Search results for: Anthropogenic risks mitigation

Authors: Dana Craciun, Daniela Dascalu, Adriana Isvoran

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Phthalates are a class of plastic additives that are used to enhance the physical properties of plastics and as solvents in paintings and some of them proved to be of particular concern for the human health. There are insufficient data concerning the health risks of phthalates and further research on evaluating their effects in humans is needed. As humans are not volunteers for such experiments, computational analysis may be used to predict the biological effects of phthalates in humans. Within this study we have used some computational approaches (SwissADME, admetSAR, FAFDrugs) for predicting the absorption, distribution, metabolization, excretion and toxicity (ADME-Tox) profiles and pharmacokinetics for the most common used phthalates. These computational tools are based on quantitative structure-activity relationship modeling approach. The predictions are further compared to the known effects of each considered phthalate in humans and correlations between computational results and experimental data are discussed. Our data revealed that phthalates are a class of compounds reflecting high toxicity both when ingested and when inhaled, but by inhalation their toxicity is even greater. The predicted harmful effects of phthalates are: toxicity and irritations of the respiratory and gastrointestinal tracts, dyspnea, skin and eye irritations and disruption of the functions of liver and of the reproductive system. Many of investigated phthalates are predicted to be able to inhibit some of the cytochromes involved in the metabolism of numerous drugs and consequently to affect the efficiency of administrated treatments for many diseases and to intensify the adverse drugs reactions. The obtained predictions are in good agreement with clinical data concerning the observed effects of some phthalates in cases of acute exposures. Our study emphasizes the possible health effects of numerous phthalates and underlines the applicability of computational methods for predicting the biological effects of xenobiotics.

Keywords: phthalates, ADME-Tox, pharmacokinetics, biological effects

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Authors: J. Pazourek, K. Šmejkal, P. Kollár, J. Rajchard, J. Šinko, Z. Balounová, E. Vlková, H. Salmonová

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Pectinatella magnifica (Leidy, 1851) is an invasive freshwater animal that lives in colonies. A colony of Pectinatella magnifica (a gelatinous blob) can be up to several feet in diameter large and under favorable conditions it exhibits an extreme growth rate. Recently European countries around rivers of Elbe, Oder, Danube, Rhine and Vltava have confirmed invasion of Pectinatella magnifica, including freshwater reservoirs in South Bohemia (Czech Republic). Our project (Czech Science Foundation, GAČR P503/12/0337) is focused onto biology and chemistry of Pectinatella magnifica. We monitor the organism occurrence in selected South Bohemia ponds and sandpits during the last years, collecting information about physical properties of surrounding water, and sampling the colonies for various analyses (classification, maps of secondary metabolites, toxicity tests). Because the gelatinous matrix is during the colony lifetime also a host for algae, bacteria and cyanobacteria (co-habitants), in this contribution, we also applied a high performance liquid chromatography (HPLC) method for determination of potentially present cyanobacterial toxins (microcystin-LR, microcystin-RR, nodularin). Results from the last 3-year monitoring show that these toxins are under limit of detection (LOD), so that they do not represent a danger yet. The final goal of our study is to assess toxicity risks related to fresh water resources invaded by Pectinatella magnifica, and to understand the process of invasion, which can enable to control it.

Keywords: cyanobacteria, fresh water resources, Pectinatella magnifica invasion, toxicity monitoring

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Authors: Sophia Shi

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Acute kidney injury (AKI) is the sudden onset of kidney damage in which the kidneys cannot filter waste from the blood, requiring emergency hospitalization. AKI patient mortality rate is high in the ICU and is virtually impossible for doctors to predict because it is so unexpected. Currently, there is no hybrid model predicting AKI that takes advantage of two types of data. De-identified patient data from the MIMIC-III database and de-identified kidney images and corresponding patient records from the Beijing Hospital of the Ministry of Health were collected. Using data features including serum creatinine among others, two numeric models using MIMIC and Beijing Hospital data were built, and with the hospital ultrasounds, an image-only model was built. Convolutional neural networks (CNN) were used, VGG and Resnet for numeric data and Resnet for image data, and they were combined into a hybrid model by concatenating feature maps of both types of models to create a new input. This input enters another CNN block and then two fully connected layers, ending in a binary output after running through Softmax and additional code. The hybrid model successfully predicted AKI and the highest AUROC of the model was 0.953, achieving an accuracy of 90% and F1-score of 0.91. This model can be implemented into urgent clinical settings such as the ICU and aid doctors by assessing the risk of AKI shortly after the patient’s admission to the ICU, so that doctors can take preventative measures and diminish mortality risks and severe kidney damage.

Keywords: Acute kidney injury, Convolutional neural network, Hybrid deep learning, Patient record data, ResNet, Ultrasound kidney images, VGG

