Search results for: natural language grammar models

Authors: Kirsten Techmer, Jan-Erik Rybak, Simon Rudolph

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Natural formed pyrites (FeS2) are frequent sulfides in sedimentary and metamorphic rocks. Growth textures of idiomorphic pyrite assemblages reflect the conditions during their formation in the geologic sequence, furtheron the local texture analyses of the growth patterns of pyrite assemblages by EBSD reveal the possibility to resolve the growth conditions during the formation of pyrite at the micron scale. The spatial resolution of local texture measurements in the Scanning Electron Microscope used can be in the nanomete scale. Orientation contrasts resulting from domains of smaller misorientations within larger pyrite crystals can be resolved as well. The electron optical studies have been carried out in a Field-Emission Scanning Electron Microscope (FEI Quanta 200) equipped with a CCD camera to study the orientation contrasts along the surfaces of pyrite. Idiomorphic cubic single crystals of pyrite, polycrystalline assemblages of pyrite, spherically grown spheres of pyrite as well as pyrite-bearing ammonites have been studied by EBSD in the Scanning Electron Microscope. Samples were chosen to show no or minor secondary deformation and an idiomorphic 3D crystal habit, so the local textures of pyrite result mainly from growth and minor from deformation. The samples studied derived from Navajun (Spain), Chalchidiki (Greece), Thüringen (Germany) and Unterkliem (Austria). Chemical analyses by EDAX show pyrite with minor inhomogeneities e.g., single crystals of galena and chalcopyrite along the grain boundaries of larger pyrite crystals. Intergrowth between marcasite and pyrite can be detected in one sample. Pyrite may form intense growth twinning lamellae on {011}. Twinning, e.g., contact twinning is abundant within the crystals studied and the individual twinning lamellaes can be resolved by EBSD. The ammonites studied show a replacement of the shale by newly formed pyrite resulting in an intense intergrowth of calcite and pyrite. EBSD measurements indicate a polycrystalline microfabric of both minerals, still reflecting primary surface structures of the ammonites e.g, the Septen. Discs of pyrite (“pyrite dollar”) as well as pyrite framboids show growth patterns comprising a typical microfabric. EBSD studies reveal an equigranular matrix in the inner part of the discs of pyrite and a fiber growth with larger misorientations in the outer regions between the individual segments. This typical microfabric derived from a formation of pyrite crystals starting at a higher nucleation rate and followed by directional crystal growth. EBSD studies show, that the growth texture of pyrite in the samples studied reveals a correlation between nucleation rate and following growth rate of the pyrites, thus leading to the characteristic crystal habits. Preferential directional growth at lower nucleation rates may lead to the formation of 3D framboids of pyrite. Crystallographic misorientations between the individual fibers are similar. In ammonites studied, primary anisotropies of the substrates like e.g., ammonitic sutures, influence the nucleation, crystal growth and habit of the newly formed pyrites along the surfaces.

Keywords: Electron Back Scatter Diffraction (EBSD), growth pattern, Fe-sulfides (pyrite), texture analyses

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Authors: Аndrey Marchenko, Oleg Linkov, Alexander Osetrov, Sergiy Kravchenko

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The low-calorie of gases include biogas, coal gas, coke oven gas, associated petroleum gas, gases sewage, etc. These gases are usually released into the atmosphere or burned on flares, causing substantial damage to the environment. However, with the right approach, low-calorie gas fuel can become a valuable source of energy. Specified determines the relevance of areas related to the development of low-calorific gas utilization technologies. As an example, in the work considered one of way of utilization of coalmine gas, because Ukraine ranks fourth in the world in terms of coal mine gas emission (4.7% of total global emissions, or 1.2 billion m³ per year). Experts estimate that coal mine gas is actively released in the 70-80 percent of existing mines in Ukraine. The main component of coal mine gas is methane (25-60%) Methane in 21 times has a greater impact on the greenhouse effect than carbon dioxide disposal problem has become increasingly important in the context of the increasing need to address the problems of climate, ecology and environmental protection. So marked causes negative effect of both local and global nature. The efforts of the United Nations and the World Bank led to the adoption of the program 'Zero Routine Flaring by 2030' dedicated to the cessation of these gases burn in flares and disposing them with the ability to generate heat and electricity. This study proposes to use coal gas as a fuel for gas engines to generate heat and electricity. Analyzed the physical-chemical properties of low-calorie gas fuels were allowed to choose a suitable engine, as well as estimate the influence of the composition of the fuel at its techno-economic indicators. Most suitable for low-calorie gas is engine with pre-combustion chamber jet ignition. In Ukraine is accumulated extensive experience in exploitation and production of gas engines with capacity of 1100 kW type GD100 (10GDN 207/2 * 254) fueled by natural gas. By using system pre- combustion chamber jet ignition and quality control in the engines type GD100 introduces the concept of burning depleted burn fuel mixtures, which in turn leads to decrease in the concentration of harmful substances of exhaust gases. The main problems of coal mine gas as a fuel for ICE is low calorific value, the presence of components that adversely affect combustion processes and terms of operation of the ICE, the instability of the composition, weak ignition. In some cases, these problems can be solved by adaptation engine design using coal mine gas as fuel (changing compression ratio, fuel injection quantity increases, change ignition time, increase energy plugs, etc.). It is shown that the use of coal mine gas engines with prechamber has not led to significant changes in the indicator parameters (ηi = 0.43 - 0.45). However, this significantly increases the volumetric fuel consumption, which requires increased fuel injection quantity to ensure constant nominal engine power. Thus, the utilization of low-calorie gas fuels in stationary gas engine type-based GD100 will significantly reduce emissions of harmful substances into the atmosphere when the generate cheap electricity and heat.

Keywords: gas engine, low-calorie gas, methane, pre-combustion chamber, utilization

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Authors: Ruolan Zhang, Ryo Imai, Naoko Senda, Tomoyuki Sakai

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Enzymes have attracted increasing attentions in industrial manufacturing for their applicability in catalyzing complex chemical reactions under mild conditions. Directed evolution has become a powerful approach to optimize enzymes and exploit their full potentials under the circumstance of insufficient structure-function knowledge. With the incorporation of cell-free synthetic biotechnology, rapid enzyme synthesis can be realized because no cloning procedure such as transfection is needed. Its open environment also enables direct enzyme measurement. These properties of cell-free biotechnology lead to excellent throughput of enzymes generation. However, the capabilities of current screening methods have limitations. Fluorescence-based assay needs applicable fluorescent label, and the reliability of acquired enzymatic activity is influenced by fluorescent label’s binding affinity and photostability. To acquire the natural activity of an enzyme, another method is to combine pre-screening step and high-performance liquid chromatography (HPLC) measurement. But its throughput is limited by necessary time investment. Hundreds of variants are selected from libraries, and their enzymatic activities are then identified one by one by HPLC. The turn-around-time is 30 minutes for one sample by HPLC, which limits the acquirable enzyme improvement within reasonable time. To achieve the real high-throughput enzyme screening, i.e., obtain reliable enzyme improvement within reasonable time, a widely applicable high-throughput measurement of enzymatic reactions is highly demanded. Here, a high-throughput screening method using broadband coherent anti-Stokes Raman spectroscopy (CARS) was proposed. CARS is one of coherent Raman spectroscopy, which can identify label-free chemical components specifically from their inherent molecular vibration. These characteristic vibrational signals are generated from different vibrational modes of chemical bonds. With the broadband CARS, chemicals in one sample can be identified from their signals in one broadband CARS spectrum. Moreover, it can magnify the signal levels to several orders of magnitude greater than spontaneous Raman systems, and therefore has the potential to evaluate chemical's concentration rapidly. As a demonstration of screening with CARS, alcohol dehydrogenase, which converts ethanol and nicotinamide adenine dinucleotide oxidized form (NAD+) to acetaldehyde and nicotinamide adenine dinucleotide reduced form (NADH), was used. The signal of NADH at 1660 cm⁻¹, which is generated from nicotinamide in NADH, was utilized to measure the concentration of it. The evaluation time for CARS signal of NADH was determined to be as short as 0.33 seconds while having a system sensitivity of 2.5 mM. The time course of alcohol dehydrogenase reaction was successfully measured from increasing signal intensity of NADH. This measurement result of CARS was consistent with the result of a conventional method, UV-Vis. CARS is expected to have application in high-throughput enzyme screening and realize more reliable enzyme improvement within reasonable time.

