Search results for: pharmaceutical applications

Authors: Ok-Kyun Im, Kyoung Hee Kim

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We live in an era that faces global challenges of climate changes and resource depletion. With the rapid urbanization and growing energy consumption in the built environment, building facades become ever more important in architectural practice and environmental stewardship. Furthermore, building facade undergoes complex dynamics of social, cultural, environmental and technological changes. Kinetic facades have drawn attention of architects, designers, and engineers in the field of adaptable, responsive and interactive architecture since 1980’s. Materials and building technologies have gradually evolved to address the technical implications of kinetic facades. The kinetic façade is becoming an independent system of the building, transforming the design methodology to sustainable building solutions. Accordingly, there is a need for a new design methodology to guide the design of a kinetic façade and evaluate its sustainable performance. The research objectives are two-fold: First, to establish a new design methodology for kinetic facades and second, to develop a micro-oculi façade system and assess its performance using the established design method. The design approach to the micro-oculi facade is comprised of 1) façade geometry optimization and 2) dynamic building energy simulation. The façade geometry optimization utilizes multi-objective optimization process, aiming to balance the quantitative and qualitative performances to address the sustainability of the built environment. The dynamic building energy simulation was carried out using EnergyPlus and Radiance simulation engines with scripted interfaces. The micro-oculi office was compared with an office tower with a glass façade in accordance with ASHRAE 90.1 2013 to understand its energy efficiency. The micro-oculi facade is constructed with an array of circular frames attached to a pair of micro-shades called a micro-oculus. The micro-oculi are encapsulated between two glass panes to protect kinetic mechanisms with longevity. The micro-oculus incorporates rotating gears that transmit the power to adjacent micro-oculi to minimize the number of mechanical parts. The micro-oculus rotates around its center axis with a step size of 15deg depending on the sun’s position while maximizing daylighting potentials and view-outs. A 2 ft by 2ft prototyping was undertaken to identify operational challenges and material implications of the micro-oculi facade. In this research, a systematic design methodology was proposed, that integrates multi-objectives of kinetic façade design criteria and whole building energy performance simulation within a holistic design process. This design methodology is expected to encourage multidisciplinary collaborations between designers and engineers to collaborate issues of the energy efficiency, daylighting performance and user experience during design phases. The preliminary energy simulation indicated that compared to a glass façade, the micro-oculi façade showed energy savings due to its improved thermal properties, daylighting attributes, and dynamic solar performance across the day and seasons. It is expected that the micro oculi façade provides a cost-effective, environmentally-friendly, sustainable, and aesthetically pleasing alternative to glass facades. Recommendations for future studies include lab testing to validate the simulated data of energy and optical properties of the micro-oculi façade. A 1:1 performance mock-up of the micro-oculi façade can suggest in-depth understanding of long-term operability and new development opportunities applicable for urban façade applications.

Keywords: energy efficiency, kinetic facades, sustainable architecture, urban facades

Procedia PDF Downloads 255

Authors: Satya Narayan

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India, a rapidly growing economy with a burgeoning population, grapples with the dual challenge of meeting rising energy demands and reducing its carbon footprint. Geothermal energy, an often overlooked and underutilized renewable source, holds immense potential for addressing this challenge. Geothermal resources offer a valuable, consistent, and sustainable energy source, and may significantly contribute to India's energy. This paper discusses the importance of geothermal exploration in India, emphasizing its role in achieving sustainable energy production while mitigating environmental impacts. It also delves into the methodology employed to assess geothermal resource feasibility, including geophysical surveys and borehole drilling. The results and discussion sections highlight promising geothermal sites across India, illuminating the nation's vast geothermal potential. It detects potential geothermal reservoirs, characterizes subsurface structures, maps temperature gradients, monitors fluid flow, and estimates key reservoir parameters. Globally, geothermal energy falls into high and low enthalpy categories, with India mainly having low enthalpy resources, especially in hot springs. The northwestern Himalayan region boasts high-temperature geothermal resources due to geological factors. Promising sites, like Puga Valley, Chhumthang, and others, feature hot springs suitable for various applications. The Son-Narmada-Tapti lineament intersects regions rich in geological history, contributing to geothermal resources. Southern India, including the Godavari Valley, has thermal springs suitable for power generation. The Andaman-Nicobar region, linked to subduction and volcanic activity, holds high-temperature geothermal potential. Geophysical surveys, utilizing gravity, magnetic, seismic, magnetotelluric, and electrical resistivity techniques, offer vital information on subsurface conditions essential for detecting, evaluating, and exploiting geothermal resources. The gravity and magnetic methods map the depth of the mantle boundary (high-temperature) and later accurately determine the Curie depth. Electrical methods indicate the presence of subsurface fluids. Seismic surveys create detailed sub-surface images, revealing faults and fractures and establishing possible connections to aquifers. Borehole drilling is crucial for assessing geothermal parameters at different depths. Detailed geochemical analysis and geophysical surveys in Dholera, Gujarat, reveal untapped geothermal potential in India, aligning with renewable energy goals. In conclusion, geophysical surveys and borehole drilling play a pivotal role in economically viable geothermal site selection and feasibility assessments. With ongoing exploration and innovative technology, these surveys effectively minimize drilling risks, optimize borehole placement, aid in environmental impact evaluations, and facilitate remote resource exploration. Their cost-effectiveness informs decisions regarding geothermal resource location and extent, ultimately promoting sustainable energy and reducing India's reliance on conventional fossil fuels.

Keywords: geothermal resources, geophysical methods, exploration, exploitation

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Authors: Satam Alotibi, Osama A. Hussein, Aziz H. Al-Shaibani, Nawaf A. Al-Aqeel, Abdellah Kaiba, Fatehia S. Alhakami, Mohammed Alyami, Talal F. Qahtan

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The demand for sustainable and efficient energy conversion using solar energy has grown rapidly in recent years. In this pursuit, solar-to-chemical conversion has emerged as a promising approach, with oxygen vacancies-rich tungsten trioxide (WO₃) playing a crucial role. This study presents a method for synthesizing oxygen vacancies-rich WO3, resulting in a significant enhancement of its photocatalytic activity, representing a significant step towards sustainable energy solutions. Experimental results underscore the importance of oxygen vacancies in modifying the properties of WO₃. These vacancies introduce additional energy states within the material, leading to a reduction in the bandgap, increased light absorption, and acting as electron traps, thereby reducing emissions. Our focus lies in developing oxygen vacancies-rich WO₃, which demonstrates unparalleled potential for improved photocatalytic applications. The effectiveness of oxygen vacancies-rich WO₃ in solar-to-chemical conversion was showcased through rigorous assessments of its photocatalytic degradation performance. Sunlight irradiation was employed to evaluate the material's effectiveness in degrading organic pollutants in wastewater. The results unequivocally demonstrate the superior photocatalytic performance of oxygen vacancies-rich WO₃ compared to conventional WO₃ nanomaterials, establishing its efficacy in sustainable and efficient energy conversion. Furthermore, the synthesized material is utilized to fabricate films, which are subsequently employed in immobilized WO₃ and oxygen vacancies-rich WO₃ reactors for water purification under natural sunlight irradiation. This application offers a sustainable and efficient solution for water treatment, harnessing solar energy for effective decontamination. In addition to investigating the photocatalytic capabilities, we extensively analyze the structural and chemical properties of the synthesized material. The synthesis process involves in situ thermal reduction of WO₃ nano-powder in a nitrogen environment, meticulously monitored using thermogravimetric analysis (TGA) to ensure precise control over the synthesis of oxygen vacancies-rich WO₃. Comprehensive characterization techniques such as UV-Vis spectroscopy, X-ray photoelectron spectroscopy (XPS), FTIR, Raman spectroscopy, scanning electron microscopy (SEM), transmission electron microscopy (TEM), and selected area electron diffraction (SAED) provide deep insights into the material's optical properties, chemical composition, elemental states, structure, surface properties, and crystalline structure. This study represents a significant advancement in sustainable energy conversion through solar-to-chemical processes and water purification. By harnessing the unique properties of oxygen vacancies-rich WO₃, we not only enhance our understanding of energy conversion mechanisms but also pave the way for the development of highly efficient and environmentally friendly photocatalytic materials. The application of this material in water purification demonstrates its versatility and potential to address critical environmental challenges. These findings bring us closer to a sustainable energy future and cleaner water resources, laying a solid foundation for a more sustainable planet.

Keywords: sustainable energy conversion, solar-to-chemical conversion, oxygen vacancies-rich tungsten trioxide (WO₃), photocatalytic activity enhancement, water purification

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Authors: Mahyar Mehrafarin, Reza Mehrafarin

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The Sistan region in eastern Iran is a significant archaeological area in Iran and the Middle East, encompassing 10,000 square kilometers. Previous archeological field surveys have identified 1662 ancient sites dating from prehistoric periods to the Islamic period. Research Aim: This article aims to explore the utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, and the benefits derived from their implementation. Methodology: The research employs a descriptive-analytical approach combined with field methods. New technologies and software, such as GPS, drones, magnetometers, equipped cameras, satellite images, and software programs like GIS, Map source, and Excel, were utilized to collect information and analyze data. Findings: The use of modern technologies and computers in archaeological field surveys proved to be essential. Traditional archaeological activities, such as excavation and field surveys, are time-consuming and costly. Employing modern technologies helps in preserving ancient sites, accurately recording archaeological data, reducing errors and mistakes, and facilitating correct and accurate analysis. Creating a comprehensive and accessible database, generating statistics, and producing graphic designs and diagrams are additional advantages derived from the use of efficient technologies in archaeology. Theoretical Importance: The integration of computers and modern technologies in archaeology contributes to interdisciplinary collaborations and facilitates the involvement of specialists from various fields, such as geography, history, art history, anthropology, laboratory sciences, and computer engineering. The utilization of computers in archaeology spanned across diverse areas, including database creation, statistical analysis, graphics implementation, laboratory and engineering applications, and even artificial intelligence, which remains an unexplored area in Iranian archaeology. Data Collection and Analysis Procedures: Information was collected using modern technologies and software, capturing geographic coordinates, aerial images, archeogeophysical data, and satellite images. This data was then inputted into various software programs for analysis, including GIS, Map source, and Excel. The research employed both descriptive and analytical methods to present findings effectively. Question Addressed: The primary question addressed in this research is how the use of modern technologies and computers in archeological field surveys in Sistan, Iran, can enhance archaeological data collection, preservation, analysis, and accessibility. Conclusion: The utilization of modern technologies and computers in archaeological field surveys in Sistan, Iran, has proven to be necessary and beneficial. These technologies aid in preserving ancient sites, accurately recording archaeological data, reducing errors, and facilitating comprehensive analysis. The creation of accessible databases, statistics generation, graphic designs, and interdisciplinary collaborations are further advantages observed. It is recommended to explore the potential of artificial intelligence in Iranian archaeology as an unexplored area. The research has implications for cultural heritage organizations, archaeology students, and universities involved in archaeological field surveys in Sistan and Baluchistan province. Additionally, it contributes to enhancing the understanding and preservation of Iran's archaeological heritage.

