Search results for: social work education and pedagogy
Commenced in January 2007
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Edition: International
Paper Count: 25883

Search results for: social work education and pedagogy

23 Circular Tool and Dynamic Approach to Grow the Entrepreneurship of Macroeconomic Metabolism

Authors: Maria Areias, Diogo Simões, Ana Figueiredo, Anishur Rahman, Filipa Figueiredo, João Nunes

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It is expected that close to 7 billion people will live in urban areas by 2050. In order to improve the sustainability of the territories and its transition towards circular economy, it’s necessary to understand its metabolism and promote and guide the entrepreneurship answer. The study of a macroeconomic metabolism involves the quantification of the inputs, outputs and storage of energy, water, materials and wastes for an urban region. This quantification and analysis representing one opportunity for the promotion of green entrepreneurship. There are several methods to assess the environmental impacts of an urban territory, such as human and environmental risk assessment (HERA), life cycle assessment (LCA), ecological footprint assessment (EF), material flow analysis (MFA), physical input-output table (PIOT), ecological network analysis (ENA), multicriteria decision analysis (MCDA) among others. However, no consensus exists about which of those assessment methods are best to analyze the sustainability of these complex systems. Taking into account the weaknesses and needs identified, the CiiM - Circular Innovation Inter-Municipality project aims to define an uniform and globally accepted methodology through the integration of various methodologies and dynamic approaches to increase the efficiency of macroeconomic metabolisms and promoting entrepreneurship in a circular economy. The pilot territory considered in CiiM project has a total area of 969,428 ha, comprising a total of 897,256 inhabitants (about 41% of the population of the Center Region). The main economic activities in the pilot territory, which contribute to a gross domestic product of 14.4 billion euros, are: social support activities for the elderly; construction of buildings; road transport of goods, retailing in supermarkets and hypermarkets; mass production of other garments; inpatient health facilities; and the manufacture of other components and accessories for motor vehicles. The region's business network is mostly constituted of micro and small companies (similar to the Central Region of Portugal), with a total of 53,708 companies identified in the CIM Region of Coimbra (39 large companies), 28,146 in the CIM Viseu Dão Lafões (22 large companies) and 24,953 in CIM Beiras and Serra da Estrela (13 large companies). For the construction of the database was taking into account data available at the National Institute of Statistics (INE), General Directorate of Energy and Geology (DGEG), Eurostat, Pordata, Strategy and Planning Office (GEP), Portuguese Environment Agency (APA), Commission for Coordination and Regional Development (CCDR) and Inter-municipal Community (CIM), as well as dedicated databases. In addition to the collection of statistical data, it was necessary to identify and characterize the different stakeholder groups in the pilot territory that are relevant to the different metabolism components under analysis. The CIIM project also adds the potential of a Geographic Information System (GIS) so that it is be possible to obtain geospatial results of the territorial metabolisms (rural and urban) of the pilot region. This platform will be a powerful visualization tool of flows of products/services that occur within the region and will support the stakeholders, improving their circular performance and identifying new business ideas and symbiotic partnerships.

Keywords: circular economy tools, life cycle assessment macroeconomic metabolism, multicriteria decision analysis, decision support tools, circular entrepreneurship, industrial and regional symbiosis

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22 Fabrication of Highly Stable Low-Density Self-Assembled Monolayers by Thiolyne Click Reaction

Authors: Leila Safazadeh, Brad Berron

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Self-assembled monolayers have tremendous impact in interfacial science, due to the unique opportunity they offer to tailor surface properties. Low-density self-assembled monolayers are an emerging class of monolayers where the environment-interfacing portion of the adsorbate has a greater level of conformational freedom when compared to traditional monolayer chemistries. This greater range of motion and increased spacing between surface-bound molecules offers new opportunities in tailoring adsorption phenomena in sensing systems. In particular, we expect low-density surfaces to offer a unique opportunity to intercalate surface bound ligands into the secondary structure of protiens and other macromolecules. Additionally, as many conventional sensing surfaces are built upon gold surfaces (SPR or QCM), these surfaces must be compatible with gold substrates. Here, we present the first stable method of generating low-density self assembled monolayer surfaces on gold for the analysis of their interactions with protein targets. Our approach is based on the 2:1 addition of thiol-yne chemistry to develop new classes of y-shaped adsorbates on gold, where the environment-interfacing group is spaced laterally from neighboring chemical groups. This technique involves an initial deposition of a crystalline monolayer of 1,10 decanedithiol on the gold substrate, followed by grafting of a low-packed monolayer on through a photoinitiated thiol-yne reaction in presence of light. Orthogonality of the thiol-yne chemistry (commonly referred to as a click chemistry) allows for preparation of low-density monolayers with variety of functional groups. To date, carboxyl, amine, alcohol, and alkyl terminated monolayers have been prepared using this core technology. Results from surface characterization techniques such as FTIR, contact angle goniometry and electrochemical impedance spectroscopy confirm the proposed low chain-chain interactions of the environment interfacing groups. Reductive desorption measurements suggest a higher stability for the click-LDMs compared to traditional SAMs, along with the equivalent packing density at the substrate interface, which confirms the proposed stability of the monolayer-gold interface. In addition, contact angle measurements change in the presence of an applied potential, supporting our description of a surface structure which allows the alkyl chains to freely orient themselves in response to different environments. We are studying the differences in protein adsorption phenomena between well packed and our loosely packed surfaces, and we expect this data will be ready to present at the GRC meeting. This work aims to contribute biotechnology science in the following manner: Molecularly imprinted polymers are a promising recognition mode with several advantages over natural antibodies in the recognition of small molecules. However, because of their bulk polymer structure, they are poorly suited for the rapid diffusion desired for recognition of proteins and other macromolecules. Molecularly imprinted monolayers are an emerging class of materials where the surface is imprinted, and there is not a bulk material to impede mass transfer. Further, the short distance between the binding site and the signal transduction material improves many modes of detection. My dissertation project is to develop a new chemistry for protein-imprinted self-assembled monolayers on gold, for incorporation into SPR sensors. Our unique contribution is the spatial imprinting of not only physical cues (seen in current imprinted monolayer techniques), but to also incorporate complementary chemical cues. This is accomplished through a photo-click grafting of preassembled ligands around a protein template. This conference is important for my development as a graduate student to broaden my appreciation of the sensor development beyond surface chemistry.