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Authors: Manuel Jose Oyson

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The Intergovernmental Panel on Climate Change (IPCC) warned in its most recent report for the entire world “to both mitigate and adapt to climate change if it is to effectively avoid harmful climate impacts.” The IPCC observed “with high confidence” a more rapid rise in total anthropogenic greenhouse gas emissions (GHG) emissions from 2000 to 2010 than in the past three decades that “were the highest in human history”, which if left unchecked will entail a continuing process of global warming and can alter the climate system. Current efforts, however, to respond to the threat of global warming, such as the United Nations Framework Convention on Climate Change and the Kyoto Protocol, have focused on states, and fail to involve Transnational Corporations (TNCs) which are responsible for a vast amount of GHG emissions. Involving TNCs in the search for solutions to climate change is consistent with an acknowledgment by contemporary international law that there is an international role for other international persons, including TNCs, and departs from the traditional “state-centric” response to climate change. Putting the focus of GHG emissions away from states recognises that the activities of TNCs “are not bound by national borders” and that the international movement of goods meets the needs of consumers worldwide. Although there is no legally-binding instrument that covers TNC activities or legal responsibilities generally, TNCs have increasingly been made legally responsible under international law for violations of human rights, exploitation of workers and environmental damage, but not for climate change damage. Imposing on TNCs a legally-binding obligation to reduce their GHG emissions or a legal liability for climate change damage is arguably formidable and unlikely in the absence a recognisable source of obligation in international law or municipal law. Instead a recourse to “soft law” and non-legally binding instruments may be a way forward for TNCs to reduce their GHG emissions and help in addressing climate change. Positive effects have been noted by various studies to voluntary approaches. TNCs have also in recent decades voluntarily committed to “soft law” international agreements. This development reflects a growing recognition among corporations in general and TNCs in particular of their corporate social responsibility (CSR). While CSR used to be the domain of “small, offbeat companies”, it has now become part of mainstream organization. The paper argues that TNCs must voluntarily commit to reducing their GHG emissions and helping address climate change as part of their CSR. One, as a serious “global commons problem”, climate change requires international cooperation from multiple actors, including TNCs. Two, TNCs are not innocent bystanders but are responsible for a large part of GHG emissions across their vast global operations. Three, TNCs have the capability to help solve the problem of climate change. Assuming arguendo that TNCs did not strongly contribute to the problem of climate change, society would have valid expectations for them to use their capabilities, knowledge-base and advanced technologies to help address the problem. It would seem unthinkable for TNCs to do nothing while the global environment fractures.

Keywords: climate change law, corporate social responsibility, greenhouse gas emissions, transnational corporations

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Authors: Ayoub. El Bourtali, Abdessamed.Najine, Amrou Moussa. Benmoussa

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One of the main goals of river engineering is river training, which is defined as controlling and predicting the behavior of a river. It is taking effective measurements to eliminate all related risks and thus improve the river system. In some rivers, the riverbed continues to erode and degrade; therefore, equilibrium will never be reached. Generally, river geometric characteristics and riverbed erosion analysis are some of the most complex but critical topics in river engineering and sediment hydraulics; riverbank erosion is the second answering process in hydrodynamics, which has a major impact on the ecological chain and socio-economic process. This study aims to integrate the new computer technology that can analyze erosion and hydraulic problems through computer simulation and modeling. Choosing the right model remains a difficult and sensitive job for field engineers. This paper makes use of the 5.0.4 version of the HEC-RAS model. The river section is adopted according to the gauged station and the proximity of the adjustment. In this work, we will demonstrate how 2D hydraulic modeling helped clarify the design and cover visuals to set up depth and velocities at riverbanks and throughout advanced structures. The hydrologic engineering center's-river analysis system (HEC-RAS) 2D model was used to create a hydraulic study of the erosion model. The geometric data were generated from the 12.5-meter x 12.5-meter resolution digital elevation model. In addition to showing eroded or overturned river sections, the model output also shows patterns of riverbank changes, which can help us reduce problems caused by erosion.

Keywords: 2D hydraulics model, erosion, floodplain, hydrodynamic, HEC-RAS, riverbed erosion, river morphology, resolution digital data, sediment

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Authors: Jordana Lenhardt

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This paperwork aims to promote a reflection on the critical literacy and multiliteracies concepts in the English language teaching, under an emancipatory perspective, in the English language classroom at the Federal Institute of Mato Grosso (IFMT), Rondonópolis Campus. Some Authors place the relationship between the world conscience and the self-conscience in a direct reason, compromising one to the other, and others defend that emancipatory teaching practice must be connected in all the spheres of the social context; with this paperwork, we intend to analyze students’ interactions with the English language, in order to verify if they demonstrate critical conscience about language and the world around them. The study is still at a preliminary level and is grounded in discourse critical analysis and systemic-functional linguistics. We understand that text is irremediable, linked to a context, and that the linguistic selection made by the speaker builds social representations. This research foresees the analysis of some students’ speeches in an interview about their classes at the Federal Institute in the city of Rondonópolis and the methodology being used on them. Discourse critical analysis explains that, through the awareness of the language uses, learners can become more conscious of the coercions in their own language practices, the possibilities of risks, and the costs of the individual or collective challenges, to engage themselves in emancipatory linguistic practice. The critical language conscience contributes, on the other hand, to make students more aware of the practices in which they are involved, as producers and consumers of texts, of the social forces, ideologies, and power relations, their effects on the identities and social relations, as well as the discourse role in the social and cultural processes.

Keywords: multiliteracies, critical literacy, emancipation, social transformation

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Authors: Kedar Nath Nepal, Dyutiman Choudhary, Naba Raj Pandit, Yam Gahire

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Crop fertilizer recommendations are outdated as these are based on the response trails conducted over half a century ago. Further, these recommendations were based on the response trials conducted over large geographical area ignoring the large spatial variability in indigenous nutrient supplying capacity of soils typical of most smallholder systems. Application of fertilizer following such blanket recommendation in fields with varying native nutrient supply capacity leads to under application in some places and over application in others leading to reduced nutrient-use-efficiency (NUE), loss of profitability, and increased environmental risks associated with loss of unutilized nutrient through emissions or leaching. Opportunities exist to further increase yield and profitability through a significant gain in fertilizer use efficiency with commercialization of affordable and precise application technologies. We conducted participatory trails in Maize (Zea Mays), Cauliflower (Brassica oleracea var. botrytis) and Tomato (Solanum lycopersicum) in Mid Hills of Nepal to evaluate the efficacy of Urea Deep Placement (UDP and Polymer Coated Urea (PCU);. UDP contains 46% of N having individual briquette size 2.7 gm each and PCU contains 44% of N . Both PCU and urea briquette applied at reduced amount (100 kg N/ha) during planting produced similar yields (p>0.05) compared with regular urea (200 Kg N/ha). . These fertilizers also reduced N fertilizer by 35 - 50% over government blanket recommendations. Further, PCU and urea briquette increased farmer’s net income by USD 60 to 80.

