Search results for: word formation patterns

Authors: Muhammad Bilal Shaikh

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Mineral processing plants play a pivotal role in extracting valuable minerals from raw ores, contributing significantly to various industries. However, the optimization of plant throughput remains a complex challenge, necessitating innovative approaches for increased efficiency and productivity. This research paper investigates the application of Multimodal Artificial Intelligence (MAI) techniques to address this challenge, aiming to improve overall plant throughput in mineral processing operations. The integration of multimodal AI leverages a combination of diverse data sources, including sensor data, images, and textual information, to provide a holistic understanding of the complex processes involved in mineral extraction. The paper explores the synergies between various AI modalities, such as machine learning, computer vision, and natural language processing, to create a comprehensive and adaptive system for optimizing mineral processing plants. The primary focus of the research is on developing advanced predictive models that can accurately forecast various parameters affecting plant throughput. Utilizing historical process data, machine learning algorithms are trained to identify patterns, correlations, and dependencies within the intricate network of mineral processing operations. This enables real-time decision-making and process optimization, ultimately leading to enhanced plant throughput. Incorporating computer vision into the multimodal AI framework allows for the analysis of visual data from sensors and cameras positioned throughout the plant. This visual input aids in monitoring equipment conditions, identifying anomalies, and optimizing the flow of raw materials. The combination of machine learning and computer vision enables the creation of predictive maintenance strategies, reducing downtime and improving the overall reliability of mineral processing plants. Furthermore, the integration of natural language processing facilitates the extraction of valuable insights from unstructured textual data, such as maintenance logs, research papers, and operator reports. By understanding and analyzing this textual information, the multimodal AI system can identify trends, potential bottlenecks, and areas for improvement in plant operations. This comprehensive approach enables a more nuanced understanding of the factors influencing throughput and allows for targeted interventions. The research also explores the challenges associated with implementing multimodal AI in mineral processing plants, including data integration, model interpretability, and scalability. Addressing these challenges is crucial for the successful deployment of AI solutions in real-world industrial settings. To validate the effectiveness of the proposed multimodal AI framework, the research conducts case studies in collaboration with mineral processing plants. The results demonstrate tangible improvements in plant throughput, efficiency, and cost-effectiveness. The paper concludes with insights into the broader implications of implementing multimodal AI in mineral processing and its potential to revolutionize the industry by providing a robust, adaptive, and data-driven approach to optimizing plant operations. In summary, this research contributes to the evolving field of mineral processing by showcasing the transformative potential of multimodal artificial intelligence in enhancing plant throughput. The proposed framework offers a holistic solution that integrates machine learning, computer vision, and natural language processing to address the intricacies of mineral extraction processes, paving the way for a more efficient and sustainable future in the mineral processing industry.

Keywords: multimodal AI, computer vision, NLP, mineral processing, mining

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Authors: A.Cifarelli, L. Boggioni, F. Bertini, L. Magon, M. Pitalieri, S. Losio

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Nowadays, the growing environmental awareness and the dwindling of fossil resources stimulate the polyurethane (PU) industry towards renewable polymers with low carbon footprint to replace the feed stocks from petroleum sources. The main challenge in this field consists in replacing high-performance products from fossil-fuel with novel synthetic polymers derived from 'green monomers'. The bio-polyols from plant oils have attracted significant industrial interest and major attention in scientific research due to their availability and biodegradability. Triglycerides rich in unsaturated fatty acids, such as soybean oil (SBO) and linseed oil (ELO), are particularly interesting because their structures and functionalities are tunable by chemical modification in order to obtain polymeric materials with expected final properties. Unfortunately, their use is still limited for processing or performance problems because a high functionality, as well as OH number of the polyols will result in an increase in cross-linking densities of the resulting PUs. The main aim of this study is to evaluate soy and linseed-based polyols as precursors to prepare prepolymers for the production of polyurethane foams (PUFs) or waterborne-polyurethanes (WPU) used as coatings. An effective reaction route is employed for its simplicity and economic impact. Indeed, bio-polyols were synthesized by a two-step method: epoxidation of the double bonds in vegetable oils and solvent-free ring-opening reaction of the oxirane with organic acids. No organic solvents have been used. Acids with different moieties (aliphatic or aromatics) and different length of hydrocarbon backbones can be used to customize polyols with different functionalities. The ring-opening reaction requires a fine tuning of the experimental conditions (time, temperature, molar ratio of carboxylic acid and epoxy group) to control the acidity value of end-product as well as the amount of residual starting materials. Besides, a Lewis base catalyst is used to favor the ring opening reaction of internal epoxy groups of the epoxidized oil and minimize the formation of cross-linked structures in order to achieve less viscous and more processable polyols with narrower polydispersity indices (molecular weight lower than 2000 g/mol⁻¹). The functionality of optimized polyols is tuned from 2 to 4 per molecule. The obtained polyols are characterized by means of GPC, NMR (¹H, ¹³C) and FT-IR spectroscopy to evaluate molecular masses, molecular mass distributions, microstructures and linkage pathways. Several polyurethane foams have been prepared by prepolymer method blending conventional synthetic polyols with new bio-polyols from soybean and linseed oils without using organic solvents. The compatibility of such bio-polyols with commercial polyols and diisocyanates is demonstrated. The influence of the bio-polyols on the foam morphology (cellular structure, interconnectivity), density, mechanical and thermal properties has been studied. Moreover, bio-based WPUs have been synthesized by well-established processing technology. In this synthesis, a portion of commercial polyols is substituted by the new bio-polyols and the properties of the coatings on leather substrates have been evaluated to determine coating hardness, abrasion resistance, impact resistance, gloss, chemical resistance, flammability, durability, and adhesive strength.

Keywords: bio-polyols, polyurethane foams, solvent free synthesis, waterborne-polyurethanes

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Authors: M. Doudi, M. H. Pazandeh, L. Rahimzadeh Torabi

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Bedsores are pressure ulcers that occur on the skin or tissue due to being immobile and lying in bed for extended periods. Bedsores have the potential to progress into open ulcers, increasing the possibility of a variety of bacterial infections. Acinetobacter baumannii, a pathogen of considerable clinical importance, exhibited a significant correlation with Bedsores (pressure ulcers) infections, thereby manifesting a wide spectrum of antibiotic resistance. The emergence of drug resistance has led researchers to focus on alternative methods, particularly phage therapy, for tackling bacterial infections. Phage therapy has emerged as a novel therapeutic approach to regulate the activity of these agents. The management of bacterial infections greatly benefits from the clinical utilization of bacteriophages as a valuable antimicrobial intervention. The primary objective of this investigation consisted of isolating and discerning potent bacteriophage capable of targeting multi-drug-resistant (MDR) and extensively drug-resistant (XDR) bacteria obtained from pressure ulcers. The present study analyzed and isolated A. baumannii strains obtained from a cohort of patients suffering from pressure ulcers at Taleghani Hospital in Ahvaz, Iran. An approach that included biochemical and molecular identification techniques was used to determine the taxonomic classification of bacterial isolates at the genus and species levels. The molecular identification process was facilitated by using the 16S rRNA gene in combination with universal primers 27 F and 1492 R. Bacteriophage was obtained through the isolation process conducted on treatment plant sewage located in Isfahan, Iran. The main goal of this study was to evaluate different characteristics of phage, such as their appearance, the range of hosts they can infect, how quickly they can enter a host, their stability at varying temperatures and pH levels, their effectiveness in killing bacteria, the growth pattern of a single phage stage, mapping of enzymatic digestion, and identification of proteomics patterns. The findings demonstrated that an examination was conducted on a sample of 50 specimens, wherein 15 instances of A. baumannii were identified. These microorganisms are the predominant Gram-negative agents known to cause wound infections in individuals suffering from bedsores. The study's findings indicated a high prevalence of antibiotic resistance in the strains isolated from pressure ulcers, excluding the clinical strains that exhibited responsiveness to colistin. According to the findings obtained from assessments of host range and morphological characteristics of bacteriophage VbɸAB-1, it can be concluded that this phage possesses specificity towards A. Baumannii BAH_Glau1001 was classified as a member of the Podoviridae family. The bacteriophage mentioned earlier showed the strongest antibacterial effect at a temperature of 18 °C and a pH of 6.5. Through the utilization of sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) analysis on protein fragments, it was established that the bacteriophage VbɸAB-1 exhibited a size range between 50 and 75 kilodaltons (KDa). The numerous research findings on the effectiveness of phages and the safety studies conducted suggest that the phages studied in this research can be considered as a practical solution and recommended approach for controlling and treating stubborn pathogens in burn wounds among hospitalized patients. The findings of our research indicated that isolated phages could be an effective antimicrobial and an appreciate candidate for prophylaxis against pressure ulcers.

Keywords: acinetobacter baumannii, extremely drug-resistant, phage therapy, surgery wound

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Authors: Irakli Gamkrelidze, David Shengelia, Giorgi Chichinadze, Tamara Tsutsunava, Giorgi Beridze, Tamara Tsamalashvili, Ketevan Tedliashvili, Irakli Javakhishvili

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The Caucasus is situated between the Eurasian and Africa-Arabian plates and represents a component of the Mediterranean (Alpine-Himalayan) collision belt. The Loki crystalline massif crops out within one of the terranes of the Caucasus – Baiburt-Sevanian terrane. By the end of 2018, a digital geological map (1:50 000) of the Loki massif was compiled. The presented map is of great importance for the region since there is no large-scale geological map which reflects the present standards of the geological study of the massif up to the last time. The existing State Geological Map of the Loki massif is very outdated. A new map drown by using GIS (Geographic Information System) technology is loaded with multi-informative details that include: specified contours of geological units and separate tectonic scales, key mineral assemblages and facies of metamorphism, temperature conditions of metamorphism, ages of metamorphism events and the massif rocks, genetic-geodynamic types of magmatic rocks. Explanatory note, attached to the map includes the large specter of scientific information. It contains characterization of the geological setting, composition and petrogenetic and geodynamic models of the massif formation. To create a geological map of the Loki crystalline massif, appropriate methodologies were applied: a sampling of rocks, GIS technology-based mapping of geological units, microscopic description of the material, composition analysis of rocks, microprobe analysis of minerals and a new interpretation of obtained data. To prepare a digital version of the map the appropriated activities were held including the creation of a common database. Finally, the design was created that includes the elaboration of legend and the final visualization of the map. The results of the study presented in the explanatory note are given below. The autochthonous gneissose quartz diorites of normal alkalinity and sub-alkaline gabbro-diorites included in them belong to different phases of magmatism. They represent “igneous” granites corresponding to mixed mantle-crustal type granites. Four tectonic plates of the allochthonous metamorphic complex–Lower Gorastskali, Sapharlo–Lok-Jandari, Moshevani, and Lower Gorastskali differ from each other by structure and degree of metamorphism. The initial rocks of these plates are formed in different geodynamic conditions and during the Early Bretonian orogeny while overthrusting due to tectonic compression they form a thick tectonic sheet. The Lower Gorastskali overthrust sheet is a fragment of ophiolitic association corresponding to the Paleotethys oceanic crust. The protolith of the ophiolitic complex basites corresponds to the tholeiitic series of basalts. The Sapharlo–Lok-Jandari overthrust sheet is metapelites, metamorphosed in conditions of greenschist facies of regional metamorphism. The regional metamorphism of Moshevani overthrust sheet crystalline schists quartzites corresponds to a range from greenschist to hornfels facies. The “mélange” is built of rock fragments and blocks of above-mentioned overthrust sheets. Sub-alkaline and normal alkaline post-metamorphic granites of the Loki crystalline massif belong to “igneous” and rarely to “sialic” and “anorogenic” types of granites.

