Search results for: energy demand model

Authors: Samawi Zepure, Beck Christine, Gallagher Peg

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This community immersion employs the NLN Excellence Model which challenges nursing programs to create student-centered, interactive, and innovative experiences to prepare students for roles in providing high quality care, effective teaching, and leadership in the delivery of nursing services to individuals, families, and communities (NLN, 2006). Senior nursing students collaborate with ethnically and linguistically diverse participants at community-based sites and develop leadership roles of coordination of care linkage within the larger healthcare system, adherence, and self-care management. The immersion encourages students to develop competencies of the NLN Nursing Education Competencies Model (NLN, 2012), proposed to address fast changes in health care delivery, which include values of caring, diversity, and holism; and integrating concepts of context and environment, relationship, and teamwork. Students engage in critical thinking and leadership as they: 1) assess health/illness beliefs, values, attitudes, and practices, explore community resources, interview key informants, and collaborate with community participants to identify learning goals, 2) develop and implement appropriate holistic health promotion and disease prevention teaching interventions promoting continuity, sustainability, and innovation, 3) evaluate interventions through participant feedback and focus groups and, 4) reflect on the immersion experience and future professional role as advocate and citizen.

Keywords: quality of care, health of communities, students as leaders, health promotion

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Authors: Terry Lucas

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Calculations are performed to quantify the potential contribution of each greenhouse gas emission reduction strategy. This approach facilitates the visualisation of the relative benefits of each, and it provides a potential baseline for the development of a plan of action that is rooted in quantitative evaluation. Emissions reductions are converted to potential de-escalation of global average temperature. A comprehensive plan is then presented which shows the potential benefits all the way out to year 2100. A target temperature de-escalation of 2oC was selected, but the plan shows a benefit of only 1.225oC. This latter disappointing result is in spite of new and powerful technologies introduced into the equation. These include nuclear fusion and alternative nuclear fission processes. Current technologies such as wind, solar and electric vehicles show surprisingly small constributions to the whole.

Keywords: climate change, emissions, drawdown, energy

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Authors: Beenish Saba, Ann D. Christy

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Modern day municipal solid waste landfills are operated and controlled to protect the environment from contaminants during the biological stabilization and degradation of the solid waste. They are equipped with liners, caps, gas and leachate collection systems. Landfill gas is passively or actively collected and can be used as bio fuel after necessary purification, but leachate treatment is the more difficult challenge. Leachate, if not recirculated in a bioreactor landfill system, is typically transported to a local wastewater treatment plant for treatment. These plants are designed for sewage treatment, and often charge additional fees for higher strength wastewaters such as leachate if they accept them at all. Different biological, chemical, physical and integrated techniques can be used to treat the leachate. Treating that leachate with simultaneous power production using microbial fuel cells (MFC) technology has been a recent innovation, reported its application in its earliest starting phase. High chemical oxygen demand (COD), ionic strength and salt concentration are some of the characteristics which make leachate an excellent substrate for power production in MFCs. Different materials of electrodes, microbial communities, carbon co-substrates and temperature conditions are some factors that can be optimized to achieve simultaneous power production and treatment. The advantage of the MFC is its dual functionality but lower power production and high costs are the hurdles in its commercialization and more widespread application. The studies so far suggest that landfill leachate MFCs can produce 1.8 mW/m2 with 79% COD removal, while amendment with food leachate or domestic wastewater can increase performance up to 18W/m3 with 90% COD removal. The columbic efficiency is reported to vary between 2-60%. However efforts towards biofilm optimization, efficient electron transport system studies and use of genetic tools can increase the efficiency of the MFC and can determine its future potential in treating landfill leachate.

Keywords: microbial fuel cell, landfill leachate, power generation, MFC

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Authors: Zsuzsa Szakaly

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Several constitutions have explicit or implicit eternity clauses in the European Union, their classic roles were analyzed so far, albeit there are new possibilities emerging in relation to the identity of the constitutions of the Member States. The aim of the study is to look at the practice of the Constitutional Courts of the Member States in detail regarding eternity clauses where limiting constitutional amendment has practical bearing, and to examine the influence of such practice on Europeanization. There are some states that apply explicit eternity clauses embedded in the text of the constitution, e.g., Italy, Germany, and Romania. In other states, the Constitutional Court 'unearthed' the implicit eternity clauses from the text of the basic law, e.g., Slovakia and Croatia. By using comparative analysis to examine the explicit or implicit clauses of the concerned constitutions, taking into consideration the new trends of the judicial opinions of the Member States and the fresh scientific studies, the main questions are: How to wield the double-edged sword of eternity clauses? To support European Integration or to support the sovereignty of the Member State? To help Europeanization or to act against it? Eternity clauses can easily find themselves between a rock and a hard place, the law of the European Union and the law of a Member State, with more possible interpretations. As more and more Constitutional Courts started to declare elements of their Member States’ constitutional identities, these began to interfere with the eternity clauses. Will this trend eventually work against Europeanization? As a result of the research, it can be stated that a lowest common denominator exists in the practice of European Constitutional Courts regarding eternity clauses. The chance of a European model and the possibility of this model influencing the status quo between the European Union and the Member States will be examined by looking at the answers these courts have found so far.