Keywords: high efficiency fertilizers, urea deep placement, briquette polymer coated urea, zea mays, brassica, lycopersicum, Nepal

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Authors: Brennan Lodge

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Amidst a complex regulatory landscape, Retrieval Augmented Generation (RAG) emerges as a transformative tool for Governance Risk and Compliance (GRC) officers. This paper details the application of RAG in synthesizing Large Language Models (LLMs) with external knowledge bases, offering GRC professionals an advanced means to adapt to rapid changes in compliance requirements. While the development for standalone LLM’s (Large Language Models) is exciting, such models do have their downsides. LLM’s cannot easily expand or revise their memory, and they can’t straightforwardly provide insight into their predictions, and may produce “hallucinations.” Leveraging a pre-trained seq2seq transformer and a dense vector index of domain-specific data, this approach integrates real-time data retrieval into the generative process, enabling gap analysis and the dynamic generation of compliance and risk management content. We delve into the mechanics of RAG, focusing on its dual structure that pairs parametric knowledge contained within the transformer model with non-parametric data extracted from an updatable corpus. This hybrid model enhances decision-making through context-rich insights, drawing from the most current and relevant information, thereby enabling GRC officers to maintain a proactive compliance stance. Our methodology aligns with the latest advances in neural network fine-tuning, providing a granular, token-level application of retrieved information to inform and generate compliance narratives. By employing RAG, we exhibit a scalable solution that can adapt to novel regulatory challenges and cybersecurity threats, offering GRC officers a robust, predictive tool that augments their expertise. The granular application of RAG’s dual structure not only improves compliance and risk management protocols but also informs the development of compliance narratives with pinpoint accuracy. It underscores AI’s emerging role in strategic risk mitigation and proactive policy formation, positioning GRC officers to anticipate and navigate the complexities of regulatory evolution confidently.

Keywords: cybersecurity, gen AI, retrieval augmented generation, cybersecurity defense strategies

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Authors: Fatimah AlSaiari

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In recent years, newspapers in the United Kingdom have been no longer just a means of sharing news about what happens in the world; they are also used to influence target readers by having them become more up-to-date, well-informed, entertained, exasperated, delighted, and infuriated. To achieve these objectives and maintain influence on public opinion, journalists use a particular language in which they can convey emotions and opinions, organize their discourse, and establish solidarity with their audience. This type of language has been widely analyzed under different labels, such as evaluation, appraisal, and stance. There is a considerable amount of linguistic and non-linguistic research devoted to analyzing this type of interpersonal language in journalistic discourse, and most of these studies were carried out to challenge the traditional assumptions of the objectivity and impartiality of news reporting. However, very little research has been undertaken on evaluative language in newspaper institutional editorials, and there is hardly any systematic or exhaustive analysis of this type of language in British tabloid and broadsheet newspapers. This study will attempt to provide new insights into the nature of authorial and non-authorial evaluation in leading articles in popular and quality British newspapers, along with their targets, sources, and discourse functions. The study will also attempt to develop a framework of evaluation that can be applied to evaluative lexical items in newspaper opinion texts. The framework is both theory-driven (i.e., it builds on and modifies previous frameworks of evaluation such as appraisal theory and parameter-based approach) and data-driven (i.e., it elicits the evaluative categories from the analysis of the corpus, which helps in the development of the current framework). To achieve this aim, a corpus of 140 leading articles were selected. The findings revealed that the tabloids tended to express their stance through explicitness, dramatization, frequent reference to social actors’ emotions and beliefs, and exaggeration in negativity, while the broadsheets preferred to express their stance through mitigation ambiguity and implicitness. conceptual themes and propositions were more preferable targets for expressing stance in the broadsheets while human behavior and characters were preferable targets for the tabloids.

Keywords: appraisal theory, evaluative language, British newspapers, broadsheets & tabloids, evaluative adjectives

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Authors: Elham Taghizadeh, Mostafa Abedzadeh, Mostafa Setak

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Logistics network is expected that opened facilities work continuously for a long time horizon without any failure; but in real world problems, facilities may face disruptions. This paper studies a reliable joint inventory location problem to optimize cost of facility locations, customers’ assignment, and inventory management decisions when facilities face failure risks and doesn’t work. In our model we assume when a facility is out of work, its customers may be reassigned to other operational facilities otherwise they must endure high penalty costs associated with losing service. For defining the model closer to real world problems, the model is proposed based on p-median problem and the facilities are considered to have limited capacities. We define a new binary variable (Z_is) for showing that customers are not assigned to any facilities. Our problem involve a bi-objective model; the first one minimizes the sum of facility construction costs and expected inventory holding costs, the second one function that mention for the first one is minimizes maximum expected customer costs under normal and failure scenarios. For solving this model we use NSGAII and MOSS algorithms have been applied to find the pareto- archive solution. Also Response Surface Methodology (RSM) is applied for optimizing the NSGAII Algorithm Parameters. We compare performance of two algorithms with three metrics and the results show NSGAII is more suitable for our model.

Keywords: joint inventory-location problem, facility location, NSGAII, MOSS

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Authors: Sameh Shahin, Nannang Arrys

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Optimizing pit slope stability and reducing strip ratio of a mining operation are two key tasks in geotechnical engineering. With a growing demand for minerals and an increasing cost associated with extraction, companies are constantly re-evaluating the viability of mineral deposits and challenging their geological understanding. Within Rio Tinto Iron Ore, the Structural Geology (SG) team investigate and collect critical data, such as point based orientations, mapping and geological inferences from adjacent pits to re-model deposits where previous interpretations have failed to account for structurally controlled slope failures. Utilizing innovative data collection methods and data-driven investigation, SG aims to address the root causes of slope instability. Committing to a resource grid drill campaign as the primary source of data collection will often bias data collection to a specific orientation and significantly reduce the capability to identify and qualify complexity. Consequently, these limitations make it difficult to construct a realistic and coherent structural model that identifies adverse structural domains. Without the consideration of complexity and the capability of capturing these structural domains, mining operations run the risk of inadequately designed slopes that may fail and potentially harm people. Regional structural trends have been considered in conjunction with surface and in-pit mapping data to model multi-batter fold structures that were absent from previous iterations of the structural model. The risk is evident in newly identified dip-slope and rock-mass controlled sectors of the geotechnical design rather than a ubiquitous dip-slope sector across the pit. The reward is two-fold: 1) providing sectors of rock-mass controlled design in previously interpreted structurally controlled domains and 2) the opportunity to optimize the slope angle for mineral recovery and reduced strip ratio. Furthermore, a resulting high confidence model with structures and geometries that can account for historic slope instabilities in structurally controlled domains where design assumptions failed.

