Search results for: predictive insights

Authors: Keith Diamond, Tracy Collier, Ciara Sterling, Ben Kraal

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The increased frequency and intensity of disaster events in the Asia-Pacific region is likely to require organisations to better understand how their initiatives, and the support they provide to their customers, intersect with other organisations aiming to support communities in achieving disaster resilience. While there is a growing awareness that disaster response and recovery rebuild programmes need to adapt to more integrated, community-led approaches, there is often a discrepancy between how programmes intend to work and how they are collectively experienced in the community, creating undesired effects on community resilience. Following Australia’s North Queensland Monsoon Disaster of 2019, this research set out to understand and evaluate how the service and support ecosystem impacted on the local community’s experience and influenced their ability to respond and recover. The purpose of this initiative was to identify actionable, cross-sector, people-centered improvements that support communities to recover and thrive when faced with disaster. The challenge arose as a group of organisations, including utility providers, banks, insurers, and community organisations, acknowledged that improving their own services would have limited impact on community wellbeing unless the other services people need are also improved and aligned. The research applied human-centred service design methods, typically applied to single products or services, to design a new way to understand a whole-of-community journey. Phase 1 of the research conducted deep contextual interviews with residents and small business owners impacted by the North Queensland Monsoon and qualitative data was analysed to produce community journey maps that detailed how individuals navigated essential services, such as accommodation, finance, health, and community. Phase 2 conducted interviews and focus groups with frontline workers who represented industries that provided essential services to assist the community. Data from Phase 1 and Phase 2 of the research was analysed and combined to generate a systems map that visualised the positive and negative impacts that occurred across the disaster response and recovery service ecosystem. Insights gained from the research has catalysed collective action to address future Australian disaster events. The case study outlines a transformative way for sectors and industries to rethink their corporate social responsibility activities towards a cross-sector partnership model that shares responsibility and approaches disaster response and recovery as a single service that can be designed to meet the needs of communities.

Keywords: corporate social responsibility, cross sector partnerships, disaster resilience, human-centred design, service design, systems change

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Authors: Hosna Pourhashemi

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Chahar Bagh, the symbol of the world, displayed around the pool of life in the centre, attempts to emulate Eden. It represents a duality concept based on the division of the universe into two perceptional insights, a celestial and an earthly one. Chahar Bagh garden pattern refers to the Garden of Eden, that was watered and framed by main four rivers. This microcosm is combined with a mystical love of flowers, sweet-scented trees, the variety of colors, and the sense of eternal life. This symbol of the integration of spontaneous expressivity of the natural elements and reasoning awareness of man strives for the ideal of divine perfection. Through collecting and analyzing the data, the prevalence and continuous influence of Chahar Bagh concept on selected historical gardens was elaborated and evaluated. After the conquest of Persia by the Arabs in the 7th century, Chahar Bagh was adopted and spread throughout the Islamic expansion, from the Middle East, westward across northern Africa to Morocco and the Iberian Peninsula, and eastward through Iran to Central Asia and India. Furthermore, its continuity to the mid of 16th century Renaissance period is shown. By adapting the semiotic theory of Peirce and Saussure on the Persian garden, Chahar Bagh was defined as the basic pattern language for the garden culture. The hypothesis of the continuous influence of Chahar Bagh pattern language on today’s landscape architecture was examined on selected works of Dieter Kienast, as the important and relevant protagonist of his time (end of twentieth ct.) and up to our time. Chahar Bagh pattern language offers collective cultural sensitive healing wisdom transmitted down through the millennia. Through my reflections in Dieter Kienast’s works, I transformed my personal experience into a transpersonal understanding regarding the Sufi philosophy and the Jung psychology, which brings me to define new design theories and methods to form a spiritual, as I call it” Quaternary Perception Model” for landscape architecture. Based on a cognition process through self-journeying in this holistic model, human consciousness can be developed to access to “higher” levels of being and embrace the unity. The self-purification and mindfulness through transpersonal confrontation in the ”Quaternary Perception Model” generates a form of heart-based treatment. I adapted the seven spiritual levels of Sufi self-development on the perception of landscape, representing the stages of the self, ranging from absolutely self-centered to pure spiritual humanity. I redefine and reread the elements and features of Chahar Bagh pattern language for today’s landscape architecture. The “lost paradise” lies in our heart and can be perceived by all humans in landscapes and cities designed in the spirit of” Quaternary Model”.

Keywords: persian garden, pattern language of Chahar Bagh, wholistic Perception, dieter kienast, “quaternary model”

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Authors: Jeet Chakraborty, Sanjay Dutta

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Antibiotic resistance by bacteria has proved to be a severe threat to mankind in recent times, and this fortifies an urgency to design and develop potent antibacterial small molecules/compounds with nonconventional mechanisms than the conventional ones. DNA carries the genetic signature of any organism, and bacteria maintain their genomic DNA inside the cell in a well-regulated compact form with the help of various nucleoid associated proteins like HU, HNS, etc. These proteins control various fundamental processes like gene expression, replication, etc., inside the cell. Alteration of the native DNA structure of bacteria can lead to severe consequences in cellular processes inside the bacterial cell that ultimately result in the death of the organism. The change in the global DNA structure by small molecules initiates a plethora of cellular responses that have not been very well investigated. Echinomycin and Triostin-A are biologically active Quinoxaline small molecules that typically consist of a quinoxaline chromophore attached with an octadepsipeptide ring. They bind to double-stranded DNA in a sequence-specific way and have high activity against a wide variety of bacteria, mainly against Gram-positive ones. To date, few synthetic quinoxaline scaffolds were synthesized, displaying antibacterial potential against a broad scale of pathogenic bacteria. QNOs (Quinoxaline N-oxides) are known to target DNA and instigate reactive oxygen species (ROS) production in bacteria, thereby exhibiting antibacterial properties. The divergent role of Quinoxaline small molecules in medicinal research qualifies them for the evaluation of their antimicrobial properties as a potential candidate. The previous study from our lab has given new insights on a 6-nitroquinoxaline derivative 1d as an intercalator of DNA, which induces conformational changes in DNA upon binding.7 The binding event observed was dependent on the presence of a crucial benzyl substituent on the quinoxaline moiety. This was associated with a large induced CD (ICD) appearing in a sigmoidal pattern upon the interaction of 1d with dsDNA. The induction of DNA superstructures by 1d at high Drug:DNA ratios was observed that ultimately led to DNA condensation. Eviction of invitro-assembled nucleosome upon treatment with a high dose of 1d was also observed. In this work, monoquinoxaline derivatives of 1d were synthesized by various modifications of the 1d scaffold. The set of synthesized 6-nitroquinoxaline derivatives along with 1d were all subjected to antibacterial evaluation across five different bacteria species. Among the compound set, 3a displayed potent antibacterial activity against Staphylococcus aureus bacteria. 3a was further subjected to various biophysical studies to check whether the DNA structural alteration potential was still intact. The biological response of S. aureus cells upon treatment with 3a was studied using various cell biology processes, which led to the conclusion that 3d can initiate DNA damage in the S. aureus cells. Finally, the potential of 3a in disrupting preformed S.aureus and S.epidermidis biofilms was also studied.

Keywords: DNA structural change, antibacterial, intercalator, DNA superstructures, biofilms

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Authors: Lishuang Ma

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Charge transfer (CT) complex, also known as Electron donor-acceptor (EDA) complex, has received attentions increasingly in the field of synthetic chemistry community, due to the CT complex can absorb the visible light through the intermolecular charge transfer excited states, various of catalyst-free photochemical transformations under mild visible-light conditions. However, a number of fundamental questions are still ambiguous, such as the origin of visible light absorption, the photochemical and photophysical properties of the CT complex, as well as the detailed mechanism of the radical coupling pathways mediated by CT complex. Since these are critical factors for target-specific design and synthesis of more new-type CT complexes. To this end, theoretical investigations were performed in our group to answer these questions based on multiconfigurational perturbation theory. The photo-induced fluoroalkylation reactions are mediated by CT complexes, which are formed by the association of an acceptor of perfluoroalkyl halides RF−X (X = Br, I) and a suitable donor molecule such as β-naphtholate anion, were chosen as a paradigm example in this work. First, spectrum simulations were carried out by both CASPT2//CASSCF/PCM and TD-DFT/PCM methods. The computational results showed that the broadening spectra in visible light range (360-550nm) of the CT complexes originate from the 1(σπ*) excitation, accompanied by an intermolecular electron transfer, which was also found closely related to the aggregate states of the donor and acceptor. Moreover, from charge translocation analysis, the CT complex that showed larger charge transfer in the round state would exhibit smaller charge transfer in excited stated of 1(σπ*), causing blue shift relatively. Then, the excited-state potential energy surface (PES) was calculated at CASPT2//CASSCF(12,10)/ PCM level of theory to explore the photophysical properties of the CT complexes. The photo-induced C-X (X=I, Br) bond cleavage was found to occur in the triplet state, which is accessible through a fast intersystem crossing (ISC) process that is controlled by the strong spin-orbit coupling resulting from the heavy iodine and bromine atoms. Importantly, this rapid fragmentation process can compete and suppress the backward electron transfer (BET) event, facilitating the subsequent effective photochemical transformations. Finally, the reaction pathways of the radical coupling were also inspected, which showed that the radical chain propagation pathway could easy to accomplish with a small energy barrier no more than 3.0 kcal/mol, which is the key factor that promote the efficiency of the photochemical reactions induced by CT complexes. In conclusion, theoretical investigations were performed to explore the photophysical and photochemical properties of the CT complexes, as well as the mechanism of radical coupling reactions mediated by CT complex. The computational results and findings in this work can provide some critical insights into mechanism-based design for more new-type EDA complexes