Keywords: constitutional court, constitutional identity, eternity clause, European Integration

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Authors: Manuela Gamba, Niki Mandolesi

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Teenagers today have little knowledge about how to move or play together. The adults who are part of sports culture must find an effective way to foster this essential ability. Our research in Italy uses a 'holistic model' based on fantasy literature to explore the relationships between the game identities and self-identities of young people and the achievement of psycho-motor, emotional and social well-being in the realms of sport and education. Physical activity projects were carried out in schools and extra-curricular associations in Rome, combining outdoor activities and distance learning. This holistic and malleable game model is inspired by fantasy accounts of the journeys taken in The Lord of Rings and Harry Potter books. We know that many have a lot of resistance to the idea of using fantasy and play as a pedagogical tool, but the results obtained in this experience are surprising. Our interventions and investigations focused on promoting self-esteem, awareness, a sense of belonging, social integration, cooperation, well-being, and informed decision making: a basis for healthy and effective citizenship. For teenagers, creative thinking is the right stimulus to involve and compare the story of characters to their own journey through social and self-reflective identity analysis. We observed how important it is to engage students emotionally as well as cognitively and that enabling them to play with identity through relationships with peers. There is a need today for a multidisciplinary synthesis of analog and digital values, especially in response to recent distance-living experiences. There is a need for a global reconceptualization of free time and nature in the human experience.

Keywords: awareness, creativity, identity, play

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Authors: Sachi Nandan Mohanty, Shreya Sinha, Sweeti Sah, Shweta Sharma

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The advancement of natural language processing has majorly influenced the field of medical transcript classification, providing a robust framework for enhancing the accuracy of clinical data processing. It has enormous potential to transform healthcare and improve people's livelihoods. This research focuses on improving the accuracy of medical transcript categorization using Bidirectional Encoder Representations from Transformers (BERT) and its specialized variants, including BioBERT, ClinicalBERT, SciBERT, and BlueBERT. The experimental work employs Optuna, an optimization framework, for hyperparameter tuning to identify the most effective variant, concluding that BioBERT yields the best performance. Furthermore, various optimizers, including Adam, RMSprop, and Layerwise adaptive large batch optimization (LAMB), were evaluated alongside BERT's default AdamW optimizer. The findings show that the LAMB optimizer achieves a performance that is equally good as AdamW's. Synthetic data generation techniques from Gretel were utilized to augment the dataset, expanding the original dataset from 5,000 to 10,000 rows. Subsequent evaluations demonstrated that the model maintained its performance with synthetic data, with the LAMB optimizer showing marginally better results. The enhanced dataset and optimized model configurations improved classification accuracy, showcasing the efficacy of the BioBERT variant and the LAMB optimizer. It resulted in an accuracy of up to 98.2% and 90.8% for the original and combined datasets.

Keywords: BioBERT, clinical data, healthcare AI, transformer models

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Authors: U.-B. Schaer, M. Wehr, R. Hodler

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Background: Most nursing students require more training time for necessary nursing skills than defined by nursing schools curriculum to acquire basic nursing skills. Given skills training lessons are too brief to enable effective student learning, meaning in-depth skills practice and repetition various learning steps. This increases stress levels and the pressure to succeed for a nursing student with slower learning capabilities. Another possible consequence is that nursing students are less prepared in the required skills for future clinical practice. Intervention: The Bern College of Higher Education of Nursing, Switzerland, started the independent peer practice learning program in 2012. A concept was developed which defines specific aims and content as well as student’s rights and obligations. Students enlist beforehand and order the required materials. They organize themselves and train in small groups in allocated training location in the area of Learning Training and Transfer (LTT). During the peer practice, skills and knowledge can be repeatedly trained and reflected in the peer groups without the presence of a tutor. All invasive skills are practiced only on teaching dummies. This allows students to use all their potential. The students may access learning materials as literature and their own student notes. This allows nursing students to practice their skills and to deepen their knowledge on corresponding with their own learning rate. Results: Peer group discussions during the independent peer practice learning support the students in gaining certainty and confidence in their knowledge and skills. This may improve patient safety in future daily care practice. Descriptive statics show that the number of students who take advantage of the independent peer practice learning increased continuously (2012-2018). It has to be mentioned that in 2012, solely students of the first semester attended the independent peer practice learning program, while in 2018 over one-third of the participating students were in their fifth semester and final study year. It is clearly visible that the demand for independent peer practice learning is increasing. This has to be considered in the development of future teaching curricula.

Keywords: learning program, nursing students, peer learning, skill training

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Authors: Raj Kumar Rajak, Bharat Mishra

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Bio-battery represents an entirely new long term, reasonable, reachable and ecofriendly approach to production of sustainable energy. Types of batteries have been developed using MnO₂ in various ways. MnO₂ is suitable with physical, chemical, electrochemical, and catalytic properties, serving as an effective cathodic depolarizer and may be considered as being the life blood of the battery systems. In the present experimental work, we have studied the effect of generation of power by bio-battery using different concentrations of MnO₂. The tests show that it is possible to generate electricity using cow’s urine as an electrolyte. After ascertaining the optimum concentration of MnO₂, various battery parameters and performance indicates that cow urine solely produces power of 695 mW, while a combination with MnO₂ (40%) enhances power of bio-battery, i.e. 1377 mW. On adding more and more MnO₂ to the electrolyte, the power suppressed because inflation of internal resistance. The analysis of the data produced from experiment shows that MnO₂ is quite suitable to energize the bio-battery.