Keywords: Coherent Anti-Stokes Raman Spectroscopy, CARS, directed evolution, enzyme screening, Raman spectroscopy

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Authors: Alessandra Swiny, Yiorgos Hadjichristou

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There exists an on-going geographical scar creating a division through the Island of Cyprus and its capital, Nicosia. The currently amputated city center is accessed legally by the United Nations convoys, infiltrated only by Turkish and Greek Cypriot army scouts and illegal traders and scavengers. On Christmas day 1963 in Nicosia, Captain M. Hobden of the British Army took a green chinagraph pencil and on a large scale Joint Army-RAF map ‘marked’ the division. From then on this ‘buffer zone’ was called the ‘green line.' This once dividing form, separating the main communities of Greek and Turkish Cypriots from one another, has now been fully reclaimed by an autonomous intruder. It's currently most captivating inhabitant is nature. She keeps taking over, for the past fifty years indigenous and introduced fauna and flora thrive; trees emerge from rooftops and plants, bushes and flowers grow randomly through the once bustling market streets, allowing this ‘no man’s land’ to teem with wildlife. And where are its limits? The idea of fluidity is ever present; it encroaches into the urban and built environment that surrounds it, and notions of ownership and permanence are questioned. Its qualities have contributed significantly in the search for new ‘identities,' expressed in the emergence of new living conditions, be they real or surreal. Without being physically reachable, it can be glimpsed at through punctured peepholes, military bunker windows that act as enticing portals into an emotional and conceptual level of inhabitation. The zone is mystical and simultaneously suspended in time, it triggers people’s imagination, not just that of the two prevailing communities but also of immigrants, refugees, and visitors; it mesmerizes all who come within its proximity. The paper opens a discussion on the issues and the binary questions raised. What is natural and artificial; what is private and public; what is ephemeral and permanent? The ‘green line’ exists in a central fringe condition and can serve in mixing generations and groups of people; mingling functions of living with work and social interaction; merging nature and the human being in a new-found synergy of human hope and survival, allowing thus for new notions of place to be introduced. Questions seek to be answered, such as, “Is the impossibility of dwelling made possible, by interweaving these ‘in-between conditions’ into eloquently traced spaces?” The methodologies pursued are developed through academic research, professional practice projects, and students’ research/design work. Realized projects, case studies and other examples cited both nationally and internationally hold global and local applications. Both paths of the research deal with the explorative understanding of the impossibility of dwelling, testing the limits of its autonomy. The expected outcome of the experience evokes in the user a sense of a new urban landscape, created from human topographies that echo the voice of an emerging identity.

Keywords: urban wildlife, human topographies, buffer zone, no man’s land

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Authors: Joy Tweed, Jon Pike

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In Thailand, a 4.0 policy has been initiated that is designed to prepare and train an appropriate workforce to support the move to a value-based economy. One aspect of support for this policy is a project to encourage the creation of double degree programmes, specifically between Thai and UK universities. This research into the project, conducted with its key players, explores the factors that can either enable or hinder the development of such programmes. It is an area that has received little research attention to date. Key findings focus on differences in quality assurance requirements, attitudes to benefits, risks, and committed levels of institutional support, thus providing valuable input into future policy making. The Transnational Education (TNE) Development Project was initiated in 2015 by the British Council, in conjunction with the Office for Higher Education Commission (OHEC), Thailand. The purpose of the project was to facilitate opportunities for Thai Universities to partner with UK Universities so as to develop double degree programme models. In this arrangement, the student gains both a UK and a Thai qualification, spending time studying in both countries. Twenty-two partnerships were initiated via the project. Utilizing a qualitative approach, data sources included participation in TNE project workshops, peer reviews, and over 20 semi-structured interviews conducted with key informants within the participating UK and Thai universities. Interviews were recorded, transcribed, and analysed for key themes. The research has revealed that the strength of the relationship between the two partner institutions is critical. Successful partnerships are often built on previous personal contact, have senior-level involvement and are strengthened by partnership on different levels, such as research, student exchange, and other forms of mobility. The support of the British Council was regarded as a key enabler in developing these types of projects for those universities that had not been involved in TNE previously. The involvement of industry is apparent in programmes that have high scientific content but not well developed in other subject areas. Factors that hinder the development of partnership programmes include the approval processes and quality requirements of each institution. Significant differences in fee levels between Thai and UK universities provide a challenge and attempts to bridge them require goodwill on the part of the latter that may be difficult to realise. This research indicates the key factors to which attention needs to be given when developing a TNE programme. Early attention to these factors can reduce the likelihood that the partnership will fail to develop. Representatives in both partner universities need to understand their respective processes of development and approval. The research has important practical implications for policy-makers and planners involved with TNE, not only in relation to the specific TNE project but also more widely in relation to the development of TNE programmes in other countries and other subject areas. Future research will focus on assessing the success of the double degree programmes generated by the TNE Development Project from the perspective of universities, policy makers, and industry partners.

Keywords: double-degree, internationalization, partnerships, Thai-UK

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Authors: Ali Kazemi

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The digital evolution of financial services, while offering unprecedented convenience and accessibility, has also escalated the vulnerabilities to fraudulent activities. In this study, we introduce a distinct approach to real-time anomaly detection in financial transactions, aiming to fortify the defenses of banking and financial institutions against such threats. Utilizing unsupervised machine learning algorithms, specifically autoencoders and isolation forests, our research focuses on identifying irregular patterns indicative of fraud within transactional data, thus enabling immediate action to prevent financial loss. The data we used in this study included the monetary value of each transaction. This is a crucial feature as fraudulent transactions may have distributions of different amounts than legitimate ones, such as timestamps indicating when transactions occurred. Analyzing transactions' temporal patterns can reveal anomalies (e.g., unusual activity in the middle of the night). Also, the sector or category of the merchant where the transaction occurred, such as retail, groceries, online services, etc. Specific categories may be more prone to fraud. Moreover, the type of payment used (e.g., credit, debit, online payment systems). Different payment methods have varying risk levels associated with fraud. This dataset, anonymized to ensure privacy, reflects a wide array of transactions typical of a global banking institution, ranging from small-scale retail purchases to large wire transfers, embodying the diverse nature of potentially fraudulent activities. By engineering features that capture the essence of transactions, including normalized amounts and encoded categorical variables, we tailor our data to enhance model sensitivity to anomalies. The autoencoder model leverages its reconstruction error mechanism to flag transactions that deviate significantly from the learned normal pattern, while the isolation forest identifies anomalies based on their susceptibility to isolation from the dataset's majority. Our experimental results, validated through techniques such as k-fold cross-validation, are evaluated using precision, recall, and the F1 score alongside the area under the receiver operating characteristic (ROC) curve. Our models achieved an F1 score of 0.85 and a ROC AUC of 0.93, indicating high accuracy in detecting fraudulent transactions without excessive false positives. This study contributes to the academic discourse on financial fraud detection and provides a practical framework for banking institutions seeking to implement real-time anomaly detection systems. By demonstrating the effectiveness of unsupervised learning techniques in a real-world context, our research offers a pathway to significantly reduce the incidence of financial fraud, thereby enhancing the security and trustworthiness of digital financial services.

Keywords: anomaly detection, financial fraud, machine learning, autoencoders, isolation forest, transactional data analysis

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Authors: Nicholas Aerne, John P. Parmigiani

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There is an increasing desire for renewable and sustainable energy sources to replace fossil fuels. This desire is the result of several factors. First, is the role of fossil fuels in climate change. Scientific data clearly shows that global warming is occurring. It has also been concluded that it is highly likely human activity; specifically, the combustion of fossil fuels, is a major cause of this warming. Second, despite the current surplus of petroleum, fossil fuels are a finite resource and will eventually become scarce and alternatives, such as clean or renewable energy will be needed. Third, operations to obtain fossil fuels such as fracking, off-shore oil drilling, and strip mining are expensive and harmful to the environment. Given these environmental impacts, there is a need to replace fossil fuels with renewable energy sources as a primary energy source. Various sources of renewable energy exist. Many familiar sources obtain renewable energy from the sun and natural environments of the earth. Common examples include solar, hydropower, geothermal heat, ocean waves and tides, and wind energy. Often obtaining significant energy from these sources requires physically-large, sophisticated, and expensive equipment (e.g., wind turbines, dams, solar panels, etc.). Other sources of renewable energy are from the man-made environment. An example is municipal water distribution systems. The movement of water through the pipelines of these systems typically requires the reduction of hydraulic pressure through the use of pressure reducing valves. These valves are needed to reduce upstream supply-line pressures to levels suitable downstream users. The energy associated with this reduction of pressure is significant but is currently not harvested and is simply lost. While the integrity of municipal water supplies is of paramount importance, one can certainly envision means by which this lost energy source could be safely accessed. This paper provides a technical description and analysis of one such means by the technology company InPipe Energy to generate hydroelectricity by harvesting energy from municipal water distribution pressure reducing valve stations. Specifically, InPipe Energy proposes to install hydropower turbines in parallel with existing pressure reducing valves in municipal water distribution systems. InPipe Energy in partnership with Oregon State University has evaluated this approach and built a prototype system at the O. H. Hinsdale Wave Research Lab. The Oregon State University evaluation showed that the prototype system rapidly and safely initiates, maintains, and ceases power production as directed. The outgoing water pressure remained constant at the specified set point throughout all testing. The system replicates the functionality of the pressure reducing valve and ensures accurate control of down-stream pressure. At a typical water-distribution-system pressure drop of 60 psi the prototype, operating at an efficiency 64%, produced approximately 5 kW of electricity. Based on the results of this study, this proposed method appears to offer a viable means of producing significant amounts of clean renewable energy from existing pressure reducing valves.

