacities in climate change studies. The current study argues for the need for a water insecurity vulnerability assessment, especially for women into research agendas as well as policy interventions, monitoring, and evaluation. The study sought to identify and provide pathways through which female-headed households were water insecure in South Africa, the 30th driest country in the world. This was through linking the drinking water decision as well as the vulnerability frameworks. Secondary data collected during the 2016 General Household Survey (GHS) was utilised, with a sample of 5928 female-headed households. Principal Component Analysis and Structural Equation Modelling were used to analyse the data. The results show dynamic relationships between water characteristics and water treatment. There were also associations between water access and wealth status of the female-headed households. Association was also found between water access and water treatment as well as between wealth status and water treatment. The study concludes that there are dynamic relationships in water insecurity (exposure, sensitivity, and adaptive capacity) for female-headed households in South Africa. The study recommends that a multi-prong approach is required in tackling exposures, sensitivities, and adaptive capacities to water insecurity. This should include capacitating and empowering women for wealth generation, improve access to water treatment equipment as well as prioritising the improvement of infrastructure that brings piped and safe water to female-headed households.

Keywords: gender, principal component analysis, structural equation modelling, vulnerability, water insecurity

Procedia PDF Downloads 121

Authors: Wondale Getinet Alemu, Lillian Mwanri, Clemence Due, Telake Azale, Anna Ziersch

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Background: Mental illness is one of the most severe, chronic, and disabling public health problems that affect patients' Quality of life (QoL). Improving the QoL for people with mental illness is one of the most critical steps in stopping disease progression and avoiding complications of mental illness. Therefore, we aimed to assess the QoL and its determinants in patients with mental illness in outpatient clinics in Northwest Ethiopia in 2023. Methods: A facility-based cross-sectional study was conducted among people with mental illness in an outpatient clinic in Ethiopia. The sampling interval was decided by dividing the total number of study participants who had a follow-up appointment during the data collection period (2400) by the total sample size of 638, with the starting point selected by lottery method. The interviewer-administered WHOQOL BREF-26 tool was used to measure the QoL of people with mental illness. The domains and Health-Related Quality of Life (HRQoL) were identified. The indirect and direct effects of variables were calculated using structural equation modeling with SPSS-28 and Amos-28 software. A p-value of < 0.05 and a 95% CI were used to evaluate statistical significance. Results: A total of 636 (99.7%) participants responded and completed the WHOQOL-BREF questionnaire. The mean score of overall HRQoL of people with mental illness in the outpatient clinic was (49.6 ± 10 Sd). The highest QoL was found in the physical health domain (50.67 ±9.5 Sd), and the lowest mean QoL was found in the psychological health domain (48.41±10 Sd). Rural residents, drug nonadherence, suicidal ideation, not getting counseling, moderate or severe subjective severity, the family does not participate in patient care, and a family history of mental illness had an indirect negative effect on HRQoL. Alcohol use and psychological health domain had a direct positive effect on QoL. Furthermore, objective severity of illness, having low self-esteem, and having a history of mental illness in the family had both direct and indirect effects on QoL. Furthermore, sociodemographic factors (residence, educational status, marital status), social support-related factors (self-esteem, family not participating in patient care), substance use factors (alcohol use, tobacco use,) and clinical factors (objective and subjective severity of illness, not getting counseling, suicidal ideation, number of episodes, comorbid illness, family history of mental illness, poor drug adherence) directly and indirectly affected QoL. Conclusions: In this study, the QoL of people with mental illness was poor, with the psychological health domain being the most affected. Sociodemographic factors, social support-related factors, drug use factors, and clinical factors directly and indirectly, affect QoL through the mediator variables of physical health domains, psychological health domains, social relation health domains, and environmental health domains. In order to improve the QoL of people with mental illnesses, we recommend that emphasis be given to addressing the scourge of mental health, including the development of policy and practice drivers that address the above-identified factors.

Keywords: quality of life, mental wellbeing, mental illness, mental disorder, Ethiopia

Procedia PDF Downloads 80

Authors: Samuel McLennan, Tane Moleta, Andre Brown, Marc Aurel Schnabel

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The development of Ecclesiastical buildings within New Zealand has produced some unique design characteristics that take influence from both international styles and local building methods. What this research looks at is how procedural modelling can be used to define such common characteristics and understand how they are shared and developed within different examples of a similar architectural style. This will be achieved through the creation of procedural digital reconstructions of the various timber Gothic Churches built during the 19th century in the city of Wellington, New Zealand. ‘Procedural modelling’ is a digital modelling technique that has been growing in popularity, particularly within the game and film industry, as well as other fields such as industrial design and architecture. Such a design method entails the creation of a parametric ‘ruleset’ that can be easily adjusted to produce many variations of geometry, rather than a single geometry as is typically found in traditional CAD software. Key precedents within this area of digital heritage includes work by Haegler, Müller, and Gool, Nicholas Webb and Andre Brown, and most notably Mark Burry. What these precedents all share is how the forms of the reconstructed architecture have been generated using computational rules and an understanding of the architects’ geometric reasoning. This is also true within this research as Gothic architecture makes use of only a select range of forms (such as the pointed arch) that can be accurately replicated using the same standard geometric techniques originally used by the architect. The methodology of this research involves firstly establishing a sample group of similar buildings, documenting the existing samples, researching any lost samples to find evidence such as architectural plans, photos, and written descriptions, and then culminating all the findings into a single 3D procedural asset within the software ‘Houdini’. The end result will be an adjustable digital model that contains all the architectural components of the sample group, such as the various naves, buttresses, and windows. These components can then be selected and arranged to create visualisations of the sample group. Because timber gothic churches in New Zealand share many details between designs, the created collection of architectural components can also be used to approximate similar designs not included in the sample group, such as designs found beyond the Wellington Region. This creates an initial library of architectural components that can be further expanded on to encapsulate as wide of a sample size as desired. Such a methodology greatly improves upon the efficiency and adjustability of digital modelling compared to current practices found in digital heritage reconstruction. It also gives greater accuracy to speculative design, as a lack of evidence for lost structures can be approximated using components from still existing or better-documented examples. This research will also bring attention to the cultural significance these types of buildings have within the local area, addressing the public’s general unawareness of architectural history that is identified in the Wellington based research ‘Moving Images in Digital Heritage’ by Serdar Aydin et al.