Keywords: charge transfer complex, electron transfer, multiconfigurational perturbation theory, radical coupling

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Authors: Elham Bagheri, Yalda Mohsenzadeh

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Image memorability refers to the phenomenon where certain images are more likely to be remembered by humans than others. It is a quantifiable and intrinsic attribute of an image. Understanding how visual perception and memory interact is important in both cognitive science and artificial intelligence. It reveals the complex processes that support human cognition and helps to improve machine learning algorithms by mimicking the brain's efficient data processing and storage mechanisms. To explore the computational underpinnings of image memorability, this study examines the relationship between an image's reconstruction error, distinctiveness in latent space, and its memorability score. A trained autoencoder is used to replicate human-like memorability assessment inspired by the visual memory game employed in memorability estimations. This study leverages a VGG-based autoencoder that is pre-trained on the vast ImageNet dataset, enabling it to recognize patterns and features that are common to a wide and diverse range of images. An empirical analysis is conducted using the MemCat dataset, which includes 10,000 images from five broad categories: animals, sports, food, landscapes, and vehicles, along with their corresponding memorability scores. The memorability score assigned to each image represents the probability of that image being remembered by participants after a single exposure. The autoencoder is finetuned for one epoch with a batch size of one, attempting to create a scenario similar to human memorability experiments where memorability is quantified by the likelihood of an image being remembered after being seen only once. The reconstruction error, which is quantified as the difference between the original and reconstructed images, serves as a measure of how well the autoencoder has learned to represent the data. The reconstruction error of each image, the error reduction, and its distinctiveness in latent space are calculated and correlated with the memorability score. Distinctiveness is measured as the Euclidean distance between each image's latent representation and its nearest neighbor within the autoencoder's latent space. Different structural and perceptual loss functions are considered to quantify the reconstruction error. The results indicate that there is a strong correlation between the reconstruction error and the distinctiveness of images and their memorability scores. This suggests that images with more unique distinct features that challenge the autoencoder's compressive capacities are inherently more memorable. There is also a negative correlation between the reduction in reconstruction error compared to the autoencoder pre-trained on ImageNet, which suggests that highly memorable images are harder to reconstruct, probably due to having features that are more difficult to learn by the autoencoder. These insights suggest a new pathway for evaluating image memorability, which could potentially impact industries reliant on visual content and mark a step forward in merging the fields of artificial intelligence and cognitive science. The current research opens avenues for utilizing neural representations as instruments for understanding and predicting visual memory.

Keywords: autoencoder, computational vision, image memorability, image reconstruction, memory retention, reconstruction error, visual perception

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Authors: Fengjuan Wang, Azilawati Jamaludin

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Developmental Dyscalculia (DD) is defined as a particular learning difficulty with continuous challenges in learning requisite math skills that cannot be explained by intellectual disability or educational deprivation. Recent studies have increasingly recognized that DD is a heterogeneous, instead of monolithic, learning disorder with not only cognitive and behavioral deficits but so too neural dysfunction. In recent years, neuroimaging studies employed group comparison to explore the neural underpinnings of DD, which contradicted the heterogenous nature of DD and may obfuscate critical individual differences. This research aimed to investigate the neural heterogeneity of DD using case studies with functional near-infrared spectroscopy (fNIRS). A total of 54 aged 6-7 years old of children participated in this study, comprising two comprehensive cognitive assessments, an 8-minute resting state, and an 8-minute one-digit addition task. Nine children met the criteria of DD and scored at or below 85 (i.e., the 16th percentile) on the Mathematics or Math Fluency subtest of the Wechsler Individual Achievement Test, Third Edition (WIAT-III) (both subtest scores were 90 and below). The remaining 45 children formed the typically developing (TD) group. Resting-state data and brain activation in the inferior frontal gyrus (IFG), superior frontal gyrus (SFG), and intraparietal sulcus (IPS) were collected for comparison between each case and the TD group. Graph theory was used to analyze the brain network under the resting state. This theory represents the brain network as a set of nodes--brain regions—and edges—pairwise interactions across areas to reveal the architectural organizations of the nervous network. Next, a single-case methodology developed by Crawford et al. in 2010 was used to compare each case’s brain network indicators and brain activation against 45 TD children’s average data. Results showed that three out of the nine DD children displayed significant deviation from TD children’s brain indicators. Case 1 had inefficient nodal network properties. Case 2 showed inefficient brain network properties and weaker activation in the IFG and IPS areas. Case 3 displayed inefficient brain network properties with no differences in activation patterns. As a rise above, the present study was able to distill differences in architectural organizations and brain activation of DD vis-à-vis TD children using fNIRS and single-case methodology. Although DD is regarded as a heterogeneous learning difficulty, it is noted that all three cases showed lower nodal efficiency in the brain network, which may be one of the neural sources of DD. Importantly, although the current “brain norm” established for the 45 children is tentative, the results from this study provide insights not only for future work in “developmental brain norm” with reliable brain indicators but so too the viability of single-case methodology, which could be used to detect differential brain indicators of DD children for early detection and interventions.

Keywords: brain activation, brain network, case study, developmental dyscalculia, functional near-infrared spectroscopy, graph theory, neural heterogeneity

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Authors: Lina Psarra, Manogj Sundaresan, Purjeet Sutar

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In response to the global imperative for sustainable solutions, this article proposes the development of a comprehensive circularity index applicable to a wide range of products across various industries. The absence of a consensus on using a universal metric to assess circularity performance presents a significant challenge in prioritizing and effectively managing sustainable initiatives. This circularity index serves as a quantitative measure to evaluate the adherence of products, processes, and systems to the principles of a circular economy. Unlike traditional distinct metrics such as recycling rates or material efficiency, this index considers the entire lifecycle of a product in one single metric, also incorporating additional factors such as reusability, scarcity of materials, reparability, and recyclability. Through a systematic approach and by reviewing existing metrics and past methodologies, this work aims to address this gap by formulating a circularity index that can be applied to diverse product portfolio and assist in comparing the circularity of products on a scale of 0%-100%. Project objectives include developing a formula, designing and implementing a pilot tool based on the developed Product Circularity Index (PCI), evaluating the effectiveness of the formula and tool using real product data, and assessing the feasibility of integration into various sustainability initiatives. The research methodology involves an iterative process of comprehensive research, analysis, and refinement where key steps include defining circularity parameters, collecting relevant product data, applying the developed formula, and testing the tool in a pilot phase to gather insights and make necessary adjustments. Major findings of the study indicate that the PCI provides a robust framework for evaluating product circularity across various dimensions. The Excel-based pilot tool demonstrated high accuracy and reliability in measuring circularity, and the database proved instrumental in supporting comprehensive assessments. The PCI facilitated the identification of key areas for improvement, enabling more informed decision-making towards circularity and benchmarking across different products, essentially assisting towards better resource management. In conclusion, the development of the Product Circularity Index represents a significant advancement in global sustainability efforts. By providing a standardized metric, the PCI empowers companies and stakeholders to systematically assess product circularity, track progress, identify improvement areas, and make informed decisions about resource management. This project contributes to the broader discourse on sustainable development by offering a practical approach to enhance circularity within industrial systems, thus paving the way towards a more resilient and sustainable future.