Keywords: archaeological surveys, computer use, iran, modern technologies, sistan

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Authors: Mamert Mbonimpa, Ousseynou Kanteye, Élysée Tshibangu Ngabu, Rachid Amrou, Abdelkabir Maqsoud, Tikou Belem

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The management of mine wastes (waste rocks and tailings) containing sulphide minerals such as pyrite and pyrrhotite represents the main environmental challenge for the mining industry. Indeed, acid mine drainage (AMD) can be generated when these wastes are exposed to water and air. AMD is characterized by low pH and high concentrations of heavy metals, which are toxic to plants, animals, and humans. It affects the quality of the ecosystem through water and soil pollution. Different techniques involving soil materials can be used to control AMD generation, including impermeable covers (compacted clays) and oxygen barriers. The latter group includes covers with capillary barrier effects (CCBE), a multilayered cover that include the moisture retention layer playing the role of an oxygen barrier. Once AMD is produced at a mine site, it must be treated so that the final effluent at the mine site complies with regulations and can be discharged into the environment. Active neutralization with lime is one of the treatment methods used. This treatment produces sludge that is usually stored in sedimentation ponds. Other sludge management alternatives have been examined in recent years, including sludge co-disposal with tailings or waste rocks, disposal in underground mine excavations, and storage in technical landfill sites. Considering the ability of AMD neutralization sludge to maintain an alkaline to neutral pH for decades or even centuries, due to the excess alkalinity induced by residual lime within the sludge, valorization of sludge in specific applications could be an interesting management option. If done efficiently, the reuse of sludge could free up storage ponds and thus reduce the environmental impact. It should be noted that mixtures of sludge and soils could potentially constitute usable materials in CCBE for the rehabilitation of acid-generating mine sites, while sludge alone is not suitable for this purpose. The high sludge water content (up to 300%), even after sedimentation, can, however, constitute a geotechnical challenge. Adding lime to the mixtures can reduce the water content and improve the geotechnical properties. The objective of this paper is to investigate the impact of the sludge content (30, 40 and 50%) in sand-sludge mixtures (SSM) on their hydrogeotechnical properties (compaction, shrinkage behaviour, saturated hydraulic conductivity, and water retention curve). The impact of lime addition (dosages from 2% to 6%) on the moisture content, dry density after compaction and saturated hydraulic conductivity of SSM was also investigated. Results showed that sludge adding to sand significantly improves the saturated hydraulic conductivity and water retention capacity, but the shrinkage increased with sludge content. The dry density after compaction of lime-treated SSM increases with the lime dosage but remains lower than the optimal dry density of the untreated mixtures. The saturated hydraulic conductivity of lime-treated SSM after 24 hours of cure decreases by 3 orders of magnitude. Considering the hydrogeotechnical properties obtained with these mixtures, it would be possible to design CCBE whose moisture retention layer is made of SSM. Physical laboratory models confirmed the performance of such CCBE.

Keywords: mine waste, AMD neutralization sludge, sand-sludge mixture, hydrogeotechnical properties, mine site reclamation, CCBE

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Authors: Oscar Bareiro, Johannes Sackmann, Thomas Gries

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Carbon fiber reinforced polymer composites (CFRP) are used in a wide variety of applications due to its advantageous properties and design versatility. The braiding process enables the manufacture of components with good toughness and fatigue strength. However, failure mechanisms of CFRPs are complex and still present challenges associated with their maintenance and repair. Within the broad scope of structural health monitoring (SHM), strain monitoring can be applied to composite materials to improve reliability, reduce maintenance costs and safely exhaust service life. Traditional SHM systems employ e.g. fiber optics, piezoelectrics as sensors, which are often expensive, time consuming and complicated to implement. A cost-efficient alternative can be the exploitation of the conductive properties of fiber-based sensors such as carbon, copper, or constantan - a copper-nickel alloy – that can be utilized as sensors within composite structures to achieve strain monitoring. This allows the structure to provide feedback via electrical signals to a user which are essential for evaluating the structural condition of the structure. This work presents a strategy for the in-process integration of resistance-based sensors (Elektrisola Feindraht AG, CuNi23Mn, Ø = 0.05 mm) into textile preforms during its manufacture via the braiding process (Herzog RF-64/120) to achieve strain monitoring of braided composites. For this, flat samples of instrumented composite laminates of carbon fibers (Toho Tenax HTS40 F13 24K, 1600 tex) and epoxy resin (Epikote RIMR 426) were manufactured via vacuum-assisted resin infusion. These flat samples were later cut out into test specimens and the integrated sensors were wired to the measurement equipment (National Instruments, VB-8012) for data acquisition during the execution of mechanical tests. Quasi-static tests were performed (tensile, 3-point bending tests) following standard protocols (DIN EN ISO 527-1 & 4, DIN EN ISO 14132); additionally, dynamic tensile tests were executed. These tests were executed to assess the sensor response under different loading conditions and to evaluate the influence of the sensor presence on the mechanical properties of the material. Several orientations of the sensor with regards to the applied loading and sensor placements inside the laminate were tested. Strain measurements from the integrated sensors were made by programming a data acquisition code (LabView) written for the measurement equipment. Strain measurements from the integrated sensors were then correlated to the strain/stress state for the tested samples. From the assessment of the sensor integration approach it can be concluded that it allows for a seamless sensor integration into the textile preform. No damage to the sensor or negative effect on its electrical properties was detected during inspection after integration. From the assessment of the mechanical tests of instrumented samples it can be concluded that the presence of the sensors does not alter significantly the mechanical properties of the material. It was found that there is a good correlation between resistance measurements from the integrated sensors and the applied strain. It can be concluded that the correlation is of sufficient accuracy to determinate the strain state of a composite laminate based solely on the resistance measurements from the integrated sensors.

Keywords: braiding process, in-process sensor integration, instrumented composite material, resistance-based sensor, strain monitoring

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Authors: Chuanxiang Cheng, Tiantian Min, Jin Yue

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Antimicrobial active packaging enables extensive biological effects to improve food safety. However, the efficacy of antimicrobial packaging hinges on factors including the diffusion rate of the active agent toward the food surface, the initial content in the antimicrobial agent, and the targeted food shelf life. Among the possibilities of antimicrobial packaging design, an interesting approach involves the incorporation of volatile antimicrobial agents into the packaging material. In this case, the necessity for direct contact between the active packaging material and the food surface is mitigated, as the antimicrobial agent exerts its action through the packaging headspace atmosphere towards the food surface. However, it still remains difficult to achieve controlled and precise release of bioactive compounds to the specific target location with required quantity in food packaging applications. Remarkably, the development of stimuli-responsive materials for electrospinning has introduced the possibility of achieving controlled release of active agents under specific conditions, thereby yielding enduring biological effects. Relative humidity (RH) for the storage of food categories such as meat and aquatic products typically exceeds 90%. Consequently, high RH can be used as an abiotic trigger for the release of active agents to prevent microbial growth. Hence, a novel RH - responsive polyvinyl alcohol/chitosan (PVA/CS) composite nanofibrous film incorporated with 4-terpineol/β-cyclodextrin inclusion complexes (4-TA@β-CD ICs) was engineered by electrospinning that can be deposited as a functional packaging materials. The characterization results showed the thermal stability of the films was enhanced after the incorporation due to the hydrogen bonds between ICs and polymers. Remarkably, the 4 wt% 4-TA@β-CD ICs/PVA/CS film exhibited enhanced crystallinity, moderate hydrophilic (Water contact angle of 81.53°), light barrier property (Transparency of 1.96%) and water resistance (Water vapor permeability of 3.17 g mm/m2 h kPa). Moreover, this film also showed optimized mechanical performance with a Young’s modulus of 11.33 MPa, a tensile strength of 19.99 MPa and an elongation at break of 4.44 %. Notably, the antioxidant and antibacterial properties of this packaging material were significantly improved. The film demonstrated the half-inhibitory concentrations (IC50) values of 87.74% and 85.11% for scavenging 2,2-diphenyl-1-picrylhydrazyl (DPPH) and 2, 2′-azinobis (3-ethylbenzothiazoline-6-sulfonic) (ABTS) free radicals, respectively, in addition to an inhibition efficiency of 65% against Shewanella putrefaciens, the characteristic bacteria in aquatic products. Most importantly, the film achieved controlled release of 4-TA under high 98% RH by inducing the plasticization of polymers caused by water molecules, swelling of polymer chains, and destruction of hydrogen bonds within the cyclodextrin inclusion complex. Consequently, low relative humidity is suitable for the preservation of nanofibrous film, while high humidity conditions typical in fresh food packaging environments effectively stimulated the release of active compounds in the film. This film with a long-term antimicrobial effect successfully extended the shelf life of Litopenaeus vannamei shrimp to 7 days at 4 °C. This attractive design could pave the way for the development of new food packaging materials.