Keywords: bio-batteries, cow’s urine, manganese dioxide, non-conventional

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Authors: Juan P. Novoa, Mario A. Rios

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This paper presents a transmission planning methodology that considers the conversion of HVAC transmission lines to HVDC as an alternative of expansion of power systems, as a consequence of restrictions for the construction of new lines. The transmission expansion planning problem formulates an optimization problem that minimizes the total cost that includes the investment cost to convert lines from HVAC to HVDC and possible required reinforcements of the power system prior to the conversion. The costs analysis assesses the impact of the conversion on the reliability because transmission lines are out of service during the conversion work. The presented methodology is applied to a test system considering a planning a horizon of 10 years.

Keywords: transmission expansion planning, HVDC, cost optimization, energy non-supplied

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Authors: Atef Aladwan

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This research will focus on stimulating greater freedom and facilitating small and medium-sized enterprises (SMEs) in Jordan to create jobs, as it is emerging as a key development issue. It will highlight the importance of integrating SMEs into development strategies. Jordan has potentially a large market for its products as a result of proximity to developed country markets, signing of various free trades agreements with European countries, cheap energy sources and vast sovereign funds willing to invest in the development of local enterprises. It is beginning to be accepted by governments that SMEs rather than government need to be the main player in domestic economic activity, especially as providers of employment opportunities, and hence generators of sources of income for many households. To foster SME development, it is generally recognised that reforms are needed in Jordan in order to bring about a more globally competitive and business-friendly environment.

Keywords: SMEs, competitiveness, entrepreneurship, jordan, development

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Authors: A. O. Adebayo, G. A. Idowu, F. Odegbemi

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Investigations on the recovery of nickel from aqueous solution using 2-hydroxy-5-nonyl- acetophenone oxime (LIX-84I) impregnated on activated charcoal was carried out. The LIX-84I was impregnated onto the pores of dried activated charcoal by dry method and optimum conditions for different equilibrium parameters (pH, adsorbent dosage, extractant concentration, agitation time and temperature) were determined using a simulated solution of nickel. The kinetics and adsorption isotherm studies were also evaluated. It was observed that the efficiency of recovery with LIX-84I impregnated on charcoal was dependent on the pH of the aqueous solution as there was little or no recovery at pH below 4. However, as the pH was raised, percentage recovery increases and peaked at pH 5.0. The recovery was found to increase with temperature up to 60ºC. Also it was observed that nickel adsorbed onto the loaded charcoal best at a lower concentration (0.1M) of the extractant when compared with higher concentrations. Similarly, a moderately low dosage (1 g) of the adsorbent showed better recovery than larger dosages. These optimum conditions were used to recover nickel from the leachate of Ni-MH batteries dissolved with sulphuric acid, and a 99.6% recovery was attained. Adsorption isotherm studies showed that the equilibrium data fitted best to Temkin model, with a negative value of constant, b (-1.017 J/mol) and a high correlation coefficient, R² of 0.9913. Kinetic studies showed that the adsorption process followed a pseudo-second order model. Thermodynamic parameter values (∆G⁰, ∆H⁰, and ∆S⁰) showed that the adsorption was endothermic and spontaneous. The impregnated charcoal appreciably recovered nickel using a relatively smaller volume of extractant than what is required in solvent extraction. Desorption studies showed that the loaded charcoal is reusable for three times, and so might be economical for nickel recovery from waste battery.

Keywords: charcoal, impregnated, LIX-84I, nickel, recovery

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Authors: Jerome Blackman, Pamela Franklin, Volha Roshchanka

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The US coal mining sector accounts for 6% of total US Methane emissions (2021). 60% of US coal mining methane emissions come from active underground mine ventilation systems. Abandoned mines contribute about 13% of methane emissions from coal mining. While there are thousands of abandoned underground coal mines in the US, the Environmental Protection Agency (EPA) estimates that fewer than 100 have sufficient methane resources for viable methane recovery and use projects. Many abandoned mines are in remote areas far from potential energy customers and may be flooded, further complicating methane recovery. Because these mines are no longer active, recovery projects can be simpler to implement.