Keywords: low-density self-assembled monolayers, thiol-yne click reaction, molecular imprinting

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21 Critical Factors for Successful Adoption of Land Value Capture Mechanisms – An Exploratory Study Applied to Indian Metro Rail Context

Authors: Anjula Negi, Sanjay Gupta

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Paradigms studied inform inadequacies of financial resources, be it to finance metro rails for construction or to meet operational revenues or to derive profits in the long term. Funding sustainability is far and wide for much-needed public transport modes, like urban rail or metro rails, to be successfully operated. India embarks upon a sustainable transport journey and has proposed metro rail systems countrywide. As an emerging economic leader, its fiscal constraints are paramount, and the land value capture (LVC) mechanism provides necessary support and innovation toward development. India’s metro rail policy promotes multiple methods of financing, including private-sector investments and public-private-partnership. The critical question that remains to be addressed is what factors can make such mechanisms work. Globally, urban rail is a revolution noted by many researchers as future mobility. Researchers in this study deep dive by way of literature review and empirical assessments into factors that can lead to the adoption of LVC mechanisms. It is understood that the adoption of LVC methods is in the nascent stages in India. Research posits numerous challenges being faced by metro rail agencies in raising funding and for incremental value capture. A few issues pertaining to land-based financing, inter alia: are long-term financing, inter-institutional coordination, economic/ market suitability, dedicated metro funds, land ownership issues, piecemeal approach to real estate development, property development legal frameworks, etc. The question under probe is what are the parameters that can lead to success in the adoption of land value capture (LVC) as a financing mechanism. This research provides insights into key parameters crucial to the adoption of LVC in the context of Indian metro rails. Researchers have studied current forms of LVC mechanisms at various metro rails of the country. This study is significant as little research is available on the adoption of LVC, which is applicable to the Indian context. Transit agencies, State Government, Urban Local Bodies, Policy makers and think tanks, Academia, Developers, Funders, Researchers and Multi-lateral agencies may benefit from this research to take ahead LVC mechanisms in practice. The study deems it imperative to explore and understand key parameters that impact the adoption of LVC. Extensive literature review and ratification by experts working in the metro rails arena were undertaken to arrive at parameters for the study. Stakeholder consultations in the exploratory factor analysis (EFA) process were undertaken for principal component extraction. 43 seasoned and specialized experts participated in a semi-structured questionnaire to scale the maximum likelihood on each parameter, represented by various types of stakeholders. Empirical data was collected on chosen eighteen parameters, and significant correlation was extracted for output descriptives and inferential statistics. Study findings reveal these principal components as institutional governance framework, spatial planning features, legal frameworks, funding sustainability features and fiscal policy measures. In particular, funding sustainability features highlight sub-variables of beneficiaries to pay and use of multiple revenue options towards success in LVC adoption. Researchers recommend incorporation of these variables during early stage in design and project structuring for success in adoption of LVC. In turn leading to improvements in revenue sustainability of a public transport asset and help in undertaking informed transport policy decisions.

Keywords: Exploratory factor analysis, land value capture mechanism, financing metro rails, revenue sustainability, transport policy

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20 XAI Implemented Prognostic Framework: Condition Monitoring and Alert System Based on RUL and Sensory Data

Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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Accurate estimation of RUL provides a basis for effective predictive maintenance, reducing unexpected downtime for industrial equipment. However, while models such as the Random Forest have effective predictive capabilities, they are the so-called ‘black box’ models, where interpretability is at a threshold to make critical diagnostic decisions involved in industries related to aviation. The purpose of this work is to present a prognostic framework that embeds Explainable Artificial Intelligence (XAI) techniques in order to provide essential transparency in Machine Learning methods' decision-making mechanisms based on sensor data, with the objective of procuring actionable insights for the aviation industry. Sensor readings have been gathered from critical equipment such as turbofan jet engine and landing gear, and the prediction of the RUL is done by a Random Forest model. It involves steps such as data gathering, feature engineering, model training, and evaluation. These critical components’ datasets are independently trained and evaluated by the models. While suitable predictions are served, their performance metrics are reasonably good; such complex models, however obscure reasoning for the predictions made by them and may even undermine the confidence of the decision-maker or the maintenance teams. This is followed by global explanations using SHAP and local explanations using LIME in the second phase to bridge the gap in reliability within industrial contexts. These tools analyze model decisions, highlighting feature importance and explaining how each input variable affects the output. This dual approach offers a general comprehension of the overall model behavior and detailed insight into specific predictions. The proposed framework, in its third component, incorporates the techniques of causal analysis in the form of Granger causality tests in order to move beyond correlation toward causation. This will not only allow the model to predict failures but also present reasons, from the key sensor features linked to possible failure mechanisms to relevant personnel. The causality between sensor behaviors and equipment failures creates much value for maintenance teams due to better root cause identification and effective preventive measures. This step contributes to the system being more explainable. Surrogate Several simple models, including Decision Trees and Linear Models, can be used in yet another stage to approximately represent the complex Random Forest model. These simpler models act as backups, replicating important jobs of the original model's behavior. If the feature explanations obtained from the surrogate model are cross-validated with the primary model, the insights derived would be more reliable and provide an intuitive sense of how the input variables affect the predictions. We then create an iterative explainable feedback loop, where the knowledge learned from the explainability methods feeds back into the training of the models. This feeds into a cycle of continuous improvement both in model accuracy and interpretability over time. By systematically integrating new findings, the model is expected to adapt to changed conditions and further develop its prognosis capability. These components are then presented to the decision-makers through the development of a fully transparent condition monitoring and alert system. The system provides a holistic tool for maintenance operations by leveraging RUL predictions, feature importance scores, persistent sensor threshold values, and autonomous alert mechanisms. Since the system will provide explanations for the predictions given, along with active alerts, the maintenance personnel can make informed decisions on their end regarding correct interventions to extend the life of the critical machinery.

Keywords: predictive maintenance, explainable artificial intelligence, prognostic, RUL, machine learning, turbofan engines, C-MAPSS dataset

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19 PsyVBot: Chatbot for Accurate Depression Diagnosis using Long Short-Term Memory and NLP

Authors: Thaveesha Dheerasekera, Dileeka Sandamali Alwis

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

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

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18 Harnessing the Power of Artificial Intelligence: Advancements and Ethical Considerations in Psychological and Behavioral Sciences

Authors: Nayer Mofidtabatabaei

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

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

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17 A Case Report on the Course and Outcome of a Patient Diagnosed with Trichotillomania and Major Depressive Disorder