Keywords: digital geological map, 1:50 000 scale, crystalline massif, the caucasus

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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Authors: Mohammadjavad Sotoudeheian, Navid Farahmandian

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Kawasaki disease (KD) is the primary cause of acquired pediatric heart disease as an acute vasculitis. In children with prolonged fever, rash, and inflammation of the mucosa KD must be considered as a clinical diagnosis. There is a persuasive suggestion of immune-mediated damage as the pathophysiologic cascade of KD. For example, the invasion of cytotoxic T-cells supports a viral etiology and the inflammasome of the innate immune system is a critical component in the vasculitis formation in KD. Animal models of KD propose the cytokine profiles, such as increased IL-1 and GM-CSF, which cause vascular damage. CRP and IFN-γ elevated expression and the upregulation of IL-6, and IL-10 production are also described in previous studies. Untreated KD is a critical risk factor for coronary artery diseases and myocardial infarction. Vascular damage may encompass amplified T-cell activity. SMAD3 is an essential molecule in down-regulating T-cells and increasing expression of FoxP3. It has a critical effect in the differentiation of regulatory T-cells. The discrepancy of regulatory T-cells and pro-inflammatory Th17 has been studied in acute coronary syndrome during KD. However in the coronary artery damaged lymphocytes and IgA plasma cells are seen at the lesion locations, the major immune cells in the coronary lesions are monocytes/macrophages and neutrophils. These cells secrete TNF-α, and activates matrix metalloprotease (MMP)-9, reducing the integrity of vessels and prompting patients to arise aneurysm. MMPs can break down the components of the extracellular matrix and assist immune cell movement. IVIG as an effective form of treatment clarified the role of the immune system, which may target pathogenic antigens and regulate cytokine production. Several reports have revealed that in the coronary arteries, high expression of MMP-9 in monocyte/macrophage results in pathologic cascades. Curcumin is a potent antioxidant and anti-inflammatory molecule. Curcumin decreases the production of reactive oxygen and nitrogen species and inhibits transcription factors like AP-1 and NF-κB. Curcumin also contains the characteristics of inhibitory effects on MMPs, especially MMP-9. The upregulation of MMP-9 is an important cellular response. Curcumin treatment caused a reverse effect and down-regulates MMP-9 gene expression which may fund the anti-inflammatory effect. Curcumin inhibits MMP-9 expression via PKC and AMPK-dependent pathways in Human monocytes cells. Elevated expression and activity of MMP-9 are correlated with advanced vascular lesions. AMPK controls lipid metabolism and oxidation, and protein synthesis. AMPK is also necessary for the MMP-9 activity and THP-1 cell adhesion to endothelial cells. Curcumin was shown to inhibit the activation of AMPKα. Compound C (AMPK inhibitor) inhibits MMP-9 expression level. Therefore, through inactivating AMPKs and PKC, curcumin decreases the MMP-9 level, which results in inhibiting monocyte/macrophage differentiation. Compound C also suppress the phosphorylation of three major classes of MAP kinase signaling, suggesting that curcumin may suppress MMP-9 level by inactivation of MAPK pathways. MAPK cascades are activated to induce the expression of MMP-9. Curcumin inhibits MAPKs phosphorylation, which contributes to the down-regulation of MMP-9. This study demonstrated that the potential inhibitory properties of curcumin over MMP-9 lead to a therapeutic strategy to reduce the risk of coronary artery involvement during KD.

Keywords: MMP-9, coronary artery aneurysm, Kawasaki’s disease, curcumin, AMPK, immune system, NF-κB, MAPK

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Authors: Sophy Joseph

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The study uses the concept of ‘Settler city’ to understand the nature of peripheralization that a neoliberal city initiates. The settler city designs powerless communities without inherent rights, title and sovereignty. Kathputli Colony, home to generations of artists/craftsmen, who have kept heritage of arts/crafts alive, has undergone eviction of its population from urban space. The proposed study, ‘Neoliberal Settler City: Socio-spatial segregation and livelihood of artists/craftsmen in Delhi’ would problematize the settler city as a colonial technology. The colonial regime has ‘erased’ the ‘unwanted’ as primitive and swept them to peripheries in the city. This study would also highlight how structural change in political economy has undermined their crafts/arts by depriving them from practicing/performing it with dignity in urban space. The interconnections between citizenship and In-Situ Private Public Partnership in Kathputli rehabilitation has become part of academic exercise. However, a comprehensive study connecting inherent characteristics of neoliberal settler city, trajectory of political economy of unorganized workers - artists/craftsmen and legal containment and exclusion leading to dispossession and marginalization of communities from the city site, is relevant to contextualize the trauma of spatial segregation. This study would deal with political, cultural, social and economic dominant behavior of the structure in the state formation, accumulation of property and design of urban space, fueled by segregation of marginalized/unorganized communities and disowning the ‘footloose proletariat’, the migrant workforce. The methodology of study involves qualitative research amongst communities and the field work-oral testimonies and personal accounts- becomes the primary material to theorize the realities. The secondary materials in the forms of archival materials about historical evolution of Delhi as a planned city from various archives, would be used. As the study also adopt ‘narrative approach’ in qualitative study, the life experiences of craftsmen/artists as performers and emotional trauma of losing their livelihood and space forms an important record to understand the instability and insecurity that marginalization and development attributes on urban poor. The study attempts to prove that though there was a change in political tradition from colonialism to constitutional democracy, new state still follows the policy of segregation and dispossession of the communities. It is this dispossession from the space, deprivation of livelihood and non-consultative process in rehabilitation that reflects the neoliberal approach of the state and also critical findings in the study. This study would entail critical spatial lens analyzing ethnographic and sociological data, representational practices and development debates to understand ‘urban otherization’ against craftsmen/artists. This seeks to develop a conceptual framework for understanding the resistance of communities against primitivity attached with them and to decolonize the city. This would help to contextualize the demand for declaring Kathputli Colony as ‘heritage artists village’. The conceptualization and contextualization would help to argue for right to city of the communities, collective rights to property, services and self-determination. The aspirations of the communities also help to draw normative orientation towards decolonization. It is important to study this site as part of the framework, ‘inclusive cities’ because cities are rarely noted as important sites of ‘community struggles’.

Keywords: neoliberal settler city, socio-spatial segregation, the livelihood of artists/craftsmen, dispossession of indigenous communities, urban planning and cultural uprooting

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Authors: Marco F. Benaglia, Mei H. Chen, Kune M. Tsai, Chia H. Hung

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As societal and family structures, consumer dietary habits, and awareness about food safety and quality continue to evolve in most developed countries, the demand for refrigerated and frozen foods has been growing, and the issues related to their preservation have gained increasing attention. A well-established cold chain logistics system is essential to avoid any temperature abuse; therefore, assessing potential disruptions in the operational processes of cold chain logistics centers becomes pivotal. This study preliminarily employs HACCP to find disruption factors in cold chain logistics centers that may cause temperature abuse. Then, concept mapping is applied: selected experts engage in brainstorming sessions to identify any further factors. The panel consists of ten experts, including four from logistics and home delivery, two from retail distribution, one from the food industry, two from low-temperature logistics centers, and one from the freight industry. Disruptions include equipment-related aspects, human factors, management aspects, and process-related considerations. The areas of observation encompass freezer rooms, refrigerated storage areas, loading docks, sorting areas, and vehicle parking zones. The experts also categorize the disruption factors based on perceived similarities and build a similarity matrix. Each factor is evaluated for its impact, frequency, and investment importance. Next, multiple scale analysis, cluster analysis, and other methods are used to analyze these factors. Simultaneously, key disruption factors are identified based on their impact and frequency, and, subsequently, the factors that companies prioritize and are willing to invest in are determined by assessing investors’ risk aversion behavior. Finally, Cumulative Prospect Theory (CPT) is applied to verify the risk patterns. 66 disruption factors are found and categorized into six clusters: (1) "Inappropriate Use and Maintenance of Hardware and Software Facilities", (2) "Inadequate Management and Operational Negligence", (3) "Product Characteristics Affecting Quality and Inappropriate Packaging", (4) "Poor Control of Operation Timing and Missing Distribution Processing", (5) "Inadequate Planning for Peak Periods and Poor Process Planning", and (6) "Insufficient Cold Chain Awareness and Inadequate Training of Personnel". This study also identifies five critical factors in the operational processes of cold chain logistics centers: "Lack of Personnel’s Awareness Regarding Cold Chain Quality", "Personnel Not Following Standard Operating Procedures", "Personnel’s Operational Negligence", "Management’s Inadequacy", and "Lack of Personnel’s Knowledge About Cold Chain". The findings show that cold chain operators prioritize prevention and improvement efforts in the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster, particularly focusing on the factors of "Temperature Setting Errors" and "Management’s Inadequacy". However, through the application of CPT theory, this study reveals that companies are not usually willing to invest in the improvement of factors related to the "Inappropriate Use and Maintenance of Hardware and Software Facilities" cluster due to its low occurrence likelihood, but they acknowledge the severity of the consequences if it does occur. Hence, the main implication is that the key disruption factors in cold chain logistics centers’ processes are associated with personnel issues; therefore, comprehensive training, periodic audits, and the establishment of reasonable incentives and penalties for both new employees and managers may significantly reduce disruption issues.