Keywords: pressure reducing valve, renewable energy, sustainable energy, water supply

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Authors: Matthias Leitner, Gernot Pottlacher

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Experimental determination of critical point data like critical temperature, critical pressure, critical volume and critical compressibility of high-melting metals such as niobium is very rare due to the outstanding experimental difficulties in reaching the necessary extreme temperature and pressure regimes. Experimental techniques to achieve such extreme conditions could be diamond anvil devices, two stage gas guns or metal samples hit by explosively accelerated flyers. Electrical pulse-heating under increased pressures would be another choice. This technique heats thin wire samples of 0.5 mm diameter and 40 mm length from room temperature to melting and then further to the end of the stable phase, the spinodal line, within several microseconds. When crossing the spinodal line, the sample explodes and reaches the gaseous phase. In our laboratory, pulse-heating experiments can be performed under variation of the ambient pressure from 1 to 5000 bar and allow a direct determination of critical point data for low-melting, but not for high-melting metals. However, the critical point also can be estimated by extrapolating the liquid phase density according to theoretical models. A reasonable prerequisite for the extrapolation is the existence of data that cover as much as possible of the liquid phase and at the same time exhibit small uncertainties. Ohmic pulse-heating was therefore applied to determine thermal volume expansion, and from that density of niobium over the entire liquid phase. As a first step, experiments under ambient pressure were performed. The second step will be to perform experiments under high-pressure conditions. During the heating process, shadow images of the expanding sample wire were captured at a frame rate of 4 × 105 fps to monitor the radial expansion as a function of time. Simultaneously, the sample radiance was measured with a pyrometer operating at a mean effective wavelength of 652 nm. To increase the accuracy of temperature deduction, spectral emittance in the liquid phase is also taken into account. Due to the high heating rates of about 2 × 108 K/s, longitudinal expansion of the wire is inhibited which implies an increased radial expansion. As a consequence, measuring the temperature dependent radial expansion is sufficient to deduce density as a function of temperature. This is accomplished by evaluating the full widths at half maximum of the cup-shaped intensity profiles that are calculated from each shadow image of the expanding wire. Relating these diameters to the diameter obtained before the pulse-heating start, the temperature dependent volume expansion is calculated. With the help of the known room-temperature density, volume expansion is then converted into density data. The so-obtained liquid density behavior is compared to existing literature data and provides another independent source of experimental data. In this work, the newly determined off-critical liquid phase density was in a second step utilized as input data for the estimation of niobium’s critical point. The approach used, heuristically takes into account the crossover from mean field to Ising behavior, as well as the non-linearity of the phase diagram’s diameter.

Keywords: critical point data, density, liquid metals, niobium, ohmic pulse-heating, volume expansion

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Authors: Azhar Naila, Steuer Benjamin

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Over-exploitation of resources and the burden on natural systems have provoked worldwide concerns about the potential resource as well as supply risks in the future. It has been estimated that the consumption of materials and resources will double by 2060, substantially mounting the amount of waste and emissions produced by individuals, organizations, and businesses, which necessitates sustainable technological innovations to address the problem. Therefore, there is a need to design products and services purposefully for material resource efficiency. This directs us toward the conceptualization and implementation of the ‘Circular Economy (CE),’ which has gained considerable attention among policymakers, researchers, and businesses in the past decade. A large amount of literature focuses on the concept of CE. However, contextual empirical research on the need to embrace CE in an emerging economy like Pakistan is still scarce, where the traditional economic model of take-make-dispose is quite common. Textile exports account for approximately 61% of Pakistan's total exports, and the industry provides employment for about 40% of the country's total industrial workforce. The industry provides job opportunities to above 10 million farmers, with cotton as the main crop of Pakistan. Consumers, companies, as well as the government have explored very limited CE potential in the country. This gap has motivated us to carry out the present study. The study is based on a mixed method approach, for which key informant interviews have been conducted to get insight into the present situation of the ecosystem readiness for the adoption of CE in 20 textile manufacturing industries. The subject study has been conducted on the following areas i) the level of understanding of the CE concept among key stakeholders in the textile manufacturing industry ii) Companies are pushing boundaries to invest in circularity-based initiatives, exploring the depths of risk-taking iii) the current national policy framework support the adoption of CE. Qualitative assessment has been undertaken using MAXQDA to analyze the data received after the key informant interviews. The data has been transcribed and coded for further analysis. The results show that most of the key stakeholders have a clear understanding of the concept, whereas few consider it to be only relevant to the end-of-life treatment of waste generated from the industry. Non-governmental organizations have been observed to be key players in creating awareness among the manufacturing industries. Maximum companies have shown their consent to invest in initiatives related to the adoption of CE. Whereas a few consider themselves far behind the race due to a lack of financial resources and support from responsible institutions. Mostly, the industries have an ambitious vision for integrating CE into the company’s policy but seem not to be ready to take any significant steps to nurture a culture for experimentation. However, the government is not playing any vital role in the transition towards CE; rather, they have been busy with the state’s uncertain political situation. Presently, Pakistan does not have any policy framework that supports the transition towards CE. Acknowledging the present landscape a well-informed CE transition is immediately required.

Keywords: circular economy, textile supply chain, textile manufacturing industries, resource efficiency, ecosystem readiness, multi-case study analysis

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Authors: Tran Tran

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Mental health issues are prevalent among Vietnamese undergraduate students, and they are greatly exacerbated during the COVID-19 pandemic for this population. While there is empirical evidence supporting the effectiveness and efficiency of therapy on mental health issues among college students, the rates of Vietnamese college students seeking professional mental health services were alarmingly low. Multiple factors can prevent those in need from finding support. The Internalized Stigma Model posits that public stigma directly affects intentions to seek psychological help via self-stigma and attitudes toward seeking help. However, little research has focused on what factors can predict public stigma toward seeking professional psychological support, especially among this population. A potential predictor is academic majors since academic majors can influence undergraduate students' perceptions, attitudes, and intentions. A study suggested that students who have completed two or more psychology courses have a more positive attitude toward seeking care for mental health issues and reduced stigma, which might be attributed to increased mental health literacy. In addition, research has shown that women are more likely to utilize mental health services and have lower stigma than men. Finally, studies have also suggested that experience of mental health services can increase endorsement of perceived need and lower stigma. Thus, it is expected that perceived helpfulness from past service uses can reduce stigma. This study aims to address this gap in the literature and investigate which factors can predict public stigma, specifically academic major, gender, and perceived helpfulness, potentially suggesting an avenue of prevention and ultimately improving the well-being of Vietnamese college students. The sample includes 408 undergraduate students (Mage = 20.44; 80.88% female) Hanoi city, Vietnam. Participants completed a pen-and-paper questionnaire. Students completed the Stigma Scale for Receiving Psychological Help, which yielded a mean public stigma score. Participants also completed a measurement assessing their perceived helpfulness of their university’s counseling center, which included eight subscales: future self-development, learning issues, career counseling, medical and health issues, mental health issues, conflicts between teachers and students, conflicts between parents and students, and interpersonal relationships. Items were summed to create a composite perceived helpfulness score. Finally, participants provided demographic information. This included gender, which was dichotomized between female and other. Additionally, it included academic major, which was also similarly dichotomized between psychology and other (e.g., natural science, social science, and pedagogy & social work). Linear relationships between public stigma and gender, academic major, and perceived helpfulness were analyzed individually with a regression model. Findings suggested that academic major, gender, and perceived counseling center's helpfulness predicted stigma against seeking professional psychological help. Specifically, being a psychology major predicted lower levels of public stigma (β = -.25, p < .001). Additionally, gender female predicted lower levels of public stigma (β = -.11, p < .05). Lastly, higher levels of perceived helpfulness of the counseling center also predicted lower levels of public stigma (β = -.16, p < .01). The study’s results offer potential intervention avenues to help reduce stigma and increase well-being for Vietnamese college students.