Keywords: digital forensics, digital heritage, gothic architecture, Houdini, procedural modelling

Procedia PDF Downloads 131

Authors: Zi Y. Kang, Tracy D. Cassidy, Tom Cassidy

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3D apparel CAD is one of the remarkable products in advanced technology which enables intuitive design, visualisation and evaluation of garments through stereoscopic drape simulation. The progressive improvements of 3D apparel CAD have led to the creation of more realistic clothing simulation which is used not only in design development but also in presentation, promotion and communication for fashion as well as other industries such as film, game and social network services. As a result, 3D clothing technology is becoming more ubiquitous in human culture and lives today. This study considers that such phenomenon implies that the technology has reached maturity and it is time to inspect the status of current technology and to explore its potential uses in ways to create cultural values to further move forward. For this reason, this study aims to generate virtual costumes as culturally significant objects using 3D apparel CAD and to assess its capability, applicability and attitudes of the audience towards clothing simulation through comparison with physical counterparts. Since the access to costume collection is often limited due to the conservative issues, the technology may make valuable contribution by democratization of culture and knowledge for museums and its audience. This study is expected to provide foundation knowledge for development of clothing technology and for expanding its boundary of practical uses. To prevent any potential damage, two replicas of the costumes in the 1860s and 1920s at the Museum of London were chosen as samples. Their structural, visual and physical characteristics were measured and collected using patterns, scanned images of fabrics and objective fabric measurements with scale, KES-F (Kawabata Evaluation System of Fabrics) and Titan. Commercial software, DC Suite 5.0 was utilised to create virtual costumes applying collected data and the following outcomes were produced for the evaluation: Images of virtual costumes and video clips showing static and dynamic simulation. Focus groups were arranged with fashion design students and the public for evaluation which exposed the outcomes together with physical samples, fabrics swatches and photographs. The similarities, application and acceptance of virtual costumes were estimated through discussion and a questionnaire. The findings show that the technology has the capability to produce realistic or plausible simulation but expression of some factors such as details and capability of light material requires improvements. While the use of virtual costumes was viewed as more interesting and futuristic replacements to physical objects by the public group, the fashion student group noted more differences in detail and preferred physical garments highlighting the absence of tangibility. However, the advantages and potential of virtual costumes as effective and useful visual references for educational and exhibitory purposes were underlined by both groups. Although 3D apparel CAD has sufficient capacity to assist garment design process, it has limits in identical replication and more study on accurate reproduction of details and drape is needed for its technical improvements. Nevertheless, the virtual costumes in this study demonstrated the possibility of the technology to contribute to cultural and knowledgeable value creation through its applicability and as an interesting way to offer 3D visual information.

Keywords: digital clothing technology, garment simulation, 3D Apparel CAD, virtual costume

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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

Procedia PDF Downloads 125

Authors: Beverly Redman

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With the Theatre Season of 2020-2021 cancelled due to COVID-19 at Purdue University, Fort Wayne, IN, USA, faculty directors found themselves scrambling to create theatre production opportunities for their students in the Department of Theatre. Redman, Chair of the Department, found her community to be suffering from anxieties brought on by a confluence of issues: the global-scale Covid-19 Pandemic, the United States’ Black Lives Matter protests erupting in cities all across the country and the coming Presidential election, arguably the most important and most contentious in the country’s history. Redman wanted to give her students the opportunity to speak not only on these issues but also to be able to record who they were at this time in their personal lives, as well as in this broad socio-political context. She also wanted to invite them into an experience of feeling empathy, too, at a time when empathy in this world seems to be sorely lacking. Returning to a mode of Devising Theatre she had used with community groups in the past, in which storytelling and re-enactment of participants’ life events combined with oral history documentation practices, Redman planned The Shared Breath Project. The process involved three months of workshops, in which participants alternated between theatre exercises and oral history collection and documentation activities as a way of generating original material for a theatre production. The goal of the first half of the project was for each participant to produce a solo piece in the form of a monologue after many generations of potential material born out of gammes, improvisations, interviews and the like. Along the way, many film and audio clips recorded the process of each person’s written documentation—documentation prepared by the subject him or herself but also by others in the group assigned to listen, watch and record. Then, in the second half of the project—and only once each participant had taken their own contributions from raw improvisatory self-presentations and through the stages of composition and performative polish, participants then exchanged their pieces. The second half of the project involved taking on each other’s words, mannerisms, gestures, melodic and rhythmic speech patterns and inhabiting them through the rehearsal process as their own, thus the title, The Shared Breath Project. Here, in stage two the acting challenges evolved to be those of capturing the other and becoming the other through accurate mimicry that embraces Denis Diderot’s concept of the Paradox of Acting, in that the actor is both seeming and being simultaneous. This paper shares the carefully documented process of making the live-streamed theatre production that resulted from these workshops, writing processes and rehearsals, and forming, The Shared Breath Project, which ultimately took the students’ Realist, life-based pieces and edited them into a single unified theatre production. The paper also utilizes research on the Paradox of Acting, putting a Post-Structuralist spin on Diderot’s theory. Here, the paper suggests the limitations of inhabiting the other by allowing that the other is always already a thing impenetrable but nevertheless worthy of unceasing empathetic, striving and delving in an epoch in which slow, careful attention to our fellows is in short supply.