Authors: Ziara Carmelli G. Tan, Irene Carmelle S. Tan

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Background: Trichotillomania (TTM) and Major Depressive Disorder (MDD) are two psychiatric conditions that frequently co-occur, presenting a significant challenge for treatment due to their complex interplay. TTM involves repetitive hair-pulling, leading to noticeable hair loss and distress, while MDD is characterized by persistent low mood and loss of interest or pleasure, leading to dysfunctionality. This case report examines the intricate relationship between TTM and MDD in a young adult female, emphasizing the need for a comprehensive, multifaceted therapeutic approach to address both disorders effectively. Case Presentation: The patient is a 21-year-old female college student and youth church leader who presented with chronic hair-pulling and depressive symptoms. Her premorbid personality was marked by low self-esteem and a strong need for external validation. Despite her academic and social responsibilities and achievements, she struggled with managing her emotional distress, which was exacerbated by her family dynamics and her role within her church community. Her hair-pulling and mood symptoms were particularly triggered by self-esteem threats and feelings of inadequacy. She was diagnosed with Trichotillomania, Scalp and Major Depressive Disorder. Intervention/Management: The patient’s treatment plan was comprehensive, incorporating both pharmacological and non-pharmacological interventions. Initial pharmacologic management was Fluoxetine 20mg/day up, titrated to 40mg/day with no improvement; hence, shifted to Escitalopram 20mg/day and started with N-acetylcysteine 600mg/day with noted significant improvement in symptoms. Psychotherapeutic strategies played a crucial role in her treatment. These included supportive-expressive psychodynamic psychotherapy, which helped her explore and understand underlying emotional conflicts. Cognitive-behavioral techniques were employed to modify her maladaptive thoughts and behaviors. Grief processing was integrated to help her cope with significant losses. Family therapy was done to address conflicts and collaborate with the treatment process. Psychoeducation was provided to enhance her understanding of her condition and to empower her in her treatment journey. A suicide safety plan was developed to ensure her safety during critical periods. An interprofessional approach, which involved coordination with the Dermatology service for co-management, was also a key component of her treatment. Outcome: Over the course of 15 therapy sessions, the patient demonstrated significant improvement in both her depressive symptoms and hair-pulling behavior. Her active engagement in therapy, combined with pharmacological support, facilitated better emotional regulation and a more cohesive sense of self. Her adherence to the treatment plan, along with the collaborative efforts of the interprofessional team, contributed to her positive outcomes. Discussion: This case underscores the significance of addressing both TTM and its comorbid conditions to achieve effective treatment outcomes. The intricate interplay between TTM and MDD in the patient’s case highlights the importance of a comprehensive treatment plan that includes both pharmacological and psychotherapeutic approaches. Supportive-expressive psychodynamic psychotherapy, Cognitive-behavioral techniques, and Family therapy were particularly beneficial in addressing the complex emotional and behavioral aspects of her condition. The involvement of an interprofessional team, including dermatology co-management, was crucial in providing holistic care. Future practice should consider the benefits of such a multidisciplinary approach to managing complex cases like this, ensuring that both the psychological and physiological aspects of the disorders are adequately addressed.

Keywords: cognitive-behavioral therapy, interprofessional approach, major depressive disorder, psychodynamic psychotherapy, trichotillomania

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16 Consecration from the Margins: El Anatsui in Venice and the Turbine Hall

Authors: Jonathan Adeyemi

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Context: This study focuses on El Anatsui and his global acclaim in the art world despite his origins from the global artworld’s margins. It addresses the disparities in the treatment between Western and non-Western artists and questions whether Anatsui’s consecration is a result of exoticism or the growing consensus on decolonization. Research Aim: The aim of this study is to investigate how El Anatsui achieved global acclaim from the margins of the art world and determine if his consecration represents a mark of decolonization or the typical Western desire for exoticism. Methodology: The study utilizes a case study approach, literature analysis, and in-depth interviews. The artist, the organizers of the Venice Biennale, the relevant curators at Tate Modern London, and the October Gallery in London, and other galleries in Nigeria, which represent the artist were interviewed for data collection. Findings: The study seeks to determine the authenticity of the growing consensus on decolonization, inclusion, and diversity in the global artistic field. Preliminary findings show that domestic socio-economic and political factors debilitated the mechanisms for local validation in Nigeria, weakening the domestic foundation for international engagement. However, alternative systems of exhibition, especially in London and the USA contributed critically to providing the initial international visibility, which formed the foundation for his global acclaim. Out of the 21 winners of the Golden Lion for Lifetime Achievement since its inception at the 47th Venice Biennale in 1997, American artists have dominated with 10 recipients, 8 recipients from Europe, 2 recipients from Africa (2007 and 2015) and 1 from Asia. This aligns with Bourdieu’s concept of cultural and economic capital, which prevented Africa countries from participation until recently. Moreover, while the average age of recipients is 76 years, Anatsui received the award at the age of 71, while Malick Sidibé (Mali) was awarded at 72. Thus, the Venice Biennale award for El Anatsui incline more towards a commitment to decolonisation than exoticism. Theoretical Importance: This study contributes to the field by examining the dynamics of the art world's monopoly of legitimation and the role of national, ethnicity and cultural differences in the promotion of artists. It aims to challenge the Westernized hierarchy of valorization and consecration in the art world. The research supports Bourdieu’s artistic field theory, which emphasises the importance of cultural, economic and social capital in determining agents’ position and access to the field resources (symbolic capital). Bourdieu also established that dominated agents can change their position in the field’s hierarchy either by establishing or navigating alternative systems. Data Collection and Analysis Procedures: The opacity of art world’s operations places the required information within the purview of the insiders (agents). Thus, the study collects data through in-depth interviews with relevant and purposively selected individuals and organizations. The data was/will be analyzed using qualitative methods, such as thematic analysis and content analysis. The interpretive analytical approach adopted facilitated the construction of meanings that may not be apparent in the data or responses. Questions Addressed: The study addresses how El Anatsui achieved global acclaim despite being from the margins, whether his consecration represents decolonization or exoticism, and the extent to which the global artistic field embraces decolonization, inclusion, and diversity. Conclusion: The study will contribute to knowledge by providing insights into the extent of commitment to decolonization, inclusion, and diversity in the global artistic field. It also shed light on the mechanisms behind El Anatsui's rise to global acclaim and challenge Western-dominated artistic hierarchies.