Keywords: concept mapping, cold chain, HACCP, cumulative prospect theory

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Authors: Catherine Bradshaw

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Educators often report difficulty managing behavior problems and other mental health concerns that students display at school. These concerns also interfere with the learning process and can create distraction for teachers and other students. As such, schools play an important role in both preventing and intervening with students who experience these types of challenges. A number of models have been proposed to serve as a framework for delivering prevention and early intervention services in schools. One such model is called Positive Behavioral Interventions and Supports (PBIS), which has been scaled-up to over 26,000 schools in the U.S. and many other countries worldwide. PBIS aims to improve a range of student outcomes through early detection of and intervention related to behavioral and mental health symptoms. PBIS blends and applies social learning, behavioral, and organizational theories to prevent disruptive behavior and enhance the school’s organizational health. PBIS focuses on creating and sustaining tier 1 (universal), tier 2 (selective), and tier 3 (individual) systems of support. Most schools using PBIS have focused on the core elements of the tier 1 supports, which includes the following critical features. The formation of a PBIS team within the school to lead implementation. Identification and training of a behavioral support ‘coach’, who serves as a on-site technical assistance provider. Many of the individuals identified to serve as a PBIS coach are also trained as a school psychologist or guidance counselor; coaches typically have prior PBIS experience and are trained to conduct functional behavioral assessments. The PBIS team also identifies a set of three to five positive behavioral expectations that are implemented for all students and by all staff school-wide (e.g., ‘be respectful, responsible, and ready to learn’); these expectations are posted in all settings across the school, including in the classroom, cafeteria, playground etc. All school staff define and teach the school-wide behavioral expectations to all students and review them regularly. Finally, PBIS schools develop or adopt a school-wide system to reward or reinforce students who demonstrate those 3-5 positive behavioral expectations. Staff and administrators create an agreed upon system for responding to behavioral violations that include definitions about what constitutes a classroom-managed vs. an office-managed discipline problem. Finally, a formal system is developed to collect, analyze, and use disciplinary data (e.g., office discipline referrals) to inform decision-making. This presentation provides a brief overview of PBIS and reports findings from a series of four U.S. based longitudinal randomized controlled trials (RCTs) documenting the impacts of PBIS on school climate, discipline problems, bullying, and academic achievement. The four RCTs include 80 elementary, 40 middle, and 58 high schools and results indicate a broad range of impacts on multiple student and school-wide outcomes. The session will highlight lessons learned regarding PBIS implementation and scale-up. We also review the ways in which PBIS can help educators and school leaders engage in data-based decision-making and share data with other decision-makers and stakeholders (e.g., students, parents, community members), with the overarching goal of increasing use of evidence-based programs in schools.

Keywords: positive behavioral interventions and supports, mental health, randomized trials, school-based prevention

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Authors: Sam Weber, Deepak Mishra, Susan Wilde, Elizabeth Kramer

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The frequency and severity of cyanobacteria harmful blooms (CyanoHABs) have been increasing over time, with point and non-point source eutrophication and shifting climate paradigms being blamed as the primary culprits. Excessive nutrients, warm temperatures, quiescent water, and heavy and less regular rainfall create more conducive environments for CyanoHABs. CyanoHABs have the potential to produce a spectrum of toxins that cause gastrointestinal stress, organ failure, and even death in humans and animals. To promote enhanced, proactive CyanoHAB management, risk modeling using geospatial tools can act as predictive mechanisms to supplement current CyanoHAB monitoring, management and mitigation efforts. The risk maps would empower water managers to focus their efforts on high risk water bodies in an attempt to prevent CyanoHABs before they occur, and/or more diligently observe those waterbodies. For this research, exploratory spatial data analysis techniques were used to identify the strongest predicators for CyanoHAB blooms based on remote sensing-derived cyanobacteria cell density values for 771 waterbodies in the Georgia Piedmont and landscape characteristics of their watersheds. In-situ datasets for cyanobacteria cell density, nutrients, temperature, and rainfall patterns are not widely available, so free gridded geospatial datasets were used as proxy variables for assessing CyanoHAB risk. For example, the percent of a watershed that is agriculture was used as a proxy for nutrient loading, and the summer precipitation within a watershed was used as a proxy for water quiescence. Cyanobacteria cell density values were calculated using atmospherically corrected images from the European Space Agency’s Sentinel-2A satellite and multispectral instrument sensor at a 10-meter ground resolution. Seventeen explanatory variables were calculated for each watershed utilizing the multi-petabyte geospatial catalogs available within the Google Earth Engine cloud computing interface. The seventeen variables were then used in a multiple linear regression model, and the strongest predictors of cyanobacteria cell density were selected for the final regression model. The seventeen explanatory variables included land cover composition, winter and summer temperature and precipitation data, topographic derivatives, vegetation index anomalies, and soil characteristics. Watershed maximum summer temperature, percent agriculture, percent forest, percent impervious, and waterbody area emerged as the strongest predictors of cyanobacteria cell density with an adjusted R-squared value of 0.31 and a p-value ~ 0. The final regression equation was used to make a normalized cyanobacteria cell density index, and a Jenks Natural Break classification was used to assign waterbodies designations of low, medium, or high risk. Of the 771 waterbodies, 24.38% were low risk, 37.35% were medium risk, and 38.26% were high risk. This study showed that there are significant relationships between free geospatial datasets representing summer maximum temperatures, nutrient loading associated with land use and land cover, and the area of a waterbody with cyanobacteria cell density. This data analytics approach to CyanoHAB risk assessment corroborated the literature-established environmental triggers for CyanoHABs, and presents a novel approach for CyanoHAB risk mapping in waterbodies across the greater southeastern United States.

Keywords: cyanobacteria, land use/land cover, remote sensing, risk mapping

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Authors: Ariesny Vera, Rodrigo Montecinos

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The rare-earth elements (REEs) or rare-earth metals (REMs), correspond to seventeen chemical elements composed by the fifteen lanthanoids, as well as scandium and yttrium. Lanthanoids corresponds to lanthanum and the f-block elements, from cerium to lutetium. Scandium and yttrium are considered rare-earth elements because they have ionic radii similar to the lighter f-block elements. These elements were called rare earths because they are simply more difficult to extract and separate individually than the most metals and, generally, they do not accumulate in minerals, they are rarely found in easily mined ores and are often unfavorably distributed in common ores/minerals. REEs show unique chemical and physical properties, in comparison to the other metals in the periodic table. Nowadays, these physicochemical properties are utilized in a wide range of synthetic, catalytic, electronic, medicinal, and military applications. Because of their applications, the global demand for rare earth metals is becoming progressively more important in the transition to a self-sustaining society and greener economy. However, due to the difficult separation between lanthanoid ions, the high cost and pollution of these processes, the scientists search the development of a method that combines selectivity and quantitative separation of lanthanoids from the leaching liquor, while being more economical and environmentally friendly processes. This motivation has favored the design and development of more efficient and environmentally friendly cation extractors with the incorporation of compounds as ionic liquids, membrane inclusion polymers (PIM) and supramolecular systems. Supramolecular chemistry focuses on the development of host-guest systems, in which a host molecule can recognize and bind a certain guest molecule or ion. Normally, the formation of a host-guest complex involves non-covalent interactions Additionally, host-guest interactions can be influenced among others effects by the structural nature of host and guests. The different macrocyclic hosts for lanthanoid species that have been studied are crown ethers, cyclodextrins, cucurbituryls, calixarenes and pillararenes.Among all the factors that can influence and affect lanthanoid (III) coordination, perhaps the most basic of them is the systematic control using macrocyclic substituents that promote a selective coordination. In this sense, macrocycles pillar[n]arenes (P[n]As) present a relatively easy functionalization and they have more π-rich cavity than other host molecules. This gives to P[n]As a negative electrostatic potential in the cavity which would be responsible for the selectivity of these compounds towards cations. Furthermore, the cavity size, the linker, and the functional groups of the polar headgroups could be modified in order to control the association of lanthanoid cations. In this sense, different P[n]As systems, specifically derivatives of the pentamer P[5]A functionalized with amide, amine, phosphate and sulfate derivatives, have been designed in terms of experimental synthesis and molecular dynamics, and the interaction between these P[5]As and some lanthanoid ions such as La³+, Eu³+ and Lu³+ has been studied by physicochemical characterization by 1H-NMR, ITC and fluorescence in the case of Eu³+ systems. The molecular dynamics study of these systems was developed in hexane as solvent, also taking into account the lanthanoid ions mentioned above, and the respective comparison studies between the different ions.

Keywords: lanthanoids, macrocycles, pillar[n]arenes, rare-earth metal extraction, supramolecular chemistry, supramolecular complexes.