Keywords: structural geology, geotechnical design, optimization, slope stability, risk mitigation

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Authors: Sara Camino, Fernando Vega, Mercedes Cano, Benito Navarrete, José A. Camino

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Carbon capture and storage (CCS) technologies should play a relevant role towards low-carbon systems in the European Union by 2030. Partial oxy-combustion emerges as a promising CCS approach to mitigate anthropogenic CO₂ emissions. Its advantages respect to other CCS technologies rely on the production of a higher CO₂ concentrated flue gas than these provided by conventional air-firing processes. The presence of more CO₂ in the flue gas increases the driving force in the separation process and hence it might lead to further reductions of the energy requirements of the overall CO₂ capture process. A higher CO₂ concentrated flue gas should enhance the CO₂ capture by chemical absorption in solvent kinetic and CO₂ cyclic capacity. They have impact on the performance of the overall CO₂ absorption process by reducing the solvent flow-rate required for a specific CO₂ removal efficiency. Lower solvent flow-rates decreases the reboiler duty during the regeneration stage and also reduces the equipment size and pumping costs. Moreover, R&D activities in this field are focused on novel solvents and blends that provide lower CO₂ absorption enthalpies and therefore lower energy penalties associated to the solvent regeneration. In this respect, sterically hindered amines are considered potential solvents for CO₂ capture. They provide a low energy requirement during the regeneration process due to its molecular structure. However, its absorption kinetics are slow and they must be promoted by blending with faster solvents such as monoethanolamine (MEA) and piperazine (PZ). In this work, the kinetic behavior of two sterically hindered amines were studied under partial oxy-combustion conditions and compared with MEA. A lab-scale semi-batch reactor was used. The CO₂ composition of the synthetic flue gas varied from 15%v/v – conventional coal combustion – to 60%v/v – maximum CO₂ concentration allowable for an optimal partial oxy-combustion operation. Firstly, 2-amino-2-methyl-1-propanol (AMP) showed a hybrid behavior with fast kinetics and a low enthalpy of CO₂ absorption. The second solvent was Isophrondiamine (IF), which has a steric hindrance in one of the amino groups. Its free amino group increases its cyclic capacity. In general, the presence of higher CO₂ concentration in the flue gas accelerated the CO₂ absorption phenomena, producing higher CO₂ absorption rates. In addition, the evolution of the CO2 loading also exhibited higher values in the experiments using higher CO₂ concentrated flue gas. The steric hindrance causes a hybrid behavior in this solvent, between both fast and slow kinetic solvents. The kinetics rates observed in all the experiments carried out using AMP were higher than MEA, but lower than the IF. The kinetic enhancement experienced by AMP at a high CO2 concentration is slightly over 60%, instead of 70% – 80% for IF. AMP also improved its CO₂ absorption capacity by 24.7%, from 15%v/v to 60%v/v, almost double the improvements achieved by MEA. In IF experiments, the CO₂ loading increased around 10% from 15%v/v to 60%v/v CO₂ and it changed from 1.10 to 1.34 mole CO₂ per mole solvent, more than 20% of increase. This hybrid kinetic behavior makes AMP and IF promising solvents for partial oxy–combustion applications.

Keywords: absorption, carbon capture, partial oxy-combustion, solvent

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Authors: Zelalem Markos Borko

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The quality of life of people with blindness is significantly influenced by the level of resilience they possess. A qualitative approach of the descriptive phenomenological design was employed to address basic study objectives. The researcher purposely selected three blind graduate students from Sidist Kilo Campus and conducted a semi-structured interview to gather data. Data were analyzed by using thematic coding techniques. The present study found that personal characteristics such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication have shaped resiliency for successful university students with visual disabilities. The finding showed that the school environment is the place in which blind students had developed/experienced social, psychological, and economical competency and hope for their academic and entire life success. Furthermore, the finding showed that blind students had experienced individual, family, school, and community-related risks in the success track. Therefore, governmental and non-governmental organizations should provide training for students with visual impairments that focus on the individual traits that shape resilience for academic success, such as commitment, living hope, motivation, positive self-esteem, self-confidence, and communication and also community-oriented training should be to break the social stigma and discriminations for the individuals with the visual impairment.

Keywords: blind students, risk and protective factors, lived experience, success

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Authors: Bastien Sanglard, Simon Cayez, Guillaume Viau, Thomas Blon, Julian Carrey, Sébastien Lachaize