Keywords: stigma, vietnamese college students, counseling services, help-seeking

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Authors: Eman AbdelSabour

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Sustainability is increasingly being considered as a critical aspect in shaping the urban environment. It works as an invention development basis for global urban growth. Currently, different models and structures impact the means of interpreting the criteria that would be included in defining a sustainable city. There is a collective need to improve the growth path to an extremely durable path by presenting different suggestions regarding multi-scale initiatives. The global rise in urbanization has led to increased demand and pressure for better urban planning choice and scenarios for a better sustainable urban alternative. The need for an assessment tool at the urban scale was prompted due to the trend of developing increasingly sustainable urban development (SUD). The neighborhood scale is being managed by a growing research committee since it seems to be a pertinent scale through which economic, environmental, and social impacts could be addressed. Although neighborhood design is a comparatively old practice, it is in the initial years of the 21st century when environmentalists and planners started developing sustainable assessment at the neighborhood level. Through this, urban reality can be considered at a larger scale whereby themes which are beyond the size of a single building can be addressed, while it still stays small enough that concrete measures could be analyzed. The neighborhood assessment tool has a crucial role in helping neighborhood sustainability to perform approach and fulfill objectives through a set of themes and criteria. These devices are also known as neighborhood assessment tool, district assessment tool, and sustainable community rating tool. The primary focus of research has been on sustainability from the economic and environmental aspect, whereas the social, cultural issue is rarely focused. Therefore, this research is based on Doha, Qatar, the current urban conditions of the neighborhoods is discussed in this study. The research problem focuses on the spatial features in relation to the socio-cultural aspects. This study is outlined in three parts; the first section comprises of review of the latest use of wellbeing assessment methods to enhance decision process of retrofitting physical features of the neighborhood. The second section discusses the urban settlement development, regulations and the process of decision-making rule. An analysis of urban development policy with reference to neighborhood development is also discussed in this section. Moreover, it includes a historical review of the urban growth of the neighborhoods as an atom of the city system present in Doha. Last part involves developing quantified indicators regarding subjective well-being through a participatory approach. Additionally, applying GIS will be utilized as a visualizing tool for the apparent Quality of Life (QoL) that need to develop in the neighborhood area as an assessment approach. Envisaging the present QoL situation in Doha neighborhoods is a process to improve current condition neighborhood function involves many days to day activities of the residents, due to which areas are considered dynamic.

Keywords: neighborhood, subjective wellbeing, decision support tools, Doha, retrofiring

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Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

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Authors: Jyoti Sahu, Vinay A. Juvekar

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Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

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Authors: Evonne Kaplan-Liss, Val Lantz-Gefroh

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Arts and humanities are often incorporated into medical education to help deepen understanding of the human condition and the ability to communicate from a place of compassion. However, a gap remains in our knowledge of compassionate communication training for postgraduate medical professionals (as opposed to students and residents); how training opportunities include and impact the artists themselves, and how train-the-trainer models can support learners to become teachers. In this report, the authors present results from a pilot evaluation of the UC San Diego Health: Sanford Compassionate Communication Fellowship, a 60-hour experiential program that uses theater, narrative reflection, poetry, literature, and journalism techniques to train a multidisciplinary cohort of medical professionals and artists in compassionate communication. In the culminating project, fellows design and implement their own projects as teachers of compassionate communication in their respective workplaces. Qualitative methods, including field notes and 30-minute Zoom interviews with each fellow, were used to evaluate the impact of the fellowship. The cohort included both artists (n=2) and physicians representing a range of specialties (n=7), such as occupational medicine, palliative care, and pediatrics. The authors coded the data using thematic analysis for evidence of how the multidisciplinary nature of the fellowship impacted the fellows’ experiences. The findings show that the multidisciplinary cohort contributed to a greater appreciation of compassionate communication in general. Fellows expressed that the ability to witness how those in different fields approached compassionate communication enhanced their learning and helped them see how compassion can be expressed in various contexts, which was both “exhilarating” and “humbling.” One physician expressed that the fellowship has been “really helpful to broaden my perspective on the value of good communication.” Fellows shared how what they learned in the fellowship translated to increased compassionate communication, not only in their professional roles but in their personal lives as well. A second finding was the development of a supportive community. Because each fellow brought their own experiences and expertise, there was a sense of genuine ability to contribute as well as a desire to learn from others. A “brave space” was created by the fellowship facilitators and the inclusion of arts-based activities: a space that invited vulnerability and welcomed fellows to make their own meaning without prescribing any one answer or right way to approach compassionate communication. This brave space contributed to a strong connection among the fellows and reports of increased well-being, as well as multiple collaborations post-fellowship to carry forward compassionate communication training at their places of work. Results show initial evidence of the value of a multidisciplinary fellowship for promoting compassionate communication for both artists and physicians. The next steps include maintaining the supportive fellowship community and collaborations with a post-fellowship affiliate faculty program; scaling up the fellowship with non-physicians (e.g., nurses and physician assistants); and collecting data from family members, colleagues, and patients to understand how the fellowship may be creating a ripple effect outside of the fellowship through fellows’ compassionate communication.

Keywords: compassionate communication, communication in healthcare, multidisciplinary learning, arts in medicine

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Authors: Binder Hans

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Cancer is no longer seen as solely a genetic disease where genetic defects such as mutations and copy number variations affect gene regulation and eventually lead to aberrant cell functioning which can be monitored by transcriptome analysis. It has become obvious that epigenetic alterations represent a further important layer of (de-)regulation of gene activity. For example, aberrant DNA methylation is a hallmark of many cancer types, and methylation patterns were successfully used to subtype cancer heterogeneity. Hence, unraveling the interplay between different omics levels such as genome, transcriptome and epigenome is inevitable for a mechanistic understanding of molecular deregulation causing complex diseases such as cancer. This objective requires powerful downstream integrative bioinformatics methods as an essential prerequisite to discover the whole genome mutational, transcriptome and epigenome landscapes of cancer specimen and to discover cancer genesis, progression and heterogeneity. Basic challenges and tasks arise ‘beyond sequencing’ because of the big size of the data, their complexity, the need to search for hidden structures in the data, for knowledge mining to discover biological function and also systems biology conceptual models to deduce developmental interrelations between different cancer states. These tasks are tightly related to cancer biology as an (epi-)genetic disease giving rise to aberrant genomic regulation under micro-environmental control and clonal evolution which leads to heterogeneous cellular states. Machine learning algorithms such as self organizing maps (SOM) represent one interesting option to tackle these bioinformatics tasks. The SOMmethod enables recognizing complex patterns in large-scale data generated by highthroughput omics technologies. It portrays molecular phenotypes by generating individualized, easy to interpret images of the data landscape in combination with comprehensive analysis options. Our image-based, reductionist machine learning methods provide one interesting perspective how to deal with massive data in the discovery of complex diseases, gliomas, melanomas and colon cancer on molecular level. As an important new challenge, we address the combined portrayal of different omics data such as genome-wide genomic, transcriptomic and methylomic ones. The integrative-omics portrayal approach is based on the joint training of the data and it provides separate personalized data portraits for each patient and data type which can be analyzed by visual inspection as one option. The new method enables an integrative genome-wide view on the omics data types and the underlying regulatory modes. It is applied to high and low-grade gliomas and to melanomas where it disentangles transversal and longitudinal molecular heterogeneity in terms of distinct molecular subtypes and progression paths with prognostic impact.