Keywords: abandoned mines, coal mine methane, coal mining, methane emissions, methane mitigation, recovery and use

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Authors: Rima Alfaraj, Abeer Alarawi, Murtadha AlTammar

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The global energy landscape heavily relies on the oil and gas industry, which faces the critical challenge of reducing its carbon footprint. To address this issue, the integration of advanced materials like aerogels has emerged as a promising solution to enhance sustainability and environmental performance within the industry. This study thoroughly examines the application of aerogel-based technologies in the oil and gas sector, focusing particularly on their role in carbon capture and storage (CCS) initiatives. Aerogels, known for their exceptional properties, such as high surface area, low density, and customizable pore structure, have garnered attention for their potential in various CCS strategies. The review delves into various fabrication techniques utilized in producing aerogel materials, including sol-gel, supercritical drying, and freeze-drying methods, to assess their suitability for specific industry applications. Beyond fabrication, the practicality of aerogel materials in critical areas such as flow assurance, enhanced oil recovery, and thermal insulation is explored. The analysis spans a wide range of applications, from potential use in pipelines and equipment to subsea installations, offering valuable insights into the real-world implementation of aerogels in the oil and gas sector. The paper also investigates the adsorption and storage capabilities of aerogel-based sorbents, showcasing their effectiveness in capturing and storing carbon dioxide (CO₂) molecules. Optimization of pore size distribution and surface chemistry is examined to enhance the affinity and selectivity of aerogels towards CO₂, thereby improving the efficiency and capacity of CCS systems. Additionally, the study explores the potential of aerogel-based membranes for separating and purifying CO₂ from oil and gas streams, emphasizing their role in the carbon capture and utilization (CCU) value chain in the industry. Emerging trends and future perspectives in integrating aerogel-based technologies within the oil and gas sector are also discussed, including the development of hybrid aerogel composites and advanced functional components to further enhance material performance and versatility. By synthesizing the latest advancements and future directions in aerogel used for CCS applications in the oil and gas industry, this review offers a comprehensive understanding of how these innovative materials can aid in transitioning towards a more sustainable and environmentally conscious energy landscape. The insights provided can assist in strategic decision-making, drive technology development, and foster collaborations among academia, industry, and policymakers to promote the widespread adoption of aerogel-based solutions in the oil and gas sector.

Keywords: CCS, porous, carbon capture, oil and gas, sustainability

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Authors: M. A. García, J. Vinolas, A. Hernando

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Steel is nowadays one of the most important structural materials because of its outstanding mechanical properties. Therefore, in order to look for a sustainable economic model and to optimize the use of extensive resources, new methods to monitor and prevent failure of steel-based facilities are required. The classical mechanical tests, as for instance building tasting, are invasive and destructive. Moreover, for facilities where the steel element is embedded, (as reinforced concrete) these techniques are directly non applicable. Hence, non-invasive monitoring techniques to prevent failure, without altering the structural properties of the elements are required. Among them, electromagnetic methods are particularly suitable for non-invasive inspection of the mechanical state of steel-based elements. The magnetoelastic coupling effects induce a modification of the electromagnetic properties of an element upon applied stress. Since most steels are ferromagnetic because of their large Fe content, it is possible to inspect their structure and state in a non-invasive way. We present here a distinct electromagnetic method for contactless evaluation of internal stress in steel-based elements. In particular, this method relies on measuring the magnetic induction between two coils with the steel specimen in between them. We found that the alteration of electromagnetic properties of the steel specimen induced by applied stress-induced changes in the induction allowed us to detect stress well below half of the elastic limit of the material. Hence, it represents an outstanding non-invasive method to prevent failure in steel-based facilities. We here describe the theoretical model, present experimental results to validate it and finally we show a practical application for detection of stress and inhomogeneities in train railways.

Keywords: magnetoelastic, magnetic induction, mechanical stress, steel

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Authors: Sauradipta Ganguly, Akhato Sumi, Sanjeet Kumar Hom, Ajan T. Lotha

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Populus deltoides is a hardwood used predominantly for the manufacturing of plywood, matchsticks, and paper in India and hence has a higher economical significance. Wood-decaying fungi cause serious damage to Populus deltoides products, as the wood itself is perishable and vulnerable to decaying agents, decreasing their aesthetical value which in return results in significant monetary loss for the wood industries concerned. The aim of the study was to determine the antifungal activity of Cedrus deodara oil against three primary wood-decaying fungi namely white-rot fungi (Trametes versicolor), brown-rot fungi (Oligoporus placentus) and soft-rot fungi (Xylaria acuminata) on Populus deltoides samples under optimum laboratory conditions. The susceptibility of Populus deltoides samples on the fungal attack and the ability of deodar oil to control colonization of the wood rotting fungi on the samples were assessed. Three concentrations of deodar oil were considered for the study as treating solutions, i.e., 4%, 5%, and 6%. The Populus deltoides samples were treated with treating solutions, and the ability of the same to prevent a fungal attack on the samples were assessed using accelerated test in the laboratory at Biochemical Oxygen Demand incubator at temperature (25 ± 2°C) and relative humidity 70 ± 4%. Efficacy test and statistical analysis of deodar oil against Trametes versicolor, Oligoporus placentus, and Xylariaacuminataon P. deltoides samples exhibited light, minor and negligible mycelia growth at 4 %, 5% and 6% concentrations of deodar oil, respectively. Whereas, moderate to heavy attack was observed on the surface of the control samples. Statistical analysis further established that the treatments were statistically significant and had significantly inhibited fungal growth of all the three fungus spp by almost 3 to 5 times.