Keywords: controlled release, electrospinning, nanofibrous film, relative humidity–responsive, shrimp preservation

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Authors: Deon Bezuidenhout

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Pre-seeding with autologous endothelial cells improves the long-term patency of synthetic vascular grafts levels obtained with autografts, but is limited to a single centre due to resource, time and other constraints. Spontaneous in vivo endothelialization would obviate the need for pre-seeding, but has been shown to be absent in man due to limited transanastomotic and fallout healing, and the lack of transmural ingrowth due to insufficient porosity. Two types of graft scaffolds with increased interconnected porosity for improved tissue ingrowth and healing are thus proposed and described. Foam-type polyurethane (PU) scaffolds with small, medium and large, interconnected pores were made by phase inversion and spherical porogen extraction, with and without additional surface modification with covalently attached heparin and subsequent loading with and delivery of growth factors. Fibrillar scaffolds were made either by standard electrospinning using degradable PU (Degrapol®), or by dual electrospinning using non-degradable PU. The latter process involves sacrificial fibres that are co-spun with structural fibres and subsequently removed to increased porosity and pore size. Degrapol samples were subjected to in vitro degradation, and all scaffold types were evaluated in vivo for tissue ingrowth and vascularization using rat subcutaneous model. The foam scaffolds were additionally evaluated in a circulatory (rat infrarenal aortic interposition) model that allows for the grafts to be anastomotically and/or ablumenally isolated to discern and determine endothelialization mode. Foam-type grafts with large (150 µm) pores showed improved subcutaneous healing in terms of vascularization and inflammatory response over smaller pore sizes (60 and 90µm), and vascularization of the large porosity scaffolds was significantly increased by more than 70% by heparin modification alone, and by 150% to 400% when combined with growth factors. In the circulatory model, extensive transmural endothelialization (95±10% at 12 w) was achieved. Fallout healing was shown to be sporadic and limited in groups that were ablumenally isolated to prevent transmural ingrowth (16±30% wrapped vs. 80±20% control; p<0.002). Heparinization and GF delivery improved both mural vascularization and lumenal endothelialization. Degrapol electrospun scaffolds showed decrease in molecular mass and corresponding tensile strength over the first 2 weeks, but very little decrease in mass over the 4w test period. Studies on the effect of tissue ingrowth with and without concomitant degradation of the scaffolds, are being used to develop material models for the finite element modelling. In the case of the dual-spun scaffolds, the PU fibre fraction could be controlled shown to vary linearly with porosity (P = −0.18FF +93.5, r2=0.91), which in turn showed inverse linear correlation with tensile strength and elastic modulus (r2 > 0.96). Calculated compliance and burst pressures of the scaffolds increased with fibre fraction, and compliances matching the human popliteal artery (5-10 %/100 mmHg), and high burst pressures (> 2000 mmHg) could be achieved. Increasing porosity (76 to 82 and 90%) resulted in increased tissue ingrowth from 33±7 to 77±20 and 98±1% after 28d. Transmural endothelialization of highly porous foamed grafts is achievable in a circulatory model, and the enhancement of porosity and tissue ingrowth may hold the key the development of spontaneously endothelializing electrospun grafts.

Keywords: electrospinning, endothelialization, porosity, scaffold, vascular graft

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Authors: Ali Raza

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The dynamic landscape of communication has brought about significant advancements that intersect with the realms of public health and journalism. This abstract explores the evolving synergy between these fields, highlighting how their intersection has contributed to informed societies and improved public health outcomes. In the digital age, communication plays a pivotal role in shaping public perception, policy formulation, and collective action. Public health, concerned with safeguarding and improving community well-being, relies on effective communication to disseminate information, encourage healthy behaviors, and mitigate health risks. Simultaneously, journalism, with its commitment to accurate and timely reporting, serves as the conduit through which health information reaches the masses. Advancements in communication technologies have revolutionized the ways in which public health information is both generated and shared. The advent of social media platforms, mobile applications, and online forums has democratized the dissemination of health-related news and insights. This democratization, however, brings challenges, such as the rapid spread of misinformation and the need for nuanced strategies to engage diverse audiences. Effective collaboration between public health professionals and journalists is pivotal in countering these challenges, ensuring that accurate information prevails. The synergy between public health and journalism is most evident during public health crises. The COVID-19 pandemic underscored the pivotal role of journalism in providing accurate and up-to-date information to the public. However, it also highlighted the importance of responsible reporting, as sensationalism and misinformation could exacerbate the crisis. Collaborative efforts between public health experts and journalists led to the amplification of preventive measures, the debunking of myths, and the promotion of evidence-based interventions. Moreover, the accessibility of information in the digital era necessitates a strategic approach to health communication. Behavioral economics and data analytics offer insights into human decision-making and allow tailored health messages to resonate more effectively with specific audiences. This approach, when integrated into journalism, enables the crafting of narratives that not only inform but also influence positive health behaviors. Ethical considerations emerge prominently in this alliance. The responsibility to balance the public's right to know with the potential consequences of sensational reporting underscores the significance of ethical journalism. Health journalists must meticulously source information from reputable experts and institutions to maintain credibility, thus fortifying the bridge between public health and the public. As both public health and journalism undergo transformative shifts, fostering collaboration between these domains becomes essential. Training programs that familiarize journalists with public health concepts and practices can enhance their capacity to report accurately and comprehensively on health issues. Likewise, public health professionals can gain insights into effective communication strategies from seasoned journalists, ensuring that health information reaches a wider audience. In conclusion, the convergence of public health and journalism, facilitated by communication advancements, is a cornerstone of informed societies. Effective communication strategies, driven by collaboration, ensure the accurate dissemination of health information and foster positive behavior change. As the world navigates complex health challenges, the continued evolution of this synergy holds the promise of healthier communities and a more engaged and educated public.

Keywords: public awareness, journalism ethics, health promotion, media influence, health literacy

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Authors: Jayanta Basak, Somprakash Bandyopadhyay, Parama Bhaumik, Siuli Roy

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To solve the life and livelihood related problems of socially and economically backward rural women in India, several Women Self-Help Groups (WSHG) are formed in Indian villages. WSHGs are micro-communities (with 10-to 15 members) within a village community. WSHGs have been conceived not just to promote savings and provide credit, but also to act as a vehicle of change through the creation of women micro-entrepreneurs at the village level. However, in spite of huge investment and volume of people involved in the whole process, the success is still limited. Most of these entrepreneurial activities happen in small household workspaces where sales are limited to the inconsistent and unpredictable local markets. As a result, these entrepreneurs are perennially trapped in the vicious cycle of low risk taking ability, low investment capacity, low productivity, weak market linkages and low revenue. Market separation including customer-producer separation is one of the key problems in this domain. Researchers suggest that there are four types of market separation: (i) spatial, (ii) financial, (iii) temporal, and (iv) informational, which in turn impacts the nature of markets and marketing. In this context, a large group of intermediaries (the 'middleman') plays important role in effectively reducing the factors that separate markets by utilizing the resource of rural entrepreneurs, their products and thus, accelerate market development. The rural entrepreneurs are heavily dependent on these middlemen for marketing of their products and these middlemen exploit rural entrepreneurs by creating a huge informational separation between the rural producers and end-consumers in the market and thus hiding the profit margins. The objective of this study is to develop a transparent, online communities of purpose among rural and urban entrepreneurs using internet and web 2.0 technologies in order to decrease market separation and improve mutual awareness of available and potential products and market demands. Communities of purpose are groups of people who have an ability to influence, can share knowledge and learn from others, and be committed to achieving a common purpose. In this study, a cluster of SHG women located in a village 'Kandi' of West Bengal, India has been studied closely for six months. These women are primarily engaged in producing garments, soft toys, fabric painting on clothes, etc. These women were equipped with internet-enabled smart-phones where they can use chat applications in local language and common social networking websites like Facebook, Instagram, etc. A few handicraft experts and micro-entrepreneurs from the city (the 'seed') were included in their mobile messaging app group that enables the creation of a 'community of purpose' in order to share thoughts and ideas on product designs, market trends, and practices, and thus decrease the rural-urban market separation. After six months of regular group interaction in mobile messaging app among these rural-urban community members, it is observed that SHG women are empowered now to share their product images, design ideas, showcase, and promote their products in global marketplace using some common social networking websites through which they can also enhance and augment their community of purpose.

Keywords: communities of purpose, market separation, self-help group, social technologies

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Authors: Rita Sassine, Yassine Hassani, Mohamad Al Omari, Stéphanie Guibert

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Building Information Modelling (BIM) is the process of creating, managing, and centralizing information during the building lifecycle. BIM can be used all over a construction project, from the initiation phase to the planning and execution phases to the maintenance and lifecycle management phase. For existing buildings, BIM can be used for specific applications such as lifecycle management. However, most of the existing buildings don’t have a BIM model. Creating a compatible BIM for existing buildings is very challenging. It requires special equipment for data capturing and efforts to convert these data into a BIM model. The main difficulties for such projects are to define the data needed, the level of development (LOD), and the methodology to be adopted. In addition to managing information for an existing building, studying the impact of the built environment is a challenging topic. So, integrating the existing terrain that surrounds buildings into the digital model is essential to be able to make several simulations as flood simulation, energy simulation, etc. Making a replication of the physical model and updating its information in real-time to make its Digital Twin (DT) is very important. The Digital Terrain Model (DTM) represents the ground surface of the terrain by a set of discrete points with unique height values over 2D points based on reference surface (e.g., mean sea level, geoid, and ellipsoid). In addition, information related to the type of pavement materials, types of vegetation and heights and damaged surfaces can be integrated. Our aim in this study is to define the methodology to be used in order to provide a 3D BIM model for the site and the existing building based on the case study of “Ecole Spéciale des Travaux Publiques (ESTP Paris)” school of engineering campus. The property is located on a hilly site of 5 hectares and is composed of more than 20 buildings with a total area of 32 000 square meters and a height between 50 and 68 meters. In this work, the campus precise levelling grid according to the NGF-IGN69 altimetric system and the grid control points are computed according to (Réseau Gédésique Français) RGF93 – Lambert 93 french system with different methods: (i) Land topographic surveying methods using robotic total station, (ii) GNSS (Global Network Satellite sytem) levelling grid with NRTK (Network Real Time Kinematic) mode, (iii) Point clouds generated by laser scanning. These technologies allow the computation of multiple building parameters such as boundary limits, the number of floors, the floors georeferencing, the georeferencing of the 4 base corners of each building, etc. Once the entry data are identified, the digital model of each building is done. The DTM is also modeled. The process of altimetric determination is complex and requires efforts in order to collect and analyze multiple data formats. Since many technologies can be used to produce digital models, different file formats such as DraWinG (DWG), LASer (LAS), Comma-separated values (CSV), Industry Foundation Classes (IFC) and ReViT (RVT) will be generated. Checking the interoperability between BIM models is very important. In this work, all models are linked together and shared on 3DEXPERIENCE collaborative platform.