Keywords: integrative bioinformatics, machine learning, molecular mechanisms of cancer, gliomas and melanomas

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Authors: Claudio Di Benedetto, Irene Bengo

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The objective of the paper is to study how large European companies develop social business (SB) at the base of the economic pyramid (BoP). BoP markets are defined as the four billions people living with an annual income below $3,260 in local purchasing power. Despite they are heterogeneous in terms of geographic range they present some common characteristics: the presence of significant unmet (social) needs, high level of informal economy and the so-called ‘poverty penalty’. As a result, most people living at BoP are excluded from the value created by the global market economy. But it is worth noting, that BoP population with an aggregate purchasing power of around $5 trillion a year, represent a huge opportunity for companies that want to enhance their long-term profitability perspective. We suggest that in this context, the development of SB is, for companies, an innovative and promising way to satisfy unmet social needs and to experience new forms of value creation. Indeed, SB can be considered a strategic model to develop CSR programs that fully integrate the social dimension into the business to create economic and social value simultaneously. Despite in literature many studies have been conducted on social business, only few have explicitly analyzed such phenomenon from a company perspective and their role in the development of such initiatives remains understudied with fragmented results. To fill this gap the paper analyzes the key characteristics of the social business initiatives developed by European companies at BoP. The study was performed analyzing 1475 European companies participating in the United Nation Global Compact, the world’s leading corporate social responsibility program. Through the analysis of the corporate websites the study identifies companies that actually do SB at BoP. For SB initiatives identified, information were collected according to a framework adapted from the SB model developed by preliminary results show that more than one hundred European companies have already implemented social businesses at BoP accounting for the 6,5% of the total. This percentage increases to 15% if the focus is on companies with more than 10.440 employees. In terms of geographic distribution 80% of companies doing SB at BoP are located in western and southern Europe. The companies more active in promoting SB belong to financial sector (20%), energy sector (17%) and food and beverage sector (12%). In terms of social needs addressed almost 30% of the companies develop SB to provide access to energy and WASH, 25% of companies develop SB to reduce local unemployment or to promote local entrepreneurship and 21% of companies develop SB to promote financial inclusion of poor. In developing SB companies implement different social business configurations ranging from forms of outsourcing to internal development models. The study identifies seven main configurations through which company develops social business and each configuration present distinguishing characteristics respect to the involvement of the company in the management, the resources provided and the benefits achieved. By performing different analysis on data collected the paper provides detailed insights on how European companies develop SB at BoP.

Keywords: base of the economic pyramid, corporate social responsibility, social business, social enterprise

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Authors: Inês Amorim Leitão, Loes van Shaick, António Dinis Ferreira, Violette Geissen

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Plastic pollution is a growing concern worldwide: plastics are commercialized in large quantities and it takes a long time for them to degrade. When in the environment, plastic is fragmented into microplastics (<5mm), which have been found in all environmental compartments at different locations. Microplastics contribute to the environmental pollution in water, air and soil and are linked to human health problems. The progressive increase of population living in cities led to the aggravation of the pollution problem worldwide, especially in urban environments. Urban areas represent a strong source of pollution, through the roads, industrial production, wastewater, landfills, etc. It is expected that pollutants such as microplastics are transported diffusely from the sources through different pathways such as wind and rain. Therefore, it is very complex to quantify, control and treat these pollutants, designated current problematic issues by the European Commission. Green areas are pointed out by experts as natural filters for contaminants in cities, through their capacity of retention by vegetation. These spaces have thus the capacity to control the load of pollutants transported. This study investigates the spatial distribution of microplastics in urban soils of different land uses, their transport through atmospheric deposition, wind erosion, runoff and streams, as well as their deposition in vegetation like grass and tree leaves in urban environment. Coimbra, a medium large city located in the central Portugal, is the case-study. All the soil, sediments, water and vegetation samples were collected in Coimbra and were later analyzed in the Wageningen University & Research laboratory. Microplastics were extracted through the density separation using Sodium Phosphate as solution (~1.4 g cm−3) and filtration methods, visualized under a stereo microscope and identified using the u-FTIR method. Microplastic particles were found in all the different samples. In terms of soils, higher concentrations of microplastics were found in green parks, followed by landfills and industrial places, and the lowest concentrations in forests and pasture land-uses. Atmospheric deposition and streams after rainfall events seems to represent the strongest pathways of microplastics. Tree leaves can retain microplastics on their surfaces. Small leaves such as needle leaves seem to present higher amounts of microplastics per leaf area than bigger leaves. Rainfall episodes seem to reduce the concentration of microplastics on leaves surface, which suggests the wash of microplastics down to lower levels of the tree or to the soil. When in soil, different types of microplastics could be transported to the atmosphere through wind erosion. Grass seems to present high concentrations of microplastics, and the enlargement of the grass cover leads to a reduction of the amount of microplastics in soil, but also of the microplastics moved from the ground to the atmosphere by wind erosion. This study proof that vegetation can help to control the transport and dispersion of microplastics. In order to control the entry and the concentration of microplastics in the environment, especially in cities, it is essential to defining and evaluating nature-based land-use scenarios, considering the role of green urban areas in filtering small particles.

Keywords: microplastics, cities, sources, pathways, vegetation

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Authors: Madushani Rodrigo, Banuka Athuraliya

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In today's world of medical diagnosis and prediction, machine learning stands out as a strong tool, transforming old ways of caring for health. This study analyzes the use of machine learning in the specialized domain of sports medicine, with a focus on the timely and accurate detection of bone fractures in cricket athletes. Failure to identify bone fractures in real time can result in malunion or non-union conditions. To ensure proper treatment and enhance the bone healing process, accurately identifying fracture locations and types is necessary. When interpreting X-ray images, it relies on the expertise and experience of medical professionals in the identification process. Sometimes, radiographic images are of low quality, leading to potential issues. Therefore, it is necessary to have a proper approach to accurately localize and classify fractures in real time. The research has revealed that the optimal approach needs to address the stated problem and employ appropriate radiographic image processing techniques and object detection algorithms. These algorithms should effectively localize and accurately classify all types of fractures with high precision and in a timely manner. In order to overcome the challenges of misidentifying fractures, a distinct model for fracture localization and classification has been implemented. The research also incorporates radiographic image enhancement and preprocessing techniques to overcome the limitations posed by low-quality images. A classification ensemble model has been implemented using ResNet18 and VGG16. In parallel, a fracture segmentation model has been implemented using the enhanced U-Net architecture. Combining the results of these two implemented models, the FracXpert system can accurately localize exact fracture locations along with fracture types from the available 12 different types of fracture patterns, which include avulsion, comminuted, compressed, dislocation, greenstick, hairline, impacted, intraarticular, longitudinal, oblique, pathological, and spiral. This system will generate a confidence score level indicating the degree of confidence in the predicted result. Using ResNet18 and VGG16 architectures, the implemented fracture segmentation model, based on the U-Net architecture, achieved a high accuracy level of 99.94%, demonstrating its precision in identifying fracture locations. Simultaneously, the classification ensemble model achieved an accuracy of 81.0%, showcasing its ability to categorize various fracture patterns, which is instrumental in the fracture treatment process. In conclusion, FracXpert has become a promising ML application in sports medicine, demonstrating its potential to revolutionize fracture detection processes. By leveraging the power of ML algorithms, this study contributes to the advancement of diagnostic capabilities in cricket athlete healthcare, ensuring timely and accurate identification of bone fractures for the best treatment outcomes.

Keywords: multiclass classification, object detection, ResNet18, U-Net, VGG16

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Authors: Mary T. McKinley

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As socio-economic globalization impacts education and turns knowledge into a commodity, institutions of higher education are becoming more intentional about infusing a global and intercultural perspective into education via the recruitment of international students. Coming from dissimilar cultures, many of these students are evaluated and held accountable to Euro-American values of independence, self-reliance, and autonomy. Not surprisingly, these students often experience culture shock with deleterious effects on their mental health and academic functioning. Thus, it is critical to understand the experiences of international students with the hope that such knowledge will keep the field of psychology from promulgating Eurocentric ideals and values and prevent the training of these students as good-enough White therapists. Using a critical narrative inquiry framework, this study elicits stories about the challenges encountered by international students as they navigate their clinical training in the presence of acculturative stress and potentially different worldviews. With its emphasis on story-telling as meaning making, narrative research design is hinged on the assumption that people are interpretive beings who make meaning of themselves and their world through the language of stories. Also, dominant socially-constructed narratives play a central role in creating and maintaining hegemonic structures that privilege certain individuals and ideologies at the expense of others. On this premise, narrative inquiry begins with an exploration of the experiences of participants in their lived stories. Bounded narrative segments were read, interpreted, and analyzed using a critical events approach. Throughout the process, issues of reliability and researcher bias were addressed by keeping a reflective analytic memo, as well as triangulating the data using peer-reviewers and check-ins with participants. The findings situate culture at the epicenter of international students’ acculturation challenges as well as their resiliency in psychology doctoral programs. It was not uncommon for these international students to experience ethical dilemmas inherent in learning content that conflicted with their cultural beliefs and values. Issues of cultural incongruence appear to be further exacerbated by visible markers for differences like speech accent and clothing attire. These stories also link the acculturative stress reported by international students to the experiences of perceived racial discrimination and lack of support from the faculty, administration, peers, and the society at large. Beyond the impact on the international students themselves, there are implications for internationalization in psychology with the goal of equipping doctoral programs to be better prepared to meet the needs of their international students. More than ever before, programs need to liaise with international students’ services and work in tandem to meet the unique needs of this population of students. Also, there exists a need for multiculturally competent supervisors working with international students with varying degrees of acculturation. In addition to making social justice and advocacy salient in students’ multicultural training, it may be helpful for psychology doctoral programs to be more intentional about infusing cross-cultural theories, indigenous psychotherapies, and/or when practical, the possibility for geographically cross-cultural practicum experiences in the home countries of international students while taking into consideration the ethical issues for virtual supervision.