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Authors: Pauline Nyssen, Ange Mouithys-Mickalad, Maryse Hoebeke

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Inflammation is a complex physiological phenomenon involving chemical and enzymatic mechanisms. Polymorphonuclear neutrophil leukocytes (PMNs) play an important role by producing reactive oxygen species (ROS) and releasing myeloperoxidase (MPO), a pro-oxidant enzyme. Released both in the phagolysosome and the extracellular medium, MPO produces during its peroxidase and halogenation cycles oxidant species, including hypochlorous acid, involved in the destruction of pathogen agents, like bacteria or viruses. Inflammatory pathologies, like rheumatoid arthritis, atherosclerosis induce an excessive stimulation of the PMNs and, therefore, an uncontrolled release of ROS and MPO in the extracellular medium, causing severe damages to the surrounding tissues and biomolecules such as proteins, lipids, and DNA. The treatment of chronic inflammatory pathologies remains a challenge. For many years, MPO has been used as a target for the development of effective treatments. Numerous studies have been focused on the design of new drugs presenting more efficient MPO inhibitory properties. However, some designed inhibitors can be toxic. An alternative consists of assessing the potential inhibitory action of clinically-known molecules, having antioxidant activity. Propofol, 2,6-diisopropyl phenol, which is used as an intravenous anesthetic agent, meets these requirements. Besides its anesthetic action employed to induce a sedative state during surgery or in intensive care units, propofol and its injectable form Diprivan indeed present antioxidant properties and act as ROS and free radical scavengers. A study has also evidenced the ability of propofol to inhibit the formation of the neutrophil extracellular traps fibers, which are important to trap pathogen microorganisms during the inflammation process. The aim of this study was to investigate the potential inhibitory action mechanism of propofol and Diprivan on MPO activity. To go into the anti-inflammatory action of propofol in-depth, two of its oxidative derivatives, 2,6-diisopropyl-1,4-p-benzoquinone (PPFQ) and 3,5,3’,5’-tetra isopropyl-(4,4’)-diphenoquinone (PPFDQ), were studied regarding their inhibitory action. Specific immunological extraction followed by enzyme detection (SIEFED) and molecular modeling have evidenced the low anti-catalytic action of propofol. Stopped-flow absorption spectroscopy and direct MPO activity analysis have proved that propofol acts as a reversible MPO inhibitor by interacting as a reductive substrate in the peroxidase cycle and promoting the accumulation of redox compound II. Overall, Diprivan exhibited a weaker inhibitory action than the active molecule propofol. In contrast, PPFQ seemed to bind and obstruct the enzyme active site, preventing the trigger of the MPO oxidant cycles. PPFQ induced a better chlorination cycle inhibition at basic and neutral pH in comparison to propofol. PPFDQ did not show any MPO inhibition activity. The three interest molecules have also demonstrated their inhibition ability on an important step of the inflammation pathway, the PMNs superoxide anions production, thanks to EPR spectroscopy and chemiluminescence. In conclusion, propofol presents an interesting immunomodulatory activity by acting as a reductive substrate in the peroxidase cycle of MPO, slowing down its activity, whereas PPFQ acts more as an anti-catalytic substrate. Although PPFDQ has no impact on MPO, it can act on the inflammation process by inhibiting the superoxide anions production by PMNs.

Keywords: Diprivan, inhibitor, myeloperoxidase, propofol, spectroscopy

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Authors: Andreas Rudisch, Ralf Lampert, Andreas Kolbitsch

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It is a well-known fact among the engineering community that earthquakes with comparatively low magnitudes can cause serious damage to nonstructural components (NSCs) of buildings, even when the supporting structure performs relatively well. Past research works focused mainly on NSCs of nuclear power plants and industrial plants. Particular attention should also be given to architectural façade elements of old masonry buildings (e.g. ornamental figures, balustrades, vases), which are very vulnerable under seismic excitation. Large numbers of these historical nonstructural components (HiNSCs) can be found in highly frequented historical city centers and in the event of failure, they pose a significant danger to persons. In order to estimate the vulnerability of acceleration sensitive HiNSCs, the peak horizontal floor acceleration (PHFA) is used. The PHFA depends on the dynamic characteristics of the building, the ground excitation, and induced nonlinearities. Consequently, the PHFA can not be generalized as a simple function of height. In the present research work, an extensive case study was conducted to investigate the influence of induced nonlinearity on the PHFA for old masonry buildings. Probabilistic nonlinear FE time-history analyses considering three different hazard levels were performed. A set of eighteen synthetically generated ground motions was used as input to the structure models. An elastoplastic macro-model (multiPlas) for nonlinear homogenized continuum FE-calculation was calibrated to multiple scales and applied, taking specific failure mechanisms of masonry into account. The macro-model was calibrated according to the results of specific laboratory and cyclic in situ shear tests. The nonlinear macro-model is based on the concept of multi-surface rate-independent plasticity. Material damage or crack formation are detected by reducing the initial strength after failure due to shear or tensile stress. As a result, shear forces can only be transmitted to a limited extent by friction when the cracking begins. The tensile strength is reduced to zero. The first goal of the calibration was the consistency of the load-displacement curves between experiment and simulation. The calibrated macro-model matches well with regard to the initial stiffness and the maximum horizontal load. Another goal was the correct reproduction of the observed crack image and the plastic strain activities. Again the macro-model proved to work well in this case and shows very good correlation. The results of the case study show that there is significant scatter in the absolute distribution of the PHFA between the applied ground excitations. An absolute distribution along the normalized building height was determined in the framework of probability theory. It can be observed that the extent of nonlinear behavior varies for the three hazard levels. Due to the detailed scope of the present research work, a robust comparison with code-recommendations and simplified PHFA distributions are possible. The chosen methodology offers a chance to determine the distribution of PHFA along the building height of old masonry structures. This permits a proper hazard assessment of HiNSCs under seismic loads.

Keywords: nonlinear macro-model, nonstructural components, time-history analysis, unreinforced masonry

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Authors: Eunjung Lee

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This research investigates the intricate connection between cultural differences and online consumer behaviors by integrating Hofstede's Cultural Dimensions theory with analysis methodologies such as text mining, data mining, and topic analysis. Our aim is to provide a comprehensive understanding of how national cultural differences influence individuals' behaviors when engaging with online reviews. To ensure the relevance of our investigation, we systematically analyze and interpret the cultural nuances influencing online consumer behaviors, especially in the context of online reviews. By anchoring our research in Hofstede's Cultural Dimensions theory, we seek to offer valuable insights for marketers to tailor their strategies based on the cultural preferences of diverse global consumer bases. In our methodology, we employ advanced text mining techniques to extract insights from a diverse range of online reviews gathered globally for a specific product or service like Netflix. This approach allows us to reveal hidden cultural cues in the language used by consumers from various backgrounds. Complementing text mining, data mining techniques are applied to extract meaningful patterns from online review datasets collected from different countries, aiming to unveil underlying structures and gain a deeper understanding of the impact of cultural differences on online consumer behaviors. The study also integrates topic analysis to identify recurring subjects, sentiments, and opinions within online reviews. Marketers can leverage these insights to inform the development of culturally sensitive strategies, enhance target audience segmentation, and refine messaging approaches aligned with cultural preferences. Anchored in Hofstede's Cultural Dimensions theory, our research employs sophisticated methodologies to delve into the intricate relationship between cultural differences and online consumer behaviors. Applied to specific cultural dimensions, such as individualism vs. collectivism, masculinity vs. femininity, uncertainty avoidance, and long-term vs. short-term orientation, the study uncovers nuanced insights. For example, in exploring individualism vs. collectivism, we examine how reviewers from individualistic cultures prioritize personal experiences while those from collectivistic cultures emphasize communal opinions. Similarly, within masculinity vs. femininity, we investigate whether distinct topics align with cultural notions, such as robust features in masculine cultures and user-friendliness in feminine cultures. Examining information-seeking behaviors under uncertainty avoidance reveals how cultures differ in seeking detailed information or providing succinct reviews based on their comfort with ambiguity. Additionally, in assessing long-term vs. short-term orientation, the research explores how cultural focus on enduring benefits or immediate gratification influences reviews. These concrete examples contribute to the theoretical enhancement of Hofstede's Cultural Dimensions theory, providing a detailed understanding of cultural impacts on online consumer behaviors. As online reviews become increasingly crucial in decision-making, this research not only contributes to the academic understanding of cultural influences but also proposes practical recommendations for enhancing online review systems. Marketers can leverage these findings to design targeted and culturally relevant strategies, ultimately enhancing their global marketing effectiveness and optimizing online review systems for maximum impact.

Keywords: comparative analysis, cultural dimensions, marketing intelligence, national culture, online consumer behavior, text mining

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Authors: Junkal Gutierrez, Hernane S. Barud, Sidney J. L. Ribeiro, Agnieszka Tercjak

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Nowadays the interest on green nanocomposites and on the development of more environmental friendly products has been increased. Bacterial cellulose has been recently investigated as an attractive environmentally friendly material for the preparation of low-cost nanocomposites. The formation of cellulose by laboratory bacterial cultures is an interesting and attractive biomimetic access to obtain pure cellulose with excellent properties. Additionally, properties as molar mass, molar mass distribution, and the supramolecular structure could be control using different bacterial strain, culture mediums and conditions, including the incorporation of different additives. This kind of cellulose is a natural nanomaterial, and therefore, it has a high surface-to-volume ratio which is highly advantageous in composites production. Such property combined with good biocompatibility, high tensile strength, and high crystallinity makes bacterial cellulose a potential material for applications in different fields. The aim of this investigation work was the fabrication of novel hybrid inorganic-organic composites based on bacterial cellulose, cultivated in our laboratory, as a template. This kind of biohybrid nanocomposites gathers together excellent properties of bacterial cellulose with the ones displayed by typical inorganic nanoparticles like optical, magnetic and electrical properties, luminescence, ionic conductivity and selectivity, as well as chemical or biochemical activity. In addition, the functionalization of cellulose with inorganic materials opens new pathways for the fabrication of novel multifunctional hybrid materials with promising properties for a wide range of applications namely electronic paper, flexible displays, solar cells, sensors, among others. In this work, different pathways for fabrication of multifunctional biohybrid nanopapers with tunable properties based on BC modified with amphiphilic poly(ethylene oxide-b-propylene oxide-b-ethylene oxide) (EPE) block copolymer, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and functionalized iron oxide nanoparticles will be presented. In situ (biosynthesized) and ex situ (at post-production level) approaches were successfully used to modify BC membranes. Bacterial cellulose based biocomposites modified with different EPE block copolymer contents were developed by in situ technique. Thus, BC growth conditions were manipulated to fabricate EPE/BC nanocomposite during the biosynthesis. Additionally, hybrid inorganic/organic nanocomposites based on BC membranes and inorganic nanoparticles were designed via ex-situ method, by immersion of never-dried BC membranes into different nanoparticle solutions. On the one hand, sol-gel synthesized nanoparticles (titanium, vanadium and a mixture of both oxides) and on the other hand superparamagnetic iron oxide nanoparticles (SPION), Fe2O3-PEO solution. The morphology of designed novel bionanocomposites hybrid materials was investigated by atomic force microscopy (AFM) and scanning electron microscopy (SEM). In order to characterized obtained materials from the point of view of future applications different techniques were employed. On the one hand, optical properties were analyzed by UV-vis spectroscopy and spectrofluorimetry and on the other hand electrical properties were studied at nano and macroscale using electric force microscopy (EFM), tunneling atomic force microscopy (TUNA) and Keithley semiconductor analyzer, respectively. Magnetic properties were measured by means of magnetic force microscopy (MFM). Additionally, mechanical properties were also analyzed.