Keywords: otherness, paradox of acting, oral history theatre, devised theatre, political theatre, community-based theatre, peoples’ theatre

Procedia PDF Downloads 184

Authors: Ajay Kumar Pandey, Mayank Kumar

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White grub (Coleoptera: Scarabaeidae) is a major destructive pest in western Himalayan region of Uttarakhand. Beetles feed on apple, apricot, plum, walnut etc. during night while, second and third instar grubs feed on live roots of cultivated as well as non-cultivated crops. Collection and identification of scarab beetles through light trap was carried out at Crop Research Centre, Govind Ballab Pant University Pantnagar, Udham Singh Nagar (Uttarakhand) during 2018. Field trials were also conducted in 2018 to evaluate pre and post sown application of different insecticides against the white grub infesting soybean. The insecticides like Carbofuran 3 Granule (G) (750 g a.i./ha), Clothianidin 50 Water Dispersal Granule (WG) (120 g a.i./ha), Fipronil 0.3 G (50 g a.i./ha), Thiamethoxam 25 WG (80 g a.i./ha), Imidacloprid 70 WG (300 g a.i./ha), Chlorantraniliprole 0.4% G(100 g a.i./ha) and mixture of Fipronil 40% and Imidacloprid 40% WG (300 g a.i./ha) were applied at the time of sowing in pre sown experiment while same dosage of insecticides were applied in standing soybean crop during (first fortnight of July). Commutative plant mortality data were recorded after 20, 40, 60 days intervals and compared with untreated control. Total 23 species of white grub beetles recorded on the light trap and Holotrichia serrata Fabricious (Coleoptera: Melolonthinae) was found to be predominant species by recording 20.6% relative abundance out of the total light trap catch (i.e. 1316 beetles) followed by Phyllognathus sp. (14.6% relative abundance). H. rosettae and Heteronychus lioderus occupied third and fourth rank with 11.85% and 9.65% relative abundance, respectively. The emergence of beetles of predominant species started from 15th March, 2018. In April, average light trap catch was 382 white grub beetles, however, peak emergence of most of the white grub species was observed from June to July, 2018 i.e. 336 beetles in June followed by 303 beetles in the July. On the basis of the emergence pattern of white grub beetles, it may be concluded that the Peak Emergence Period (PEP) for the beetles of H. serrata was second fortnight of April for the total period of 15 days. In May, June and July relatively low population of H. serrata was observed. A decreasing trend in light trap catch was observed and went on till September during the study. No single beetle of H. serrata was observed on light trap from September onwards. The cumulative plant mortality data in both the experiments revealed that all the insecticidal treatments were significantly superior in protection-wise (6.49-16.82% cumulative plant mortality) over untreated control where highest plant mortality was 17.28 to 39.65% during study. The mixture of Fipronil 40% and Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective having lowest plant mortality i.e. 9.29 and 10.94% in pre and post sown crop, followed by Clothianidin 50 WG (120 g a.i. per ha) where the plant mortality was 10.57 and 11.93% in pre and post sown treatments, respectively. Both treatments were found significantly at par among each other. Production-wise, all the insecticidal treatments were found statistically superior (15.00-24.66 q per ha grain yields) over untreated control where the grain yield was 8.25 & 9.13 q per ha. Treatment Fipronil 40% + Imidacloprid 40% WG applied at the rate of 300 g a.i. per ha proved to be most effective and significantly superior over Imidacloprid 70WG applied at the rate of 300 g a.i. per ha.