Keywords: decolonisation, exorticism, artistic field, culture game

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15 Socio-Sensorial Assessment of Nursing Homes in Singapore: Towards Integrated Enabling Design

Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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14 Saving Lives from a Laptop: How to Produce a Live Virtual Media Briefing That Will Inform, Educate, and Protect Communities in Crisis

Authors: Cory B. Portner, Julie A. Grauert, Lisa M. Stromme, Shelby D. Anderson, Franji H. Mayes

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Introduction: WASHINGTON state in the Pacific Northwest of the United States is internationally known for its technology industry, fisheries, agriculture, and vistas. On January 21, 2020, Washington state also became known as the first state with a confirmed COVID-19 case in the United States, thrusting the state into the international spotlight as the world came to grips with the global threat of this disease presented. Tourism is Washington state’s fourth-largest industry. Tourism to the state generates over 1.8 billion dollars (USD) in local and state tax revenue and employs over 180,000 people. Communicating with residents, stakeholders, and visitors on the status of disease activity, prevention measures, and response updates was vital to stopping the pandemic and increasing compliance and awareness. Significance: In order to communicate vital public health updates, guidance implementation, and safety measures to the public, the Washington State Department of Health established routine live virtual media briefings to reach audiences via social media, internet television, and broadcast television. Through close partnership with regional broadcast news stations and the state public affairs news network, the Washington State Department of Health hosted 95 media briefings from January 2020 through September 2022 and continues to regularly host live virtual media briefings to accommodate the needs of the public and media. Methods: Our methods quickly evolved from hosting briefings in the cement closet of a military base to being able to produce and stream the briefings live from any home-office location. The content was tailored to the hot topic of the day and to the reporter's questions and needs. Virtual media briefings hosted through inexpensive or free platforms online are extremely cost-effective: the only mandatory components are WiFi, a laptop, and a monitor. There is no longer a need for a fancy studio or expensive production software to achieve the goal of communicating credible, reliable information promptly. With minimal investment and a small learning curve, facilitators and panelists are able to host highly produced and engaging media availabilities from their living rooms. Results: The briefings quickly developed a reputation as the best source for local and national journalists to get the latest and most factually accurate information about the pandemic. In the height of the COVID-19 response, 135 unique media outlets logged on to participate in the briefing. The briefings typically featured 4-5 panelists, with as many as 9 experts in attendance to provide information and respond to media questions. Preparation was always a priority: Public Affairs staff for the Washington State Department of Health produced over 170 presenter remarks, including guidance on talking points for 63 expert guest panelists. Implication For Practice: Information is today’s most valuable currency. The ability to disseminate correct information urgently and on a wide scale is the most effective tool in crisis communication. Due to our role as the first state with a confirmed COVID-19 case, we were forced to develop the most accurate and effective way to get life-saving information to the public. The cost-effective, web-based methods we developed can be applied in any crisis to educate and protect communities under threat, ultimately saving lives from a laptop.

Keywords: crisis communications, public relations, media management, news media

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13 Surface Acoustic Wave (SAW)-Induced Mixing Enhances Biomolecules Kinetics in a Novel Phase-Interrogation Surface Plasmon Resonance (SPR) Microfluidic Biosensor

Authors: M. Agostini, A. Sonato, G. Greco, M. Travagliati, G. Ruffato, E. Gazzola, D. Liuni, F. Romanato, M. Cecchini

Abstract:

Since their first demonstration in the early 1980s, surface plasmon resonance (SPR) sensors have been widely recognized as useful tools for detecting chemical and biological species, and the interest of the scientific community toward this technology has known a rapid growth in the past two decades owing to their high sensitivity, label-free operation and possibility of real-time detection. Recent works have suggested that a turning point in SPR sensor research would be the combination of SPR strategies with other technologies in order to reduce human handling of samples, improve integration and plasmonic sensitivity. In this light, microfluidics has been attracting growing interest. By properly designing microfluidic biochips it is possible to miniaturize the analyte-sensitive areas with an overall reduction of the chip dimension, reduce the liquid reagents and sample volume, improve automation, and increase the number of experiments in a single biochip by multiplexing approaches. However, as the fluidic channel dimensions approach the micron scale, laminar flows become dominant owing to the low Reynolds numbers that typically characterize microfluidics. In these environments mixing times are usually dominated by diffusion, which can be prohibitively long and lead to long-lasting biochemistry experiments. An elegant method to overcome these issues is to actively perturb the liquid laminar flow by exploiting surface acoustic waves (SAWs). With this work, we demonstrate a new approach for SPR biosensing based on the combination of microfluidics, SAW-induced mixing and the real-time phase-interrogation grating-coupling SPR technology. On a single lithium niobate (LN) substrate the nanostructured SPR sensing areas, interdigital transducer (IDT) for SAW generation and polydimethylsiloxane (PDMS) microfluidic chambers were fabricated. SAWs, impinging on the microfluidic chamber, generate acoustic streaming inside the fluid, leading to chaotic advection and thus improved fluid mixing, whilst analytes binding detection is made via SPR method based on SPP excitation via gold metallic grating upon azimuthal orientation and phase interrogation. Our device has been fully characterized in order to separate for the very first time the unwanted SAW heating effect with respect to the fluid stirring inside the microchamber that affect the molecules binding dynamics. Avidin/biotin assay and thiol-polyethylene glycol (bPEG-SH) were exploited as model biological interaction and non-fouling layer respectively. Biosensing kinetics time reduction with SAW-enhanced mixing resulted in a ≈ 82% improvement for bPEG-SH adsorption onto gold and ≈ 24% for avidin/biotin binding—≈ 50% and 18% respectively compared to the heating only condition. These results demonstrate that our biochip can significantly reduce the duration of bioreactions that usually require long times (e.g., PEG-based sensing layer, low concentration analyte detection). The sensing architecture here proposed represents a new promising technology satisfying the major biosensing requirements: scalability and high throughput capabilities. The detection system size and biochip dimension could be further reduced and integrated; in addition, the possibility of reducing biological experiment duration via SAW-driven active mixing and developing multiplexing platforms for parallel real-time sensing could be easily combined. In general, the technology reported in this study can be straightforwardly adapted to a great number of biological system and sensing geometry.

Keywords: biosensor, microfluidics, surface acoustic wave, surface plasmon resonance

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12 Regenerative Agriculture Standing at the Intersection of Design, Mycology, and Soil Fertility

Authors: Andrew Gennett

Abstract:

Designing for fungal development means embracing the symbiotic relationship between the living system and built environment. The potential of mycelium post-colonization is explored for the fabrication of advanced pure mycelium products, going beyond the conventional methods of aggregating materials. Fruiting induction imparts desired material properties such as enhanced environmental resistance. Production approach allows for simultaneous generation of multiple products while scaling up raw materials supply suitable for architectural applications. The following work explores the integration of fungal environmental perception with computational design of built fruiting chambers. Polyporales, are classified by their porous reproductive tissues supported by a wood-like context tissue covered by a hard waterproofing coat of hydrobpobins. Persisting for years in the wild, these species represent material properties that would be highly desired in moving beyond flat sheets of arial mycelium as with leather or bacon applications. Understanding the inherent environmental perception of fungi has become the basis for working with and inducing desired hyphal differentiation. Working within the native signal interpretation of a mycelium mass during fruiting induction provides the means to apply textures and color to the final finishing coat. A delicate interplay between meeting human-centered goals while designing around natural processes of living systems represents a blend of art and science. Architecturally, physical simulations inform model design for simple modular fruiting chambers that change as fungal growth progresses, while biological life science principles describe the internal computations occurring within the fungal hyphae. First, a form filling phase of growth is controlled by growth chamber environment. Second, an initiation phase of growth forms the final exterior finishing texture. Hyphal densification induces cellular cascades, in turn producing the classical hardened cuticle, UV protective molecule production, as well, as waterproofing finish. Upon fruiting process completion, the fully colonized spent substrate holds considerable value and is not considered waste. Instead, it becomes a valuable resource in the next cycle of production scale-up. However, the acquisition of new substrate resources poses a critical question, particularly as these resources become increasingly scarce. Pursuing a regenerative design paradigm from the environmental perspective, the usage of “agricultural waste” for architectural materials would prove a continuation of the destructive practices established by the previous industrial regime. For these residues from fields and forests serve a vital ecological role protecting the soil surface in combating erosion while reducing evaporation and fostering a biologically diverse food web. Instead, urban centers have been identified as abundant sources of new substrate material. Diverting the waste from secondary locations such as food processing centers, papers mills, and recycling facilities not only reduces landfill burden but leverages the latent value of these waste steams as precious resources for mycelium cultivation. In conclusion, working with living systems through innovative built environments for fungal development, provides the needed gain of function and resilience of mycelium products. The next generation of sustainable fungal products will go beyond the current binding process, with a focus upon reducing landfill burden from urban centers. In final considerations, biophilic material builds to an ecologically regenerative recycling production cycle.

Keywords: regenerative agriculture, mycelium fabrication, growth chamber design, sustainable resource acquisition, fungal morphogenesis, soil fertility

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11 An Intelligent Search and Retrieval System for Mining Clinical Data Repositories Based on Computational Imaging Markers and Genomic Expression Signatures for Investigative Research and Decision Support

Authors: David J. Foran, Nhan Do, Samuel Ajjarapu, Wenjin Chen, Tahsin Kurc, Joel H. Saltz

Abstract:

The large-scale data and computational requirements of investigators throughout the clinical and research communities demand an informatics infrastructure that supports both existing and new investigative and translational projects in a robust, secure environment. In some subspecialties of medicine and research, the capacity to generate data has outpaced the methods and technology used to aggregate, organize, access, and reliably retrieve this information. Leading health care centers now recognize the utility of establishing an enterprise-wide, clinical data warehouse. The primary benefits that can be realized through such efforts include cost savings, efficient tracking of outcomes, advanced clinical decision support, improved prognostic accuracy, and more reliable clinical trials matching. The overarching objective of the work presented here is the development and implementation of a flexible Intelligent Retrieval and Interrogation System (IRIS) that exploits the combined use of computational imaging, genomics, and data-mining capabilities to facilitate clinical assessments and translational research in oncology. The proposed System includes a multi-modal, Clinical & Research Data Warehouse (CRDW) that is tightly integrated with a suite of computational and machine-learning tools to provide insight into the underlying tumor characteristics that are not be apparent by human inspection alone. A key distinguishing feature of the System is a configurable Extract, Transform and Load (ETL) interface that enables it to adapt to different clinical and research data environments. This project is motivated by the growing emphasis on establishing Learning Health Systems in which cyclical hypothesis generation and evidence evaluation become integral to improving the quality of patient care. To facilitate iterative prototyping and optimization of the algorithms and workflows for the System, the team has already implemented a fully functional Warehouse that can reliably aggregate information originating from multiple data sources including EHR’s, Clinical Trial Management Systems, Tumor Registries, Biospecimen Repositories, Radiology PAC systems, Digital Pathology archives, Unstructured Clinical Documents, and Next Generation Sequencing services. The System enables physicians to systematically mine and review the molecular, genomic, image-based, and correlated clinical information about patient tumors individually or as part of large cohorts to identify patterns that may influence treatment decisions and outcomes. The CRDW core system has facilitated peer-reviewed publications and funded projects, including an NIH-sponsored collaboration to enhance the cancer registries in Georgia, Kentucky, New Jersey, and New York, with machine-learning based classifications and quantitative pathomics, feature sets. The CRDW has also resulted in a collaboration with the Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) at the U.S. Department of Veterans Affairs to develop algorithms and workflows to automate the analysis of lung adenocarcinoma. Those studies showed that combining computational nuclear signatures with traditional WHO criteria through the use of deep convolutional neural networks (CNNs) led to improved discrimination among tumor growth patterns. The team has also leveraged the Warehouse to support studies to investigate the potential of utilizing a combination of genomic and computational imaging signatures to characterize prostate cancer. The results of those studies show that integrating image biomarkers with genomic pathway scores is more strongly correlated with disease recurrence than using standard clinical markers.

Keywords: clinical data warehouse, decision support, data-mining, intelligent databases, machine-learning.

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10 From Linear to Circular Model: An Artificial Intelligence-Powered Approach in Fosso Imperatore

Authors: Carlotta D’Alessandro, Giuseppe Ioppolo, Katarzyna Szopik-Depczyńska

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— The growing scarcity of resources and the mounting pressures of climate change, water pollution, and chemical contamination have prompted societies, governments, and businesses to seek ways to minimize their environmental impact. To combat climate change, and foster sustainability, Industrial Symbiosis (IS) offers a powerful approach, facilitating the shift toward a circular economic model. IS has gained prominence in the European Union's policy framework as crucial enabler of resource efficiency and circular economy practices. The essence of IS lies in the collaborative sharing of resources such as energy, material by-products, waste, and water, thanks to geographic proximity. It can be exemplified by eco-industrial parks (EIPs), which are natural environments for boosting cooperation and resource sharing between businesses. EIPs are characterized by group of businesses situated in proximity, connected by a network of both cooperative and competitive interactions. They represent a sustainable industrial model aimed at reducing resource use, waste, and environmental impact while fostering economic and social wellbeing. IS, combined with Artificial Intelligence (AI)-driven technologies, can further optimize resource sharing and efficiency within EIPs. This research, supported by the “CE_IPs” project, aims to analyze the potential for IS and AI, in advancing circularity and sustainability at Fosso Imperatore. The Fosso Imperatore Industrial Park in Nocera Inferiore, Italy, specializes in agriculture and the industrial transformation of agricultural products, particularly tomatoes, tobacco, and textile fibers. This unique industrial cluster, centered around tomato cultivation and processing, also includes mechanical engineering enterprises and agricultural packaging firms. To stimulate the shift from a traditional to a circular economic model, an AI-powered Local Development Plan (LDP) is developed for Fosso Imperatore. It can leverage data analytics, predictive modeling, and stakeholder engagement to optimize resource utilization, reduce waste, and promote sustainable industrial practices. A comprehensive SWOT analysis of the AI-powered LDP revealed several key factors influencing its potential success and challenges. Among the notable strengths and opportunities arising from AI implementation are reduced processing times, fewer human errors, and increased revenue generation. Furthermore, predictive analytics minimize downtime, bolster productivity, and elevate quality while mitigating workplace hazards. However, the integration of AI also presents potential weaknesses and threats, including significant financial investment, since implementing and maintaining AI systems can be costly. The widespread adoption of AI could lead to job losses in certain sectors. Lastly, AI systems are susceptible to cyberattacks, posing risks to data security and operational continuity. Moreover, an Analytic Hierarchy Process (AHP) analysis was employed to yield a prioritized ranking of the outlined AI-driven LDP practices based on the stakeholder input, ensuring a more comprehensive and representative understanding of their relative significance for achieving sustainability in Fosso Imperatore Industrial Park. While this study provides valuable insights into the potential of AIpowered LDP at the Fosso Imperatore, it is important to note that the findings may not be directly applicable to all industrial parks, particularly those with different sizes, geographic locations, or industry compositions. Additional study is necessary to scrutinize the generalizability of these results and to identify best practices for implementing AI-driven LDP in diverse contexts.