Keywords: bacterial cellulose, block copolymer, advanced characterization techniques, nanoparticles

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Authors: Maari Sugawara

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This ethnographic research interrogates female masochism within contemporary Japan, focusing on fifteen female BDSM (Bondage, Discipline, Dominance, Submission, Sadism, and Masochism) practitioners who identify as masochists, bottoms, and/or submissives. The study employs semi-structured interviews with these practitioners, representing diverse backgrounds and ages, to explore the intersection of sexuality and individual and/or collective trauma. The study focuses on a specific group of sadomasochists who, as survivors of gender and sexual violence, reenact their trauma through BDSM practices. This exploration draws on feminist performance studies, postcolonial studies, psychoanalysis, and affect analysis to highlight the complexities of female masochism. In a cultural milieu that often reduces female masochism to mere compliance with heteropatriarchy, this study argues that specific masochistic practices transcend submission, serving as vital strategies for confronting trauma and dismantling entrenched cultural narratives. Engaging with Lacan’s concept of feminine jouissance and the notion of "creative masochism" in the context of Japan's proximity to the imperial US, the study facilitates a nuanced exploration of female masochistic enjoyment. The study shows that these practices can act as both a means of survival and a mode of resilience, challenging dominant narratives that portray masochism solely as a form of subjugation, drawing on feminist performance studies, postcolonial studies, psychoanalysis, and affect analysis. It interprets masochism as a complex terrain of affective engagement, where shared suffering and consensual pain foster transformative possibilities. By analyzing BDSM as a cultural site, this research reframes masochism not only as a personal negotiation of pain but also as a broader allegory for Japan’s ongoing geopolitical self-positioning. Central to this analysis is the concept of "creative masochism," which positions masochism as both a metaphor and a practice through which Japan addresses its historical subordination to the United States. This framework allows for a deeper understanding of how participants' lived desires intersect with national narratives, illuminating the relationship between personal experiences and larger socio-political dynamics. It incorporates sadomasochistic metaphors into Japan-U.S. interactions, reflecting underlying patterns of submission, resistance, and cultural negotiation. Additionally, this research examines the effects, affects, and limitations of masochism within the post-WWII Japanese context, providing insights into how masochism can reshape one's relationship with their surroundings. This study challenges the notion that female masochism is entirely subsumed by hegemonic structures, revealing instead that subjects can assert their autonomy within their experiences of pleasure and pain. The consensual enactment of violence within these encounters emerges as a complex and ambivalent process, wherein pain transforms into a generative force for reimagining alternative forms of sociality and belonging. Additionally, the research identifies contradictions and connections between the personal and political, examining how kink practices shape participants' daily lives and identities, and vice versa, highlighting the profound impact of these practices on their sense of self and community. Ultimately, it reaffirms agency in the face of pervasive heteronormative power dynamics, suggesting that masochism can serve as a site of both resistance and redefinition.

Keywords: female masochism, BDSM, Japan, masochism, trauma, sexual violence

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Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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The escalating prevalence of mental health issues, such as depression and suicidal ideation, is a matter of significant global concern. It is plausible that a variety of factors, such as life events, social isolation, and preexisting physiological or psychological health conditions, could instigate or exacerbate these conditions. Traditional approaches to diagnosing depression entail a considerable amount of time and necessitate the involvement of adept practitioners. This underscores the necessity for automated systems capable of promptly detecting and diagnosing symptoms of depression. The PsyVBot system employs sophisticated natural language processing and machine learning methodologies, including the use of the NLTK toolkit for dataset preprocessing and the utilization of a Long Short-Term Memory (LSTM) model. The PsyVBot exhibits a remarkable ability to diagnose depression with a 94% accuracy rate through the analysis of user input. Consequently, this resource proves to be efficacious for individuals, particularly those enrolled in academic institutions, who may encounter challenges pertaining to their psychological well-being. The PsyVBot employs a Long Short-Term Memory (LSTM) model that comprises a total of three layers, namely an embedding layer, an LSTM layer, and a dense layer. The stratification of these layers facilitates a precise examination of linguistic patterns that are associated with the condition of depression. The PsyVBot has the capability to accurately assess an individual's level of depression through the identification of linguistic and contextual cues. The task is achieved via a rigorous training regimen, which is executed by utilizing a dataset comprising information sourced from the subreddit r/SuicideWatch. The diverse data present in the dataset ensures precise and delicate identification of symptoms linked with depression, thereby guaranteeing accuracy. PsyVBot not only possesses diagnostic capabilities but also enhances the user experience through the utilization of audio outputs. This feature enables users to engage in more captivating and interactive interactions. The PsyVBot platform offers individuals the opportunity to conveniently diagnose mental health challenges through a confidential and user-friendly interface. Regarding the advancement of PsyVBot, maintaining user confidentiality and upholding ethical principles are of paramount significance. It is imperative to note that diligent efforts are undertaken to adhere to ethical standards, thereby safeguarding the confidentiality of user information and ensuring its security. Moreover, the chatbot fosters a conducive atmosphere that is supportive and compassionate, thereby promoting psychological welfare. In brief, PsyVBot is an automated conversational agent that utilizes an LSTM model to assess the level of depression in accordance with the input provided by the user. The demonstrated accuracy rate of 94% serves as a promising indication of the potential efficacy of employing natural language processing and machine learning techniques in tackling challenges associated with mental health. The reliability of PsyVBot is further improved by the fact that it makes use of the Reddit dataset and incorporates Natural Language Toolkit (NLTK) for preprocessing. PsyVBot represents a pioneering and user-centric solution that furnishes an easily accessible and confidential medium for seeking assistance. The present platform is offered as a modality to tackle the pervasive issue of depression and the contemplation of suicide.

Keywords: chatbot, depression diagnosis, LSTM model, natural language process

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Authors: Chusit Apirumanekul, Chayanis Krittasudthacheewa, Ratchapat Ratanavaraha, Yanyong Inmuong

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Rapid economic development in the Lower Mekong region is leading to changes in water quantity and quality. Changes in land- and forest-use, infrastructure development, increasing urbanization, migration patterns and climate risks are increasing demands for water, within various sectors, placing pressure on scarce water resources. Appropriate policies, strategies, and planning are urgently needed for improved water resource management. Over the last decade, Thailand has experienced more frequent and intense drought situations, affecting the level of water storage in reservoirs along with insufficient water allocation for agriculture during the dry season. The Huay Saibat River Basin, one of the well-known water-scarce areas in the northeastern region of Thailand, is experiencing ongoing water scarcity that affects both farming livelihoods and household consumption. Drought management in Thailand mainly focuses on emergency responses, rather than advance preparation and mitigation for long-term solutions. Despite many efforts from local authorities to mitigate the drought situation, there is yet no long-term comprehensive water management strategy, that integrates climate risks alongside other uncertainties. This paper assesses the application in the Huay Saibat River Basin, of the Robust Decision Support framework, to explore the feasibility of multiple drought management policies; including a shift in cropping season, in crop changes, in infrastructural operations and in the use of groundwater, under a wide range of uncertainties, including climate and land-use change. A series of consultative meetings were organized with relevant agencies and experts at the local level, to understand and explore plausible water resources strategies and identify thresholds to evaluate the performance of those strategies. Three different climate conditions were identified (dry, normal and wet). Other non-climatic factors influencing water allocation were further identified, including changes from sugarcane to rubber, delaying rice planting, increasing natural retention storage and using groundwater to supply demands for household consumption and small-scale gardening. Water allocation and water use in various sectors, such as in agriculture, domestic, industry and the environment, were estimated by utilising the Water Evaluation And Planning (WEAP) system, under various scenarios developed from the combination of climatic and non-climatic factors mentioned earlier. Water coverage (i.e. percentage of water demand being successfully supplied) was defined as a threshold for water resource strategy assessment. Thresholds for different sectors (agriculture, domestic, industry, and environment) were specified during multi-stakeholder engagements. Plausible water strategies (e.g. increasing natural retention storage, change of crop type and use of groundwater as an alternative source) were evaluated based on specified thresholds in 4 sectors (agriculture, domestic, industry, and environment) under 3 climate conditions. 'Business as usual' was evaluated for comparison. The strategies considered robust, emerge when performance is assessed as successful, under a wide range of uncertainties across the river basin. Without adopting any strategy, the water scarcity situation is likely to escalate in the future. Among the strategies identified, the use of groundwater as an alternative source was considered a potential option in combating water scarcity for the basin. Further studies are needed to explore the feasibility for groundwater use as a potential sustainable source.

Keywords: climate change, robust decision support, scenarios, water resources management

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Authors: Hyohun Kim, Dongwha Shin, Yeonseok Kim, Ji-Su Ahn, Kensuke Nakamura, Dongeun Choi, Byung-Woo Hong

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Artefacts are commonly encountered in the imaging process of clinical computed tomography (CT) where the artefact refers to any systematic discrepancy between the reconstructed observation and the true attenuation coefficient of the object. It is known that CT images are inherently more prone to artefacts due to its image formation process where a large number of independent detectors are involved, and they are assumed to yield consistent measurements. There are a number of different artefact types including noise, beam hardening, scatter, pseudo-enhancement, motion, helical, ring, and metal artefacts, which cause serious difficulties in reading images. Thus, it is desired to remove nuisance factors from the degraded image leaving the fundamental intrinsic information that can provide better interpretation of the anatomical and pathological characteristics. However, it is considered as a difficult task due to the high dimensionality and variability of data to be recovered, which naturally motivates the use of machine learning techniques. We propose an image restoration algorithm based on the deep neural network framework where the denoising auto-encoders are stacked building multiple layers. The denoising auto-encoder is a variant of a classical auto-encoder that takes an input data and maps it to a hidden representation through a deterministic mapping using a non-linear activation function. The latent representation is then mapped back into a reconstruction the size of which is the same as the size of the input data. The reconstruction error can be measured by the traditional squared error assuming the residual follows a normal distribution. In addition to the designed loss function, an effective regularization scheme using residual-driven dropout determined based on the gradient at each layer. The optimal weights are computed by the classical stochastic gradient descent algorithm combined with the back-propagation algorithm. In our algorithm, we initially decompose an input image into its intrinsic representation and the nuisance factors including artefacts based on the classical Total Variation problem that can be efficiently optimized by the convex optimization algorithm such as primal-dual method. The intrinsic forms of the input images are provided to the deep denosing auto-encoders with their original forms in the training phase. In the testing phase, a given image is first decomposed into the intrinsic form and then provided to the trained network to obtain its reconstruction. We apply our algorithm to the restoration of the corrupted CT images by the artefacts. It is shown that our algorithm improves the readability and enhances the anatomical and pathological properties of the object. The quantitative evaluation is performed in terms of the PSNR, and the qualitative evaluation provides significant improvement in reading images despite degrading artefacts. The experimental results indicate the potential of our algorithm as a prior solution to the image interpretation tasks in a variety of medical imaging applications. This work was supported by the MISP(Ministry of Science and ICT), Korea, under the National Program for Excellence in SW (20170001000011001) supervised by the IITP(Institute for Information and Communications Technology Promotion).