Keywords: circular economy, circular metrics, circularity assessment, circularity tool, sustainable product design, product circularity index

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Authors: Julia Mathew

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This paper explores the use of Bollywood and Chinese movies as soft power instruments within the larger context of India-China contention in South Asia. As India and China compete for influence in South Asia, they have increasingly relied on cultural diplomacy, using cinema to change perceptions, promote goodwill, and build cultural linkages. Bollywood, with its long-standing popularity and cultural resonance, has been a powerful instrument for projecting Indian ideals and identity throughout South Asia. In contrast, China has made concerted attempts in recent years to promote its own films, showing Chinese culture and values in a positive manner to offset Bollywood’s effect. This study examines the ways in which Chinese and Bollywood films influence public opinion and appeal to South Asian audiences while also supporting their respective countries’ soft power goals. To learn about this, we take a mixed-methods approach that incorporates content analysis of popular Bollywood and Chinese films released in South Asia, focussing on issues such as cultural identity, nationalism, and social values. In addition, we use sentiment analysis and surveys to map how these two cinematic traditions are received in various South Asian countries. This study takes into account government activities and cultural policies that promote each country’s cinema industry as a diplomatic instrument. The present study uses case studies from Nepal, Sri Lanka, Bangladesh, and Bhutan to demonstrate the subtle ways in which Bollywood and Chinese movies influence regional attitudes. For example, in Nepal and Bangladesh, Bollywood’s deep cultural ties have historically given India an advantage, but China’s growing economic relations and media presence have presented Chinese cinema as an alternative cultural influence. In contrast, Sri Lanka exemplifies a complicated relationship in which Bollywood’s cultural attraction is strong, but Chinese state-backed media diplomacy is making inroads, altering the cultural landscape. Due to limited cultural interchange and Bhutan’s historical alignment with India, Chinese cinema has a small presence in the country. The findings highlight cinema’s significance as a soft power tool in India and China’s regional ambitions. Bollywood’s emotional resonance and cultural familiarity have long bolstered India’s prominence, but Chinese cinema’s expansion reflects China’s desire to shift cultural narratives in its favour. This paper closes by presenting insights into the broader implications of cultural diplomacy within the India-China competition, arguing that as India and China continue to compete for influence in South Asia, film will play an increasingly crucial role in defining the soft power environment.

Keywords: soft power, China, India, Bollywood, Chinese cinema

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Authors: Moustafa Osman Mohammed

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This paper introduces Luhmann’s autopoietic social systems starting with the original concept of autopoiesis by biologists and scientists, including the modification of general systems based on socialized medicine. A specific type of autopoietic system is explained in the three existing groups of the ecological phenomena: interaction, social and medical sciences. This hypothesis model, nevertheless, has a nonlinear interaction with its natural environment ‘interactional cycle’ for the exchange of photon energy with molecular without any changes in topology. The external forces in the systems environment might be concomitant with the natural fluctuations’ influence (e.g. radioactive radiation, electromagnetic waves). The cantilever sensor deploys insights to the future chip processor for prevention of social metabolic systems. Thus, the circuits with resonant electric and optical properties are prototyped on board as an intra–chip inter–chip transmission for producing electromagnetic energy approximately ranges from 1.7 mA at 3.3 V to service the detection in locomotion with the least significant power losses. Nowadays, therapeutic systems are assimilated materials from embryonic stem cells to aggregate multiple functions of the vessels nature de-cellular structure for replenishment. While, the interior actuators deploy base-pair complementarity of nucleotides for the symmetric arrangement in particular bacterial nanonetworks of the sequence cycle creating double-stranded DNA strings. The DNA strands must be sequenced, assembled, and decoded in order to reconstruct the original source reliably. The design of exterior actuators have the ability in sensing different variations in the corresponding patterns regarding beat-to-beat heart rate variability (HRV) for spatial autocorrelation of molecular communication, which consists of human electromagnetic, piezoelectric, electrostatic and electrothermal energy to monitor and transfer the dynamic changes of all the cantilevers simultaneously in real-time workspace with high precision. A prototype-enabled dynamic energy sensor has been investigated in the laboratory for inclusion of nanoscale devices in the architecture with a fuzzy logic control for detection of thermal and electrostatic changes with optoelectronic devices to interpret uncertainty associated with signal interference. Ultimately, the controversial aspect of molecular frictional properties is adjusted to each other and forms its unique spatial structure modules for providing the environment mutual contribution in the investigation of mass temperature changes due to pathogenic archival architecture of clusters.

Keywords: autopoiesis, nanoparticles, quantum photonics, portable energy, photonic structure, photodynamic therapeutic system

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Authors: Nirmani Wijenayake, Louise Lutze-Mann, Lucy Jo, John Wilson, Vivian Yeung, Dean Lovett, Kim Snepvangers

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Sessional academic staff at universities have the most influence and impact on student learning, engagement, and experience as they have the most direct contact with undergraduate students. A blended technology-enhanced program was created for the development and support of sessional staff to ensure adequate training is provided to deliver quality educational outcomes for the students. This program combines innovative mixed media educational modules, a peer-driven support forum, and face-to-face workshops to provide a comprehensive training and support package for staff. Additionally, the program encourages the development of learning communities and peer mentoring among the sessional staff to enhance their support system. In 2018, the program was piloted on 100 sessional staff in the School of Biotechnology and Biomolecular Sciences to evaluate the effectiveness of this model. As part of the program, rotoscope animations were developed to showcase ‘typical’ interactions between staff and students. These were designed around communication, confidence building, consistency in grading, feedback, diversity awareness, and mental health and wellbeing. When surveyed, 86% of sessional staff found these animations to be helpful in their teaching. An online platform (Moodle) was set up to disseminate educational resources and teaching tips, to host a discussion forum for peer-to-peer communication and to increase critical thinking and problem-solving skills through scenario-based lessons. The learning analytics from these lessons were essential in identifying difficulties faced by sessional staff to further develop supporting workshops to improve outcomes related to teaching. The face-to-face professional development workshops were run by expert guest speakers on topics such as cultural diversity, stress and anxiety, LGBTIQ and student engagement. All the attendees of the workshops found them to be useful and 88% said they felt these workshops increase interaction with their peers and built a sense of community. The final component of the program was to use an adaptive e-learning platform to gather feedback from the students on sessional staff teaching twice during the semester. The initial feedback provides sessional staff with enough time to reflect on their teaching and adjust their performance if necessary, to improve the student experience. The feedback from students and the sessional staff on this model has been extremely positive. The training equips the sessional staff with knowledge and insights which can provide students with an exceptional learning environment. This program is designed in a flexible and scalable manner so that other faculties or institutions could adapt components for their own training. It is anticipated that the training and support would help to build the next generation of educators who will directly impact the educational experience of students.

Keywords: designing effective instruction, enhancing student learning, implementing effective strategies, professional development

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Authors: Shamsulhaq Amin

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Unbound granular materials (UGMs) are pivotal in ensuring long-term quality, especially in the layers under the surface of flexible pavements and other constructions. This study seeks to better understand the behavior of the UGMs by looking at popular models for predicting lasting deformation under various levels of stresses and load cycles. These models focus on variables such as the number of load cycles, stress levels, and features specific to materials and were evaluated on the basis of their ability to accurately predict outcomes. The study showed that these factors play a crucial role in how well the models work. Therefore, the research highlights the need to look at a wide range of stress situations to more accurately predict how much the UGMs bend or shift. The research looked at important factors, like how permanent deformation relates to the number of times a load is applied, how quickly this phenomenon happens, and the shakedown effect, in two different types of UGMs: granite and limestone. A detailed study was done over 100,000 load cycles, which provided deep insights into how these materials behave. In this study, a number of factors, such as the level of stress applied, the number of load cycles, the density of the material, and the moisture present were seen as the main factors affecting permanent deformation. It is vital to fully understand these elements for better designing pavements that last long and handle wear and tear. A series of laboratory tests were performed to evaluate the mechanical properties of materials and acquire model parameters. The testing included gradation tests, CBR tests, and Repeated load triaxial tests. The repeated load triaxial tests were crucial for studying the significant components that affect deformation. This test involved applying various stress levels to estimate model parameters. In addition, certain model parameters were established by regression analysis, and optimization was conducted to improve outcomes. Afterward, the material parameters that were acquired were used to construct graphs for each model. The graphs were subsequently compared to the outcomes obtained from the repeated load triaxial testing. Additionally, the models were evaluated to determine if they demonstrated the two inherent deformation behaviors of materials when subjected to repetitive load: the initial phase, post-compaction, and the second phase volumetric changes. In this study, using log-log graphs was key to making the complex data easier to understand. This method made the analysis clearer and helped make the findings easier to interpret, adding both precision and depth to the research. This research provides important insight into picking the right models for predicting how these materials will act under expected stress and load conditions. Moreover, it offers crucial information regarding the effect of load cycle and permanent deformation as well as the shakedown effect on granite and limestone UGMs.