Keywords: bio efficacy, insecticide, soybean, white grub

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Authors: Babak Forouraghi

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A genetic circuit is a collection of interacting genes and proteins that enable individual cells to implement and perform vital biological functions such as cell division, growth, death, and signaling. In cell engineering, synthetic gene circuits are engineered networks of genes specifically designed to implement functionalities that are not evolved by nature. These engineered networks enable scientists to tackle complex problems such as engineering cells to produce therapeutics within the patient's body, altering T cells to target cancer-related antigens for treatment, improving antibody production using engineered cells, tissue engineering, and production of genetically modified plants and livestock. Construction of computational models to realize genetic circuits is an especially challenging task since it requires the discovery of flow of genetic information in complex biological systems. Building synthetic biological models is also a time-consuming process with relatively low prediction accuracy for highly complex genetic circuits. The primary goal of this study was to investigate the utility of a pre-trained bidirectional encoder transformer that can accurately predict gene expressions in genetic circuit designs. The main reason behind using transformers is their innate ability (attention mechanism) to take account of the semantic context present in long DNA chains that are heavily dependent on spatial representation of their constituent genes. Previous approaches to gene circuit design, such as CNN and RNN architectures, are unable to capture semantic dependencies in long contexts as required in most real-world applications of synthetic biology. For instance, RNN models (LSTM, GRU), although able to learn long-term dependencies, greatly suffer from vanishing gradient and low-efficiency problem when they sequentially process past states and compresses contextual information into a bottleneck with long input sequences. In other words, these architectures are not equipped with the necessary attention mechanisms to follow a long chain of genes with thousands of tokens. To address the above-mentioned limitations of previous approaches, a transformer model was built in this work as a variation to the existing DNA Bidirectional Encoder Representations from Transformers (DNABERT) model. It is shown that the proposed transformer is capable of capturing contextual information from long input sequences with attention mechanism. In a previous work on genetic circuit design, the traditional approaches to classification and regression, such as Random Forrest, Support Vector Machine, and Artificial Neural Networks, were able to achieve reasonably high R2 accuracy levels of 0.95 to 0.97. However, the transformer model utilized in this work with its attention-based mechanism, was able to achieve a perfect accuracy level of 100%. Further, it is demonstrated that the efficiency of the transformer-based gene expression classifier is not dependent on presence of large amounts of training examples, which may be difficult to compile in many real-world gene circuit designs.

Keywords: transformers, generative ai, gene expression design, classification

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Authors: Sevelina Ndlovu

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Financial Technology (fintech) advancement is recognised as one of the most transformational innovations in the financial industry. Fintech has given rise to internet-only digital banking, a novel financial technology advancement, and innovation that allows banking services through internet applications with no need for physical branches. This technology is becoming a new banking normal among consumers for its ubiquitous and real-time access advantages. There is evident switching and migration from traditional banking towards these fintech facilities, which could possibly pose a systemic risk if not properly understood and monitored. Fintech advancement has also brought about the emergence and escalation of financial technology consumption themes such as trust, security, perceived risk, and sustainability within the banking industry, themes scarcely covered in existing theoretic literature. To that end, the objective of this research is to investigate factors that determine fintech adoption and propose an integrated adoption model. This study aims to establish what the significant drivers of adoption are and develop a conceptual model that integrates technological, behavioral, and environmental constructs by extending the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). It proposes integrating constructs that influence financial consumption themes such as trust, perceived risk, security, financial incentives, micro-investing opportunities, and environmental consciousness to determine the impact of these factors on the adoption and intention to use digital banking apps. The main advantage of this conceptual model is the consolidation of a greater number of predictor variables that can provide a fuller explanation of the consumer's adoption of digital banking Apps. Moderating variables of age, gender, and income are incorporated. To the best of author’s knowledge, this study is the first that extends the UTAUT2 model with this combination of constructs to investigate user’s intention to adopt internet-only digital banking apps in the UK context. By investigating factors that are not included in the existing theories but are highly pertinent to the adoption of internet-only banking services, this research adds to existing knowledge and extends the generalisability of the UTAUT2 in a financial services adoption context. This is something that fills a gap in knowledge, as highlighted to needing further research on UTAUT2 after reviewing the theory in 2016 from its original version of 2003. To achieve the objectives of this study, this research assumes a quantitative research approach to empirically test the hypotheses derived from existing literature and pilot studies to give statistical support to generalise the research findings for further possible applications in theory and practice. This research is explanatory or casual in nature and uses cross-section primary data collected through a survey method. Convenient and purposive sampling using structured self-administered online questionnaires is used for data collection. The proposed model is tested using Structural Equation Modelling (SEM), and the analysis of primary data collected through an online survey is processed using Smart PLS software with a sample size of 386 digital bank users. The results are expected to establish if there are significant relationships between the dependent and independent variables and establish what the most influencing factors are.

Keywords: banking applications, digital banking, financial technology, technology adoption, UTAUT2