Keywords: building information modeling, digital terrain model, existing buildings, interoperability

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Authors: Lacramioara Ochiuz, Aurelia Vasile, Iulian Stoleriu, Cristina Ghiciuc, Maria Ignat

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Topical administration of chemotherapeutic agents (eg. carmustine, bexarotene, mechlorethamine etc.) in local treatment of cutaneous T-cell lymphoma (CTCL) is accompanied by multiple side effects, such as contact hypersensitivity, pruritus, skin atrophy or even secondary malignancies. A known method of reducing the side effects of anticancer agent is the development of modified drug release systems using drug incapsulation in biocompatible nanoporous inorganic matrices, such as mesoporous MCM-41 silica. Mesoporous MCM-41 silica is characterized by large specific surface, high pore volume, uniform porosity, and stable dispersion in aqueous medium, excellent biocompatibility, in vivo biodegradability and capacity to be functionalized with different organic groups. Therefore, MCM-41 is an attractive candidate for a wide range of biomedical applications, such as controlled drug release, bone regeneration, protein immobilization, enzymes, etc. The main advantage of this material lies in its ability to host a large amount of the active substance in uniform pore system with adjustable size in a mesoscopic range. Silanol groups allow surface controlled functionalization leading to control of drug loading and release. This study shows (I) the amino-grafting optimization of mesoporous MCM-41 silica matrix by means of co-condensation during synthesis and post-synthesis using APTES (3-aminopropyltriethoxysilane); (ii) loading the therapeutic agent (carmustine) obtaining a modified drug release systems; (iii) determining the profile of in vitro carmustine release from these systems; (iv) assessment of carmustine release kinetics by fitting on four mathematical models. Obtained powders have been described in terms of structure, texture, morphology thermogravimetric analysis. The concentration of the therapeutic agent in the dissolution medium has been determined by HPLC method. In vitro dissolution tests have been done using cell Enhancer in a 12 hours interval. Analysis of carmustine release kinetics from mesoporous systems was made by fitting to zero-order model, first-order model Higuchi model and Korsmeyer-Peppas model, respectively. Results showed that both types of highly ordered mesoporous silica (amino grafted by co-condensation process or post-synthesis) are thermally stable in aqueous medium. In what regards the degree of loading and efficiency of loading with the therapeutic agent, there has been noticed an increase of around 10% in case of co-condensation method application. This result shows that direct co-condensation leads to even distribution of amino groups on the pore walls while in case of post-synthesis grafting many amino groups are concentrated near the pore opening and/or on external surface. In vitro dissolution tests showed an extended carmustine release (more than 86% m/m) both from systems based on silica functionalized directly by co-condensation and after synthesis. Assessment of carmustine release kinetics revealed a release through diffusion from all studied systems as a result of fitting to Higuchi model. The results of this study proved that amino-functionalized mesoporous silica may be used as a matrix for optimizing the anti-cancer topical therapy by loading carmustine and developing prolonged-release systems.

Keywords: carmustine, silica, controlled, release

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Authors: Zhiwu Zheng, Prakhar Kumar, Sigurd Wagner, Naveen Verma, James C. Sturm

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Soft robots have drawn great interest recently due to a rich range of possible shapes and motions they can take on to address new applications, compared to traditional rigid robots. Large-area electronics (LAE) provides a unique platform for creating soft robots by leveraging thin-film technology to enable the integration of a large number of actuators, sensors, and control circuits on flexible sheets. However, the rich shapes and motions possible, especially when interacting with complex environments, pose significant challenges to forming well-generalized and robust models necessary for robot design and control. In this work, we describe an analytical model for predicting the shape and locomotion of a flexible (steel-foil-based) piezoelectric-actuated 2D robot based on Euler-Bernoulli beam theory. It is nominally (unpowered) lying flat on the ground, and when powered, its shape is controlled by an array of piezoelectric thin-film actuators. Key features of the models are its ability to incorporate the significant effects of gravity on the shape and to precisely predict the spatial distribution of friction against the contacting surfaces, necessary for determining inchworm-type motion. We verified the model by developing a distributed discrete element representation of a continuous piezoelectric actuator and by comparing its analytical predictions to discrete-element robot simulations using PyBullet. Without gravity, predicting the shape of a sheet with a linear array of piezoelectric actuators at arbitrary voltages is straightforward. However, gravity significantly distorts the shape of the sheet, causing some segments to flatten against the ground. Our work includes the following contributions: (i) A self-consistent approach was developed to exactly determine which parts of the soft robot are lifted off the ground, and the exact shape of these sections, for an arbitrary array of piezoelectric voltages and configurations. (ii) Inchworm-type motion relies on controlling the relative friction with the ground surface in different sections of the robot. By adding torque-balance to our model and analyzing shear forces, the model can then determine the exact spatial distribution of the vertical force that the ground is exerting on the soft robot. Through this, the spatial distribution of friction forces between ground and robot can be determined. (iii) By combining this spatial friction distribution with the shape of the soft robot, in the function of time as piezoelectric actuator voltages are changed, the inchworm-type locomotion of the robot can be determined. As a practical example, we calculated the performance of a 5-actuator system on a 50-µm thick steel foil. Piezoelectric properties of commercially available thin-film piezoelectric actuators were assumed. The model predicted inchworm motion of up to 200 µm per step. For independent verification, we also modelled the system using PyBullet, a discrete-element robot simulator. To model a continuous thin-film piezoelectric actuator, we broke each actuator into multiple segments, each of which consisted of two rigid arms with appropriate mass connected with a 'motor' whose torque was set by the applied actuator voltage. Excellent agreement between our analytical model and the discrete-element simulator was shown for both for the full deformation shape and motion of the robot.

Keywords: analytical modeling, piezoelectric actuators, soft robot locomotion, thin-film technology

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Authors: Salvatore Luongo, Carlo Luongo

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This paper discusses the implementation solutions to reduce the computational load for the Traffic Situational Awareness with Alerts (TSAA) application, based on Automatic Dependent Surveillance-Broadcast (ADS-B) technology. In 2008, there were 23 total mid-air collisions involving general aviation fixed-wing aircraft, 6 of which were fatal leading to 21 fatalities. These collisions occurred during visual meteorological conditions, indicating the limitations of the see-and-avoid concept for mid-air collision avoidance as defined in the Federal Aviation Administration’s (FAA). The commercial aviation aircraft are already equipped with collision avoidance system called TCAS, which is based on classic transponder technology. This system dramatically reduced the number of mid-air collisions involving air transport aircraft. In general aviation, the same reduction in mid-air collisions has not occurred, so this reduction is the main objective of the TSAA application. The major difference between the original conflict detection application and the TSAA application is that the conflict detection is focused on preventing loss of separation in en-route environments. Instead TSAA is devoted to reducing the probability of mid-air collision in all phases of flight. The TSAA application increases the flight crew traffic situation awareness providing alerts of traffic that are detected in conflict with ownship in support of the see-and-avoid responsibility. The relevant effort has been spent in the design process and the code generation in order to maximize the efficiency and performances in terms of computational load and memory consumption reduction. The TSAA architecture is divided into two high-level systems: the “Threats database” and the “Conflict detector”. The first one receives the traffic data from ADS-B device and provides the memorization of the target’s data history. Conflict detector module estimates ownship and targets trajectories in order to perform the detection of possible future loss of separation between ownship and each target. Finally, the alerts are verified by additional conflict verification logic, in order to prevent possible undesirable behaviors of the alert flag. In order to reduce the computational load, a pre-check evaluation module is used. This pre-check is only a computational optimization, so the performances of the conflict detector system are not modified in terms of number of alerts detected. The pre-check module uses analytical trajectories propagation for both target and ownship. This allows major accuracy and avoids the step-by-step propagation, which requests major computational load. Furthermore, the pre-check permits to exclude the target that is certainly not a threat, using an analytical and efficient geometrical approach, in order to decrease the computational load for the following modules. This software improvement is not suggested by FAA documents, and so it is the main innovation of this work. The efficiency and efficacy of this enhancement are verified using fast-time and real-time simulations and by the execution on a real device in several FAA scenarios. The final implementation also permits the FAA software certification in compliance with DO-178B standard. The computational load reduction allows the installation of TSAA application also on devices with multiple applications and/or low capacity in terms of available memory and computational capabilities

Keywords: traffic situation awareness, general aviation, aircraft conflict detection, computational load reduction, implementation solutions, software certification

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Authors: K. O'Malley

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Background: The emergence and rapid evolution of large language models (LLMs) (i.e., models of generative artificial intelligence, or AI) has been unprecedented. ChatGPT is one of the most widely used LLM platforms. Using natural language processing technology, it generates customized responses to user prompts, enabling it to mimic human conversation. Responses are generated using predictive modeling of vast internet text and data swathes and are further refined and reinforced through user feedback. The popularity of LLMs is increasing, with a growing number of students utilizing these platforms for study and revision purposes. Notwithstanding its many novel applications, LLM technology is inherently susceptible to bias and error. This poses a significant challenge in the educational setting, where academic integrity may be undermined. This study aims to evaluate the performance of the latest iteration of ChatGPT (ChatGPT4.0) in standardized state medical licensing examinations. Methods: A considered search strategy was used to interrogate the PubMed electronic database. The keywords ‘ChatGPT’ AND ‘medical education’ OR ‘medical school’ OR ‘medical licensing exam’ were used to identify relevant literature. The search included all peer-reviewed literature published in the past five years. The search was limited to publications in the English language only. Eligibility was ascertained based on the study title and abstract and confirmed by consulting the full-text document. Data was extracted into a Microsoft Excel document for analysis. Results: The search yielded 345 publications that were screened. 225 original articles were identified, of which 11 met the pre-determined criteria for inclusion in a narrative synthesis. These studies included performance assessments in national medical licensing examinations from the United States, United Kingdom, Saudi Arabia, Poland, Taiwan, Japan and Germany. ChatGPT 4.0 achieved scores ranging from 67.1 to 88.6 percent. The mean score across all studies was 82.49 percent (SD= 5.95). In all studies, ChatGPT exceeded the threshold for a passing grade in the corresponding exam. Conclusion: The capabilities of ChatGPT in standardized academic assessment in medicine are robust. While this technology can potentially revolutionize higher education, it also presents several challenges with which educators have not had to contend before. The overall strong performance of ChatGPT, as outlined above, may lend itself to unfair use (such as the plagiarism of deliverable coursework) and pose unforeseen ethical challenges (arising from algorithmic bias). Conversely, it highlights potential pitfalls if users assume LLM-generated content to be entirely accurate. In the aforementioned studies, ChatGPT exhibits a margin of error between 11.4 and 32.9 percent, which resonates strongly with concerns regarding the quality and veracity of LLM-generated content. It is imperative to highlight these limitations, particularly to students in the early stages of their education who are less likely to possess the requisite insight or knowledge to recognize errors, inaccuracies or false information. Educators must inform themselves of these emerging challenges to effectively address them and mitigate potential disruption in academic fora.