Keywords: permanent deformation, unbound granular materials, load cycles, stress level

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Authors: Timothy Akinwande, Eddie Hui, Karien Dekker

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Housing the urban poor remains a persistent challenge, despite evident research attention over many years. It is, therefore, pertinent to investigate affordable housing provision challenges with novel approaches. For innovative solutions to affordable housing constraints, it is apposite to thoroughly examine housing solutions vis a vis the key elements of the housing supply value chain (HSVC), which are housing finance, housing construction and land acquisition. A pragmatic analysis will examine affordable housing solutions from demand and supply perspectives to arrive at consolidated solutions from bilateral viewpoints. This study thoroughly examined informal housing finance strategies of the urban poor and diligently investigated expert opinion on affordable housing finance solutions. The research questions were: (1) What mutual grounds exist between informal housing finance solutions of the urban poor and housing expert solutions to affordable housing finance constraints in developing economies? (2) What are effective approaches to affordable housing finance in developing economies from an integrated demand - supply perspective? Semi-structured interviews were conducted in the 5 largest slums of Lagos, Nigeria, with 40 informal settlers for demand-oriented solutions, while focus group discussion and in-depth interviews were conducted with 12 housing experts in Nigeria for supply-oriented solutions. Following a rigorous thematic, content and descriptive analyses of data using NVivo and Excel, findings ascertained mutual solutions from both demand and supply standpoints that can be consolidated into more effective affordable housing finance solutions in Nigeria. Deliberate finance models that recognise and include the finance realities of the urban poor was found to be the most significant supply-side housing finance solution, representing 25.4% of total expert responses. Findings also show that 100% of sampled urban poor engage in vocations where they earn little irregular income or zero income, limiting their housing finance capacities and creditworthiness. Survey revealed that the urban poor are involved in community savings and employ microfinance institutions within the informal settlements to tackle their housing finance predicaments. These are informal finance models of the urban poor, revealing common grounds between demand and supply solutions for affordable housing financing. Effective, affordable housing approach will be to modify, institutionalise and incorporate the informal finance strategies of the urban poor into deliberate government policies. This consolidation of solutions from demand and supply perspectives can eliminate the persistent misalliance between affordable housing demand and affordable housing supply. This study provides insights into mutual housing solutions from demand and supply perspectives, and findings are informative for effective, affordable housing provision approaches in developing countries. This study is novel in consolidating affordable housing solutions from demand and supply viewpoints, especially in relation to housing finance as a key component of HSVC. The framework for effective, affordable housing finance in developing economies from a consolidated viewpoint generated in this study is significant for the achievement of sustainable development goals, especially goal 11 for sustainable, resilient and inclusive cities. Findings are vital for future housing studies.

Keywords: affordable housing, affordable housing finance, developing economies, effective affordable housing, housing policy, urban poor, sustainable development goal, sustainable affordable housing

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Authors: Pei Yi Lin

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Objective: The objective of this study is to use machine learning methods to build an early prediction classifier model for acute delirium to improve the quality of medical care for intensive care patients. Background: Delirium is a common acute and sudden disturbance of consciousness in critically ill patients. After the occurrence, it is easy to prolong the length of hospital stay and increase medical costs and mortality. In 2021, the incidence of delirium in the intensive care unit of internal medicine was as high as 59.78%, which indirectly prolonged the average length of hospital stay by 8.28 days, and the mortality rate is about 2.22% in the past three years. Therefore, it is expected to build a delirium prediction classifier through big data analysis and machine learning methods to detect delirium early. Method: This study is a retrospective study, using the artificial intelligence big data database to extract the characteristic factors related to delirium in intensive care unit patients and let the machine learn. The study included patients aged over 20 years old who were admitted to the intensive care unit between May 1, 2022, and December 31, 2022, excluding GCS assessment <4 points, admission to ICU for less than 24 hours, and CAM-ICU evaluation. The CAMICU delirium assessment results every 8 hours within 30 days of hospitalization are regarded as an event, and the cumulative data from ICU admission to the prediction time point are extracted to predict the possibility of delirium occurring in the next 8 hours, and collect a total of 63,754 research case data, extract 12 feature selections to train the model, including age, sex, average ICU stay hours, visual and auditory abnormalities, RASS assessment score, APACHE-II Score score, number of invasive catheters indwelling, restraint and sedative and hypnotic drugs. Through feature data cleaning, processing and KNN interpolation method supplementation, a total of 54595 research case events were extracted to provide machine learning model analysis, using the research events from May 01 to November 30, 2022, as the model training data, 80% of which is the training set for model training, and 20% for the internal verification of the verification set, and then from December 01 to December 2022 The CU research event on the 31st is an external verification set data, and finally the model inference and performance evaluation are performed, and then the model has trained again by adjusting the model parameters. Results: In this study, XG Boost, Random Forest, Logistic Regression, and Decision Tree were used to analyze and compare four machine learning models. The average accuracy rate of internal verification was highest in Random Forest (AUC=0.86), and the average accuracy rate of external verification was in Random Forest and XG Boost was the highest, AUC was 0.86, and the average accuracy of cross-validation was the highest in Random Forest (ACC=0.77). Conclusion: Clinically, medical staff usually conduct CAM-ICU assessments at the bedside of critically ill patients in clinical practice, but there is a lack of machine learning classification methods to assist ICU patients in real-time assessment, resulting in the inability to provide more objective and continuous monitoring data to assist Clinical staff can more accurately identify and predict the occurrence of delirium in patients. It is hoped that the development and construction of predictive models through machine learning can predict delirium early and immediately, make clinical decisions at the best time, and cooperate with PADIS delirium care measures to provide individualized non-drug interventional care measures to maintain patient safety, and then Improve the quality of care.

Keywords: critically ill patients, machine learning methods, delirium prediction, classifier model

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Authors: Soumya Rajan

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While delving into the heart of any organization, the structural pre-requisites which form the framework of its system, allures and sometimes invokes great interest. In an attempt to understand the ecosystem of Knowledge that existed in organizations with diverse ownership and legal blueprints, Cooperative Societies, which form a crucial part of the neo-liberal movement in India, was studied. The exploration surprisingly led to the re-designing of at least a set of premises of the researcher on the drivers of engagement in an otherwise structured trade environment. The liberal organizational structure of Cooperative Societies has been empowered with certain terminologies: Voluntary, Democratic, Equality and Distributive Justice. To condense in Hubert Calvert’ words, ‘Co-operation is a form of organization wherein persons voluntarily associated together as human beings on the basis of equality for the promotion of the economic interest of themselves.’ In India, largely the institutions which work under this principle is registered under Cooperative Societies Act of the Central or State laws. A Worker Cooperative Society which originated as a movement in the state of Kerala and spread its wings across the country - Indian Coffee House was chosen as the enterprise for further inquiry for it being a living example and a highly successful working model in the designated space. The exploratory study reached out to employees and key stakeholders of Indian Coffee House to understand the nuances of the structure and the scope it provides for engagement. The key questions which formed shape in the mind of researcher while engaging in the inquiry were: How has the organization sustained despite its principle of accepting employees with no skills into employment and later training and empowering them? How can a system which has pre-independence and post-independence (independence here means the colonial independence from Great Britain) existence seek to engage employees within the premise of equality? How was the value of socialism ingrained in a commercial enterprise which has a turnover of several hundreds of Crores each year? How did the vision of a flat structure, way back in the 1940’s find its way into the organizational structure and has continued to remain as the way of life? These questions were addressed by the Case study research that ensued and placing Knowledge as the key premise, the possibilities of engagement of the organization man was pictured. Understanding that although the macro or holistic unit of analysis is the organization, it is pivotal to understand the structures and processes which best reflect on the actors. The embedded design which was adopted in this study delivered insights from the different stakeholder actors from diverse departments. While moving through variables which define and sometimes defy bounds in rationality, the study brought to light the inherent features of the organization structure and how it influences the actors who form a crucial part of the scheme of things. The research brought forth the key enablers for engagement and specifically explored the standpoint of knowledge in the larger structure of the Cooperative Society.