Keywords: populus deltoides, Trametes versicolor, Oligoporus placentus, Xylaria acuminata, Deodar oil, treatment

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Authors: Hadeer Ibrahiem, Mahmoud Nasr, Masarrat M. M. Migahid, Mohamed A. Ghazy

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The release of textile wastewater loaded with 1,4 dioxane into aquatic ecosystems has been associated with various human health risks and adverse environmental impacts. In parallel, phytoremediation has been recently employed to treat highly polluted wastewater because various plant species tend to produce certain enzymes as a defense mechanism against a toxic environment. To our best knowledge, this study is the first to investigate the ability of phytoremediation using Eichhornia crassipes for the removal of various pollutants, including 1,4 dioxane, from textile wastewater. A phytoremediation system composed of Eichhornia crassipes was acclimatized for 10 d, and then operated in four lab-scale hydroponic systems, viz., negative control, positive control, and two different 1,4 dioxane concentration (400 and 500 mg/L). After 11 d of operation, the phytoremediation system achieved removal efficiencies of 67.5±3.4%, 89.4±4.4%, 83.6±3.8% for 1,4 dioxane (at initial concentration 400 mg/L), chemical oxygen demand (COD) (at initial concentration 679 mg/L), and cumulative heavy metals, respectively. The removal of these pollutants was mainly supported by the phyto-sorption and phytodegradation mechanisms. The economic feasibility of this phytoremediation system was validated by estimating the capital and operating costs, requiring 4.6 USD for the treatment of 1 m3 textile wastewater. The study concluded that the phytoremediation process could be used as a practical and economical approach to treat textile wastewater laden with various organic and inorganic pollutants. Due to the observed pollution reduction and human health protection, the study objectives would fulfill the targets of SDG 3 “Good Health and Well-being” and SDG 6 “Clean Water and Sanitation”. Further studies are required to (i) investigate the ability of plant species to withstand higher concentrations of 1,4 dioxane for an extended operation time and (ii) understand the biochemical pathways for the degradation of 1,4 dioxane via the action of plant enzymes and the associated microbial community.

Keywords: 1, 4 dioxane concentrations, hydrophytes, Eichhornia crassipes, phytoremediation effectiveness, SDGs, textile industrial effluent

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Authors: David Sudre

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Today, the National Basketball Association (NBA) is the cultural model of reference for most of the French basketball community stakeholders (players, coaches, team and league managers). In addition to the strong impact it has on how this sport is played and perceived, the NBA also influences the ways professional basketball shows are organized in France (within the Jeep Elite league). The objective of this research is to see how and to what extent the NBA show, as a globalized cultural product, disrupts Jeep Elite's professional basketball cultural codes in the organization of its shows. The article will aim at questioning the intercultural phenomenon at stake in sports cultures in France through the prism of the basketball match. This angle will shed some light on the underlying relationships between local and global elements. The results of this research come from a one-year survey conducted in a small town in northern France, Le Portel, where the Etoile Sportive Saint Michel (ESSM), a Jeep Elite's club, operates. An ethnographic approach was favored. It entailed many participating observations and semi-directive interviews with supporters of the ESSM Le Portel. Through this ethnographic work with the team's fan groups (before the games, during the games and after the games), it was possible for the researchers to understand better all the cultural and identity issues that play out in the "Cauldron," the basketball arena of the ESSM Le Portel. The results demonstrate, at first glance, that many basketball events organized in France are copied from the American model. It seems difficult not to try to imitate the American reference that the NBA represents, whether it be at the French All-Star Game or a Jeep Elite Game at Le Portel. In this case, an acculturation process seems to occur, not only in the way people play but also in the creation of the show (cheerleaders, animations, etc.). However, this American culture of globalized basketball, although re-appropriated, is also being modified by the members of ESSM Le Portel within their locality. Indeed, they juggle between their culture of origin and their culture of reference to build their basketball show within their sociocultural environment. In this way, Le Portel managers and supporters introduce elements that are characteristic of their local culture into the show, such as carnival customs and celebrations, two ingredients that fully contribute to the creation of their identity. Ultimately, in this context of "glocalization," this research will ascertain, on the one hand, that the identity of French basketball becomes harder to outline, and, on the other hand, that the "Cauldron" turns out to be a place to preserve (fantasized) local identities, or even a place of (unconscious) resistance to the dominant model of American basketball culture.

Keywords: basketball, carnival, culture, globalization, identity, show, sport, supporters.

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Authors: Zhan Chen, Wenquan Bi

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This paper focuses on examining the strength of Midori against impossible differential attack. The Midori family of light weight block cipher orienting to energy-efficiency is proposed in ASIACRYPT2015. Using a 6-round property, the authors implement an 11-round impossible differential attack on Midori64 by extending two rounds on the top and three rounds on the bottom. There is enough key space to consider pre-whitening keys in this attack. An impossible differential path that minimises the key bits involved is used to reduce computational complexity. Several additional observations such as partial abort technique are used to further reduce data and time complexities. This attack has data complexity of 2 ⁶⁹·² chosen plaintexts, requires 2 ¹⁴·⁵⁸ blocks of memory and 2 ⁹⁴·⁷ 11- round Midori64 encryptions.