Keywords: artificial intelligence, climate change, Fosso Imperatore, industrial park, industrial symbiosis

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9 Effect of Varied Climate, Landuse and Human Activities on the Termite (Isoptera: Insecta) Diversity in Three Different Habitats of Shivamogga District, Karnataka, India

Authors: C. M. Kalleshwaraswamy, G. S. Sathisha, A. S. Vidyashree, H. B. Pavithra

Abstract:

Isoptera are an interesting group of social insects with different castes and division of labour. They are primarily wood-feeders, but also feed on a variety of other organic substrates, such as living trees, leaf litter, soil, lichens and animal faeces. The number of species and their biomass are especially large in tropics. In natural ecosystems, they perform a beneficial role in nutrient cycles by accelerating decomposition. The magnitude and dimension of ecological role played by termites is a function of their diversity, population density, and biomass. Termite assemblage composition has a strong response to habitat disturbance and may be indicative of quantitative changes in the decomposition process. Many previous studies in Western Ghat region of India suggest increased anthropogenic activities that adversely affect the soil macrofauna and diversity. Shivamogga district provides a good opportunity to study the effect of topography, cropping pattern, human disturbance on the termite fauna, thereby acquiring accurate baseline information for conservation decision making. The district has 3 distinct agro-ecological areas such as maidan area, semi-malnad and Western Ghat region. Thus, the district provides a unique opportunity to study the effect of varied climate and anthropogenic disturbance on the termite diversity. The standard protocol of belt transects method developed by Eggleton et al. (1997) was used for sampling termites. Sampling was done at monthly interval from September-2014 to August-2015 in Western Ghats, semi-malnad and maidan habitats. The transect was 100m long and 2m wide and divided into 20 contiguous sections, each 5 x 2m in each habitat. Within each section, all the probable microhabitats of termites were searched, which include dead logs, fallen tree, branch, sticks, leaf litter, vegetation etc.,. All the castes collected were labelled, preserved in 80% alcohol, counted and identified to species level. The number of encounters of a species in the transect was used as an indicator of relative abundance of species. The species diversity, species richness, density were compared in three different habitats such as Western Ghats, semi-malnad and maidan region. The study indicated differences in the species composition in the three different habitats. A total of 15 species were recorded which belonging to four sub family and five genera in three habitats. Eleven species viz., Odontotermes obesus, O. feae, O. anamallensis, O. bellahunisensis, O. adampurensis, O. boveni, Microcerotermes fletcheri, M. pakistanicus, Nasutitermes anamalaiensis, N. indicola, N. krishna were recorded in Western Ghat region. Similarly, 11 species viz., Odontotermes obesus, O. feae, O. anamallensis, O. bellahunisensis, O. hornii, O. bhagwathi, Microtermes obesi, Microcerotermes fletcheri, M. pakistanicus, Nasutitermes indicola and Pericapritermes sp. were recorded in semi-malnad habitat. However, only four species viz., O. obesus, O. feae, Microtemes obesi and Pericapritermes sp. species were recorded in maidan area. Shannon’s wiener diversity index (H) showed that Western Ghats had more species dominance (1.56) followed by semi- malnad (1.36) and lowest in maidan (0.89) habitats. Highest value of simpson’s index (D) was observed in Western Ghats habitat (0.70) with more diverse species followed by semi-malnad (0.58) and lowest in maidan (0.53). Similarly, evenness was highest (0.65) in Western Ghats followed by maidan (0.64) and least in semi-malnad habitat (0.54). Menhinick’s index (Dmn) value was ranging from 0.03 to 0.06 in different habitats in the study area. Highest index was observed in Western Ghats (0.06) followed by semi-malnad (0.05) and lowest in maidan (0.03). The study conclusively demonstrated that Western Ghat had highest species diversity compared to semi-malnad and maidan habitat indicating these two habitats are continuously subjected to anthropogenic disturbances. Efforts are needed to conserve the uncommon species which otherwise may become extinct due to human activities.

Keywords: anthropogenic disturbance, isoptera, termite species diversity, Western ghats

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8 Blockchain Based Hydrogen Market (BBH₂): A Paradigm-Shifting Innovative Solution for Climate-Friendly and Sustainable Structural Change