Keywords: knowledge, organizational structure, engagement, worker cooperative

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Authors: Hai L. Tran

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In the digital age, evidence-based reporting is touted as a best practice for seeking the truth and keeping the public well-informed. Journalists are expected to rely on evidence to demonstrate the validity of a factual statement and lend credence to an individual account. Evidence can be obtained from various sources, and due to a rich supply of evidence types available, the definition of this important concept varies semantically. To promote clarity and understanding, it is necessary to break down the various types of evidence and categorize them in a more coherent, systematic way. There is a wide array of devices that digital journalists deploy as proof to back up or refute a truth claim. Evidence can take various formats, including verbal and visual materials. Verbal evidence encompasses quotes, soundbites, talking heads, testimonies, voice recordings, anecdotes, and statistics communicated through written or spoken language. There are instances where evidence is simply non-verbal, such as when natural sounds are provided without any verbalized words. On the other hand, other language-free items exhibited in photos, video footage, data visualizations, infographics, and illustrations can serve as visual evidence. Moreover, there are different sources from which evidence can be cited. Supporting materials, such as public or leaked records and documents, data, research studies, surveys, polls, or reports compiled by governments, organizations, and other entities, are frequently included as informational evidence. Proof can also come from human sources via interviews, recorded conversations, public and private gatherings, or press conferences. Expert opinions, eye-witness insights, insider observations, and official statements are some of the common examples of testimonial evidence. Digital journalism studies tend to make broad references when comparing qualitative versus quantitative forms of evidence. Meanwhile, limited efforts are being undertaken to distinguish between sister terms, such as “data,” “statistical,” and “base-rate” on one side of the spectrum and “narrative,” “anecdotal,” and “exemplar” on the other. The present study seeks to develop the evidence taxonomy, which classifies evidence through the quantitative-qualitative juxtaposition and in a hierarchical order from broad to specific. According to this scheme, data, statistics, and base rate belong to the quantitative evidence group, whereas narrative, anecdote, and exemplar fall into the qualitative evidence group. Subsequently, the taxonomical classification arranges data versus narrative at the top of the hierarchy of types of evidence, followed by statistics versus anecdote and base rate versus exemplar. This research reiterates the central role of evidence in how journalists describe and explain social phenomena and issues. By defining the various types of evidence and delineating their logical connections it helps remove a significant degree of conceptual inconsistency, ambiguity, and confusion in digital journalism studies.

Keywords: evidence, evidence forms, evidence types, taxonomy

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Farnaz Jafari

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The surge in mass timber construction represents a pivotal moment in sustainable building practices, yet the lack of comprehensive education in construction management poses a challenge in harnessing this innovation effectively. This research endeavors to bridge this gap by developing a curriculum framework integrating mass timber construction into undergraduate and industry certificate programs. To optimize learning outcomes, the study explores the impact of two prototype formats -Virtual Reality (VR) simulations and physical mock-ups- on students' understanding and skill development. The curriculum framework aims to equip future construction managers with a holistic understanding of mass timber, covering its unique properties, construction methods, building codes, and sustainable advantages. The study adopts a mixed-methods approach, commencing with a systematic literature review and leveraging surveys and interviews with educators and industry professionals to identify existing educational gaps. The iterative development process involves incorporating stakeholder feedback into the curriculum. The evaluation of prototype impact employs pre- and post-tests administered to participants engaged in pilot programs. Through qualitative content analysis and quantitative statistical methods, the study seeks to compare the effectiveness of VR simulations and physical mock-ups in conveying knowledge and skills related to mass timber construction. The anticipated findings will illuminate the strengths and weaknesses of each approach, providing insights for future curriculum development. The curriculum's expected contribution to sustainable construction education lies in its emphasis on practical application, bridging the gap between theoretical knowledge and hands-on skills. The research also seeks to establish a standard for mass timber construction education, contributing to the field through a unique comparative analysis of VR simulations and physical mock-ups. The study's significance extends to the development of best practices and evidence-based recommendations for integrating technology and hands-on experiences in construction education. By addressing current educational gaps and offering a comparative analysis, this research aims to enrich the construction management education experience and pave the way for broader adoption of sustainable practices in the industry. The envisioned curriculum framework is designed for versatile integration, catering to undergraduate programs and industry training modules, thereby enhancing the educational landscape for aspiring construction professionals. Ultimately, this study underscores the importance of proactive educational strategies in preparing industry professionals for the evolving demands of the construction landscape, facilitating a seamless transition towards sustainable building practices.

Keywords: curriculum framework, mass timber construction, physical vs. virtual prototypes, sustainable building practices

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Authors: Mamunur Rashid, Jialin Yan

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The current years have witnessed a rapid evolution and integration of artificial intelligence (AI) in various fields, prominently influencing the education industry. Acknowledging this transformative wave, AI tools like ChatGPT and Grammarly have undeniably introduced perspectives and skills, enriching the educational experiences of higher education students. The prevalence of AI utilization in higher education also drives an increasing number of researchers' attention in various dimensions. Departments, offices, and professors in universities also designed and released a set of policies and guidelines on using AI effectively. In regard to this, the study targets exploring and analyzing graduate students' perspectives regarding AI guidelines set by teachers. A mixed-methods study will be mainly conducted in this study, employing in-depth interviews and focus groups to investigate and collect students' perspectives. Relevant materials, such as syllabi and course instructions, will also be analyzed through the documentary analysis to facilitate understanding of the study. Surveys will also be used for data collection and students' background statistics. The integration of both interviews and surveys will provide a comprehensive array of student perspectives across various academic disciplines. The study is anchored in the theoretical framework of self-determination theory (SDT), which emphasizes and explains the students' perspective under the AI guidelines through three core needs: autonomy, competence, and relatedness. This framework is instrumental in understanding how AI guidelines influence students' intrinsic motivation and sense of empowerment in their learning environments. Through qualitative analysis, the study reveals a sense of confusion and uncertainty among students regarding the appropriate application and ethical considerations of AI tools, indicating potential challenges in meeting their needs for competence and autonomy. The quantitative data further elucidates these findings, highlighting a significant communication gap between students and educators in the formulation and implementation of AI guidelines. The critical findings of this study mainly come from two aspects: First, the majority of graduate students are uncertain and confused about relevant AI guidelines given by teachers. Second, this study also demonstrates that the design and effectiveness of course materials, such as the syllabi and instructions, also need to adapt in regard to AI policies. It indicates that certain of the existing guidelines provided by teachers lack consideration of students' perspectives, leading to a misalignment with students' needs for autonomy, competence, and relatedness. More emphasize and efforts need to be dedicated to both teacher and student training on AI policies and ethical considerations. To conclude, in this study, graduate students' perspectives on teacher-provided AI guidelines are explored and reflected upon, calling for additional training and strategies to improve how these guidelines can be better disseminated for their effective integration and adoption. Although AI guidelines provided by teachers may be helpful and provide new insights for students, educational institutions should take a more anchoring role to foster a motivating, empowering, and student-centered learning environment. The study also provides some relevant recommendations, including guidance for students on the ethical use of AI and AI policy training for teachers in higher education.

Keywords: higher education policy, graduate students’ perspectives, higher education teacher, AI guidelines, AI in education

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Authors: dr. Bendes Ákos

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Digital skepticism, a critical stance towards digital technology and its pervasive influence on society, presents significant challenges when analyzed from a legal philosophical perspective. This abstract aims to explore the intersection of digital skepticism and legal philosophy, emphasizing the implications for justice, rights, and the rule of law in the digital age. Digital skepticism arises from concerns about privacy, security, and the ethical implications of digital technology. It questions the extent to which digital advancements enhance or undermine fundamental human values. Legal philosophy, which interrogates the foundations and purposes of law, provides a framework for examining these concerns critically. One key area where digital skepticism and legal philosophy intersect is in the realm of privacy. Digital technologies, particularly data collection and surveillance mechanisms, pose substantial threats to individual privacy. Legal philosophers must grapple with questions about the limits of state power and the protection of personal autonomy. They must consider how traditional legal principles, such as the right to privacy, can be adapted or reinterpreted in light of new technological realities. Security is another critical concern. Digital skepticism highlights vulnerabilities in cybersecurity and the potential for malicious activities, such as hacking and cybercrime, to disrupt legal systems and societal order. Legal philosophy must address how laws can evolve to protect against these new forms of threats while balancing security with civil liberties. Ethics plays a central role in this discourse. Digital technologies raise ethical dilemmas, such as the development and use of artificial intelligence and machine learning algorithms that may perpetuate biases or make decisions without human oversight. Legal philosophers must evaluate the moral responsibilities of those who design and implement these technologies and consider the implications for justice and fairness. Furthermore, digital skepticism prompts a reevaluation of the concept of the rule of law. In an increasingly digital world, maintaining transparency, accountability, and fairness becomes more complex. Legal philosophers must explore how legal frameworks can ensure that digital technologies serve the public good and do not entrench power imbalances or erode democratic principles. Finally, the intersection of digital skepticism and legal philosophy has practical implications for policy-making. Legal scholars and practitioners must work collaboratively to develop regulations and guidelines that address the challenges posed by digital technology. This includes crafting laws that protect individual rights, ensure security, and promote ethical standards in technology development and deployment. In conclusion, digital skepticism provides a crucial lens for examining the impact of digital technology on law and society. A legal philosophical approach offers valuable insights into how legal systems can adapt to protect fundamental values in the digital age. By addressing privacy, security, ethics, and the rule of law, legal philosophers can help shape a future where digital advancements enhance, rather than undermine, justice and human dignity.