Keywords: cryptanalysis, impossible differential, light weight block cipher, Midori

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Authors: Victor Rocha Carvalho

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The Bonner Sphere Spectrometry was used to obtain the average energy, the fluence rate, and radioprotection quantities such as the personal and ambient dose equivalent of the ²⁴¹AmLi and ²⁴¹AmF isotopic neutron sources used in the Neutron Metrology Laboratory - LN. The counts of the sources were performed with six different spherical moderators around the detector. Through this, the neutron spectrum was obtained by means of the software named NeuraLN, developed by the LN, that uses the neural networks technique. The 241AmLi achieved a result close to the literature, and 241AmF, which contains few published references, acquired a result with a slight variation from the literature. Therefore, besides fulfilling its objective, the work raises questions about a possible standard of the ²⁴¹AmLi and about the lack of work with the ²⁴¹AmF.

Keywords: nuclear physics, neutron metrology, neutron spectrometry, bonner sphere spectrometers

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Authors: Juzhong Tan, William Kerr

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Conching is one critical procedure in chocolate processing, where special flavors are developed, and smooth mouse feel the texture of the chocolate is developed due to particle size reduction of cocoa mass and other additives. Therefore, determination of the particle size and volatile compounds profile of cocoa bean is important for chocolate manufacturers to ensure the quality of chocolate products. Currently, precise particle size measurement is usually done by laser scattering which is expensive and inaccessible to small/medium size chocolate manufacturers. Also, some other alternatives, such as micrometer and microscopy, can’t provide good measurements and provide little information. Volatile compounds analysis of cocoa during conching, has similar problems due to its high cost and limited accessibility. In this study, a self-made electronic nose system consists of gas sensors (TGS 800 and 2000 series) was inserted to a conching machine and was used to monitoring the volatile compound profile of chocolate during the conching. A model correlated volatile compounds profiles along with factors including the content of cocoa, sugar, and the temperature during the conching to particle size of chocolate particles by genetic programming was established. The model was used to predict the particle size reduction of chocolates with different cocoa mass to sugar ratio (1:2, 1:1, 1.5:1, 2:1) at 8 conching time (15min, 30min, 1h, 1.5h, 2h, 4h, 8h, and 24h). And the predictions were compared to laser scattering measurements of the same chocolate samples. 91.3% of the predictions were within the range of later scatting measurement ± 5% deviation. 99.3% were within the range of later scatting measurement ± 10% deviation.

Keywords: cocoa bean, conching, electronic nose, genetic programming

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Authors: ShyamKrishna Kirithivasan, Shreyas Battula, Aditi Soori, Richa Ramesh, Ramamoorthy Srinath

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The human brain, among the most complex and mysterious aspects of the body, harbors vast potential for extensive exploration. Unraveling these enigmas, especially within neural perception and cognition, delves into the realm of neural decoding. Harnessing advancements in generative AI, particularly in Visual Computing, seeks to elucidate how the brain comprehends visual stimuli observed by humans. The paper endeavors to reconstruct human-perceived visual stimuli using Functional Magnetic Resonance Imaging (fMRI). This fMRI data is then processed through pre-trained deep-learning models to recreate the stimuli. Introducing a new architecture named LatentNeuroNet, the aim is to achieve the utmost semantic fidelity in stimuli reconstruction. The approach employs a Latent Diffusion Model (LDM) - Stable Diffusion v1.5, emphasizing semantic accuracy and generating superior quality outputs. This addresses the limitations of prior methods, such as GANs, known for poor semantic performance and inherent instability. Text conditioning within the LDM's denoising process is handled by extracting text from the brain's ventral visual cortex region. This extracted text undergoes processing through a Bootstrapping Language-Image Pre-training (BLIP) encoder before it is injected into the denoising process. In conclusion, a successful architecture is developed that reconstructs the visual stimuli perceived and finally, this research provides us with enough evidence to identify the most influential regions of the brain responsible for cognition and perception.

Keywords: BLIP, fMRI, latent diffusion model, neural perception.

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Authors: Shafait Hussain Ali

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Since its outbreak in China, the Covid_19 19 disease has been caused by the corona virus SARS N coyote 2. Italy was the first Western country to be severely affected, and the first country to take drastic measures to control the disease. In start of December 2019, the sudden outbreaks of the Coronary Virus Disease was caused by a new Corona 2 virus (SARS-CO2) of acute respiratory syndrome in china city Wuhan. The World Health Organization declared the epidemic a public health emergency of international concern on January 30, 2020,. On February 14, 2020, 49,053 laboratory-confirmed deaths and 1481 deaths have been reported worldwide. The threat of the disease has forced most of the governments to implement various control measures. Therefore it becomes necessary to analyze the Italian data very carefully, in particular to investigates and to find out the present condition and the number of infected persons in the form of positive cases, death, hospitalized or some other features of infected persons will clear in simple form. So used such a model that will clearly shows the real facts and figures and also understandable to every readable person which can get some real benefit after reading it. The model used must includes(total positive cases, current positive cases, hospitalized patients, death, recovered peoples frequency rates ) all features that explains and clear the wide range facts in very simple form and helpful to administration of that country.