Keywords: artificial intelligence, ChatGPT, generative ai, large language models, licensing exam, medical education, medicine, university

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Authors: Andrea Scapolo, Zaya Rustamova, Arturo Matute Castro

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The “Voices in Dissent” initiative aims at collecting and making available in a digital format, testimonies, letters, and other narratives produced by victims of political oppression from different geographical spaces across the Atlantic. By recovering silenced voices behind the official narratives, this open-access online database will provide indispensable tools for rewriting the history of authoritarian regimes from the margins as memory debates continue to provoke controversy among academic and popular transnational circles. In providing an extensive database of non-hegemonic discourses in a variety of political and social contexts, the project will complement the existing European and Latin-American studies, and invite further interdisciplinary and trans-national research. This digital resource will be available to academic communities and the general audience and will be organized geographically and chronologically. “Voices in Dissent” will offer a first comprehensive study of these personal accounts of persecution and repression against determined historical backgrounds and their impact on collective memory formation in contemporary societies. The digitalization of these texts will allow to run metadata analyses and adopt comparatist approaches for a broad range of research endeavors. Most of the testimonies included in our archive are testimonies of trauma: the trauma of exile, imprisonment, torture, humiliation, censorship. The research on trauma has now reached critical mass and offers a broad spectrum of critical perspectives. By putting together testimonies from different geographical and historical contexts, our project will provide readers and scholars with an extraordinary opportunity to investigate how culture shapes individual and collective memories and provides or denies resources to make sense and cope with the trauma. For scholars dealing with the epistemological and rhetorical analysis of testimonies, an online open-access archive will prove particularly beneficial to test theories on truth status and the formation of belief as well as to study the articulation of discourse. An important aspect of this project is also its pedagogical applications since it will contribute to the creation of Open Educational Resources (OER) to support students and educators worldwide. Through collaborations with our Library System, the archive will form part of the Digital Commons database. The texts collected in this online archive will be made available in the original languages as well as in English translation. They will be accompanied by a critical apparatus that will contextualize them historically by providing relevant background information and bibliographical references. All these materials can serve as a springboard for a broad variety of educational projects and classroom activities. They can also be used to design specific content courses or modules. In conclusion, the desirable outcomes of the “Voices in Dissent” project are: 1. the collections and digitalization of political dissent testimonies; 2. the building of a network of scholars, educators, and learners involved in the design, development, and sustainability of the digital archive; 3. the integration of the content of the archive in both research and teaching endeavors, such as publication of scholarly articles, design of new upper-level courses, and integration of the materials in existing courses.

Keywords: digital archive, dissent, open educational resources, testimonies, transatlantic studies

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Authors: Francesca Crivellari, Nicholas Mavrogiannis, Zachary Gagnon

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Portable diagnostic methods have become increasingly important for a number of different purposes: point-of-care screening in developing nations, environmental contamination studies, bio/chemical warfare agent detection, and end-user use for commercial health monitoring. The cheapest and most portable methods currently available are paper-based – lateral flow and dipstick methods are widely available in drug stores for use in pregnancy detection and blood glucose monitoring. These tests are successful because they are cheap to produce, easy to use, and require minimally invasive sampling. While adequate for their intended uses, in the realm of blood-borne pathogens and numerous cancers, these paper-based methods become unreliable, as they lack the nM/pM sensitivity currently achieved by clinical diagnostic methods. Clinical diagnostics, however, utilize techniques involving surface plasmon resonance (SPR) and enzyme-linked immunosorbent assays (ELISAs), which are expensive and unfeasible in terms of portability. To develop a better, competitive biosensor, we must reduce the cost of one, or increase the sensitivity of the other. Electric fields are commonly utilized in microfluidic devices to manipulate particles, biomolecules, and cells. Applications in this area, however, are primarily limited to interfaces formed between immiscible interfaces. Miscible, liquid-liquid interfaces are common in microfluidic devices, and are easily reproduced with simple geometries. Here, we demonstrate the use of electrical fields at liquid-liquid electrical interfaces, known as fluidic dielectrophoresis, (fDEP) for biodetection in a microfluidic device. In this work, we apply an AC electric field across concurrent laminar streams with differing conductivities and permittivities to polarize the interface and induce a discernible, near-immediate, frequency-dependent interfacial tilt. We design this aqueous electrical interface, which becomes the biosensing “substrate,” to be intelligent – it “moves” only when a target of interest is present. This motion requires neither labels nor expensive electrical equipment, so the biosensor is inexpensive and portable, yet still capable of sensitive detection. Nanoparticles, due to their high surface-area-to-volume ratio, are often incorporated to enhance detection capabilities of schemes like SPR and fluorimetric assays. Most studies currently investigate binding at an immobilized solid-liquid or solid-gas interface, where particles are adsorbed onto a planar surface, functionalized with a receptor to create a reactive substrate, and subsequently flushed with a fluid or gas with the relevant analyte. These typically involve many preparation and rinsing steps, and are susceptible to surface fouling. Our microfluidic device is continuously flowing and renewing the “substrate,” and is thus not subject to fouling. In this work, we demonstrate the ability to electrokinetically detect biomolecules binding to functionalized nanoparticles at liquid-liquid interfaces using fDEP. In biotin-streptavidin experiments, we report binding detection limits on the order of 1-10 pM, without amplifying signals or concentrating samples. We also demonstrate the ability to detect this interfacial motion, and thus the presence of binding, using impedance spectroscopy, allowing this scheme to become non-optical, in addition to being label-free.

Keywords: biodetection, dielectrophoresis, microfluidics, nanoparticles

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Authors: Mohammad R. Aghakashkooli, Milutin G. Jovanovic

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The brushless doubly-fed reluctance generator (BDFRG) is an emerging, medium-speed alternative to a conventional wound rotor slip-ring doubly-fed induction generator (DFIG) in wind energy conversion systems (WECS). It can provide competitive overall performance and similar low failure rates of a typically 30% rated back-to-back power electronics converter in 2:1 speed ranges but with the following important reliability and cost advantages over DFIG: the maintenance-free operation afforded by its brushless structure, 50% synchronous speed with the same number of rotor poles (allowing the use of a more compact, and more efficient two-stage gearbox instead of a vulnerable three-stage one), and superior grid integration properties including simpler protection for the low voltage ride through compliance of the fractional converter due to the comparatively higher leakage inductances and lower fault currents. Vector controlled pulse-width-modulated converters generally feature a much lower total harmonic distortion relative to hysteresis counterparts with variable switching rates and as such have been a predominant choice for BDFRG (and DFIG) wind turbines. Eliminating a shaft position sensor, which is often required for control implementation in this case, would be desirable to address the associated reliability issues. This fact has largely motivated the recent growing research of sensorless methods and developments of various rotor position and/or speed estimation techniques for this purpose. The main limitation of all the observer-based control approaches for grid-connected wind power applications of the BDFRG reported in the open literature is the requirement for pre-commissioning procedures and prior knowledge of the machine inductances, which are usually difficult to accurately identify by off-line testing. A model reference adaptive system (MRAS) based sensor-less vector control scheme to be presented will overcome this shortcoming. The true machine parameter independence of the proposed field-oriented algorithm, offering robust, inherently decoupled real and reactive power control of the grid-connected winding, is achieved by on-line estimation of the inductance ratio, the underlying rotor angular velocity and position MRAS observer being reliant upon. Such an observer configuration will be more practical to implement and clearly preferable to the existing machine parameter dependent solutions, and especially bearing in mind that with very little modifications it can be adapted for commercial DFIGs with immediately obvious further industrial benefits and prospects of this work. The excellent encoder-less controller performance with maximum power point tracking in the base speed region will be demonstrated by realistic simulation studies using large-scale BDFRG design data and verified by experimental results on a small laboratory prototype of the WECS emulation facility.