Keywords: decolonizing pedagogies, international students, multiculturalism, psychology doctoral programs

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Authors: Ross Calvert, Colin Whittaker, Alison Raby, Alistair G. L. Borthwick, Ton S. van den Bremer

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Large concentrations of plastic have polluted the seas in the last half century, with harmful effects on marine wildlife and potentially to human health. Plastic pollution will have lasting effects because it is expected to take hundreds or thousands of years for plastic to decay in the ocean. The question arises how waves transport plastic in the ocean. The predominant motion induced by waves creates ellipsoid orbits. However, these orbits do not close, resulting in a drift. This is defined as Stokes drift. If a particle is infinitesimally small and the same density as water, it will behave exactly as the water does, i.e., as a purely Lagrangian tracer. However, as the particle grows in size or changes density, it will behave differently. The particle will then have its own inertia, the fluid will exert drag on the particle, because there is relative velocity, and it will rise or sink depending on the density and whether it is on the free surface. Previously, plastic pollution has all been considered to be purely Lagrangian. However, the steepness of waves in the ocean is small, normally about α = k₀a = 0.1 (where k₀ is the wavenumber and a is the wave amplitude), this means that the mean drift flows are of the order of ten times smaller than the oscillatory velocities (Stokes drift is proportional to steepness squared, whilst the oscillatory velocities are proportional to the steepness). Thus, the particle motion must have the forces of the full motion, oscillatory and mean flow, as well as a dynamic buoyancy term to account for the free surface, to determine whether inertia is important. To track the motion of a floating inertial particle under wave action requires the fluid velocities, which form the forcing, and the full equations of motion of a particle to be solved. Starting with the equation of motion of a sphere in unsteady flow with viscous drag. Terms can added then be added to the equation of motion to better model floating plastic: a dynamic buoyancy to model a particle floating on the free surface, quadratic drag for larger particles and a slope sliding term. Using perturbation methods to order the equation of motion into sequentially solvable parts allows a parametric equation for the transport of inertial finite-sized floating particles to be derived. This parametric equation can then be validated using numerical simulations of the equation of motion and flume experiments. This paper presents a parametric equation for the transport of inertial floating finite-size particles by ocean waves. The equation shows an increase in Stokes drift for larger, less dense particles. The equation has been validated using numerical solutions of the equation of motion and laboratory flume experiments. The difference in the particle transport equation and a purely Lagrangian tracer is illustrated using worlds maps of the induced transport. This parametric transport equation would allow ocean-scale numerical models to include inertial effects of floating plastic when predicting or tracing the transport of pollutants.

Keywords: perturbation methods, plastic pollution transport, Stokes drift, wave flume experiments, wave-induced mean flow

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Authors: Sonja Giese, Tess N. Peacock

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South African based Innovation Edge is experimenting with technology to drive positive behavior change, enable data-driven decision making, and scale quality early years services. This paper uses five case studies to illustrate how technology can be used in resource-constrained environments to first, encourage parenting practices that build early language development (using a stage-based mobile messaging pilot, ChildConnect), secondly, to improve the quality of ECD programs (using a mobile application, CareUp), thirdly, how to affordably scale services for the early detection of visual and hearing impairments (using a mobile tool, HearX), fourthly, how to build a transparent and accountable system for the registration and funding of ECD (using a blockchain enabled platform, Amply), and finally enable rapid data collection and feedback to facilitate quality enhancement of programs at scale (the Early Learning Outcomes Measure). ChildConnect and CareUp were both developed using a design based iterative research approach. The usage and uptake of ChildConnect and CareUp was evaluated with qualitative and quantitative methods. Actual child outcomes were not measured in the initial pilots. Although parents who used and engaged on either platform felt more supported and informed, parent engagement and usage remains a challenge. This is contrast to ECD practitioners whose usage and knowledge with CareUp showed both sustained engagement and knowledge improvement. HearX is an easy-to-use tool to identify hearing loss and visual impairment. The tool was tested with 10000 children in an informal settlement. The feasibility of cost-effectively decentralising screening services was demonstrated. Practical and financial barriers remain with respect to parental consent and for successful referrals. Amply uses mobile and blockchain technology to increase impact and accountability of public services. In the pilot project, Amply is being used to replace an existing paper-based system to register children for a government-funded pre-school subsidy in South Africa. Early Learning Outcomes Measure defines what it means for a child to be developmentally ‘on track’ at aged 50-69 months. ELOM administration is enabled via a tablet which allows for easy and accurate data collection, transfer, analysis, and feedback. ELOM is being used extensively to drive quality enhancement of ECD programs across multiple modalities. The nature of ECD services in South Africa is that they are in large part provided by disconnected private individuals or Non-Governmental Organizations (in contrast to basic education which is publicly provided by the government). It is a disparate sector which means that scaling successful interventions is that much harder. All five interventions show the potential of technology to support and enhance a range of ECD services, but pathways to scale are still being tested.

Keywords: assessment, behavior change, communication, data, disabilities, mobile, scale, technology, quality

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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

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Authors: Kotaro Sasai, Daijiro Mizutani, Kiyoyuki Kaito

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Expressways in Japan have been built in an accelerating manner since the 1960s with the aid of rapid economic growth. About 40 percent in length of expressways in Japan is now 30 years and older and has become superannuated. Time-related deterioration has therefore reached to a degree that administrators, from a standpoint of operation and maintenance, are forced to take prompt measures on a large scale aiming at repairing inner damage deep in pavements. These measures have already been performed for bridge management in Japan and are also expected to be embodied for pavement management. Thus, planning methods for the measures are increasingly demanded. Deterioration of layers around road surface such as surface course and binder course is brought about at the early stages of whole pavement deterioration process, around 10 to 30 years after construction. These layers have been repaired primarily because inner damage usually becomes significant after outer damage, and because surveys for measuring inner damage such as Falling Weight Deflectometer (FWD) survey and open-cut survey are costly and time-consuming process, which has made it difficult for administrators to focus on inner damage as much as they have been supposed to. As expressways today have serious time-related deterioration within them deriving from the long time span since they started to be used, it is obvious the idea of repairing layers deep in pavements such as base course and subgrade must be taken into consideration when planning maintenance on a large scale. This sort of maintenance requires precisely predicting degrees of deterioration as well as grasping the present situations of pavements. Methods for predicting deterioration are determined to be either mechanical or statistical. While few mechanical models have been presented, as far as the authors know of, previous studies have presented statistical methods for predicting deterioration in pavements. One describes deterioration process by estimating Markov deterioration hazard model, while another study illustrates it by estimating Proportional deterioration hazard model. Both of the studies analyze deflection data obtained from FWD surveys and present statistical methods for predicting deterioration process of layers around road surface. However, layers of base course and subgrade remain unanalyzed. In this study, data collected from FWD surveys are analyzed to predict deterioration process of layers deep in pavements in addition to surface layers by a means of estimating a deterioration hazard model using continuous indexes. This model can prevent the loss of information of data when setting rating categories in Markov deterioration hazard model when evaluating degrees of deterioration in roadbeds and subgrades. As a result of portraying continuous indexes, the model can predict deterioration in each layer of pavements and evaluate it quantitatively. Additionally, as the model can also depict probability distribution of the indexes at an arbitrary point and establish a risk control level arbitrarily, it is expected that this study will provide knowledge like life cycle cost and informative content during decision making process referring to where to do maintenance on as well as when.