Keywords: machine learning tools and techniques, rapid miner tool, Naive-Bayes algorithm, predictions

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Abhishek Kumar, Mohamed Awadein, Georg Gramse, Luyang Song, He Sun, Wolfgang Schofberger, Stefan Müllegger

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Electron transfer is a crucial part of chemical reactions which drive everyday processes. With the help of an electro-chemical radio frequency scanning tunneling microscopy (EC-RF-STM) setup, we are observing single electron mediated oxidation-reduction processes in molecules like ferrocene and transition metal corroles. Combining the techniques of scanning microwave microscopy and cyclic voltammetry allows us to monitor such processes with attoampere sensitivity. A systematic study of such phenomena would be critical to understanding the nano-scale behavior of catalysts, molecular sensors, and batteries relevant to the development of novel material and energy applications.

Keywords: radiofrequency, STM, cyclic voltammetry, ferrocene

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Juan Huang, Nanqu Huang, Jingshan Shi, Yu Qiu

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Objectives: There are pathophysiological connections between type 2 diabetes mellitus (T2DM) and Alzheimer's disease (AD), and research on drugs with hypoglycemic and beta-amyloid (Aβ)-clearing effects have great therapeutic potential for AD. Dendrobium nobile Lindl. Alkaloids (DNLA) as one of the active compounds of Dendrobium nobile Lindl. In this study, we attempted to verify the hypoglycemic effect and investigate the effects of DNLA on the amyloid precursor protein (APP) metabolic pathway of the hippocampus in db/db mice. Methods: 4-weeks-old male C57BL/KsJ mice were the control group. And the same age and sexuality db/db mice were: model, DNLA-L (20 mg/kg), DNLA-M (40 mg/kg), and DNLA-H (80 mg/kg). After, mice were treated with different concentrations of DNLA for 17 weeks. The fasting blood glucose (FBG) was detected by glucose oxidase assay every week from the 4th to last week. The protein expression of β-amyloid 1-42 (Aβ1-42), β-site amyloid precursor protein-cleaving enzyme 1 (BACE1), and APP were examined by Western blotting. Results: The concentration of FBG and the protein expression of Aβ1-42, BACE1, and APP were increased in the hippocampus of the model group. Moreover, DNLA not only significantly decreased the concentration of FBG but also reduced the protein expressions of Aβ1-42, BACE1 and APP in the hippocampus of db/db mice in a dose-dependent manner. Conclusions: DNLA can decrease the protein expressions of Aβ1-42 in the hippocampus of db/db mice, and the mechanism may be involved in the APP metabolic pathway.

Keywords: Alzheimer's disease, type 2 diabetes mellitus, β-site amyloid precursor protein-cleaving enzyme 1, traditional Chinese medicines, beta-amyloid

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Authors: Pamela R. Jackson, Andrea Hawkins-Daarud, Cassandra R. Rickertsen, Kamala Clark-Swanson, Scott A. Whitmire, Kristin R. Swanson

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Glioblastoma Multiforme (GBM), the most common primary brain tumor, often presents with hyperintensity on T2-weighted or T2-weighted fluid attenuated inversion recovery (T2/FLAIR) magnetic resonance imaging (MRI). This hyperintensity corresponds with vasogenic edema, however there are likely many infiltrating tumor cells within the hyperintensity as well. While MRIs do not directly indicate tumor cells, MRIs do reflect the microenvironmental water abnormalities caused by the presence of tumor cells and edema. The inherent heterogeneity and resulting MRI features of GBMs complicate assessing disease response. To understand how hyperintensity on T2/FLAIR MRI may correlate with edema in the extracellular space (ECS), a multi-compartmental MRI signal equation which takes into account tissue compartments and their associated volumes with input coming from a mathematical model of glioma growth that incorporates edema formation was explored. The reasonableness of two possible extracellular space schema was evaluated by varying the T2 of the edema compartment and calculating the possible resulting T2s in tumor and peripheral edema. In the mathematical model, gliomas were comprised of vasculature and three tumor cellular phenotypes: normoxic, hypoxic, and necrotic. Edema was characterized as fluid leaking from abnormal tumor vessels. Spatial maps of tumor cell density and edema for virtual tumors were simulated with different rates of proliferation and invasion and various ECS expansion schemes. These spatial maps were then passed into a multi-compartmental MRI signal model for generating simulated T2/FLAIR MR images. Individual compartments’ T2 values in the signal equation were either from literature or estimated and the T2 for edema specifically was varied over a wide range (200 ms – 9200 ms). T2 maps were calculated from simulated images. T2 values based on simulated images were evaluated for regions of interest (ROIs) in normal appearing white matter, tumor, and peripheral edema. The ROI T2 values were compared to T2 values reported in literature. The expanding scheme of extracellular space is had T2 values similar to the literature calculated values. The static scheme of extracellular space had a much lower T2 values and no matter what T2 was associated with edema, the intensities did not come close to literature values. Expanding the extracellular space is necessary to achieve simulated edema intensities commiserate with acquired MRIs.

Keywords: extracellular space, glioblastoma multiforme, magnetic resonance imaging, mathematical modeling

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Authors: Yousef Farhaoui

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An IDS is a tool which is used to improve the level of security. We present in this paper different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection) for securing web servers and applications by the Intrusion Detection System (IDS).