Keywords: legal philosophy, privacy, security, ethics, digital skepticism

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Authors: Colin Schmidt, Adrien Lecossier, Pascal Crubleau, Philippe Blanchard, Simon Richir

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Introduction:The widespread availability of artificial intelligence, exemplified by Generative Pre-trained Transformers (GPT) relying on large language models (LLM), has caused a seismic shift in the realm of knowledge. Everyone now has the capacity to swiftly learn how these models can either serve them well or not. Today, conversational AI like ChatGPT is grounded in neural transformer models, a significant advance in natural language processing facilitated by the emergence of renowned LLMs constructed using neural transformer architecture. Inventiveness of an LLM : OpenAI's GPT-3 stands as a premier LLM, capable of handling a broad spectrum of natural language processing tasks without requiring fine-tuning, reliably producing text that reads as if authored by humans. However, even with an understanding of how LLMs respond to questions asked, there may be lurking behind OpenAI’s seemingly endless responses an inventive model yet to be uncovered. There may be some unforeseen reasoning emerging from the interconnection of neural networks here. Just as a Soviet researcher in the 1940s questioned the existence of Common factors in inventions, enabling an Under standing of how and according to what principles humans create them, it is equally legitimate today to explore whether solutions provided by LLMs to complex problems also share common denominators. Theory of Inventive Problem Solving (TRIZ) : We will revisit some fundamentals of TRIZ and how Genrich ALTSHULLER was inspired by the idea that inventions and innovations are essential means to solve societal problems. It's crucial to note that traditional problem-solving methods often fall short in discovering innovative solutions. The design team is frequently hampered by psychological barriers stemming from confinement within a highly specialized knowledge domain that is difficult to question. We presume ChatGPT Utilizes TRIZ 40. Hence, the objective of this research is to decipher the inventive model of LLMs, particularly that of ChatGPT, through a comparative study. This will enhance the efficiency of sustainable innovation processes and shed light on how the construction of a solution to a complex problem was devised. Description of the Experimental Protocol : To confirm or reject our main hypothesis that is to determine whether ChatGPT uses TRIZ, we will follow a stringent protocol that we will detail, drawing on insights from a panel of two TRIZ experts. Conclusion and Future Directions : In this endeavor, we sought to comprehend how an LLM like GPT addresses complex challenges. Our goal was to analyze the inventive model of responses provided by an LLM, specifically ChatGPT, by comparing it to an existing standard model: TRIZ 40. Of course, problem solving is our main focus in our endeavours.

Keywords: artificial intelligence, Triz, ChatGPT, inventiveness, problem-solving

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Authors: Sempiga Olivier, Dominika Latusek-Jurczak

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The conflict in Ukraine has had far-reaching economic consequences, not only for the countries directly involved in it but also for their trading partners and allies, and on the global economy in general. Different European Union (EU) countries, being some of Ukraine and Russia's major trading partners, have also felt the impact of the conflict on their economy. In a special way, the energy sector has suffered the most due to the fact that Russia is a huge exporter of gas and other energy sources on which rely European countries. Energy is a locomotive of the economy and once energy prices skyrocket there is a spill over effects in other areas causing different commodities’ prices to rise thereby affecting people’s social economic lifestyles. To minimise the impact energy crisis’ socio-political and economic consequences, the EU and countries have tightened their regulatory mechanisms to stop some energy firms exploit the crisis at the expense of the vulnerable mass. The key question is to what extent these regulatory instruments put in place during the energy crisis times have an affect on citizen trust in the governing institutions. The question is of paramount importance after years of declining trust in the EU and in most countries in Europe. Earlier research have analysed how wars or global political risks relate to citizen trust in government and organizations but very few empirical research have examined the relationship between regulatory instruments during the time of crisis on citizen trust in government and institutions. Using data from INSEE (the French National Institute of Statistics and Economic Studies) and European Social Survey (ESS), it carry out a multilinear regression analysis and investigate the impact of regulation both from the EU and different countries on energy prices on citizen trust. To understand the dynamics between regulatory actions during crises and citizen trust, this study draws on the theoretical framework of institutional trust and regulatory legitimacy. Institutional trust theory posits that citizens’ trust in government and institutions is influenced by perceptions of fairness, transparency, and efficacy in governance. Regulatory legitimacy, a related concept, suggests that regulatory measures, especially in response to crises, are more effective when perceived as just, necessary, and in the public interest. Results of this cross sectional study show that regulatory frameworks strongly affect the levels of trust, the association varying from strong to moderate depending on countries and period. This study contributes to the understanding of the vital relationship between regulatory measures implemented during crises and citizen trust in government institutions. By identifying the conditions under which trust is fostered or eroded, the findings provide policymakers with valuable insights into effective strategies for enhancing public confidence, ultimately guiding interventions that can mitigate the socio-political impacts of future energy crises.

Keywords: energy crisis, price, regulation, russia-Ukraine conflict, trust

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Authors: Iris Vural Gursel, Andrea Ramirez

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Effective utilization of lignin is an important mean for developing economically profitable biorefineries. Current literature suggests that large amounts of lignin will become available in second generation biorefineries. New conversion technologies will, therefore, be needed to carry lignin transformation well beyond combustion to produce energy, but towards high-value products such as chemicals and transportation fuels. In recent years, significant progress on catalysis has been made to improve transformation of lignin, and new catalytic processes are emerging. In this work, a techno-economic assessment of two of these novel conversion routes and comparison with more established lignin pyrolysis route were made. The aim is to provide insights into the potential performance and potential hotspots in order to guide the experimental research and ease the commercialization by early identifying cost drivers, strengths, and challenges. The lignin conversion routes selected for detailed assessment were: (non-catalytic) lignin pyrolysis as the benchmark, direct hydrodeoxygenation (HDO) of lignin and hydrothermal lignin depolymerisation. Products generated were mixed oxygenated aromatic monomers (MOAMON), light organics, heavy organics, and char. For the technical assessment, a basis design followed by process modelling in Aspen was done using experimental yields. A design capacity of 200 kt/year lignin feed was chosen that is equivalent to a 1 Mt/y scale lignocellulosic biorefinery. The downstream equipment was modelled to achieve the separation of the product streams defined. For determining external utility requirement, heat integration was considered and when possible gasses were combusted to cover heating demand. The models made were used in generating necessary data on material and energy flows. Next, an economic assessment was carried out by estimating operating and capital costs. Return on investment (ROI) and payback period (PBP) were used as indicators. The results of the process modelling indicate that series of separation steps are required. The downstream processing was found especially demanding in the hydrothermal upgrading process due to the presence of significant amount of unconverted lignin (34%) and water. Also, external utility requirements were found to be high. Due to the complex separations, hydrothermal upgrading process showed the highest capital cost (50 M€ more than benchmark). Whereas operating costs were found the highest for the direct HDO process (20 M€/year more than benchmark) due to the use of hydrogen. Because of high yields to valuable heavy organics (32%) and MOAMON (24%), direct HDO process showed the highest ROI (12%) and the shortest PBP (5 years). This process is found feasible with a positive net present value. However, it is very sensitive to the prices used in the calculation. The assessments at this stage are associated with large uncertainties. Nevertheless, they are useful for comparing alternatives and identifying whether a certain process should be given further consideration. Among the three processes investigated here, the direct HDO process was seen to be the most promising.