Authors: Volker Wannack

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Regional, national, and international strategies focusing on hydrogen (H₂) and blockchain are driving significant advancements in hydrogen and blockchain technology worldwide. These strategies lay the foundation for the groundbreaking "Blockchain Based Hydrogen Market (BBH₂)" project. The primary goal of this project is to develop a functional Blockchain Minimum Viable Product (B-MVP) for the hydrogen market. The B-MVP will leverage blockchain as an enabling technology with a common database and platform, facilitating secure and automated transactions through smart contracts. This innovation will revolutionize logistics, trading, and transactions within the hydrogen market. The B-MVP has transformative potential across various sectors. It benefits renewable energy producers, surplus energy-based hydrogen producers, hydrogen transport and distribution grid operators, and hydrogen consumers. By implementing standardized, automated, and tamper-proof processes, the B-MVP enhances cost efficiency and enables transparent and traceable transactions. Its key objective is to establish the verifiable integrity of climate-friendly "green" hydrogen by tracing its supply chain from renewable energy producers to end users. This emphasis on transparency and accountability promotes economic, ecological, and social sustainability while fostering a secure and transparent market environment. A notable feature of the B-MVP is its cross-border operability, eliminating the need for country-specific data storage and expanding its global applicability. This flexibility not only broadens its reach but also creates opportunities for long-term job creation through the establishment of a dedicated blockchain operating company. By attracting skilled workers and supporting their training, the B-MVP strengthens the workforce in the growing hydrogen sector. Moreover, it drives the emergence of innovative business models that attract additional company establishments and startups and contributes to long-term job creation. For instance, data evaluation can be utilized to develop customized tariffs and provide demand-oriented network capacities to producers and network operators, benefitting redistributors and end customers with tamper-proof pricing options. The B-MVP not only brings technological and economic advancements but also enhances the visibility of national and international standard-setting efforts. Regions implementing the B-MVP become pioneers in climate-friendly, sustainable, and forward-thinking practices, generating interest beyond their geographic boundaries. Additionally, the B-MVP serves as a catalyst for research and development, facilitating knowledge transfer between universities and companies. This collaborative environment fosters scientific progress, aligns with strategic innovation management, and cultivates an innovation culture within the hydrogen market. Through the integration of blockchain and hydrogen technologies, the B-MVP promotes holistic innovation and contributes to a sustainable future in the hydrogen industry. The implementation process involves evaluating and mapping suitable blockchain technology and architecture, developing and implementing the blockchain, smart contracts, and depositing certificates of origin. It also includes creating interfaces to existing systems such as nomination, portfolio management, trading, and billing systems, testing the scalability of the B-MVP to other markets and user groups, developing data formats for process-relevant data exchange, and conducting field studies to validate the B-MVP. BBH₂ is part of the "Technology Offensive Hydrogen" funding call within the research funding of the Federal Ministry of Economics and Climate Protection in the 7th Energy Research Programme of the Federal Government.

Keywords: hydrogen, blockchain, sustainability, innovation, structural change

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7 Maternity Care Model during Natural Disaster or Humanitarian Emegerncy Setting in Rural Pakistan

Authors: Humaira Maheen, Elizabeth Hoban, Catherine Bennette

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Background: Globally, role of Community Health Workers (CHW) as front line disaster health work force is underutilized. Developing countries which are at risk of natural disasters or humanitarian emergencies should lay down effective strategies especially to ensure adequate access to maternity care during crisis situation by using CHW as they are local, trained, and most of them possess a good relationship with the community. The Minimum Initial Service Package (MISP) is a set of universal guidelines that addresses women’s reproductive health needs during the first phase of an emergency. According to the MISP, pregnant women should have access to a skilled birth attendant and adequate transportation arrangements so they can access a maternity care facility. Pakistan is one of the few countries which has been severely affected by a number of natural disaster as well as humanitarian emergencies in last decade. Pakistan has a young and structured National Disaster Management System in place, where District Authorities play a vital role in disaster management. The District Health Department develops the contingency health plan for an emergency situation and implements it under the existing district health human resources (health workers and medical staff at the health facility) and infrastructure (health care facilities). Methods: A mixed methods study was conducted in rural villages of Sindh adjacent to the river Indus, and included in-depth interviews with 15 women who gave birth during the floods, structured interviews with 668 women who were pregnant during 2010-2014, and in-depth interviews with 25 community health workers (CHW) and 30 key informants. Results: Women said that giving birth in the relief camps during the floods was one of the most challenging times of their life. The district health department didn’t make transportation arrangement for labouring women from relief camp to the nearest health care facility. As a result 91.2% women gave birth in temporary shelters with the help of a traditional birth attendant (Dai) with no clean physical space available to birth. Of the 332 women who were pregnant at the time of the floods, 26 had adverse birth outcomes; 10 had miscarriages, 14 had stillbirths and there were four neonatal deaths. Conclusion: The district health department was not able to provide access to adequate maternity care during according to the international standard during the floods in 2011. We propose a model where CHWs will be used as frontline maternity care providers during any emergency or disaster situations in Pakistan. A separate "birthing station" should be mandatory in all district relief camps, managed by CHWs. Community midwives (CMW) would and the Lady Health Workers (LHW) would provide antenatal and postnatal care alongside, vaccination for pregnant women, neonates and children under five. There must be an ambulance facility for emergency obstetric cases and all district health facilities should have at least two medical staff identified and trained for emergency obstetric management. The District Health Department must provide clean birthing kits and regular and emergency contraceptives in the relief camps. Methods: A mixed methods study was conducted in rural villages of Sindh adjacent to the river Indus, and included in-depth interviews with 15 women who gave birth during the floods, structured interviews with 668 women who were pregnant during 2010-2014, and in-depth interviews with 25 community health workers (CHW) and 30 key informants. Results: Women said that giving birth in the relief camps during the floods was one of the most challenging times of their life. Nearly 91.2% women gave birth in temporary shelters with the help of a traditional birth attendant (Dai) with no clean physical space available to birth, and the health camp was mostly accessed by men and always overcrowded. There was no obstetric trained medical staff in the health camps or transportation provided to take women with complications to the nearest health facility. The rate of adverse outcome following disaster was 22.2% (95% CI: 8.62% – 42.2%) amongst 27 women who did not evacuate as compare to 7.91% (95% CI: 5.03% – 11.8%) among 278 women who lived in relief camp study participants. There were 27 women who evacuated on pre-flood warning and had 0% rate of adverse outcome. Conclusion: We propose a model where CHWs will be used as frontline maternity care providers during any emergency or disaster situations in Pakistan. A separate "birthing station" should be mandatory in all district relief camps, managed by CHWs. Community midwives (CMW) would and the Lady Health Workers (LHW) would provide antenatal and postnatal care alongside, vaccination for pregnant women, neonates and children under five. There must be an ambulance facility for emergency obstetric cases and all district health facilities should have at least two medical staff identified and trained for emergency obstetric management. The District Health Department must provide clean birthing kits and regular and emergency contraceptives in the relief camps.