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The need to develop clean production processes is a key challenge of any industry. Steel and iron industries are particularly concerned since they emit 6.8% of global anthropogenic greenhouse gas emissions. One key step of the process is the high-temperature reduction of iron ore using coke, leading to large amounts of CO2 emissions. One route to decrease impacts is to get rid of fossil fuels by changing both the heat source and the reducer. The present work aims at investigating experimentally the possibility to use concentrated solar energy and carbon-free reducing agents. Two sets of experimentations were realized. First, in situ X-ray diffraction on pure and industrial powder of hematite was realized to study the phase evolution as a function of temperature during reduction under hydrogen and ammonia. Secondly, experiments were performed on industrial iron ore pellets, which were reduced by NH3 or H2 into a “solar furnace” composed of a controllable 1600W Xenon lamp to simulate and control the solar concentrated irradiation of a glass reactor and of a diaphragm to control light flux. Temperature and pressure were recorded during each experiment via thermocouples and pressure sensors. The percentage of iron oxide converted to iron (called thereafter “reduction ratio”) was found through Rietveld refinement. The power of the light source and the reduction time were varied. Results obtained in the diffractometer reaction chamber show that iron begins to form at 300°C with pure Fe2O3 powder and 400°C with industrial iron ore when maintained at this temperature for 60 minutes and 80 minutes, respectively. Magnetite and wuestite are detected on both powders during the reduction under hydrogen; under ammonia, iron nitride is also detected for temperatures between400°C and 600°C. All the iron oxide was converted to iron for a reaction of 60 min at 500°C, whereas a conversion ratio of 96% was reached with industrial powder for a reaction of 240 min at 600°C under hydrogen. Under ammonia, full conversion was also reached after 240 min of reduction at 600 °C. For experimentations into the solar furnace with iron ore pellets, the lamp power and the shutter opening were varied. An 83.2% conversion ratio was obtained with a light power of 67 W/cm2 without turning over the pellets. Nevertheless, under the same conditions, turning over the pellets in the middle of the experiment permits to reach a conversion ratio of 86.4%. A reduction ratio of 95% was reached with an exposure of 16 min by turning over pellets at half time with a flux of 169W/cm2. Similar or slightly better results were obtained under an ammonia reducing atmosphere. Under the same flux, the highest reduction yield of 97.3% was obtained under ammonia after 28 minutes of exposure. The chemical reaction itself, including the solar heat source, does not produce any greenhouse gases, so solar metallurgy represents a serious way to reduce greenhouse gas emission of metallurgy industry. Nevertheless, the ecological impact of the reducers must be investigated, which will be done in future work.

Keywords: solar concentration, metallurgy, ammonia, hydrogen, sustainability

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Authors: Qingyu Zhang, Helin Ma, Lili Weng, Mei Cao

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Green supply chain management has been an important organizational strategy to reduce environmental risks and improve financial performance. Firms have to adopt green supply chain practices to meet the official regulations and reduce peer pressure in China. This paper exhibits an empirical study of the drivers of green supply chain management practices and the environmental and economic performance of green supply chain management implementation in Chinese firms. While China is the fastest-growing emerging economy, it has paid a high ecological price. It is reported that China hosts 7 of the world’s 10 most polluted cities. The continued environmental deterioration and the resultant heightened regulatory control and public scrutiny have posed new operating challenges to firms conducting business in China. These challenges make the country an ideal setting to conduct the present study. A research questionnaire was developed to gather data in China. The questionnaire targeted managers and employees in Chinese companies. The data were collected in the last quarter of 2015, involving industries such as electronic & communicational equipment, textile & clothing, pharmaceutical & healthcare, and so on. This study confirms and validates that (1) both internal and external drivers play a significant role in the implementation of green supply chain management practices; (2) green purchase and investment recovery have a significant impact on firms’ environmental and economic performance; (3) with the improvement of the firms’ environmental performance, their economic performance will improve.

Keywords: economic performance, environmental performance, external driver, green supply chain management

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Authors: Manisha Bal, Amit Verma, B. C. Meikap

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Carbon dioxide (CO₂) is the most abundant waste produced by human activities. It is estimated to be one of the major contributors of greenhouse effect and also considered as a major air pollutant formed by burning of fossil fuels. The main sources of emissions are flue gas from thermal power plants and process industries. It is also a contributor of acid rain. Its exposure through inhalation can lead to health risks. Therefore, control of CO₂ emission in the environment is very necessary. The main focus of this study is on the removal of carbon dioxide from off gases using a self-priming venturi scrubber in submerged conditions using sodium hydroxide as the scrubbing liquid. A self-priming submerged venturi scrubber is an efficient device to remove gaseous pollutants. In submerged condition, venturi scrubber remains submerged in the liquid tank and the liquid enters at the throat section of venturi scrubber due to the pressure difference which includes the hydrostatic pressure of the liquid and static pressure of the gas. The inlet polluted air stream enters through converging section which moves at very high velocity in the throat section and atomizes the liquid droplets. This leads to absorption of CO₂ from the off gases in scrubbing liquid which resulted in removal of CO₂ gas from the off gases. Detailed investigation on the scrubbing of carbon dioxide has been done in this literature. Experiments were conducted at different throat gas velocities, liquid levels in outer cylinder and CO₂ inlet concentrations to study the carbon dioxide removal efficiency. Experimental results give more than 95% removal efficiency of CO₂ in the self priming venturi scrubber which can meet the environmental emission limit of CO₂ to save the human life.

Keywords: carbon dioxide, scrubbing, pollution control, self-priming venturi scrubber

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Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

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In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

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Authors: Poojan Vora, Hardik Pancholi, Sanket Tajane, Harsh Shah, Elias Keedy

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The global COVID-19 pandemic has affected the industry drastically in many ways. Even though the vaccine is being distributed quickly and despite the decreasing number of positive cases, testing is projected to remain a key aspect of the ‘new normal’. Improving existing plant layout and improving safety within the facility are of great importance in today’s industries because of the need to ensure productivity optimization and reduce safety risks. In practice, it is essential for any manufacturing plant to reduce nonvalue adding steps such as the movement of materials and rearrange similar processes. In the current pandemic situation, optimized layouts will not only increase safety measures but also decrease the fixed cost per unit manufactured. In our case study, we carefully studied the existing layout and the manufacturing steps of a new Texas start-up company that manufactures COVID testing kits. The effects of production rate are incorporated with the computerized relative allocation of facilities technique (CRAFT) algorithm to improve the plant layout and estimate the optimization parameters. Our work reduces the company’s material handling time and increases their daily production. Real data from the company are used in the case study to highlight the importance of colleges in fostering small business needs and improving the collaboration between college researchers and industries by using existing models to advance best practices.