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Authors: V. Jayanthi

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Urbanization and pace of urbanization have increased tremendously in last few decades. More towns are now getting converted into cities. Urbanization trend is seen all over the world but is becoming most dominant in Asia. Today, the scale of urbanization in India is so huge that Indian cities are among the fastest-growing in the world, including Bangalore, Hyderabad, Pune, Chennai, Delhi, and Mumbai. Urbanization remains a single predominant factor that is continuously linked to the destruction of urban green spaces. With reference to Chennai as a case study, which is suffering from rapid deterioration of its green spaces, this paper sought to fill this gap by exploring key factors aside urbanization that is responsible for the destruction of green spaces. The paper relied on a research approach and triangulated data collection techniques such as interviews, focus group discussion, personal observation and retrieval of archival data. It was observed that apart from urbanization, problem of ownership of green space lands, low priority to green spaces, poor maintenance, enforcement of development controls, wastage of underpass spaces, and uncooperative attitudes of the general public, play a critical role in the destruction of urban green spaces. Therefore the paper narrows down to a point, that for a city to have a proper sustainable urban green space, broader city development plans are essential. Though rapid urbanization is an indicator of positive development, it is also accompanied by a host of challenges. Chennai lost a lot of greenery, as the city urbanized rapidly that led to a steep fall in vegetation cover. Environmental deterioration will be the big price we pay if Chennai continues to grow at the expense of greenery. Soaring skyscrapers, multistoried complexes, gated communities, and villas, frame the iconic skyline of today’s Chennai city which reveals that we overlook the importance of our green cover, which is important to balance our urban and lung spaces. Chennai, with a clumped landscape at the center of the city, is predicted to convert 36% of its total area into urban areas by 2026. One major issue is that a city designed and planned in isolation creates underused spaces all around the cities which are of negligence. These urban voids are dead, underused, unused spaces in the cities that are formed due to inefficient decision making, poor land management, and poor coordination. Urban voids have huge potential of creating a stronger urban fabric, exploited as public gathering spaces, pocket parks or plazas or just enhance public realm, rather than dumping of debris and encroachments. Flyovers need to justify their existence themselves by being more than just traffic and transport solutions. The vast, unused space below the Kathipara flyover is a case in point. This flyover connects three major routes: Tambaram, Koyambedu, and Adyar. This research will focus on the concept of urban voids, how these voids under the flyovers, can be used for place making process, how this space beneath flyovers which are neglected, can be a part of the urban realm through urban design and landscaping.

Keywords: landscape design, flyovers, public spaces, reclaiming lost spaces, urban voids

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Authors: Pedro Llanos, Diego García

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Spaceflight is considered the last frontier in terms of science, technology, and engineering. But it is also the next frontier in terms of human physiology and performance. After more than 200,000 years humans have evolved under earth’s gravity and atmospheric conditions, spaceflight poses environmental stresses for which human physiology is not adapted. Hypoxia, accelerations, and radiation are among such stressors, our research involves suborbital flights aiming to develop effective countermeasures in order to assure sustainable human space presence. The physiologic baseline of spaceflight participants is subject to great variability driven by age, gender, fitness, and metabolic reserve. The objective of the present study is to characterize different physiologic variables in a population of STEM practitioners during an aerobatic flight. Cardiovascular and pulmonary responses were determined in Science Astronaut Candidates (SACs) during unusual attitude aerobatic flight indoctrination. Physiologic data recordings from 20 subjects participating in high-G flight training were analyzed. These recordings were registered by wearable sensor-vest that monitored electrocardiographic tracings (ECGs), signs of dysrhythmias or other electric disturbances during all the flight. The same cardiovascular parameters were also collected approximately 10 min pre-flight, during each high-G/unusual attitude maneuver and 10 min after the flights. The ratio (pre-flight/in-flight/post-flight) of the cardiovascular responses was calculated for comparison of inter-individual differences. The resulting tracings depicting the cardiovascular responses of the subjects were compared against the G-loads (Gs) during the aerobatic flights to analyze cardiovascular variability aspects and fluid/pressure shifts due to the high Gs. In-flight ECG revealed cardiac variability patterns associated with rapid Gs onset in terms of reduced heart rate (HR) and some scattered dysrhythmic patterns (15% premature ventricular contractions-type) that were considered as triggered physiological responses to high-G/unusual attitude training and some were considered as instrument artifact. Variation events were observed in subjects during the +Gz and –Gz maneuvers and these may be due to preload and afterload, sudden shift. Our data reveal that aerobatic flight influenced the breathing rate of the subject, due in part by the various levels of energy expenditure due to the increased use of muscle work during these aerobatic maneuvers. Noteworthy was the high heterogeneity in the different physiological responses among a relatively small group of SACs exposed to similar aerobatic flights with similar Gs exposures. The cardiovascular responses clearly demonstrated that SACs were subjected to significant flight stress. Routine ECG monitoring during high-G/unusual attitude flight training is recommended to capture pathology underlying dangerous dysrhythmias in suborbital flight safety. More research is currently being conducted to further facilitate the development of robust medical screening, medical risk assessment approaches, and suborbital flight training in the context of the evolving commercial human suborbital spaceflight industry. A more mature and integrative medical assessment method is required to understand the physiology state and response variability among highly diverse populations of prospective suborbital flight participants.

Keywords: g force, aerobatic maneuvers, suborbital flight, hypoxia, commercial astronauts

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Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

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Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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Authors: Giulia Fredi, Andrea Dorigato, Luca Fambri, Alessandro Pegoretti