Keywords: deterioration hazard model, falling weight deflectometer, inner damage, load bearing capacity, pavement

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Authors: Amer Ait Sidhoum

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Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

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Authors: komal verma, V. S. Moholkar

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In this current study, the challenge of effectively treating and mineralizing industrial wastewater prior to its discharge into natural water bodies, such as rivers and lakes, is being addressed. Particularly, the focus is on the wastewater produced by chemical process industries, including refineries, petrochemicals, fertilizer, pharmaceuticals, pesticides, and dyestuff industries. These wastewaters often contain stubborn organic pollutants that conventional techniques, such as microbial processes cannot efficiently degrade. To tackle this issue, a ternary hybrid technique comprising of adsorption, heterogeneous Fenton process, and sonication has been employed. The study aims to evaluate the effectiveness of this approach for treating and mineralizing wastewater from a fertilizer industry located in Northeast India. The study comprises several key components, starting with the synthesis of the Fe3O4@AC nanocomposite using the co-precipitation method. The nanocomposite is then subjected to comprehensive characterization through various standard techniques, including FTIR, FE-SEM, EDX, TEM, BET surface area analysis, XRD, and magnetic property determination using VSM. Next, the process parameters of wastewater treatment are statistically optimized, focusing on achieving a high level of COD (Chemical Oxygen Demand) removal as the response variable. The Fe3O4@AC nanocomposite's adsorption characteristics and kinetics are also assessed in detail. The remarkable outcome of this study is the successful application of the ternary hybrid technique, combining adsorption, Fenton process, and sonication. This approach proves highly effective, leading to nearly complete mineralization (or TOC removal) of the fertilizer industry wastewater. The results highlight the potential of the Fe3O4@AC nanocomposite and the ternary hybrid technique as a promising solution for tackling challenging wastewater pollutants from various chemical process industries. This paper reports investigations in the mineralization of industrial wastewater (COD = 3246 mg/L, TOC = 2500 mg/L) using a ternary (ultrasound + Fenton + adsorption) hybrid advanced oxidation process. Fe3O4 decorated activated charcoal (Fe3O4@AC) nanocomposites (surface area = 538.88 m2/g; adsorption capacity = 294.31 mg/g) were synthesized using co-precipitation. The wastewater treatment process was optimized using central composite statistical design. At optimum conditions, viz. pH = 4.2, H2O2 loading = 0.71 M, adsorbent dose = 0.34 g/L, reduction in COD and TOC of wastewater were 94.75% and 89%, respectively. This result results from synergistic interactions among the adsorption of pollutants onto activated charcoal and surface Fenton reactions induced due to the leaching of Fe2+/Fe3+ ions from the Fe3O4 nanoparticles. Micro-convection generated due to sonication assisted faster mass transport (adsorption/desorption) of pollutants between Fe3O4@AC nanocomposite and the solution. The net result of this synergism was high interactions and reactions among and radicals and pollutants that resulted in the effective mineralization of wastewater. The Fe3O4@AC showed excellent recovery (> 90 wt%) and reusability (> 90% COD removal) in 5 successive cycles of treatment. LC-MS analysis revealed effective (> 50%) degradation of more than 25 significant contaminants (in the form of herbicides and pesticides) after the treatment with ternary hybrid AOP. Similarly, the toxicity analysis test using the seed germination technique revealed ~ 60% reduction in the toxicity of the wastewater after treatment.

Keywords: chemical oxygen demand (cod), fe3o4@ac nanocomposite, kinetics, lc-ms, rsm, toxicity

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Authors: Laetitia Lemiere, Marie Gosme, Gerard Subsol, Marc Jaeger

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Agroforestry is recognized as a way of developing sustainable and resilient agriculture that can fight against climate change. However, the number of species combinations, spatial configurations, and management options for trees and crops is vast. These choices must be adapted to the pedoclimatic and socio-economic contexts and to the objectives of the farmer, who therefore needs support in designing his system. Participative design workshops are a good way to integrate the knowledge of several experts in order to design such complex systems. The design of agroforestry systems should take into account both spatial aspects (e.g., spacing of trees within the lines and between lines, tree line orientation, tree-crop distance, species spatial patterns) and temporal aspects (e.g., crop rotations, tree thinning and pruning, tree planting in the case of successional agroforestry). Furthermore, the interactions between trees and crops evolve as the trees grow. However, agroforestry design workshops generally emphasize the spatial aspect only through the use of static tokens to represent the different species when designing the spatial configuration of the system. Augmented reality (AR) may overcome this limitation, allowing to visualize dynamic representations of trees and crops, and also their interactions, while at the same time retaining the possibility to physically interact with the system being designed (i.e., move trees, add or remove species, etc.). We propose an ergonomic digital solution capable of assisting a group of agroforestry experts to design an agroforestry system and to represent it. We investigated the use of web-based marker-based AR that does not require specific hardware and does not require specific installation so that all users could use their own smartphones right out of the pocket. We developed a prototype mobilizing the AR.js, ArToolKit.js, and Three.js open source libraries. In our implementation, we gradually build a virtual agroforestry system pattern scene from the users' interactions. A specific set of markers initialize the scene properties, and the various plant species are added and located during the workshop design session. The full virtual scene, including the trees positions with their neighborhood, are saved for further uses, such as virtual, augmented instantiation in the farmer fields. The number of tree species available in the application is gradually increasing; we mobilize 3D digital models for walnut, poplar, wild cherry, and other popular species used in agroforestry systems. The prototype allows shadow computations and the representation of trees at various growth stages, as well as different tree generations, and is thus able to visualize the dynamics of the system over time. Future work will focus on i) the design of complex patterns mobilizing several tree/shrub organizations, not restricted to lines; ii) the design of interfaces related to cultural practices, such as clearing or pruning; iii) the representation of tree-crop interactions. Beside tree shade (light competition), our objective is to represent also below-ground competitions (water, nitrogen) or other variables of interest for the design of agroforestry systems (e.g., predicted crop yield).

Keywords: agroforestry system design, augmented reality, marker-based AR, participative design, web-based AR

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Authors: George Zhou, Yunchan Chen, Candace Chien

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Kidney replacement therapy is the current standard of care for end-stage renal diseases. In-center or home hemodialysis remains an integral component of the therapeutic regimen. Arteriovenous fistulas (AVF) make up the vascular circuit through which blood is filtered and returned. Naturally, AVF patency determines whether adequate clearance and filtration can be achieved and directly influences clinical outcomes. Our aim was to build a deep learning model for automated AVF stenosis screening based on the sound of blood flow through the AVF. A total of 311 patients with AVF were enrolled in this study. Blood flow sounds were collected using a digital stethoscope. For each patient, blood flow sounds were collected at 6 different locations along the patient’s AVF. The 6 locations are artery, anastomosis, distal vein, middle vein, proximal vein, and venous arch. A total of 1866 sounds were collected. The blood flow sounds are labeled as “patent” (normal) or “stenotic” (abnormal). The labels are validated from concurrent ultrasound. Our dataset included 1527 “patent” and 339 “stenotic” sounds. We show that blood flow sounds vary significantly along the AVF. For example, the blood flow sound is loudest at the anastomosis site and softest at the cephalic arch. Contextualizing the sound with location metadata significantly improves classification performance. How to encode and incorporate categorical metadata is an active area of research1. Herein, we study ordinal (i.e., integer) encoding schemes. The numerical representation is concatenated to the flattened feature vector. We train a vision transformer (ViT) on spectrogram image representations of the sound and demonstrate that using scalar multiples of our integer encodings improves classification performance. Models are evaluated using a 10-fold cross-validation procedure. The baseline performance of our ViT without any location metadata achieves an AuROC and AuPRC of 0.68 ± 0.05 and 0.28 ± 0.09, respectively. Using the following encodings of Artery:0; Arch: 1; Proximal: 2; Middle: 3; Distal 4: Anastomosis: 5, the ViT achieves an AuROC and AuPRC of 0.69 ± 0.06 and 0.30 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 10; Proximal: 20; Middle: 30; Distal 40: Anastomosis: 50, the ViT achieves an AuROC and AuPRC of 0.74 ± 0.06 and 0.38 ± 0.10, respectively. Using the following encodings of Artery:0; Arch: 100; Proximal: 200; Middle: 300; Distal 400: Anastomosis: 500, the ViT achieves an AuROC and AuPRC of 0.78 ± 0.06 and 0.43 ± 0.11. respectively. Interestingly, we see that using increasing scalar multiples of our integer encoding scheme (i.e., encoding “venous arch” as 1,10,100) results in progressively improved performance. In theory, the integer values do not matter since we are optimizing the same loss function; the model can learn to increase or decrease the weights associated with location encodings and converge on the same solution. However, in the setting of limited data and computation resources, increasing the importance at initialization either leads to faster convergence or helps the model escape a local minimum.