Keywords: computerized relative allocation of facilities technique, facilities planning, optimization, start-up business

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Authors: Mariangela Viviani, Daniele Germano, Simone Colace, Agostino Forestiero, Giuseppe Papuzzo, Sara Laurita

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Nowadays, people spend most of their time in closed environments, in offices, or at home. Therefore, secure and highly livable environmental conditions are needed to reduce the probability of aerial viruses spreading. Also, to lower the human impact on the planet, it is important to reduce energy consumption. Heating, Ventilation, and Air Conditioning (HVAC) systems account for the major part of energy consumption in buildings [1]. Devising systems to control and regulate the airflow is, therefore, essential for energy efficiency. Moreover, an optimal setting for thermal comfort and air quality is essential for people’s well-being, at home or in offices, and increases productivity. Thanks to the features of Artificial Intelligence (AI) tools and techniques, it is possible to design innovative systems with: (i) Improved monitoring and prediction accuracy; (ii) Enhanced decision-making and mitigation strategies; (iii) Real-time air quality information; (iv) Increased efficiency in data analysis and processing; (v) Advanced early warning systems for air pollution events; (vi) Automated and cost-effective m onitoring network; and (vii) A better understanding of air quality patterns and trends. We propose AIR SAFE, an IoT-based infrastructure designed to optimize air quality and thermal comfort in indoor environments leveraging AI tools. AIR SAFE employs a network of smart sensors collecting indoor and outdoor data to be analyzed in order to take any corrective measures to ensure the occupants’ wellness. The data are analyzed through AI algorithms able to predict the future levels of temperature, relative humidity, and CO₂ concentration [2]. Based on these predictions, AIR SAFE takes actions, such as opening/closing the window or the air conditioner, to guarantee a high level of thermal comfort and air quality in the environment. In this contribution, we present the results from the AI algorithm we have implemented on the first s et o f d ata c ollected i n a real environment. The results were compared with other models from the literature to validate our approach.

Keywords: air quality, internet of things, artificial intelligence, smart home

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Authors: Ahmet Yetik, Seyit Ali Kara, Cevat Özarpa

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Load changes occur on natural gas and oil pipelines due to natural disasters. The displacement of the soil around the natural gas and oil pipes due to situations that may cause erosion, such as earthquakes, landslides, and floods, is the source of this load change. The exposure of natural gas and oil pipes to variable loads causes deformation, cracks, and breaks in these pipes. Cracks and breaks on the pipes cause damage to people and the environment due to reasons such as explosions. Especially with the examinations made after natural disasters, it can be easily understood which of the pipes has more damage in the regions followed. It has been determined that the earthquakes in Turkey caused permanent damage to the pipelines. This project was designed and realized because it was determined that there were cracks and gas leaks in the insulation gaskets placed in the pipelines, especially at the junction points. In this study, A new SCADA (Supervisory Control and Data Acquisition) application has been developed to monitor load changes caused by natural disasters. The newly developed SCADA application monitors the changes in the x, y, and z axes of the stresses occurring in the pipes with the help of strain gauge sensors placed on the pipes. For the developed SCADA system, test setups in accordance with the standards were created during the fieldwork. The test setups created were integrated into the SCADA system, and the system was followed up. Thanks to the SCADA system developed with the field application, the load changes that will occur on the natural gas and oil pipes are instantly monitored, and the accumulations that may create a load on the pipes and their surroundings are immediately intervened, and new risks that may arise are prevented. It has contributed to energy supply security, asset management, pipeline holistic management, and sustainability.

Keywords: earthquake, natural gas pipes, oil pipes, strain measurement, stress measurement, landslide

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Authors: Sujith Gunawardhana

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The circular economy is a system in which resources and energy are derived from renewable sources, utilized efficiently, recycled, and reused to reduce waste, reduce nonrenewable resource consumption, and mitigate negative environmental impacts. However, it poses moral questions about sustainability, the environment, and societal issues. Many societies face challenges when implementing the circular economy, as the concept is still young. The equitable distribution of the advantages and costs of circularity should be ensured during implementation, as some communities, particularly disadvantaged or marginalized ones, may suffer unfairly disproportionately from the harmful effects of production and recycling facilities. Prioritizing the health and safety of workers, communities, and the environment is essential, and strict rules must be implemented to guard against harm. However, most underdeveloped countries need a legal safeguard for this situation. The ultimate objective of the circular economy is to improve social, environmental, and economic performance, but its implementation also requires consideration of the ethics of care and non-epistemic values. Those are often hindered in underdeveloped countries, as the availability of infrastructure and technology, affordability, and legislative framework are poor. To achieve long-term success in the circular economy, evaluating implementation steps and considering health, safety, environmental, and social risks is crucial. To implement the circular economy, respect ethics of care and non-epistemic values. Adopt Kantian Ethics and control technology design to ensure equal benefits for all involved. Ethical gaps may lead underdeveloped countries to generate social pressure against the circular economy.

Keywords: circular economy, ethics, values, sustainability

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Authors: Abdelsalam Gomaa, Mahjabeen Ramzan, Tooba Ali Akbar, Huma Nadeem

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The use of tobacco and the health risks linked to it are well known in this day and age due to the presence of easily available information through the internet. The media is a powerful platform that is used by many anti-smoking awareness campaigns to reach their target audience; yet, it has been found that adolescents are taking up smoking every passing day. Half of this smoking population of youngsters resides in Asia alone, which includes Qatar, the focus country of this study. As smoking happens to be one of the largest avoidable causes of serious diseases like cancers and heart problems, children are taking up smoking at an alarming rate everywhere including Qatar. Importance of the health of the citizens of Qatar is one of the pillars of the Qatar vision 2030, which is to ensure a healthy population, both physically and mentally. Since the youth makes up a significant percentage of the population and in order to achieve the health objectives of the Qatar vision 2030, it is essential to ensure the health and well-being of this part of the population of the country as they are the future of Qatar. Children, especially boys who tend to be more aggressive by nature, are highly likely to develop behavioral and health issues due to smoking at an early age. Research conducted around the world has also emphasized on this association between the smokers developing a bad behaviour as well as poor social communication skills. However, due to lack of research into this association, very little is known about the extent to which smoking impacts the children’s academics, health and behaviour. Moreover, a study of this nature has not yet been conducted in Qatar previously as most of the studies focus on adult smokers and ways to minimize the number of smoking habits in universities and workplaces. This study solely focuses on identifying a relationship between smoking and its impacts on the adolescents by conducting a research on different schools across Qatar.