Keywords: auto-encoder neural network, CT image artefact, deep learning, intrinsic image representation, noise reduction, total variation

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Authors: Nayer Mofidtabatabaei

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Advancements in artificial intelligence (AI) have transformed various fields, including psychology and behavioral sciences. This paper explores the diverse ways in which AI is applied to enhance research, diagnosis, therapy, and understanding of human behavior and mental health. We discuss the potential benefits and challenges associated with AI in these fields, emphasizing the ethical considerations and the need for collaboration between AI researchers and psychological and behavioral science experts. Artificial Intelligence (AI) has gained prominence in recent years, revolutionizing multiple industries, including healthcare, finance, and entertainment. One area where AI holds significant promise is the field of psychology and behavioral sciences. AI applications in this domain range from improving the accuracy of diagnosis and treatment to understanding complex human behavior patterns. This paper aims to provide an overview of the various AI applications in psychological and behavioral sciences, highlighting their potential impact, challenges, and ethical considerations. Mental Health Diagnosis AI-driven tools, such as natural language processing and sentiment analysis, can analyze large datasets of text and speech to detect signs of mental health issues. For example, chatbots and virtual therapists can provide initial assessments and support to individuals suffering from anxiety or depression. Autism Spectrum Disorder (ASD) Diagnosis AI algorithms can assist in early ASD diagnosis by analyzing video and audio recordings of children's behavior. These tools help identify subtle behavioral markers, enabling earlier intervention and treatment. Personalized Therapy AI-based therapy platforms use personalized algorithms to adapt therapeutic interventions based on an individual's progress and needs. These platforms can provide continuous support and resources for patients, making therapy more accessible and effective. Virtual Reality Therapy Virtual reality (VR) combined with AI can create immersive therapeutic environments for treating phobias, PTSD, and social anxiety. AI algorithms can adapt VR scenarios in real-time to suit the patient's progress and comfort level. Data Analysis AI aids researchers in processing vast amounts of data, including survey responses, brain imaging, and genetic information. Privacy Concerns Collecting and analyzing personal data for AI applications in psychology and behavioral sciences raise significant privacy concerns. Researchers must ensure the ethical use and protection of sensitive information. Bias and Fairness AI algorithms can inherit biases present in training data, potentially leading to biased assessments or recommendations. Efforts to mitigate bias and ensure fairness in AI applications are crucial. Transparency and Accountability AI-driven decisions in psychology and behavioral sciences should be transparent and subject to accountability. Patients and practitioners should understand how AI algorithms operate and make decisions. AI applications in psychological and behavioral sciences have the potential to transform the field by enhancing diagnosis, therapy, and research. However, these advancements come with ethical challenges that require careful consideration. Collaboration between AI researchers and psychological and behavioral science experts is essential to harness AI's full potential while upholding ethical standards and privacy protections. The future of AI in psychology and behavioral sciences holds great promise, but it must be navigated with caution and responsibility.

Keywords: artificial intelligence, psychological sciences, behavioral sciences, diagnosis and therapy, ethical considerations

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Authors: Laura Norfolk, Georgina Zimbitas, Jan Sefcik, Sarah Staniland

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Magnetite nanoparticles (MNP) have been an area of increasing research interest due to their extensive applications in industry, such as in carbon capture, water purification, and crucially, the biomedical industry. The use of MNP in the biomedical industry is rising, with studies on their effect as Magnetic resonance imaging contrast agents, drug delivery systems, and as hyperthermic cancer treatments becoming prevalent in the nanomaterial research community. Particles used for biomedical purposes must meet stringent criteria; the particles must have consistent shape and size between particles. Variation between particle morphology can drastically alter the effective surface area of the material, making it difficult to correctly dose particles that are not homogeneous. Particles of defined shape such as octahedral and cubic have been shown to outperform irregular shaped particles in some applications, leading to the need to synthesize particles of defined shape. In nature, highly homogeneous MNP are found within magnetotactic bacteria, a unique bacteria capable of producing magnetite nanoparticles internally under ambient conditions. Biomineralisation proteins control the properties of the MNPs, enhancing their homogeneity. One of these proteins, Mms6, has been successfully isolated and used in vitro as an additive in room-temperature co-precipitation reactions (RTCP) to produce particles of defined mono-dispersed size & morphology. When considering future industrial scale-up it is crucial to consider the costs and feasibility of an additive, as an additive that is not readily available or easily synthesized at a competitive price will not be sustainable. As such, additives selected for this research are inspired by the functional groups of biomineralisation proteins, but cost-effective, environmentally friendly, and compatible with scale-up. Diethylenetriamine (DETA), triethylenetetramine (TETA), tetraethylenepentamine (TEPA), and pentaethylenehexamine (PEHA) have been successfully used in RTCP to modulate the properties of particles synthesized, leading to the formation of octahedral nanoparticles with no use of organic solvents, heating, or toxic precursors. By extending this principle to a fluidic system, ongoing research will reveal whether the amine additives can also exert morphological control in an environment which is suited toward higher particle yield. Two fluidic systems have been employed; a peristaltic turbulent flow mixing system suitable for the rapid production of MNP, and a macrofluidic system for the synthesis of tailored nanomaterials under a laminar flow regime. The presence of the amine additives in the turbulent flow system in initial results appears to offer similar morphological control as observed under RTCP conditions, with higher proportions of octahedral particles formed. This is a proof of concept which may pave the way to green synthesis of tailored MNP on an industrial scale. Mms6 and amine additives have been used in the macrofluidic system, with Mms6 allowing magnetite to be synthesized at unfavourable ferric ratios, but no longer influencing particle size. This suggests this synthetic technique while still benefiting from the addition of additives, may not allow additives to fully influence the particles formed due to the faster timescale of reaction. The amine additives have been tested at various concentrations, the results of which will be discussed in this paper.

Keywords: bioinspired, green synthesis, fluidic, magnetite, morphological control, scale-up

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Authors: Danielle Slomberg, Jerome Labille, Riccardo Catalano, Jean-Claude Hubaud, Alexandra Lopes, Alice Tagliati, Teresa Fernandes

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In the assessment and management of cosmetics and personal care products, sunscreens are of emerging concern regarding both human and environmental health. Organic UV blockers in many sunscreens have been evidenced to undergo rapid photodegradation, induce dermal allergic reactions due to skin penetration, and to cause adverse effects on marine systems. While mineral UV-blockers may offer a safer alternative, their fate and impact and resulting regulation are still under consideration, largely related to the potential influence of nanotechnology-based products on both consumers and the environment. Nanometric titanium dioxide (TiO₂) UV-blockers have many advantages in terms of sun protection and asthetics (i.e., transparency). These UV-blockers typically consist of rutile nanoparticles coated with a primary mineral layer (silica or alumina) aimed at blocking the nanomaterial photoactivity and can include a secondary organic coating (e.g., stearic acid, methicone) aimed at favouring dispersion of the nanomaterial in the sunscreen formulation. The nanomaterials contained in the sunscreen can leave the skin either through a bathing of everyday usage, with subsequent release into rivers, lakes, seashores, and/or sewage treatment plants. The nanomaterial behaviour, fate and impact in these different systems is largely determined by its surface properties, (e.g. the nanomaterial coating type) and lifetime. The present work aims to develop the eco-design of sunscreens through the minimisation of risks associated with nanomaterials incorporated into the formulation. All stages of the sunscreen’s life cycle must be considered in this aspect, from its manufacture to its end-of-life, through its use by the consumer to its impact on the exposed environment. Reducing the potential release and/or toxicity of the nanomaterial from the sunscreen is a decisive criterion for its eco-design. TiO₂ UV-blockers of varied size and surface coating (e.g., stearic acid and silica) have been selected for this study. Hydrophobic TiO₂ UV-blockers (i.e., stearic acid-coated) were incorporated into a typical water-in-oil (w/o) formulation while hydrophilic, silica-coated TiO₂ UV-blockers were dispersed into an oil-in-water (o/w) formulation. The resulting sunscreens were characterised in terms of nanomaterial localisation, sun protection factor, and photo-passivation. The risk to the direct aquatic environment was assessed by evaluating the release of nanomaterials from the sunscreen through a simulated laboratory aging procedure. The size distribution, surface charge, and degradation state of the nano-composite by-products, as well as their nanomaterial concentration and colloidal behaviour were determined in a variety of aqueous environments (e.g., seawater and freshwater). Release of the hydrophobic nanocomposites into the aqueous environment was driven by oil droplet formation while hydrophilic nano-composites were readily dispersed. Ecotoxicity of the sunscreen by-products (from both w/o and o/w formulations) and their risk to marine organisms were assessed using coral symbiotes and tropical corals, evaluating both lethal and sublethal toxicities. The data dissemination and provided risk knowledge from the present work will help guide regulation related to nanomaterials in sunscreen, provide better information for consumers, and allow for easier decision-making for manufacturers.