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Thermal energy storage (TES) is the storage of heat for later use, thus filling the gap between energy request and supply. The most widely used materials for TES are the organic solid-liquid phase change materials (PCMs), such as paraffin. These materials store/release a high amount of latent heat thanks to their high specific melting enthalpy, operate in a narrow temperature range and have a tunable working temperature. However, they suffer from a low thermal conductivity and need to be confined to prevent leakage. These two issues can be tackled by confining PCMs with carbon nanotubes (CNTs). TES applications include the buildings industry, solar thermal energy collection and thermal management of electronics. In most cases, TES systems are an additional component to be added to the main structure, but if weight and volume savings are key issues, it would be advantageous to embed the TES functionality directly in the structure. Such multifunctional materials could be employed in the automotive industry, where the diffusion of lightweight structures could complicate the thermal management of the cockpit environment or of other temperature sensitive components. This work aims to produce epoxy/carbon structural laminates containing CNT-stabilized paraffin. CNTs were added to molten paraffin in a fraction of 10 wt%, as this was the minimum amount at which no leakage was detected above the melting temperature (45°C). The paraffin/CNT blend was cryogenically milled to obtain particles with an average size of 50 µm. They were added in various percentages (20, 30 and 40 wt%) to an epoxy/hardener formulation, which was used as a matrix to produce laminates through a wet layup technique, by stacking five plies of a plain carbon fiber fabric. The samples were characterized microstructurally, thermally and mechanically. Differential scanning calorimetry (DSC) tests showed that the paraffin kept its ability to melt and crystallize also in the laminates, and the melting enthalpy was almost proportional to the paraffin weight fraction. These thermal properties were retained after fifty heating/cooling cycles. Laser flash analysis showed that the thermal conductivity through the thickness increased with an increase of the PCM, due to the presence of CNTs. The ability of the developed laminates to contribute to the thermal management was also assessed by monitoring their cooling rates through a thermal camera. Three-point bending tests showed that the flexural modulus was only slightly impaired by the presence of the paraffin/CNT particles, while a more sensible decrease of the stress and strain at break and the interlaminar shear strength was detected. Optical and scanning electron microscope images revealed that these could be attributed to the preferential location of the PCM in the interlaminar region. These results demonstrated the feasibility of multifunctional structural TES composites and highlighted that the PCM size and distribution affect the mechanical properties. In this perspective, this group is working on the encapsulation of paraffin in a sol-gel derived organosilica shell. Submicron spheres have been produced, and the current activity focuses on the optimization of the synthesis parameters to increase the emulsion efficiency.

Keywords: carbon fibers, carbon nanotubes, lightweight materials, multifunctional composites, thermal energy storage

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Authors: Negar Vkilbashi, Hassan Kabiri

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Modern diplomacy, in its general form, refers to the people and not the governments, and diplomacy tactics are more addressed to the people than to the governments. Media diplomacy and cyber diplomacy are also one of the sub-branches of public diplomacy and, in fact, the role of media in the process of influencing public opinion and directing foreign policy. Mass media, including written, radio and television, theater, satellite, internet, and news agencies, transmit information and demands. What the Qatari government tried to implement in the countries of the region during the Arab Spring and after was through its important media, Al Jazeera. The embargo on Qatar began in 2017, when Saudi Arabia, the United Arab Emirates, Bahrain, and Egypt imposed a land, sea, and air blockade against the country. The media tool constitutes the cornerstone of soft power in the field of foreign policy, which Qatari leaders have consistently resorted to over the past two decades. Undoubtedly, the role it played in covering the events of the Arab Spring has created geopolitical tensions. The United Arab Emirates and other neighboring countries sometimes criticize Al Jazeera for providing a platform for the Muslim Brotherhood, Hamas, and other Islamists to promote their ideology. In 2011, at the same time as the Arab Spring, Al Jazeera reached the peak of its popularity. Al Jazeera's live coverage of protests in Tunisia, Egypt, Yemen, Libya, and Syria helped create a unified narrative of the Arab Spring, with audiences tuning in every Friday to watch simultaneous protests across the Middle East. Al Jazeera operates in three groups: First, it is a powerful base in the hands of the government so that it can direct and influence Arab public opinion. Therefore, this network has been able to benefit from the unlimited financial support of the Qatar government to promote its desired policies and culture. Second, it has provided an attractive platform for politicians and scientific and intellectual elites, thus attracting their support and defense from the government and its rulers. Third, during the last years of Prince Hamad's reign, the Al Jazeera network formed a deterrent weapon to counter the media and political struggle campaigns. The importance of the research is that this network covers a wide range of people in the Middle East and, therefore, has a high influence on the decision-making of countries. On the other hand, Al Jazeera is influential as a tool of public diplomacy and soft power in Qatar's foreign policy, and by studying it, the results of its effectiveness in the past years can be examined. Using a qualitative method, this research analyzes the impact of the media on the implementation of Qatar's foreign policy on the public opinion of the people of the Middle East. Data collection has been done by the secondary method, that is, reading related books, magazine articles, newspaper reports and articles, and analytical reports of think tanks. The most important findings of the research are that Al Jazeera plays an important role in Qatar's foreign policy in Qatar's public diplomacy. So that, in 2011, 2017 and 2023, it played an important role in Qatar's foreign policy in various crises. Also, the people of Arab countries use Al-Jazeera as their first reference.