Keywords: adolescents, modelling techniques, Qatar, smoking

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Authors: Md Imtiaz, Sanchita Dei, Shubham Damke

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In recent years, there has been a rapidly accelerating shift from traditional surface processing operations to subsea processing operation. This shift has been driven by a number of factors including the depletion of shallow fields around the world, technological advances in subsea processing equipment, the need for production from marginal fields, and lower initial upfront investment costs compared to traditional production facilities. Moving production facilities to the seafloor offers a number of advantage, including a reduction in field development costs, increased production rates from subsea wells, reduction in the need for chemical injection, minimization of risks to worker ,reduction in spills due to hurricane damage, and increased in oil production by enabling production from marginal fields. Subsea processing consists of a range of technologies for separation, pumping, compression that enables production from offshore well without the need for surface facilities. At present, there are two primary technologies being used for subsea processing: subsea multiphase pumping and subsea separation. Multiphase pumping is the most basic subsea processing technology. Multiphase pumping involves the use of boosting system to transport the multiphase mixture through pipelines to floating production vessels. The separation system is combined with single phase pumps or water would be removed and either pumped to the surface, re-injected, or discharged to the sea. Subsea processing can allow for an entire topside facility to be decommissioned and the processed fluids to be tied back to a new, more distant, host. This type of application reduces costs and increased both overall facility and integrity and recoverable reserve. In future, full subsea processing could be possible, thereby eliminating the need for surface facilities.

Keywords: FPSO, marginal field, Subsea processing, SWAG

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Authors: Oluwatosin Adetola Arojojoye, Olajumoke Olufunlayo Alao, Philip Odigili

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This study investigated the extent of pollution in Eleyele River in Oyo State, Nigeria by investigating the antioxidant status and malondialdehyde levels (index of lipid peroxidation) in the organs of African Catfish, Clarias gariepinus from the river. Clarias gariepinus weighing between 250g-400g were collected from Eleyele River (a suspected polluted river) and Clarias gariepinus from a clean fish farm (Durantee fisheries) were used as the control. Levels of malondialdehyde, glutathione concentration (GSH) and activities of antioxidant enzymes - superoxide dismutase, catalase and glutathione-S-transferase (GST) were evaluated in the post-mitochondrial fractions of the liver, kidney and gills of the fishes. From the results, there were increases in malondialdehyde level and GSH concentration in the liver, kidney and gills of Clarias gariepinus from Eleyele River when compared with control. Glutathione-S-transferase activity was induced in the liver and kidney of Clarias gariepinus from Eleyele River when compared with control. However, the activity of this enzyme was depleted in the gills of fishes from Eleyele River compared with control. Also there was an induction in SOD activity in the liver of Clarias gariepinus from Eleyele River when compared with control but there was a decrease in the activity of this enzyme in the kidney and gills of fishes from Eleyele River compared with control. Increase in lipid peroxidation and alterations in antioxidant system in Clarias gariepinus from Eleyele River show that the fishes were under oxidative stress. These suggest that the river is polluted probably as a result of industrial, domestic and agricultural wastes frequently discharged into the river. This could pose serious health risks to consumers of water and aquatic organisms from the river.

Keywords: antioxidant, lipid peroxidation, Clarias gariepinus, Eleyele River

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Authors: Besma Khalfoun

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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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Authors: Fatemah Alzubairi

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Terrorism financing is a theme that dramatically evolved post-9/11. Supra-national bodies, above all UN Security Council and the Financial Action Task Form (FATF), have established an executive-like mechanism, which allows blacklisting individuals and groups, freezing their funds, and restricting their travel, all of which have become part of states’ anti-terrorism frameworks. A number of problems arise from building counter-terrorism measures on the foundation of a vague definition of terrorism. This paper examines the utility and consequences of counter-terrorism financing with considering the lack of an international definition of terrorism. The main problem with national and international anti-terrorism legislation is the lack of a clear objective definition of terrorism. Most, if not all, national laws are broad and vague. Determining what terrorism remains the crucial underpinning of any successful discussion of counter-terrorism, and of the future success of counter-terrorist measures. This paper focuses on the legal and political consequences of equalizing the treatment of violent terrorist crimes, such as bombing, with non-violent terrorism-related crimes, such as funding terrorist groups. While both sorts of acts requires criminalization, treating them equally risks wrongfully or unfairly condemning innocent people who have associated with “terrorists” but are not involved in terrorist activities. This paper examines whether global obligations to counter terrorism financing focus on controlling terrorist groups more than terrorist activities. It also examines the utility of the obligations adopted by the UN Security Council and FATF, and whether they serve global security; or whether the utility is largely restricted to Western security, with little attention paid to the unique needs and demands of other regions.