Keywords: arteriovenous fistula, blood flow sounds, metadata encoding, deep learning

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Authors: Dario Milani, Guido Morgenthal

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Fluid dynamic computation of wind caused forces on bluff bodies e.g light flexible civil structures or high incidence of ground approaching airplane wings, is one of the major criteria governing their design. For such structures a significant dynamic response may result, requiring the usage of small scale devices as guide-vanes in bridge design to control these effects. The focus of this paper is on the numerical simulation of the bluff body problem involving multiscale phenomena induced by small scale devices. One of the solution methods for the CFD simulation that is relatively successful in this class of applications is the Vortex Particle Method (VPM). The method is based on a grid free Lagrangian formulation of the Navier-Stokes equations, where the velocity field is modeled by particles representing local vorticity. These vortices are being convected due to the free stream velocity as well as diffused. This representation yields the main advantages of low numerical diffusion, compact discretization as the vorticity is strongly localized, implicitly accounting for the free-space boundary conditions typical for this class of FSI problems, and a natural representation of the vortex creation process inherent in bluff body flows. When the particle resolution reaches the Kolmogorov dissipation length, the method becomes a Direct Numerical Simulation (DNS). However, it is crucial to note that any solution method aims at balancing the computational cost against the accuracy achievable. In the classical VPM method, if the fluid domain is discretized by Np particles, the computational cost is O(Np2). For the coupled FSI problem of interest, for example large structures such as long-span bridges, the aerodynamic behavior may be influenced or even dominated by small structural details such as barriers, handrails or fairings. For such geometrically complex and dimensionally large structures, resolving the complete domain with the conventional VPM particle discretization might become prohibitively expensive to compute even for moderate numbers of particles. It is possible to reduce this cost either by reducing the number of particles or by controlling its local distribution. It is also possible to increase the accuracy of the solution without increasing substantially the global computational cost by computing a correction of the particle-particle interaction in some regions of interest. In this paper different strategies are presented in order to extend the conventional VPM method to reduce the computational cost whilst resolving the required details of the flow. The methods include temporal sub stepping to increase the accuracy of the particles convection in certain regions as well as dynamically re-discretizing the particle map to locally control the global and the local amount of particles. Finally, these methods will be applied on a test case and the improvements in the efficiency as well as the accuracy of the proposed extension to the method are presented. The important benefits in terms of accuracy and computational cost of the combination of these methods will be thus presented as long as their relevant applications.

Keywords: adaptation, fluid dynamic, remeshing, substepping, vortex particle method

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Authors: Manju Bala Jassi

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The Covid 19 pandemic has badly mauled Dubai’s GDP heavily dependent on hospitality, tourism, entertainment, logistics, property and the retail sectors. In the context of the World Health protocols on social distancing for better maintenance of health and hygiene, the revival of the battered tourism and hospitality sectors has serious lessons for designers- interiors and public places. The tangible and intangible aesthetic elements and design –ambiance, materials, furnishings, colors, lighting and interior with architectural design issues of tourism and hospitality need a rethink to ensure a memorable tourist experience. Designers ought to experiment with sustainable places of tourism and design, develop, build and projects are aesthetic and leave as little negative impacts on the environment and public as possible. In short, they ought to conceive public spaces that makes use of little untouched materials and energy, and creates pollution and waste that are minimal. The spaces can employ healthier and more resource-efficient prototypes of construction, renovation, operation, maintenance, and demolition and thereby mitigate the environment impacts of the construction activities and it is sustainable These measures encompass the hospitality sector that includes hotels and restaurants which has taken the hardest fall from the pandemic. The paper sought to examine building energy efficiency and materials and design employed in public places, green buildings to achieve constructive sustainability and to establish the benefits of utilizing energy efficiency, green materials and sustainable design; to document diverse policy interventions, design and Spatial dimensions of tourism and hospitality sectors; to examine changes in the hospitality, aviation sector especially from a design perspective regarding infrastructure or operational constraints and additional risk-mitigation measures; to dilate on the nature of implications for interior designers and architects to design public places to facilitate sustainable tourism and hospitality while balancing convenient space and their operations' natural surroundings. The qualitative research approach was adopted for the study. The researcher collected and analyzed data in continuous iteration. Secondary data was collected from articles in journals, trade publications, government reports, newspaper/ magazine articles, policy documents etc. In depth interviews were conducted with diverse stakeholders. Preliminary data indicates that designers have started imagining public places of tourism and hospitality against the backdrop of the government push and WHO guidelines. For instance, with regard to health, safety, hygiene and sanitation, Emirates, the Dubai-based airline has augmented health measures at the Dubai International Airport and on board its aircraft. It has leveraged high tech/ Nano-tech, social distancing to encourage least human contact, flexible design layouts to limit the occupancy. The researcher organized the data into thematic categories and found that the Government of Dubai has initiated comprehensive measures in the hospitality, tourism and aviation sectors in compliance with the WHO guidelines.

Keywords: Covid 19, design, Dubai, hospitality, public spaces, tourism

Procedia PDF Downloads 137

Authors: Milica B. Veljković, Milica B. Simović, Marija M. Ćorović, Ana D. Milivojević, Anja I. Petrov, Katarina M. Banjanac, Dejan I. Bezbradica

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In recent decades, the scientific community has recognized the growing importance of prebiotics, and therefore, numerous studies are focused on their economic production due to their low presence in natural resources. It has been confirmed that prebiotics is a source of energy for probiotics in the gastrointestinal tract (GIT) and enable their proliferation, consequently leading to the normal functioning of the intestinal microbiota. Also, products of their fermentation are short-chain fatty acids (SCFA), which play a key role in maintaining and improving the health not only of the GIT but also of the whole organism. Among several confirmed prebiotics, fructooligosaccharides (FOS) are considered interesting candidates for use in a wide range of products in the food industry. They are characterized as low-calorie and non-cariogenic substances that represent an adequate sugar substitute and can be considered suitable for use in products intended for diabetics. The subject of this research will be the production of FOS by transforming sucrose using a fructosyltransferase (FTase) present in commercial preparation Pectinex® Ultra SP-L, with special emphasis on the development of adequate FTase immobilization method that would enable selective isolation of the enzyme responsible for the synthesis of FOS from the complex enzymatic mixture. This would lead to considerable enzyme purification and allow its direct incorporation into different sucrose-based products without the fear that the action of the other hydrolytic enzymes may adversely affect the products' functional characteristics. Accordingly, the possibility of selective immobilization of the enzyme using support with primary amino groups, Purolite® A109, which was previously activated and modified using glutaraldehyde (GA), was investigated. In the initial phase of the research, the effects of individual immobilization parameters such as pH, enzyme concentration, and immobilization time were investigated to optimize the process using support chemically activated with 15% and 0.5% GA to form dimers and monomers, respectively. It was determined that highly active immobilized preparations (371.8 IU/g of support - dimer and 213.8 IU/g of support – monomer) were achieved under acidic conditions (pH 4) provided that an enzyme concentration was 50 mg/g of support after 7 h and 3 h, respectively. Bearing in mind the obtained results of the expressed activity, it is noticeable that the formation of dimers showed higher reactivity compared to the form of monomers. Also, in the case of support modification using 15% GA, the value of the ratio of FTase and pectinase (as dominant enzyme mixture component) activity immobilization yields was 16.45, indicating the high feasibility of selective immobilization of FTase on modified polystyrene resin. After obtaining immobilized preparations of satisfactory features, they were tested in a reaction of FOS synthesis under determined optimal conditions. The maximum FOS yields of approximately 50% of total carbohydrates in the reaction mixture were recorded after 21 h. Finally, it can be concluded that the examined immobilization method yielded highly active, stable and, more importantly, refined enzyme preparation that can be further utilized on a larger scale for the development of continual processes for FOS synthesis, as well as for modification of different sucrose-based mediums.

Keywords: chemical modification, fructooligosaccharides, glutaraldehyde, immobilization of fructosyltransferase

Procedia PDF Downloads 156