Keywords: brushless doubly fed reluctance generator, model reference adaptive system, sensorless vector control, wind energy conversion

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Authors: Marian Mihalik, Kornel Csach, Martin Kovalik, Matúš Mihalik, Martina Kubovčíková, Maria Zentková, Martin Vavra, Vladimír Girman, Jaroslav Briančin, Marija Perovic, Marija Boškovic, Magdalena Fitta, Robert Pelka

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Current nanomaterials for use in biomedicine are based mainly on iron oxides and on present knowledge on magnetic nanostructures. Manganites can represent another material which can be used optionally. Manganites and their unique electronic properties have been extensively studied in the last decades not only due to fundamental interest but to possible applications of colossal magnetoresistance, magnetocaloric effect, and ferroelectric properties. It was found that the oxygen-reduction reaction on perovskite oxide is intimately connected with metal ion e.g., orbital occupation. The effect of oxygen deviation from the stoichiometric composition on crystal structure was studied very carefully by many authors on LaMnO₃. Depending on oxygen content, the crystal structure changes from orthorhombic one to rhombohedric for oxygen content 3.1. In the case of hole-doped manganites, the change from the orthorhombic crystal structure, which is typical for La1-xCaxMnO3 based manganites, to the rhombohedric crystal structure (La1-xMxMnO₃ where M = K, Ag, and Sr based materials) results in an enormous increase of the Curie temperature. In our paper, we study the effect of oxygen content on crystal structure, thermal, and magnetic properties (including magnetocaloric effect) of La1-xAgxMnO₃nano particle system. The content of oxygen in samples was tuned by heat treatment in different thermal regimes and in various environment (air, oxygen, argon). Water nanosuspensions based on La0.80Ag0.15MnO₃ magnetic particles with the Curie temperature of about 43oC were prepared by two different approaches. First, by using a laboratory circulation mill for milling of powder in the presence of sodium dodecyl sulphate (SDS) and subsequent centrifugation. Second nanosuspension was prepared using an agate bowl, etching in citric acid and HNO3, ultrasound homogeniser, centrifugation, and dextran 40 kDA or 15 kDA as surfactant. Electrostatic stabilisation obtained by the first approach did not offer long term kinetic and aggregation colloidal stability and was unable to compensate for attractive forces between particles under a magnetic field. By the second approach, we prepared suspension oversaturated by dextran 40 kDA for steric stabilisation, with evidence of the presence of superparamagnetic behaviour. Low concentration of nanoparticles and not ideal coverage of nanoparticles impacting the stability of ferrofluids was the disadvantage of this approach. Strong steric stabilisation was observable at alcaic conditions under pH = ~10. Application of dextran 15 kDA leads to relatively stable ferrofluid with pH around physiological conditions, but desegregation of powder by HNO₃ was not effective enough, and the average size of fragments was to large of about 150 nm, and we did not see any signature of superparamagnetic behaviour. The prepared ferrofluids were characterised by scanning and transition microscope method, thermogravimetry, magnetization, and AC susceptibility measurements. Specific Absorption Rate measurements were undertaken on powder as well on ferrofluids in order to estimate the potential application of La₀.₈₀Ag₀.₁₅MnO₃ magnetic particles based ferrofluid for hyperthermia. Our complex study contains an investigation of biocompatibility and potential biohazard of this material.

Keywords: manganites, magnetic nanoparticles, oxygen content, magnetic phase transition, magnetocaloric effect, ferrofluid, hyperthermia

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Authors: Sylvie Michel, François Cocula

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Digital agriculture is an approach that exploits information and communication technologies. These encompass data acquisition tools like mobile applications, satellites, sensors, connected devices, and smartphones. Additionally, it involves transfer and storage technologies such as 3G/4G coverage, low-bandwidth terrestrial or satellite networks, and cloud-based systems. Furthermore, embedded or remote processing technologies, including drones and robots for process automation, along with high-speed communication networks accessible through supercomputers, are integral components of this approach. While farm-level adoption studies regarding digital agricultural technologies have emerged in recent years, they remain relatively limited in comparison to other agricultural practices. To bridge this gap, this study delves into understanding farmers' intention to adopt digital tools, employing the technology, organization, environment framework. A qualitative research design encompassed semi-structured interviews, totaling fifteen in number, conducted with key stakeholders both prior to and following the 2020-2021 COVID-19 lockdowns in France. Subsequently, the interview transcripts underwent thorough thematic content analysis, and the data and verbatim were triangulated for validation. A coding process aimed to systematically organize the data, ensuring an orderly and structured classification. Our research extends its contribution by delineating sub-dimensions within each primary dimension. A total of nine sub-dimensions were identified, categorized as follows: perceived usefulness for communication, perceived usefulness for productivity, and perceived ease of use constitute the first dimension; technological resources, financial resources, and human capabilities constitute the second dimension, while market pressure, institutional pressure, and the COVID-19 situation constitute the third dimension. Furthermore, this analysis enriches the TOE framework by incorporating entrepreneurial orientation as a moderating variable. Managerial orientation emerges as a pivotal factor influencing adoption intention, with producers acknowledging the significance of utilizing digital sales support tools to combat "greenwashing" and elevate their overall brand image. Specifically, it illustrates that producers recognize the potential of digital tools in time-saving and streamlining sales processes, leading to heightened productivity. Moreover, it highlights that the intent to adopt digital sales support tools is influenced by a market mimicry effect. Additionally, it demonstrates a negative association between the intent to adopt these tools and the pressure exerted by institutional partners. Finally, this research establishes a positive link between the intent to adopt digital sales support tools and economic fluctuations, notably during the COVID-19 pandemic. The adoption of sales support tools in agriculture is a multifaceted challenge encompassing three dimensions and nine sub-dimensions. The research delves into the adoption of digital farming technologies at the farm level through the TOE framework. This analysis provides significant insights beneficial for policymakers, stakeholders, and farmers. These insights are instrumental in making informed decisions to facilitate a successful digital transition in agriculture, effectively addressing sector-specific challenges.

Keywords: adoption, digital agriculture, e-commerce, TOE framework

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Authors: A. Peyvan, D. Li, J. Komperda, F. Mashayek

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Turbulence can be observed in a variety fluid motions in nature and industrial applications. Recent investment in high-speed aircraft and propulsion systems has revitalized fundamental research on turbulent flows. In these systems, capturing chaotic fluid structures with different length and time scales is accomplished through the Direct Numerical Simulation (DNS) approach since it accurately simulates flows down to smallest dissipative scales, i.e., Kolmogorov’s scales. The discontinuous spectral element method (DSEM) is a high-order technique that uses spectral functions for approximating the solution. The DSEM code has been developed by our research group over the course of more than two decades. Recently, the code has been improved to run large cases in the order of billions of solution points. Running big simulations requires a considerable amount of RAM. Therefore, the DSEM code must be highly parallelized and able to start on multiple computational nodes on an HPC cluster with distributed memory. However, some pre-processing procedures, such as determining global element information, creating a global face list, and assigning global partitioning and element connection information of the domain for communication, must be done sequentially with a single processing core. A separate code has been written to perform the pre-processing procedures on a local machine. It stores the minimum amount of information that is required for the DSEM code to start in parallel, extracted from the mesh file, into text files (pre-files). It packs integer type information with a Stream Binary format in pre-files that are portable between machines. The files are generated to ensure fast read performance on different file-systems, such as Lustre and General Parallel File System (GPFS). A new subroutine has been added to the DSEM code to read the startup files using parallel MPI I/O, for Lustre, in a way that each MPI rank acquires its information from the file in parallel. In case of GPFS, in each computational node, a single MPI rank reads data from the file, which is specifically generated for the computational node, and send them to other ranks on the node using point to point non-blocking MPI communication. This way, communication takes place locally on each node and signals do not cross the switches of the cluster. The read subroutine has been tested on Argonne National Laboratory’s Mira (GPFS), National Center for Supercomputing Application’s Blue Waters (Lustre), San Diego Supercomputer Center’s Comet (Lustre), and UIC’s Extreme (Lustre). The tests showed that one file per node is suited for GPFS and parallel MPI I/O is the best choice for Lustre file system. The DSEM code relies on heavily optimized linear algebra operation such as matrix-matrix and matrix-vector products for calculation of the solution in every time-step. For this, the code can either make use of its matrix math library, BLAS, Intel MKL, or ATLAS. This fact and the discontinuous nature of the method makes the DSEM code run efficiently in parallel. The results of weak scaling tests performed on Blue Waters showed a scalable and efficient performance of the code in parallel computing.

Keywords: computational fluid dynamics, direct numerical simulation, spectral element, turbulent flow

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Authors: Shreyas Kumar, Mili Shangari

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Integrating artificial intelligence (AI) in the cyber insurance sector represents a significant advancement, offering the potential to revolutionize risk assessment, fraud detection, and claims processing. However, this integration introduces a range of regulatory and economic challenges that must be addressed to ensure responsible and effective deployment of AI technologies. This paper examines the multifaceted regulatory landscape governing AI in cyber insurance and explores the economic implications of compliance, innovation, and market dynamics. AI's capabilities in processing vast amounts of data and identifying patterns make it an invaluable tool for insurers in managing cyber risks. Yet, the application of AI in this domain is subject to stringent regulatory scrutiny aimed at safeguarding data privacy, ensuring algorithmic transparency, and preventing biases. Regulatory bodies, such as the European Union with its General Data Protection Regulation (GDPR), mandate strict compliance requirements that can significantly impact the deployment of AI systems. These regulations necessitate robust data protection measures, ethical AI practices, and clear accountability frameworks, all of which entail substantial compliance costs for insurers. The economic implications of these regulatory requirements are profound. Insurers must invest heavily in upgrading their IT infrastructure, implementing robust data governance frameworks, and training personnel to handle AI systems ethically and effectively. These investments, while essential for regulatory compliance, can strain financial resources, particularly for smaller insurers, potentially leading to market consolidation. Furthermore, the cost of regulatory compliance can translate into higher premiums for policyholders, affecting the overall affordability and accessibility of cyber insurance. Despite these challenges, the potential economic benefits of AI integration in cyber insurance are significant. AI-enhanced risk assessment models can provide more accurate pricing, reduce the incidence of fraudulent claims, and expedite claims processing, leading to overall cost savings and increased efficiency. These efficiencies can improve the competitiveness of insurers and drive innovation in product offerings. However, balancing these benefits with regulatory compliance is crucial to avoid legal penalties and reputational damage. The paper also explores the potential risks associated with AI integration, such as algorithmic biases that could lead to unfair discrimination in policy underwriting and claims adjudication. Regulatory frameworks need to evolve to address these issues, promoting fairness and transparency in AI applications. Policymakers play a critical role in creating a balanced regulatory environment that fosters innovation while protecting consumer rights and ensuring market stability. In conclusion, the integration of AI in cyber insurance presents both regulatory and economic challenges that require a coordinated approach involving regulators, insurers, and other stakeholders. By navigating these challenges effectively, the industry can harness the transformative potential of AI, driving advancements in risk management and enhancing the resilience of the cyber insurance market. This paper provides insights and recommendations for policymakers and industry leaders to achieve a balanced and sustainable integration of AI technologies in cyber insurance.