Keywords: alteration, environmental fate, sunscreens, titanium dioxide nanoparticles

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Authors: Tugba Altin

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In an era marked by pronounced climate change consequences, communities are observed to confront traumatic events that yield both tangible and intangible repercussions. Such events not only cause discernible damage to the landscape but also deeply affect the intangible aspects, including emotional distress and disruptions to cultural landscapes. The Lytton Creek Fire of 2021 serves as a case in point. Beyond the visible destruction, the less overt but profoundly impactful disturbance to place attachment (PA) is scrutinized. PA, representing the emotional and cognitive bonds individuals establish with their environments, is crucial for understanding how such events impact cultural identity and connection to the land. The study underscores the significance of addressing both tangible and intangible traumas for holistic community recovery. As communities renegotiate their affiliations with altered environments, the cultural landscape emerges as instrumental in shaping place-based identities. This renewed understanding is pivotal for reshaping adaptation planning. The research advocates for adaptation strategies rooted in the lived experiences and testimonies of the affected populations. By incorporating both the tangible and intangible facets of trauma, planning efforts are suggested to be more culturally attuned and emotionally insightful, fostering true resonance with the affected communities. Through such a comprehensive lens, this study contributes enriching the climate change discourse, emphasizing the intertwined nature of tangible recovery and the imperative of emotional and cultural healing after environmental disasters. Following the pronounced aftermath of the Lytton Creek Fire in 2021, research aims to deeply understand its impact on place attachment (PA), encompassing the emotional and cognitive bonds individuals form with their environments. The interpretive phenomenological approach, enriched by a hermeneutic framework, is adopted, emphasizing the experiences of the Lytton community and co-researchers. Phenomenology informed the understanding of 'place' as the focal point of attachment, providing insights into its formation and evolution after traumatic events. Data collection departs from conventional methods. Instead of traditional interviews, walking audio sessions and photo elicitation methods are utilized. These allow co-researchers to immerse themselves in the environment, re-experience, and articulate memories and feelings in real-time. Walking audio facilitates reflections on spatial narratives post-trauma, while photo voices captured intangible emotions, enabling the visualization of place-based experiences. The analysis is collaborative, ensuring the co-researchers' experiences and interpretations are central. Emphasizing their agency in knowledge production, the process is rigorous, facilitated by the harmonious blend of interpretive phenomenology and hermeneutic insights. The findings underscore the need for adaptation and recovery efforts to address emotional traumas alongside tangible damages. By exploring PA post-disaster, the research not only fills a significant gap but advocates for an inclusive approach to community recovery. Furthermore, the participatory methodologies employed challenge traditional research paradigms, heralding potential shifts in qualitative research norms.

Keywords: wildfire recovery, place attachment, trauma recovery, cultural landscape, visual methodologies

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Authors: E. Tan, O. McKay, T. Clarnette T., D. Croagh

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Background: Historically with pancreatic trauma, complete disruption of the main pancreatic duct (MPD), classified as Grade IV-V by the American Association for the Surgery of Trauma (AAST), necessitated a damage-control laparotomy. This was to avoid mortality, shorten diet upgrade timeframe, and hence shorter length of stay. However, acute pancreatic resection entailed complications of pancreatic fistulas and leaks. With the advance of imaging-guided interventions, non-operative management such as percutaneous and transpapillary drainage of traumatic peripancreatic collections have been trialled favourably. The aim of this case series is to evaluate the efficacy of endoscopic ultrasound-guided (EUS) transmural drainage in managing traumatic peripancreatic collections as a less invasive alternative to traditional approaches. This study also highlights the importance of anatomical knowledge regarding peripancreatic collection’s common location in the lesser sac, the pancreas relationship to adjacent organs, and the formation of the main pancreatic duct in regards to the feasibility of therapeutic internal drainage. Methodology: A retrospective case series was conducted at a single tertiary endoscopy unit, analysing patient data over a 5-year period. Inclusion criteria outlined patients age 5 to 80-years-old, traumatic pancreatic injury of at least Grade IV and haemodynamic stability. Exclusion criteria involved previous episodes of pancreatitis or abdominal trauma. Patient demographics and clinicopathological characteristics were retrospectively collected. Results: The study identified 7 patients with traumatic pancreatic injuries that were managed from 2018-2022; age ranging from 5 to 34 years old, with majority being female (n=5). Majority of the mechanisms of trauma were a handlebar injury (n=4). Diagnosis was confirmed with an elevated lipase and computerized tomotography (CT) confirmation of proximal pancreatic transection with MPD disruption. All patients sustained an isolated single organ grade IV pancreatic injury, except case 4 and 5 with other intra-abdominal visceral Grade 1 injuries. 6 patients underwent early ERCP-guided transpapillary drainage with 1 being unsuccessful for pancreatic duct stent insertion (case 1) and 1 complication of stent migration (case 2). Surveillance imaging post ERCP showed the stents were unable to bridge the disrupted duct and development of symptomatic collections with an average size of 9.9cm. Hence, all patients proceeded to EUS-guided transmural drainage, with 2/7 patients requiring repeat drainages (case 6 and 7). Majority (n=6) had a cystogastrostomy, whilst 1 (case 6) had a cystoenterostomy due to feasibility of the peripancreatic collection being adjacent to duodenum rather than stomach. However, case 6 subsequently required repeat EUS-guided drainage with cystogastrostomy for ongoing collections. Hence all patients avoided initial laparotomy with an average index length of stay of 11.7 days. Successful transmural drainage was demonstrated, with no long-term complications of pancreatic insufficiency; except for 1 patient requiring a distal pancreatectomy at 2 year follow-up due to chronic pain. Conclusion: The early results of this series support EUS-guided transmural drainage as a viable management option for traumatic peripancreatic collections, showcasing successful outcomes, minimal complications, and long-term efficacy in avoiding surgical interventions. More studies are required before the adoption of this procedure as a less invasive and complication-prone management approach for traumatic peripancreatic collections.

Keywords: endoscopic ultrasound, cystogastrostomy, pancreatic trauma, traumatic peripancreatic collection, transmural drainage

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Authors: L. Calcagni, A. Battisti, M. Hensel, D. S. Hensel

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Since the beginning of the 21st century, we have seen a dynamic growth of water-based (WB) architecture, mainly due to the increasing threat of floods caused by sea level rise and heavy rains, all correlated with climate change. At the same time, the shortage of land available for urban development also led architects, engineers, and policymakers to reclaim the seabed or to build floating structures. Furthermore, the drive to produce energy from renewable resources has expanded the sector of offshore research, mining, and energy industry which seeks new types of WB structures. In light of these considerations, the time is ripe to consider floating architecture as a full-fledged building typology. Currently, there is no universally recognized academic definition of a floating building. Research on floating architecture lacks a proper, commonly shared vocabulary and typology distinction. Moreover, there is no global international legal framework for urban development on water, and there is no structured performance based building design (PBBD) approach for floating architecture in most countries, let alone national regulatory systems. Thus, first of all, the research intends to overcome the semantic and typological issues through the conceptualization of floating architecture, laying the proto-ontological conditions for floating development, and secondly to identify the parameters to be considered in the definition of a specific PBBD framework, setting the scene for national planning strategies. The theoretical overview and re-semanticization process involve the attribution of a new meaning to the term floating architecture. This terminological work of semantic redetermination is carried out through a systematic literature review and involves quantitative and historical research as well as logical argumentation methods. As it is expected that floating urban development is most likely to take place as an extension of coastal areas, the needs and design criteria are definitely more similar to those of the urban environment than to those of the offshore industry. Therefore, the identification and categorization of parameters –looking towards the potential formation of a PBBD framework for floating development– takes the urban and architectural guidelines and regulations as the starting point, taking the missing aspects, such as hydrodynamics (i.e. stability and buoyancy) from the offshore and shipping regulatory frameworks. This study is carried out through an evidence-based assessment of regulatory systems that are effective in different countries around the world, addressing on-land and on-water architecture as well as offshore and shipping industries. It involves evidence-based research and logical argumentation methods. Overall, inhabiting water is proposed not only as a viable response to the problem of rising sea levels, thus as a resilient frontier for urban development, but also as a response to energy insecurity, clean water, and food shortages, environmental concerns, and urbanization, in line with Blue Economy principles and the Agenda 2030. This review shows how floating architecture is to all intents and purposes, an urban adaptation measure and a solution towards self-sufficiency and energy-saving objectives. Moreover, the adopted methodology is, to all extents, open to further improvements and integrations, thus not rigid and already completely determined. Along with new designs and functions that will come into play in the practice field, eventually, life on water will seem no more unusual than life on land, especially by virtue of the multiple advantages it provides not only to users but also to the environment.

Keywords: adaptation measures, building typology, floating architecture, performance based building design, rising sea levels

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Authors: L. Diogo, A. Legrand, J. Nguyen-Cao, J. Rogeau, S. Bornhofen

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Lenia is a system of cellular automata with continuous states, space and time, which surprises not only with the emergence of interesting life-like structures but also with its beauty. This paper reports ongoing research on a GPU implementation of Lenia using CUDA C++ and OpenGL Interoperability. We demonstrate how CUDA as a low-level GPU programming paradigm allows optimizing performance and memory usage of the Lenia algorithm. A comparative analysis through experimental runs with existing implementations shows that the CUDA implementation outperforms the others by one order of magnitude or more. Cellular automata hold significant interest due to their ability to model complex phenomena in systems with simple rules and structures. They allow exploring emergent behavior such as self-organization and adaptation, and find applications in various fields, including computer science, physics, biology, and sociology. Unlike classic cellular automata which rely on discrete cells and values, Lenia generalizes the concept of cellular automata to continuous space, time and states, thus providing additional fluidity and richness in emerging phenomena. In the current literature, there are many implementations of Lenia utilizing various programming languages and visualization libraries. However, each implementation also presents certain drawbacks, which serve as motivation for further research and development. In particular, speed is a critical factor when studying Lenia, for several reasons. Rapid simulation allows researchers to observe the emergence of patterns and behaviors in more configurations, on bigger grids and over longer periods without annoying waiting times. Thereby, they enable the exploration and discovery of new species within the Lenia ecosystem more efficiently. Moreover, faster simulations are beneficial when we include additional time-consuming algorithms such as computer vision or machine learning to evolve and optimize specific Lenia configurations. We developed a Lenia implementation for GPU using the C++ and CUDA programming languages, and CUDA/OpenGL Interoperability for immediate rendering. The goal of our experiment is to benchmark this implementation compared to the existing ones in terms of speed, memory usage, configurability and scalability. In our comparison we focus on the most important Lenia implementations, selected for their prominence, accessibility and widespread use in the scientific community. The implementations include MATLAB, JavaScript, ShaderToy GLSL, Jupyter, Rust and R. The list is not exhaustive but provides a broad view of the principal current approaches and their respective strengths and weaknesses. Our comparison primarily considers computational performance and memory efficiency, as these factors are critical for large-scale simulations, but we also investigate the ease of use and configurability. The experimental runs conducted so far demonstrate that the CUDA C++ implementation outperforms the other implementations by one order of magnitude or more. The benefits of using the GPU become apparent especially with larger grids and convolution kernels. However, our research is still ongoing. We are currently exploring the impact of several software design choices and optimization techniques, such as convolution with Fast Fourier Transforms (FFT), various GPU memory management scenarios, and the trade-off between speed and accuracy using single versus double precision floating point arithmetic. The results will give valuable insights into the practice of parallel programming of the Lenia algorithm, and all conclusions will be thoroughly presented in the conference paper. The final version of our CUDA C++ implementation will be published on github and made freely accessible to the Alife community for further development.