Keywords: Al Jazeera, Qatar, media, diplomacy

Procedia PDF Downloads 78

Authors: Rachana Tank, Donald. M. Lyall, Kristin Flegal, Joey Ward, Jonathan Cavanagh

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Alzheimer’s research UK estimates by 2050, 2 million individuals will be living with Late Onset Alzheimer’s disease (LOAD). However, individuals experience considerable cognitive deficits and brain pathology over decades before reaching clinically diagnosable LOAD and studies have utilised gene candidate studies such as genome wide association studies (GWAS) and polygenic risk (PGR) scores to identify high risk individuals and potential pathways. This investigation aims to determine whether high genetic risk of LOAD is associated with worse brain MRI and cognitive performance in healthy older adults within the UK Biobank cohort. Previous studies investigating associations of PGR for LOAD and measures of MRI or cognitive functioning have focused on specific aspects of hippocampal structure, in relatively small sample sizes and with poor ‘controlling’ for confounders such as smoking. Both the sample size of this study and the discovery GWAS sample are bigger than previous studies to our knowledge. Genetic interaction between loci showing largest effects in GWAS have not been extensively studied and it is known that APOE e4 poses the largest genetic risk of LOAD with potential gene-gene and gene-environment interactions of e4, for this reason we  also analyse genetic interactions of PGR with the APOE e4 genotype. High genetic loading based on a polygenic risk score of 21 SNPs for LOAD is associated with worse brain MRI and cognitive outcomes in healthy individuals within the UK Biobank cohort. Summary statistics from Kunkle et al., GWAS meta-analyses (case: n=30,344, control: n=52,427) will be used to create polygenic risk scores based on 21 SNPs and analyses will be carried out in N=37,000 participants in the UK Biobank. This will be the largest study to date investigating PGR of LOAD in relation to MRI. MRI outcome measures include WM tracts, structural volumes. Cognitive function measures include reaction time, pairs matching, trail making, digit symbol substitution and prospective memory. Interaction of the APOE e4 alleles and PGR will be analysed by including APOE status as an interaction term coded as either 0, 1 or 2 e4 alleles. Models will be adjusted partially for adjusted for age, BMI, sex, genotyping chip, smoking, depression and social deprivation. Preliminary results suggest PGR score for LOAD is associated with decreased hippocampal volumes including hippocampal body (standardised beta = -0.04, P = 0.022) and tail (standardised beta = -0.037, P = 0.030), but not with hippocampal head. There were also associations of genetic risk with decreased cognitive performance including fluid intelligence (standardised beta = -0.08, P<0.01) and reaction time (standardised beta = 2.04, P<0.01). No genetic interactions were found between APOE e4 dose and PGR score for MRI or cognitive measures. The generalisability of these results is limited by selection bias within the UK Biobank as participants are less likely to be obese, smoke, be socioeconomically deprived and have fewer self-reported health conditions when compared to the general population. Lack of a unified approach or standardised method for calculating genetic risk scores may also be a limitation of these analyses. Further discussion and results are pending.

Keywords: Alzheimer's dementia, cognition, polygenic risk, MRI

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Authors: Mukondi Esther Nethavhakone

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In 2020 World Health Organization announced the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as Coronavirus disease 2019 (COVID-19) pandemic. To curb or contain the spread of the novel coronavirus (COVID 19), global governments implemented social distancing and lockdown regulations. Subsequently, it was no longer business as per usual, life as we knew it had changed, and so many aspects of people's lives were negatively affected, including financial and employment stability. Mainly, because companies/businesses had to put their operations on hold, some had to shut down completely, resulting in the loss of income for many people globally. Finances and employment insecurities are some of the issues that exacerbated many social issues that the world was already faced with, such as school drop-outs, teenage pregnancies, sexual assaults, gender-based violence, crime, child abuse, elderly abuse, to name a few. Expectedly the majority of the population's mental health state was threatened. This resulted in an increased number of people seeking mental healthcare services. The increasing need for mental healthcare services in Low and Middle-income countries proves to be a challenge because it is a well-known fact due to financial constraints and not well-established healthcare systems, mental healthcare provision is not as prioritised as the primary healthcare in these countries. It is against this backdrop that the researcher seeks to find viable, cost-effective, and accessible mental health solutions for low and middle-income countries amid the pressures of any pandemic. The researcher will undertake a systematic review of the technology-based mental health solutions that have been implemented/adopted by developed countries during COVID 19 lockdown and social distancing periods. This systematic review study aims to determine if low and middle-income countries can adopt the cost-effective version of digital mental health solutions for the healthcare system to adequately provide mental healthcare services during critical times such as pandemics (when there's an overwhelming diminish in mental health globally). The researcher will undertake a systematic review study through mixed methods. It will adhere to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The mixed-methods uses findings from both qualitative and quantitative studies in one review study. It will be beneficial to conduct this kind of study using mixed methods because it is a public health topic that involves social interventions and it is not purely based on medical interventions. Therefore, the meta-ethnographic (qualitative data) analysis will be crucial in understanding why and which digital methods work and for whom does it work, rather than only the meta-analysis (quantitative data) providing what digital mental health methods works. The data collection process will be extensive, involving the development of a database, table of summary of evidence/findings, and quality assessment process lastly, The researcher will ensure that ethical procedures are followed and adhered to, ensuring that sensitive data is protected and the study doesn't pose any harm to the participants.