Keywords: artificial intelligence (AI), cyber insurance, regulatory compliance, economic impact, risk assessment, fraud detection, cyber liability insurance, risk management, ransomware

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Ahmad Saad, Shuja Abbas, Breanna Marine

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Introduction: This study explores the potential applications of autologous pedal fat pad grafting as a minimally invasive therapeutic strategy for addressing pedal fat pad loss. Without adequate shock absorbing tissue, a patient can experience functional deficits, ulcerations, loss of quality of life, and significant limitations with ambulation. This study details a novel technique involving autologous adipose grafting from the abdomen to enhance plantar fat pad thickness in a patient involved in a severe motor vehicle accident which resulted in total fat pad loss of the heel. Autologous adipose grafting (AAG) was used following adipose allografting in an effort to recreate a normal shock absorbing surface to allow return to activities of daily living and painless ambulation. Methods: A 46-year-old male sustained multiple open pedal fractures and necrosis to the heel fat pad after a motorcycle accident, which resulted in complete loss of the calcaneal fat pad. The patient underwent serial debridement’s, utilization of wound vac therapy and split thickness skin grafting to accomplish complete closure, despite complete loss of adipose to area. Patient presented with complaints of pain on ambulation, inability to bear weight on the heel, recurrent ulcerations, admitted had not been ambulating for two years. Clinical exam demonstrated complete loss of the plantar fat pad with a thin layer of epithelial tissue overlying the calcaneal bone, allowing visibility of the osseous contour of the calcaneus. Scar tissue had formed in place of the fat pad, with thickened epithelial tissue extending from the midfoot to the calcaneus. After conservative measures were exhausted, the patient opted for initial management by adipose allograft matrix (AAM) injections. Post operative X-ray imaging revealed noticeable improvement in calcaneal fat pad thickness. At 1 year follow up, the patient was able to ambulate without assistive devices. The fat pad at this point was significantly thicker than it was pre-operatively, but the thickness did not restore to pre-accident thickness. In order to compare the take of allograft versus autografting of adipose tissue, the decision to use adipose autograft through abdominal liposuction harvesting was deemed suitable. A general surgeon completed harvesting of adipose cells from the patient’s abdomen via liposuction, and a podiatric surgeon performed the AAG injection into the heel. Total of 15 cc’s of autologous adipose tissue injected to the calcaneus. Results: There was a visual increase in the calcaneal fat pad thickness both clinically and radiographically. At the 6-week follow up, imaging revealed retention of the calcaneal fat pad thickness. Three months postop, patient returned to activities of daily living and increased quality of life due to their increased ability to ambulate. Discussion: AAG is a novel treatment for pedal fat pad loss. These treatments may be viable and reproducible therapeutic choices for patients suffering from fat pad atrophy, fat pad loss, and/or plantar ulcerations. Both treatments of AAM and AAG exhibited similar therapeutic results by providing pain relief for ambulation and allowing for patients to return to their quality of life.

Keywords: podiatry, wound, adipose, allograft, autograft, wound care, limb reconstruction, injection, limb salvage

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Authors: Stefan K. Behfar

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The rapid growth of the Ethereum network has brought forth the urgent need for scalable analysis methods to handle the increasing volume of blockchain data. In this research, we propose efficient methodologies for making Ethereum network analysis scalable. Our approach leverages a combination of graph-based data representation, probabilistic sampling, and parallel processing techniques to achieve unprecedented scalability while preserving critical network insights. Data Representation: We develop a graph-based data representation that captures the underlying structure of the Ethereum network. Each block transaction is represented as a node in the graph, while the edges signify temporal relationships. This representation ensures efficient querying and traversal of the blockchain data. Probabilistic Sampling: To cope with the vastness of the Ethereum blockchain, we introduce a probabilistic sampling technique. This method strategically selects a representative subset of transactions and blocks, allowing for concise yet statistically significant analysis. The sampling approach maintains the integrity of the network properties while significantly reducing the computational burden. Graph Convolutional Networks (GCNs): We incorporate GCNs to process the graph-based data representation efficiently. The GCN architecture enables the extraction of complex spatial and temporal patterns from the sampled data. This combination of graph representation and GCNs facilitates parallel processing and scalable analysis. Distributed Computing: To further enhance scalability, we adopt distributed computing frameworks such as Apache Hadoop and Apache Spark. By distributing computation across multiple nodes, we achieve a significant reduction in processing time and enhanced memory utilization. Our methodology harnesses the power of parallelism, making it well-suited for large-scale Ethereum network analysis. Evaluation and Results: We extensively evaluate our methodology on real-world Ethereum datasets covering diverse time periods and transaction volumes. The results demonstrate its superior scalability, outperforming traditional analysis methods. Our approach successfully handles the ever-growing Ethereum data, empowering researchers and developers with actionable insights from the blockchain. Case Studies: We apply our methodology to real-world Ethereum use cases, including detecting transaction patterns, analyzing smart contract interactions, and predicting network congestion. The results showcase the accuracy and efficiency of our approach, emphasizing its practical applicability in real-world scenarios. Security and Robustness: To ensure the reliability of our methodology, we conduct thorough security and robustness evaluations. Our approach demonstrates high resilience against adversarial attacks and perturbations, reaffirming its suitability for security-critical blockchain applications. Conclusion: By integrating graph-based data representation, GCNs, probabilistic sampling, and distributed computing, we achieve network scalability without compromising analytical precision. This approach addresses the pressing challenges posed by the expanding Ethereum network, opening new avenues for research and enabling real-time insights into decentralized ecosystems. Our work contributes to the development of scalable blockchain analytics, laying the foundation for sustainable growth and advancement in the domain of blockchain research and application.

Keywords: Ethereum, scalable network, GCN, probabilistic sampling, distributed computing

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Authors: Piacentini Diego, Della Rovere Federica, Fattorini Laura, Lanni Francesca, Cittadini Martina, Altamura Maria Maddalena, Falasca Giuseppina

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Plants have evolved sophisticated mechanisms to cope with environmental cues. Changes in intracellular content and distribution of phytohormones, such as the auxin indole-3-acetic acid (IAA), have been involved in morphogenic adaptation to environmental stresses. In addition to phytohormones, plants can rely on a plethora of small signal molecules able to promptly sense and transduce the stress signals, resulting in morpho/physiological responses thanks also to their capacity to modulate the levels/distribution/reception of most hormones. Among these signaling molecules, nitrogen monoxide (nitric oxide – NO) is a critical component in several plant acclimation strategies to both biotic and abiotic stresses. Depending on its levels, NO increases plant adaptation by enhancing the enzymatic or non-enzymatic antioxidant systems or by acting as a direct scavenger of reactive oxygen/nitrogen (ROS/RNS) species produced during the stress. In addition, exogenous applications of NO-specific donor compounds showed the involvement of the signal molecule in auxin metabolism, transport, and signaling, under both physiological and stress conditions. However, the complex mechanisms underlying NO action in interacting with phytohormones, such as auxins, during metal stress responses are still poorly understood and need to be better investigated. Emphasis must be placed on the response of the root system since it is the first plant organ system to be exposed to metal soil pollution. The monocot Oryza sativa L. (rice) has been chosen given its importance as a stable food for some 4 billion people worldwide. In addition, increasing evidence has shown that rice is often grown in contaminated paddy soils with high levels of heavy metal cadmium (Cd) and metalloid arsenic (As). The facility through which these metals are taken up by rice roots and transported to the aerial organs up to the edible caryopses makes rice one of the most relevant sources of these pollutants for humans. This study aimed to evaluate if NO has a mitigatory activity in the roots of rice seedlings against Cd or As toxicity and to understand if this activity requires interactions with auxin. Our results show that exogenous treatments with the NO-donor SNP alleviate the stress induced by Cd, but not by As, in in-vitro-grown rice seedlings through increased intracellular root NO levels. The damages induced by the pollutants include root growth inhibition, root histological alterations and ROS (H2O2, O2●ˉ), and RNS (ONOOˉ) production. Also, SNP treatments mitigate both the root increase in root IAA levels and the IAA alteration in distribution monitored by the OsDR5::GUS system due to the toxic metal exposure. Notably, the SNP-induced mitigation of the IAA homeostasis altered by the pollutants does not involve changes in the expression of OsYUCCA1 and ASA2 IAA-biosynthetic genes. Taken together, the results highlight a mitigating role of NO in the rice root system, which is pollutant-specific, and involves the interaction of the signal molecule with both IAA and brassinosteroids at different (i.e., transport, levels, distribution) and multiple levels (i.e., transcriptional/post-translational levels). The research is supported by Progetti Ateneo Sapienza University of Rome, grant number: RG120172B773D1FF

Keywords: arsenic, auxin, cadmium, nitric oxide, rice, root system

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Authors: Wonil Nam, Xiang Ren, Inyoung Kim, Masoud Agah, Wei Zhou