Keywords: intrusion detection, architectures, characteristic, tools, security, web server

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Authors: Mozhdeh Khalili Kordabadi

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Textiles play a vital role in human life, particularly in the form of clothing. However, the alarming rate at which textiles end up in landfills presents a significant environmental risk. With approximately one garbage truck per second being filled with discarded textiles, urgent measures are required to mitigate this trend. Governments and responsible organizations are calling upon various stakeholders to shift from a linear economy to a circular economy model in the textile industry. This article highlights several key approaches that can be undertaken to address this pressing issue. These approaches include the creation of renewable raw material sources, rethinking production processes, maximizing the use and reuse of textile products, implementing reproduction and recycling strategies, exploring redistribution to new markets, and finding innovative means to extend the lifespan of textiles. By adopting these strategies, the textile industry can contribute to a more sustainable and environmentally friendly future. Introduction: Textiles, particularly clothing, are essential to human existence. However, the rapid accumulation of textiles in landfills poses a significant threat to the environment. This article explores the urgent need for the textile industry to transition from a linear economy model to a circular economy model. The linear model, characterized by the creation, use, and disposal of textiles, is unsustainable in the long term. By adopting a circular economy approach, the industry can minimize waste, reduce environmental impact, and promote sustainable practices. This article outlines key approaches that can be undertaken to drive this transition. Approaches to Address Environmental Challenges: Creation of Renewable Raw Materials Sources: Exploring and promoting the use of renewable and sustainable raw materials, such as organic cotton, hemp, and recycled fibers, can significantly reduce the environmental footprint of textile production. Rethinking Production Processes: Implementing cleaner production techniques, optimizing resource utilization, and minimizing waste generation are crucial steps in reducing the environmental impact of textile manufacturing. Maximizing Use and Reuse of Textile Products: Encouraging consumers to prolong the lifespan of textile products through proper care, maintenance, and repair services can reduce the frequency of disposal and promote a culture of sustainability. Reproduction and Recycling Strategies: Investing in innovative technologies and infrastructure to enable efficient reproduction and recycling of textiles can close the loop and minimize waste generation. Redistribution of Textiles to New Markets: Exploring opportunities to redistribute textiles to new and parallel markets, such as resale platforms, can extend their lifecycle and prevent premature disposal. Improvising Means to Extend Textile Lifespan: Encouraging design practices that prioritize durability, versatility, and timeless aesthetics can contribute to prolonging the lifespan of textiles. Conclusion: The textile industry must urgently transition from a linear economy to a circular economy model to mitigate the adverse environmental impact caused by textile waste. By implementing the outlined approaches, such as sourcing renewable raw materials, rethinking production processes, promoting reuse and recycling, exploring new markets, and extending the lifespan of textiles, stakeholders can work together to create a more sustainable and environmentally friendly textile industry. These measures require collective action and collaboration between governments, organizations, manufacturers, and consumers to drive positive change and safeguard the planet for future generations.

Keywords: textiles, circular economy, environmental challenges, renewable raw materials, production processes, reuse, recycling, redistribution, textile lifespan extension.

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Authors: Achirawatt Tungsombatsanti, Toansakul Santiboon, Kamon Ponkham

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Strategies of the STEM education was aimed to prepare of an interdisciplinary and applied approach for the instructional of science, technology, engineering, and mathematics in an integrated students for enhancing engagement of their science skills to the Problem-Based Learning (PBL) method in Borabu School with a sample consists of 80 students in 2 classes at the 12th grade level of their learning achievements on electromagnetic issue. Research administrations were to separate on two different instructional model groups, the 40-experimental group was designed with the STEM instructional experimenting preparation and induction in a 40-student class and the controlling group using the PBL was designed to students identify what they already know, what they need to know, and how and where to access new information that may lead to the resolution of the problem in other class. The learning environment perceptions were obtained using the 35-item Physics Laboratory Environment Inventory (PLEI). Students’ creating attitude skills’ sustainable development toward physics were assessed with the Test Of Physics-Related Attitude (TOPRA) The term scaling was applied to the attempts to measure the attitude objectively with the TOPRA was used to assess students’ perceptions of their science attitude toward physics. Comparisons between pretest and posttest techniques were assessed students’ learning achievements on each their outcomes from each instructional model, differently. The results of these findings revealed that the efficiency of the PLB and the STEM based on criteria indicate that are higher than the standard level of the 80/80. Statistically, significant of students’ learning achievements to their later outcomes on the controlling and experimental physics class groups with the PLB and the STEM instructional designs were differentiated between groups at the .05 level, evidently. Comparisons between the averages mean scores of students’ responses to their instructional activities in the STEM education method are higher than the average mean scores of the PLB model. Associations between students’ perceptions of their physics classes to their attitudes toward physics, the predictive efficiency R2 values indicate that 77%, and 83% of the variances in students’ attitudes for the PLEI and the TOPRA in physics environment classes were attributable to their perceptions of their physics PLB and the STEM instructional design classes, consequently. An important of these findings was contributed to student understanding of scientific concepts, attitudes, and skills as evidence with STEM instructional ought to higher responding than PBL educational teaching. Statistically significant between students’ learning achievements were differentiated of pre and post assessments which overall on two instructional models.

Keywords: learning instructional managements, problem-based learning, STEM education, method, enhancement, students learning achievements, science attitude, physics classes

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