Keywords: digital, mental health, covid, low and middle-income countries

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Authors: Man Ying Kang, Joshua Kin Man Nan

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The prolonged pandemic has posed alarming public health challenges to various parts of the world, and face-to-face mental health treatment is largely discounted for the control of virus transmission, online psychological services and self-help mental health kits have become essential. Online self-help mindfulness-based interventions have proved their effects on fostering mental health for different populations over the globe. This paper was to test the effectiveness of an online short-term audio-based mindfulness (SAM) program in enhancing wellbeing, dispositional mindfulness, and reducing stress and negative affect in community settings in China, and to explore possible mechanisms of how dispositional mindfulness, stress, and negative affect influenced the intervention effects on wellbeing. Community-dwelling adults were recruited via online social networking sites (e.g., QQ, WeChat, and Weibo). Participants (n=100) were randomized into the mindfulness group (n=50) and a waitlist control group (n=50). In the mindfulness group, participants were advised to spend 10–20 minutes listening to the audio content, including mindful-form practices (e.g., eating, sitting, walking, or breathing). Then practice daily mindfulness exercises for 3 weeks (a total of 21 sessions), whereas those in the control group received the same intervention after data collection in the mindfulness group. Participants in the mindfulness group needed to fill in the World Health Organization Five Well-Being Index (WHO), Positive and Negative Affect Schedule (PANAS), Perceived Stress Scale (PSS), and Freiburg Mindfulness Inventory (FMI) four times: at baseline (T0) and at 1 (T1), 2 (T2), and 3 (T3) weeks while those in the waitlist control group only needed to fill in the same scales at pre- and post-interventions. Repeated-measure analysis of variance, paired sample t-test, and independent sample t-test was used to analyze the variable outcomes of the two groups. The parallel process latent growth curve modeling analysis was used to explore the longitudinal moderated mediation effects. The dependent variable was WHO slope from T0 to T3, the independent variable was Group (1=SAM, 2=Control), the mediator was FMI slope from T0 to T3, and the moderator was T0NA and T0PSS separately. The different levels of moderator effects on WHO slope was explored, including low T0NA or T0PSS (Mean-SD), medium T0NA or T0PSS (Mean), and high T0NA or T0PSS (Mean+SD). The results found that SAM significantly improved and predicted higher levels of WHO slope and FMI slope, as well as significantly reduced NA and PSS. FMI slope positively predict WHO slope. FMI slope partially mediated the relationship between SAM and WHO slope. Baseline NA and PSS as the moderators were found to be significant between SAM and WHO slope and between SAM and FMI slope, respectively. The conclusion was that SAM was effective in promoting levels of mental wellbeing, positive affect, and dispositional mindfulness as well as reducing negative affect and stress in community settings in China. SAM improved wellbeing faster through the faster enhancement of dispositional mindfulness. Participants with medium-to-high negative affect and stress buffered the therapy effects of SAM on wellbeing improvement speed.

Keywords: mindfulness, negative affect, stress, wellbeing, randomized control trial

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Authors: Mingqian Zhang

Abstract:

Tip-enhanced Raman spectroscopy (TERS) is a scanning probe technique for individual objects and structured surfaces investigation that provides a wealth of enhanced spectral information with nanoscale spatial resolution and high detection sensitivity. It has become a powerful and promising chemical and physical information detection method in the nanometer scale. The TERS technique uses a sharp metallic tip regulated in the near-field of a sample surface, which is illuminated with a certain incident beam meeting the excitation conditions of the wave-vector matching. The local electric field, and, consequently, the Raman scattering, from the sample in the vicinity of the tip apex are both greatly tip-enhanced owning to the excitation of localized surface plasmons and the lightning-rod effect. Typically, a TERS setup is composed of a scanning probe microscope, excitation and collection optical configurations, and a Raman spectroscope. In the illumination configuration, an objective lens or a parabolic mirror is always used as the most important component, in order to focus the incident beam on the tip apex for excitation. In this research, a novel TERS setup was built up by introducing a plasmonic lens to the excitation optics as a focusing device. A plasmonic lens with symmetry breaking semi-annular slits corrugated on gold film was designed for the purpose of generating concentrated sub-wavelength light spots with strong longitudinal electric field. Compared to conventional far-field optical components, the designed plasmonic lens not only focuses an incident beam to a sub-wavelength light spot, but also realizes a strong z-component that dominants the electric field illumination, which is ideal for the excitation of tip-enhancement. Therefore, using a PL in the illumination configuration of TERS contributes to improve the detection sensitivity by both reducing the far-field background and effectively exciting the localized electric field enhancement. The FDTD method was employed to investigate the optical near-field distribution resulting from the light-nanostructure interaction. And the optical field distribution was characterized using an scattering-type scanning near-field optical microscope to demonstrate the focusing performance of the lens. The experimental result is in agreement with the theoretically calculated one. It verifies the focusing performance of the plasmonic lens. The optical field distribution shows a bright elliptic spot in the lens center and several arc-like side-lobes on both sides. After the focusing performance was experimentally verified, the designed plasmonic lens was used as a focusing component in the excitation configuration of TERS setup to concentrate incident energy and generate a longitudinal optical field. A collimated linearly polarized laser beam, with along x-axis polarization, was incident from the bottom glass side on the plasmonic lens. The incident light focused by the plasmonic lens interacted with the silver-coated tip apex and enhanced the Raman signal of the sample locally. The scattered Raman signal was gathered by a parabolic mirror and detected with a Raman spectroscopy. Then, the plasmonic lens based setup was employed to investigate carbon nanotubes and TERS experiment was performed. Experimental results indicate that the Raman signal is considerably enhanced which proves that the novel TERS configuration is feasible and promising.

Keywords: longitudinal electric field, plasmonics, raman spectroscopy, tip-enhancement

Procedia PDF Downloads 373