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Despite its ultrasensitive detection capability, surface-enhanced Raman spectroscopy (SERS) faces challenges as a quantitative biochemical analysis tool due to the significant dependence of local field intensity in hotspots on nanoscale geometric variations of plasmonic nanostructures. Therefore, despite enormous progress in plasmonic nanoengineering of high-performance SERS devices, it is still challenging to quantitatively correlate the measured SERS signals with the actual molecule concentrations at hotspots. A significant effort has been devoted to developing SERS calibration methods by introducing internal standards. It has been achieved by placing Raman tags at plasmonic hotspots. Raman tags undergo similar SERS enhancement at the same hotspots, and ratiometric SERS signals for analytes of interest can be generated with reduced dependence on geometrical variations. However, using Raman tags still faces challenges for real-world applications, including spatial competition between the analyte and tags in hotspots, spectral interference, laser-induced degradation/desorption due to plasmon-enhanced photochemical/photothermal effects. We show that electronic Raman scattering (ERS) signals from metallic nanostructures at hotspots can serve as the internal calibration standard to enable quantitative SERS analysis and improve biostatistical analysis. We perform SERS with Au-SiO₂ multilayered metal-insulator-metal nano laminated plasmonic nanostructures. Since the ERS signal is proportional to the volume density of electron-hole occupation in hotspots, the ERS signals exponentially increase when the wavenumber is approaching the zero value. By a long-pass filter, generally used in backscattered SERS configurations, to chop the ERS background continuum, we can observe an ERS pseudo-peak, IERS. Both ERS and SERS processes experience the |E|⁴ local enhancements during the excitation and inelastic scattering transitions. We calibrated IMRS of 10 μM Rhodamine 6G in solution by IERS. The results show that ERS calibration generates a new analytical value, ISERS/IERS, insensitive to variations from different hotspots and thus can quantitatively reflect the molecular concentration information. Given the calibration capability of ERS signals, we performed label-free SERS analysis of living biological systems using four different breast normal and cancer cell lines cultured on nano-laminated SERS devices. 2D Raman mapping over 100 μm × 100 μm, containing several cells, was conducted. The SERS spectra were subsequently analyzed by multivariate analysis using partial least square discriminant analysis. Remarkably, after ERS calibration, MCF-10A and MCF-7 cells are further separated while the two triple-negative breast cancer cells (MDA-MB-231 and HCC-1806) are more overlapped, in good agreement with the well-known cancer categorization regarding the degree of malignancy. To assess the strength of ERS calibration, we further carried out a drug efficacy study using MDA-MB-231 and different concentrations of anti-cancer drug paclitaxel (PTX). After ERS calibration, we can more clearly segregate the control/low-dosage groups (0 and 1.5 nM), the middle-dosage group (5 nM), and the group treated with half-maximal inhibitory concentration (IC50, 15 nM). Therefore, we envision that ERS calibrated SERS can find crucial opportunities in label-free molecular profiling of complicated biological systems.

Keywords: cancer cell drug efficacy, plasmonics, surface-enhanced Raman spectroscopy (SERS), SERS calibration

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Authors: William Michael Short

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Semantic Web’ technologies such as the Unified Medical Language System Metathesaurus, SNOMED-CT, and MeSH have been touted as transformational for the way users access online medical and health information, enabling both the automated analysis of natural-language data and the integration of heterogeneous healthrelated resources distributed across the Internet through the use of standardized terminologies that capture concepts and relationships between concepts that are expressed differently across datasets. However, the approaches that have so far characterized ‘semantic bioinformatics’ have not yet fulfilled the promise of the Semantic Web for medical and health information retrieval applications. This paper argues within the perspective of cognitive linguistics and cognitive anthropology that four features of human meaning-making must be taken into account before the potential of semantic technologies can be realized for this domain. First, many semantic technologies operate exclusively at the level of the word. However, texts convey meanings in ways beyond lexical semantics. For example, transitivity patterns (distributions of active or passive voice) and modality patterns (configurations of modal constituents like may, might, could, would, should) convey experiential and epistemic meanings that are not captured by single words. Language users also naturally associate stretches of text with discrete meanings, so that whole sentences can be ascribed senses similar to the senses of words (so-called ‘discourse topics’). Second, natural language processing systems tend to operate according to the principle of ‘one token, one tag’. For instance, occurrences of the word sound must be disambiguated for part of speech: in context, is sound a noun or a verb or an adjective? In syntactic analysis, deterministic annotation methods may be acceptable. But because natural language utterances are typically characterized by polyvalency and ambiguities of all kinds (including intentional ambiguities), such methods leave the meanings of texts highly impoverished. Third, ontologies tend to be disconnected from everyday language use and so struggle in cases where single concepts are captured through complex lexicalizations that involve profile shifts or other embodied representations. More problematically, concept graphs tend to capture ‘expert’ technical models rather than ‘folk’ models of knowledge and so may not match users’ common-sense intuitions about the organization of concepts in prototypical structures rather than Aristotelian categories. Fourth, and finally, most ontologies do not recognize the pervasively figurative character of human language. However, since the time of Galen the widespread use of metaphor in the linguistic usage of both medical professionals and lay persons has been recognized. In particular, metaphor is a well-documented linguistic tool for communicating experiences of pain. Because semantic medical knowledge-bases are designed to help capture variations within technical vocabularies – rather than the kinds of conventionalized figurative semantics that practitioners as well as patients actually utilize in clinical description and diagnosis – they fail to capture this dimension of linguistic usage. The failure of semantic technologies in these respects degrades the efficiency and efficacy not only of medical research, where information retrieval inefficiencies can lead to direct financial costs to organizations, but also of care provision, especially in contexts of patients’ self-management of complex medical conditions.

Keywords: ambiguity, bioinformatics, language, meaning, metaphor, ontology, semantic web, semantics

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Authors: Aliasghar Mehdizadeh Dastjerdi, Francisco Camara Pereira

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The increasing complexity and demand of transport services strains transportation systems especially in urban areas with limited possibilities for building new infrastructure. The solution to this challenge requires changes of travel behavior. One of the proposed means to induce such change is multimodal travel apps. This paper describes a study of the intention to use a real-time multi-modal travel app aimed at motivating travel behavior change in the Greater Copenhagen Region (Denmark) toward promoting sustainable transport options. The proposed app is a multi-faceted smartphone app including both travel information and persuasive strategies such as health and environmental feedback, tailoring travel options, self-monitoring, tunneling users toward green behavior, social networking, nudging and gamification elements. The prospective for mobility management travel apps to stimulate sustainable mobility rests not only on the original and proper employment of the behavior change strategies, but also on explicitly anchoring it on established theoretical constructs from behavioral theories. The theoretical foundation is important because it positively and significantly influences the effectiveness of the system. However, there is a gap in current knowledge regarding the study of mobility-management travel app with support in behavioral theories, which should be explored further. This study addresses this gap by a social cognitive theory‐based examination. However, compare to conventional method in technology adoption research, this study adopts a reverse approach in which the associations between theoretical constructs are explored by Max-Min Hill-Climbing (MMHC) algorithm as a hybrid causal discovery method. A technology-use preference survey was designed to collect data. The survey elicited different groups of variables including (1) three groups of user’s motives for using the app including gain motives (e.g., saving travel time and cost), hedonic motives (e.g., enjoyment) and normative motives (e.g., less travel-related CO2 production), (2) technology-related self-concepts (i.e. technophile attitude) and (3) use Intention of the travel app. The questionnaire items led to the formulation of causal relationships discovery to learn the causal structure of the data. Causal relationships discovery from observational data is a critical challenge and it has applications in different research fields. The estimated causal structure shows that the two constructs of gain motives and technophilia have a causal effect on adoption intention. Likewise, there is a causal relationship from technophilia to both gain and hedonic motives. In line with the findings of the prior studies, it highlights the importance of functional value of the travel app as well as technology self-concept as two important variables for adoption intention. Furthermore, the results indicate the effect of technophile attitude on developing gain and hedonic motives. The causal structure shows hierarchical associations between the three groups of user’s motive. They can be explained by “frustration-regression” principle according to Alderfer's ERG (Existence, Relatedness and Growth) theory of needs meaning that a higher level need remains unfulfilled, a person may regress to lower level needs that appear easier to satisfy. To conclude, this study shows the capability of causal discovery methods to learn the causal structure of theoretical model, and accordingly interpret established associations.

Keywords: travel app, behavior change, persuasive technology, travel information, causality

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Authors: Mukhtar Maigari

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The landscape of Higher Education (HE) institutions, especially following the CVID-19 pandemic, necessitates advanced approaches to manage Indoor Environmental Quality (IEQ) which is crucial for the comfort, health, and productivity of students and staff. This study investigates the application of Building Information Modelling (BIM) as a multifaceted tool for monitoring, assessing, and controlling IEQ in HE buildings aiming to bridge the gap between traditional management practices and the innovative capabilities of BIM. Central to the study is a comprehensive literature review, which lays the foundation by examining current knowledge and technological advancements in both IEQ and BIM. This review sets the stage for a deeper investigation into the practical application of BIM in IEQ management. The methodology consists of Post-Occupancy Evaluation (POE) which encompasses physical monitoring, questionnaire surveys, and interviews under the umbrella of case studies. The physical data collection focuses on vital IEQ parameters such as temperature, humidity, CO2 levels etc, conducted by using different equipment including dataloggers to ensure accurate data. Complementing this, questionnaire surveys gather perceptions and satisfaction levels from students, providing valuable insights into the subjective aspects of IEQ. The interview component, targeting facilities management teams, offers an in-depth perspective on IEQ management challenges and strategies. The research delves deeper into the development of a conceptual BIM-based framework, informed by the insight findings from case studies and empirical data. This framework is designed to demonstrate the critical functions necessary for effective IEQ monitoring, assessment, control and automation with real time data handling capabilities. This BIM-based framework leads to the developing and testing a BIM-based prototype tool. This prototype leverages on software such as Autodesk Revit with its visual programming tool i.e., Dynamo and an Arduino-based sensor network thereby allowing for real-time flow of IEQ data for monitoring, control and even automation. By harnessing the capabilities of BIM technology, the study presents a forward-thinking approach that aligns with current sustainability and wellness goals, particularly vital in the post-COVID-19 era. The integration of BIM in IEQ management promises not only to enhance the health, comfort, and energy efficiency of educational environments but also to transform them into more conducive spaces for teaching and learning. Furthermore, this research could influence the future of HE buildings by prompting universities and government bodies to revaluate and improve teaching and learning environments. It demonstrates how the synergy between IEQ and BIM can empower stakeholders to monitor IEQ conditions more effectively and make informed decisions in real-time. Moreover, the developed framework has broader applications as well; it can serve as a tool for other sustainability assessments, like energy analysis in HE buildings, leveraging measured data synchronized with the BIM model. In conclusion, this study bridges the gap between theoretical research and real-world application by practicalizing how advanced technologies like BIM can be effectively integrated to enhance environmental quality in educational institutions. It portrays the potential of integrating advanced technologies like BIM in the pursuit of improved environmental conditions in educational institutions.

Keywords: BIM, POE, IEQ, HE-buildings

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