Keywords: counter-terrorism, definition of terrorism, FATF, security, terrorism financing, UN Security Council

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Authors: Kayne Uriel K. Rodrigo, Jerriane Hillary Heart S. Marcial, Samuel C. Brillo

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Rice leaf diseases significantly impact yield production in rice-dependent countries, affecting their agricultural sectors. As part of precision agriculture, early and accurate detection of these diseases is crucial for effective mitigation practices and minimizing crop losses. Hence, this study proposes an enhancement to the Convolutional Neural Network (CNN), a widely-used method for Rice Leaf Disease Image Classification, by incorporating MobileViTV2—a recently advanced architecture that combines CNN and Vision Transformer models while maintaining fewer parameters, making it suitable for broader deployment on edge devices. Our methodology utilizes a publicly available rice disease image dataset from Kaggle, which was validated by a university structural biologist following the guidelines provided by the Philippine Rice Institute (PhilRice). Modifications to the dataset include renaming certain disease categories and augmenting the rice leaf image data through rotation, scaling, and flipping. The enhanced dataset was then used to train the MobileViTV2 model using the Timm library. The results of our approach are as follows: the model achieved notable performance, with 98% accuracy in both training and validation, 6% training and validation loss, and a Receiver Operating Characteristic (ROC) curve ranging from 95% to 100% for each label. Additionally, the F1 score was 97%. These metrics demonstrate a significant improvement compared to a conventional CNN-based approach, which, in a previous 2022 study, achieved only 78% accuracy after using 5 convolutional layers and 2 dense layers. Thus, it can be concluded that MobileViTV2, with its fewer parameters, outperforms traditional CNN models, particularly when applied to Rice Leaf Disease Image Identification. For future work, we recommend extending this model to include datasets validated by international rice experts and broadening the scope to accommodate biotic factors such as rice pest classification, as well as abiotic stressors such as climate, soil quality, and geographic information, which could improve the accuracy of disease prediction.

Keywords: convolutional neural network, MobileViTV2, rice leaf disease, precision agriculture, image classification, vision transformer

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Authors: Ryoo Hye Jin Agnes

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This study aims to investigate the efficacy of clickers in fostering L2 class interaction. In an L2 classroom, active learner-to-learner interactions and learner-to-teacher interactions play an important role in language acquisition. In light of this, introducing learning tools that promote such interactions would benefit L2 classroom by fostering interaction. This is because the anonymity of clickers allows learners to express their needs without the social risks associated with speaking up in the class. clickers therefore efficiently help learners express their level of understanding during the process of learning itself. This allows for an evaluative feedback loop where both learners and teachers understand the level of progress of the learners, better enabling classrooms to adapt to the learners’ needs. Eventually this tool promotes participation from learners. This, in turn, is believed to be effective in fostering classroom interaction, allowing learning to take place in a more comfortable yet vibrant way. This study is finalized by presenting the result of an experiment conducted to verify the effectiveness of this approach when teaching pragmatic aspect of Korean expressions with similar semantic functions. The learning achievement of learners in the experimental group was found higher than the learners’ in a control group. A survey was distributed to the learners, questioning them regarding the efficacy of clickers, and how it contributed to their learning in areas such as motivation, self-assessment, increasing participation, as well as giving feedback to teachers. Analyzing the data collected from the questionnaire given to the learners, the study presented data suggesting that this approach increased the scope of interactivity in the classroom, thus not only increasing participation but enhancing the type of classroom participation among learners. This participation in turn led to a marked improvement in their communicative abilities.

Keywords: second language acquisition, interaction, clickers, learner response system, output from learners, learner’s cognitive process

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Authors: Flavio Gazzani

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Nitrogen is an important agricultural input that is critical for the production. However, the introduction of large amounts of nitrogen into the environment has a number of undesirable impacts such as: the loss of biodiversity, eutrophication of waters and soils, drinking water pollution, acidification, greenhouse gas emissions, human health risks. It is a challenge to sustain or increase food production and at the same time reduce losses of reactive nitrogen to the environment, but there are many potential benefits associated with improving nitrogen use efficiency. Reducing nutrient losses from agriculture is crucial to the successful implementation of agricultural policy. Traditional regulatory instruments applied to implement environmental policies to reduce environmental impacts from nitrogen fertilizers, despite some successes, failed to address many environmental challenges and imposed high costs on the society to achieve environmental quality objectives. As a result, economic instruments started to be recognized for their flexibility and cost-effectiveness. The objective of the research project is to analyze the potential for increased use of market-based instruments in nitrogen control policy. The report reviews existing knowledge, bringing different studies together to assess the global nitrogen situation and the most relevant environmental management policy that aims to reduce pollution in a sustainable way without affect negatively agriculture production and food price. This analysis provides some guidance on how different market based instruments might be orchestrated in an overall policy framework to the development and assessment of sustainable nitrogen management from the economics, environmental and food security point of view.

Keywords: nitrogen emissions, chemical fertilizers, eutrophication, non-point of source pollution, dairy farm

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Authors: Nattapol Pourprasert, Siriwan Manowan

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This study aims to find out what budget problems Thailand is facing with and how the results from the comparison between the budgeting reform by Thailand and the reforms by OECD member countries can be used for carrying out budgeting reform of Thailand. The findings from the study on the budget problems that Thailand is facing with reveal that the budgeting system of Thailand lacks of the assessment for the cost-effectiveness of the expenditure of borrowed money and budgets in order to determine whether the expenses are worth the taxes collected from people or not. This is because most popularity policies have unlimited budgets which can lead to the financial risks. Also, these policies create great tax burdens for the descendants in the future and affect the fair distribution of incomes but the Parliament of Thailand never considers these facts. The findings from the comparison between Thai budgeting reform and those by OECD member countries manifest that the traditional budgeting system of Thailand is the department-based budgeting, which is still used without being changed or adjusted in order to fit the new administrative regimes. This traditional budgeting system suggests that a department is responsible for budgeting tasks. Meanwhile, in OECD member countries, budgeting reforms are carried out simultaneously with the reforms of civil service systems so that they are driven in the same directions. The budgeting reforms that rely only on the analyses on economic or technical dimension can hardly lead to success. The budgeting systems of OECD member countries are designed to deal with the unique problems that each of the member countries is facing with rather than adopting the modern system developed by other countries. The budgeting system that has a complicated concept and practice has to be implemented under a flexible strategy so that the departments that implement it can learn about and adjust itself to the system. Continuous and consistent development and training for staff members are also necessary.

Keywords: budgeting reforms, Thailand, OECD member countries, budget problems

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