Keywords: biorefinery, economic assessment, lignin conversion, process design

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Authors: Stacia E. H. Sitohang, S.Mn., Socrates Rudy Sirait

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The first movie theater in Indonesia was established in December 1900. The movie industry started with international movie penetration. After a while, local movie producers started to rise and created local Indonesian movies. The industry is growing through ups and downs in Indonesia. In 2008, Visinema was founded in Jakarta, Indonesia, by AnggaDwimasSasongko, one of the most respected movie director in Indonesia. After getting achievements and recognition, Visinema chose to grow the company horizontally as opposed to only grow vertically and gain another similar achievement. Visinemachose to build the ecosystem that enables them to obtain many more opportunities and generatebusiness sustainability. The company proceed as an agile company. They created several business subsidiaries to support the company’s Intellectual Property (IP) development. This research was done through interview with the key persons in the company and questionnaire to get market insights regarding Visinema. The is able to transform their IP that initially started from movies to different kinds of business model. Interestingly, Angga chose to use the start up approach to create Visinema. In 2019, the company successfully gained Series A funding from Intudo Ventures and got other various investment schemes to support the business. In early 2020, Covid-19 pandemic negatively impacted many industries in Indonesia, especially the entertainment and leisure businesses. Fortunately, Visinema did not face any significant problem regarding survival during the pandemic, there were nolay-offs nor work hour reductions. Instead, they were thinking of much bigger opportunities and problems. While other companies suffer during the pandemic, Visinema created the first focused Transactional Video On Demand (TVOD) in Indonesia named Bioskop Online. The platform was created to keep the company innovating and adapting with the new online market as the result of the Covid-19 pandemic. Other than a digital platform, Visinemainvested heavily in animation to target kids and family business. They believed that penetrating the technology and animation market is going to be the biggest opportunity in Visinema’s road map. Besides huge opportunities, Visinema is also facing problems. The first is company brand positioning. Angga, as the founder, felt the need to detach his name from the brand image of Visinema to create system sustainability and scalability. Second, the company has to create a strategy to refocus in a particular business area to maintain and improve the competitive advantages. The third problem, IP piracy is a huge structural problem in Indonesia, the company considers IP thieves as their biggest competitors as opposed to other production company. As the recommendation, we suggest a set of branding and management strategy to detach the founder’s name from Visinema’s brand and improve the competitive advantages. We also suggest Visinema invest in system building to prevent IP piracy in the entertainment industry, which later can be another business subsidiary of Visinema.

Keywords: business ecosystem, agile, sustainability, scalability, start Up, intellectual property, digital platform

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Authors: A. F. G. Van Woezik, L. M. A. Braakman-Jansen, O. A. Kulyk, J. E. W. C. Van Gemert-Pijnen

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Background: Zoonoses pose a serious threat to public health and economies worldwide, especially as antimicrobial resistance grows and newly emerging zoonoses can cause unpredictable outbreaks. In order to prevent and control emerging and re-emerging zoonoses, collaboration between veterinary, human health and public health domains is essential. In reality however, there is a lack of cooperation between these three disciplines and uncertainties exist about their tasks and responsibilities. The objective of this ongoing research project (ZonMw funded, 2014-2018) is to develop an online education and communication One Health platform, “eZoon”, for the general public and professionals working in veterinary, human health and public health domains to support the risk communication of non-alimentary zoonoses in the Netherlands. The main focus is on education and communication in times of outbreak as well as in daily non-outbreak situations. Methods: A participatory development approach was used in which stakeholders from veterinary, human health and public health domains participated. Key stakeholders were identified using business modeling techniques previously used for the design and implementation of antibiotic stewardship interventions and consisted of a literature scan, expert recommendations, and snowball sampling. We used a stakeholder salience approach to rank stakeholders according to their power, legitimacy, and urgency. Semi-structured interviews were conducted with stakeholders (N=20) from all three disciplines to identify current problems in risk communication and stakeholder values for the One Health platform. Interviews were transcribed verbatim and coded inductively by two researchers. Results: The following key values were identified (but were not limited to): (a) need for improved awareness of veterinary and human health of each other’s fields, (b) information exchange between veterinary and human health, in particularly at a regional level; (c) legal regulations need to match with daily practice; (d) professionals and general public need to be addressed separately using tailored language and information; (e) information needs to be of value to professionals (relevant, important, accurate, and have financial or other important consequences if ignored) in order to be picked up; and (f) need for accurate information from trustworthy, centrally organised sources to inform the general public. Conclusion: By applying a participatory development approach, we gained insights from multiple perspectives into the main problems of current risk communication strategies in the Netherlands and stakeholder values. Next, we will continue the iterative development of the One Health platform by presenting key values to stakeholders for validation and ranking, which will guide further development. We will develop a communication platform with a serious game in which professionals at the regional level will be trained in shared decision making in time-critical outbreak situations, a smart Question & Answer (Q&A) system for the general public tailored towards different user profiles, and social media to inform the general public adequately during outbreaks.

Keywords: ehealth, one health, risk communication, stakeholder, zoonosis

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Authors: Sarah Faulkner, Patrick Faulkner, Caroline Ellison

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Improved mental and physical health, community connection, and increased life satisfaction has been strongly associated with bike riding for those with and without a disability. However, much evidence suggests that people living with a disability face increased barriers to engaging in cycling compared to members of the general population. People with an intellectual disability often live more sedentary and socially isolated lives that negatively impact their mental and physical health, as well as life satisfaction. This paper is based on preliminary findings from a three-year intervention cycling project funded by the South Australian Government. The cycling project was developed in partnership with community stakeholders that provided weekly instruction, training, and support to individuals living with intellectual disabilities to increase their capacity in cycling. This project aimed to support people living with intellectual disabilities to foster and facilitate improved physical and mental health, confidence, and independence and enhance social networking through their engagement in community cycling. The program applied principles of social role valorisation (SRV) theory as its guiding framework. Preliminary data collected is based on qualitative interviews with over 50 program participants, results from two participant wellness questionnaires, as well as a perceptually regulated exercise test administered throughout the project implementation. Preliminary findings are further supplemented with ethnographic analyses by the researchers who took a phenology of life experience approach. Preliminary findings of the program suggest a variety of social motivations behind participants' desire to learn cycling that acknowledges previous barriers to engagement and cycling’s role to address feelings of loneliness and social isolation. Meaningful health benefits can be achieved as demonstrated by increases in predicted V02 max measures, suggesting that physical intervention can not only improve physical health outcomes but also provide a variety of other social benefits. Initial engagement in the project has demonstrated an increase in participants' sense of confidence, well-being, and physical fitness. Implementation of the project in partnership with a variety of community stakeholders has identified a number of critical factors and processes necessary for future service replication, sustainability, and success. Findings from this intervention study contribute to the development of a knowledge base on how best to support individuals living with an intellectual disability to partake in bike riding and increase positive outcomes associated with their capacity building, social interaction, increased physical activity, physical health, and mental well-being. The initial findings of this study provide critical academic insights into the social and physical benefits of cycling for people living with a disability, as well as practical advice for future human service applications.

Keywords: cycling, disability, social inclusion, capacity building

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Authors: Loren S. Bernal., Catalina Castillo, Carel E. Carvajal, José F. Ibla

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Plastic pollution, specifically microplastics, has become a significant issue in aquatic ecosystems worldwide. The large amount of plastic waste carried by water tributaries has resulted in the accumulation of microplastics in water bodies. The polymer aging process caused by environmental influences such as photodegradation and chemical degradation of additives leads to polymer embrittlement and properties change that require degradation or reduction procedures in rivers. However, there is a lack of such procedures for freshwater entities that develop over extended periods. The aim of this study is evaluate the potential of Pleurotus ostreatus a fungus, in reducing lowdensity polyethylene microplastics present in freshwater samples collected from the middle basin of the Magdalena River in Colombia. The study aims to evaluate this process both in vitro and in silico by identifying the growth capacity of Pleurotus ostreatus in the presence of microplastics and identifying the most likely interactions of Pleurotus ostreatus enzymes and their affinity energies. The study follows an engineering development methodology applied on an experimental basis. The in vitro evaluation protocol applied in this study focused on the growth capacity of Pleurotus ostreatus on microplastics using enzymatic inducers. In terms of in silico evaluation, molecular simulations were conducted using the Autodock 1.5.7 program to calculate interaction energies. The molecular dynamics were evaluated by using the myPresto Portal and GROMACS program to calculate radius of gyration and Energies.The results of the study showed that Pleurotus ostreatus has the potential to degrade low-density polyethylene microplastics. The in vitro evaluation revealed the adherence of Pleurotus ostreatus to LDPE using scanning electron microscopy. The best results were obtained with enzymatic inducers as a MnSO4 generating the activation of laccase or manganese peroxidase enzymes in the degradation process. The in silico modelling demonstrated that Pleurotus ostreatus was able to interact with the microplastics present in LDPE, showing affinity energies in molecular docking and molecular dynamics shown a minimum energy and the representative radius of gyration between each enzyme and its substract. The study contributes to the development of bioremediation processes for the removal of microplastics from freshwater sources using the fungus Pleurotus ostreatus. The in silico study provides insights into the affinity energies of Pleurotus ostreatus microplastic degrading enzymes and their interaction with low-density polyethylene. The study demonstrated that Pleurotus ostreatus can interact with LDPE microplastics, making it a good agent for the development of bioremediation processes that aid in the recovery of freshwater sources. The results of the study suggested that bioremediation could be a promising approach to reduce microplastics in freshwater systems.