Keywords: artificial life, cellular automaton, GPU optimization, Lenia, comparative analysis.

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Authors: Dmitriy Berillo, Areej K. A. Al-Jwaid, Jonathan L. Caplin, Andrew Cundy, Irina Savina

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Chlorophenols (CPs) are used as a precursor in the production of higher CPs and dyestuffs, and as a preservative. Contamination by CPs of the ground water is located in the range from 0.15-100mg/L. The EU has set maximum concentration limits for pesticides and their degradation products of 0.1μg/L and 0.5μg/L, respectively. People working in industries which produce textiles, leather products, domestic preservatives, and petrochemicals are most heavily exposed to CPs. The International Agency for Research on Cancers categorized CPs as potential human carcinogens. Existing multistep water purification processes for CPs such as hydrogenation, ion exchange, liquid-liquid extraction, adsorption by activated carbon, forward and inverse osmosis, electrolysis, sonochemistry, UV irradiation, and chemical oxidation are not always cost effective and can cause the formation of even more toxic or mutagenic derivatives. Bioremediation of CPs derivatives utilizing microorganisms results in 60 to 100% decontamination efficiency and the process is more environmentally-friendly compared with existing physico-chemical methods. Microorganisms immobilized onto a substrate show many advantages over free bacteria systems, such as higher biomass density, higher metabolic activity, and resistance to toxic chemicals. They also enable continuous operation, avoiding the requirement for biomass-liquid separation. The immobilized bacteria can be reused several times, which opens the opportunity for developing cost-effective processes for wastewater treatment. In this study, we develop a bioremediation system for CPs based on macroporous materials, which can be efficiently used for wastewater treatment. Conditions for the preparation of the macroporous material from specific bacterial strains (Pseudomonas mendocina and Rhodococus koreensis) were optimized. The concentration of bacterial cells was kept constant; the difference was only the type of cross-linking agents used e.g. glutaraldehyde, novel polymers, which were utilized at concentrations of 0.5 to 1.5%. SEM images and rheology analysis of the material indicated a monolithic macroporous structure. Phenol was chosen as a model system to optimize the function of the cryogel material and to estimate its enzymatic activity, since it is relatively less toxic and harmful compared to CPs. Several types of macroporous systems comprising live bacteria were prepared. The viability of the cross-linked bacteria was checked using Live/Dead BacLight kit and Laser Scanning Confocal Microscopy, which revealed the presence of viable bacteria with the novel cross-linkers, whereas the control material cross-linked with glutaraldehyde(GA), contained mostly dead cells. The bioreactors based on bacteria were used for phenol degradation in batch mode at an initial concentration of 50mg/L, pH 7.5 and a temperature of 30°C. Bacterial strains cross-linked with GA showed insignificant ability to degrade phenol and for one week only, but a combination of cross-linking agents illustrated higher stability, viability and the possibility to be reused for at least five weeks. Furthermore, conditions for CPs degradation will be optimized, and the chlorophenol degradation rates will be compared to those for phenol. This is a cutting-edge bioremediation approach, which allows the purification of waste water from sustainable compounds without a separation step to remove free planktonic bacteria. Acknowledgments: Dr. Berillo D. A. is very grateful to Individual Fellowship Marie Curie Program for funding of the research.

Keywords: bioremediation, cross-linking agents, cross-linked microbial cell, chlorophenol degradation

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Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

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Authors: Hilary Modir, Kyle Dutton, Michelle Swab, Shabnam Asghari

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Since its emergence, the cutaneous manifestations of COVID-19 have been documented in the literature. However, the majority are case reports with significant limitations in appraisal quality, thus leaving the role of dermatological manifestations of COVID-19 erroneously underexplored. The primary aim of this review was to systematically examine clinical patterns of dermatological manifestations as reported in the literature. This study was designed as a systematic review of case reports. The inclusion criteria consisted of all published reports and articles regarding COVID-19 in English, from September 1st, 2019, until June 22nd, 2020. The population consisted of confirmed cases of COVID-19 with associated cutaneous signs and symptoms. Exclusion criteria included research in planning stages, protocols, book reviews, news articles, review studies, and policy analyses. With the collaboration of a librarian, a search strategy was created consisting of a mixture of keyword terms and controlled vocabulary. Electronic databases searched were MEDLINE via PubMed, EMBASE, CINAHL, Web of Science, LILACS, PsycINFO, WHO Global Literature on Coronavirus Disease, Cochrane Library, Campbell Collaboration, Prospero, WHO International Clinical Trials Registry Platform, Australian and New Zealand Clinical Trials Registry, U.S. Institutes of Health Ongoing Trials Register, AAD Registry, OSF preprints, SSRN, MedRxiV and BioRxiV. The study selection featured an initial pre-screening of titles and abstracts by one independent reviewer. Results were verified by re-examining a random sample of 1% of excluded articles. Eligible studies progressed for full-text review by two calibrated independent reviewers. Covidence was used to store and extract data, such as citation information and findings pertaining to COVID-19 and cutaneous signs and symptoms. Data analysis and summarization methodology reflect the framework proposed by PRISMA and recommendations set out by Cochrane and Joanna Brigg’s Institute for conducting systematic reviews. The Oxford Centre for Evidence-Based Medicine’s level of evidence was used to appraise the quality of individual studies. The literature search revealed a total of 1221 articles. After the abstract and full-text screening, only 95 studies met the eligibility criteria, proceeding to data extraction. Studies were divided into 58% case reports and 42% series. A total of 833 manifestations were reported in 723 confirmed COVID-19 cases. The most frequent lesions were 23% maculopapular, 15% urticarial and 13% pseudo-chilblains, with 46% of lesions reporting pruritus, 16% erythema, 14% pain, 12% burning sensation, and 4% edema. The most common lesion locations were 20% trunk, 19.5% lower limbs, and 17.7% upper limbs. The time to resolution of lesions was between one and twenty-one days. In conclusion, over half of the reported cutaneous presentations in COVID-19 positive patients were maculopapular, urticarial and pseudo-chilblains, with the majority of lesions distributed to the extremities and trunk. As this review’s sample size only contained COVID-19 confirmed cases with skin presentations, it becomes difficult to deduce the direct relationship between skin findings and COVID-19. However, it can be correlated that acute onset of skin lesions, such as chilblains-like, may be associated with or may warrant consideration of COVID-19 as part of the differential diagnosis.

Keywords: COVID-19, cutaneous manifestations, cutaneous signs, general dermatology, medical dermatology, Sars-Cov-2, skin and infectious disease, skin findings, skin manifestations

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Authors: Pradipta Chandra, Titas Bhattacharjee, Bhaskar Bhowmick

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The foundation of economy in India is primarily based on agriculture while this is the most neglected in the rural setting. More significantly, household women take part in agriculture with higher involvement. However, because of lower education of women they have limited access towards financial decisions, land ownership and technology but they have vital role towards the individual family level. There are limited studies on the institution-wise training barriers with the focus of gender disparity. The main purpose of this paper is to find out the factors of institution-wise training (non-formal education) barriers in technology transfer with the focus of participation of rural women in agriculture. For this study primary and secondary data were collected in the line of qualitative and quantitative approach. Qualitative data were collected by several field visits in the adjacent areas of Seva-Bharati, Seva Bharati Krishi Vigyan Kendra through semi-structured questionnaires. In the next level detailed field surveys were conducted with close-ended questionnaires scored on the seven-point Likert scale. Sample size was considered as 162. During the data collection the focus was to include women although some biasness from the end of respondents and interviewer might exist due to dissimilarity in observation, views etc. In addition to that the heterogeneity of sample is not very high although female participation is more than fifty percent. Data were analyzed using Exploratory Factor Analysis (EFA) technique with the outcome of three significant factors of training barriers in technology adoption by farmers: (a) Failure of technology transfer training (TTT) comprehension interprets that the technology takers, i.e., farmers can’t understand the technology either language barrier or way of demonstration exhibited by the experts/ trainers. (b) Failure of TTT customization, articulates that the training for individual farmer, gender crop or season-wise is not tailored. (c) Failure of TTT generalization conveys that absence of common training methods for individual trainers for specific crops is more prominent at the community level. The central finding is that the technology transfer training method can’t fulfill the need of the farmers under an economically challenged area. The impact of such study is very high in the area of dry lateritic and resource crunch area of Jangalmahal under Paschim Medinipur district, West Bengal and areas with similar socio-economy. Towards the policy level decision this research may help in framing digital agriculture for implementation of the appropriate information technology for the farming community, effective and timely investment by the government with the selection of beneficiary, formation of farmers club/ farm science club etc. The most important research implication of this study lies upon the contribution towards the knowledge diffusion mechanism of the agricultural sector in India. Farmers may overcome the barriers to achieve higher productivity through adoption of modern farm practices. Corporates will be interested in agro-sector through investment under corporate social responsibility (CSR). The research will help in framing public or industry policy and land use pattern. Consequently, a huge mass of rural farm-women will be empowered and farmer community will be benefitted.

Keywords: dry lateritic zone, institutional barriers, technology transfer in India, farm-women participation

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