Keywords: bioremediation, in silico modelling, microplastics, Pleurotus ostreatus

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Authors: Mona Salah El-Din Hassanein

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Faced with a sudden, unexpected, and overwhelming event, the individual's normal cognitive processing may cease to function, trapping the psyche in "speechless terror", while images, feelings and sensations are experienced with emotional intensity. Unable to master such situation, the individual becomes a trauma victim who will be susceptible to traumatic recollections like intrusive thoughts, flashbacks, and repetitive re-living of the primal event in a way that blurs the distinction between past and present, and forecloses the future. Trauma is timeless, repetitious, and contagious; a trauma observer could fall prey to "secondary victimhood". Central to the process of healing the psychic wounds in the aftermath of trauma is verbalizing the traumatic experience (i.e., putting it into words) – an act which provides a chance for assimilation, testimony, and reevaluation. In light of this paradigm, this paper proposes a reading of Oscar Wilde's The Ballad of Reading Gaol, written shortly after his release from prison, as a post-traumatic text which traces the disruptive effects of the traumatic experience of Wilde's imprisonment for homosexual offences and the ensuing reversal of fortune he endured. Post-traumatic writing demonstrates the process of "working through" a trauma which may lead to the possibility of ethical agency in the form of a "survivor mission". This paper draws on fundamental concepts and key insights in literary trauma theory which is characterized by interdisciplinarity, combining the perspectives of different fields like critical theory, psychology, psychiatry, psychoanalysis, history, and social studies. Of particular relevance to this paper are the concepts of "vicarious traumatization" and "survivor mission", as The Ballad of Reading Gaol was written in response to Wilde's own prison trauma and the indirect traumatization he experienced as a result of witnessing the execution of a fellow prisoner whose story forms the narrative base of the poem. The Ballad displays Wilde's sense of mission which leads him to recognize the social as well as ethical implications of personal tragedy. Through a close textual analysis of The Ballad of Reading Gaol within the framework of literary trauma theory, the paper aims to: (a) demonstrate how the poem's thematic concerns, structure and rhetorical figures reflect the structure of trauma; (b) highlight Wilde's attempts to come to terms with the effects of the cataclysmic experience which transformed him into a social outcast; and (c) show how Wilde manages to transcend the victim status and assumes the role of ethical agent to voice a critique of the Victorian penal system and the standards of morality underlying the cruelties practiced against wrong doers and to solicit social action.

Keywords: ballad of reading of reading, post-traumatic writing, trauma theory, Wilde

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Authors: Kimberly Winnie Achieng Otieno

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The Nairobi Hospital plays a pivotal role in healthcare provision in East and Central Africa, yet it faces challenges in providing accessible dialysis care. This paper explores strategic interventions to enhance dialysis care, improve access and streamline health information management, with an aim of fostering an integrated and patient-centered healthcare system in our region. Challenges at The Nairobi Hospital The Nairobi Hospital currently grapples with insufficient dialysis machines which results in extended turn around times. This issue stems from both staffing bottle necks and infrastructural limitations given our growing demand for renal care services. Our Paper-based record keeping system and fragmented flow of information downstream hinders the hospital’s ability to manage health data effectively. There is also a need for investment in expanding The Nairobi Hospital dialysis facilities to far reaching communities. Setting up satellite clinics that are closer to people who live in areas far from the main hospital will ensure better access to underserved areas. Community Outreach and Education Implementing education programs on kidney health within local communities is vital for early detection and prevention. Collaborating with local leaders and organizations can establish a proactive approach to renal health hence reducing the demand for acute dialysis interventions. We can amplify this effort by expanding The Nairobi Hospital’s corporate social responsibility outreach program with weekend engagement activities such as walks, awareness classes and fund drives. Enhancing Efficiency in Dialysis Care Demand for dialysis services continues to rise due to an aging Kenyan population and the increasing prevalence of chronic kidney disease (CKD). Present at this years International Nursing Conference are a diverse group of caregivers from around the world who can share with us their process optimization strategies, patient engagement techniques and resource utilization efficiencies to catapult The Nairobi Hospital to the 21st century and beyond. Plans are underway to offer ongoing education opportunities to keep staff updated on best practices and emerging technologies in addition to utilizing a patient feedback mechanisms to identify areas for improvement and enhance satisfaction. Staff empowerment and suggestion boxes address The Nairobi Hospital’s organizational challenges. Current financial constraints may limit a leapfrog in technology integration such as the acquisition of new dialysis machines and an investment in predictive analytics to forecast patient needs and optimize resource allocation. Streamlining Health Information Management Fully embracing a shift to 100% Electronic Health Records (EHRs) is a transformative step toward efficient health information management. Shared information promotes a holistic understanding of patients’ medical history, minimizing redundancies and enhancing overall care quality. To manage the transition to community-based care and EHRs effectively, a phased implementation approach is recommended. Conclusion By strategically enhancing dialysis care access and streamlining health information management, The Nairobi Hospital can strengthen its position as a leading healthcare institution in both East and Central Africa. This comprehensive approach aligns with the hospital’s commitment to providing high-quality, accessible, and patient-centered care in an evolving landscape of healthcare delivery.

Keywords: Africa, urology, diaylsis, healthcare

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Authors: Andrzej Wałęga, Marta Cebulska, Agnieszka Ziernicka-Wojtaszek, Wojciech Młocek, Agnieszka Wałęga, Tommaso Caloiero

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Drought is one of the natural phenomena influencing many aspects of human activities like food production, agriculture, industry, and the ecological conditions of the environment. In the area of the Polish Carpathians, there are periods with a deficit of rainwater and an increasing frequency in dry months, especially in the cold half of the year. The aim of this work is a spatial and temporal analysis of drought, expressed as SPI in a heterogenous area of the Polish Carpathian and of the highland Region in the Central part of Europe based on long-term precipitation data. Also, to our best knowledge, for the first time in this work, drought characteristics analyzed via the SPI were discussed based on the atmospheric circulation calendar. The study region is the Upper Vistula Basin, located in the southern and south-eastern part of Poland. In this work, monthly precipitation from 56 rainfall stations was analysed from 1961 to 2022. The 3-, 6-, 9-, and 12-month Standardized Precipitation Index (SPI) were used as indicators of meteorological drought. For the 3-month SPI, the main climatic mechanisms determining extreme droughts were defined based on the calendar of synoptic circulations. The Mann-Kendall test was used to detect the trend of extreme droughts. Statistically significant trends of SPI were observed on 52.7% of all analyzed stations, and in most cases, a positive trend was observed. Statistically significant trends were more frequently observed in stations located in the western part of the analyzed region. Long-term droughts, represented by the 12-month SPI, occurred in all stations but not in all years. Short-term droughts (3-month SPI) were most frequent in the winter season, 6 and 9-month SPI in winter and spring, and 12-month SPI in winter and autumn, respectively. The spatial distribution of drought was highly diverse. The most intensive drought occurred in 1984, with the 6-month SPI covering 98% of the analyzed region and the 9 and 12-month SPI covering 90% of the entire region. Droughts exhibit a seasonal pattern, with a dominant 10-year periodicity for all analyzed variants of SPI. Additionally, Fourier analysis revealed a 2-year periodicity for the 3-, 6-, and 9-month SPI and a 31-year periodicity for the 12-month SPI. The results provide insights into the typical climatic conditions in Poland, with strong seasonality in precipitation. The study highlighted that short-term extreme droughts, represented by the 3-month SPI, are often caused by anticyclonic situations with high-pressure wedges Ka and Wa, and anticyclonic West as observed in 52.3% of cases. These findings are crucial for understanding the spatial and temporal variability of short and long-term extreme droughts in Central Europe, particularly for the agriculture sector dominant in the northern part of the analyzed region, where drought frequency is highest.

Keywords: atmospheric circulation, drought, precipitation, SPI, the Upper Vistula Basin

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Authors: Tianyu Wang, Nikita Karandikar

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The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

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