Keywords: natural disaster, maternity care model, rural, Pakistan, community health workers

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6 From Core to Hydrocarbon: Reservoir Sedimentology, Facies Analysis and Depositional Model of Early Oligocene Mahuva Formation in Tapti Daman Block, Western Offshore Basin, India

Authors: Almas Rajguru

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The Oligocene succession of the Tapti- Daman area is one of the established petroleum plays in Tapti-Daman block of the Mumbai Offshore Basin. Despite good control and production history, the sand geometry and continuity of reservoir character of these sediments are less understood as most reservoirs are thin and fall below seismic resolution. The present work focuses on a detailed analysis of the Early Oligocene Mahuva Formation at the reservoir scale through laboratory studies (sedimentology and biostratigraphy) of core and sidewall cores in integration with electro logs for firming up facies’ distribution, micro-depositional environment and sequence stratigraphy, diagenesis and reservoir characterization from seventeen wells from North Tapti-C-37 area in Tapti Daman Block, WOB. The thick shale/claystone with thin interbeds of sandstone and siltstones of deeper marine in the lower part of Mahuva Fm represents deposition in a transgressive regime. The overlying interbedded sandstone, glauconitic-siltstone/fine-grained sandstone, and thin beds of packstone/grainstone within highly fissile shale were deposited in a prograding tide-dominated delta during late-rise normal regression. Nine litho facies (F1-F9) representing deposition in various microenvironments of the tide-dominated delta are identified based on their characteristic sediment texture, structure and microfacies. Massive, gritty sandstone (F1) with poorly sorted sands lithic fragments with calcareous and Fe-rich matrix represents channel fill sediments. High-angle cross-stratified sandstone (F2) deposited in rapidly shifting/migrating bars under strong tidal currents. F3 records the laterally accreted tidal-channel point bars. F3 (low-angle cross-stratified to parallel bedded sandstone) and F4 (Clean sandstone) are often associated with F2 in a tidal bar complex. F5 (interbedded thin sand and mud) and F6 (bioturbated sandstone) represent tidal flat deposits. High energy open marine carbonate shoals (F8) and fossiliferous sandstone in offshore bars (F7) represent deepening up facies. Shallow marine standstill conditions facilitated the deposition of thick shale (F9) beds. The reservoir facies (F1-F6) are commonly poorly to moderately sorted; bimodal, immature sandstone represented by quartz-wacke. The framework grains are sub-angular to sub-rounded, medium to coarse-grained (occasionally gritty) embedded within argillaceous (kaolinite/chlorite/chamosite) to highly Fe-rich matrix (sideritic). The facies F7 and F8, representing the sandy packstone and grainstone facies, respectively, exhibit poor reservoir characteristics due to sanitization, diagenetic compaction and matrix-filled intergranular spaces. The various diagenetic features such as the presence of authigenic clays (kaolinite/dickite/smectite); ferruginous minerals like siderite, pyrite, hematite and other iron oxides; bioturbations; glauconite; calcite and quartz cementation, precipitation of gypsum, pressure solution and other compaction effects are identified. These diagenetic features, wherever present, have reduced porosity and permeability thereby adversely affecting reservoir quality. Tidal bar sandstones possess good reservoir characteristics such as moderate to good sorting, fair to good porosity and geometry that facilitates efficient lateral extension and vertical thickness of reservoir. The sand bodies of F2, F3 and F4 facies of Well L, M and Q deposited in a tidal bar complex exhibit good reservoir quality represented by relatively cleaner, poorly burrowed, loose, friable sandstone with good porosity. Sandstone facies around these wells could prove a potential hydrocarbon reservoir and could be considered for further exploration.

Keywords: reservoir sedimentology, facies analysis, HST, tide dominated delta, tidal bars

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5 The Integration of Digital Humanities into the Sociology of Knowledge Approach to Discourse Analysis

Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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Discourse analysis research approaches belong to the central research strategies applied throughout the humanities; they focus on the countless forms and ways digital texts and images shape present-day notions of the world. Despite the constantly growing number of relevant digital, multimodal discourse resources, digital humanities (DH) methods are thus far not systematically developed and accessible for discourse analysis approaches. Specifically, the significance of multimodality and meaning plurality modelling are yet to be sufficiently addressed. In order to address this research gap, the D-WISE project aims to develop a prototypical working environment as digital support for the sociology of knowledge approach to discourse analysis and new IT-analysis approaches for the use of context-oriented embedding representations. Playing an essential role throughout our research endeavor is the constant optimization of hermeneutical methodology in the use of (semi)automated processes and their corresponding epistemological reflection. Among the discourse analyses, the sociology of knowledge approach to discourse analysis is characterised by the reconstructive and accompanying research into the formation of knowledge systems in social negotiation processes. The approach analyses how dominant understandings of a phenomenon develop, i.e., the way they are expressed and consolidated by various actors in specific arenas of discourse until a specific understanding of the phenomenon and its socially accepted structure are established. This article presents insights and initial findings from D-WISE, a joint research project running since 2021 between the Institute of Anthropological Studies in Culture and History and the Language Technology Group of the Department of Informatics at the University of Hamburg. As an interdisciplinary team, we develop central innovations with regard to the availability of relevant DH applications by building up a uniform working environment, which supports the procedure of the sociology of knowledge approach to discourse analysis within open corpora and heterogeneous, multimodal data sources for researchers in the humanities. We are hereby expanding the existing range of DH methods by developing contextualized embeddings for improved modelling of the plurality of meaning and the integrated processing of multimodal data. The alignment of this methodological and technical innovation is based on the epistemological working methods according to grounded theory as a hermeneutic methodology. In order to systematically relate, compare, and reflect the approaches of structural-IT and hermeneutic-interpretative analysis, the discourse analysis is carried out both manually and digitally. Using the example of current discourses on digitization in the healthcare sector and the associated issues regarding data protection, we have manually built an initial data corpus of which the relevant actors and discourse positions are analysed in conventional qualitative discourse analysis. At the same time, we are building an extensive digital corpus on the same topic based on the use and further development of entity-centered research tools such as topic crawlers and automated newsreaders. In addition to the text material, this consists of multimodal sources such as images, video sequences, and apps. In a blended reading process, the data material is filtered, annotated, and finally coded with the help of NLP tools such as dependency parsing, named entity recognition, co-reference resolution, entity linking, sentiment analysis, and other project-specific tools that are being adapted and developed. The coding process is carried out (semi-)automated by programs that propose coding paradigms based on the calculated entities and their relationships. Simultaneously, these can be specifically trained by manual coding in a closed reading process and specified according to the content issues. Overall, this approach enables purely qualitative, fully automated, and semi-automated analyses to be compared and reflected upon.

Keywords: entanglement of structural IT and hermeneutic-interpretative analysis, multimodality, plurality of meaning, sociology of knowledge approach to discourse analysis

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4 Recent Developments in E-waste Management in India

Authors: Rajkumar Ghosh, Bhabani Prasad Mukhopadhay, Ananya Mukhopadhyay, Harendra Nath Bhattacharya

Abstract:

This study investigates the global issue of electronic waste (e-waste), focusing on its prevalence in India and other regions. E-waste has emerged as a significant worldwide problem, with India contributing a substantial share of annual e-waste generation. The primary sources of e-waste in India are computer equipment and mobile phones. Many developed nations utilize India as a dumping ground for their e-waste, with major contributions from the United States, China, Europe, Taiwan, South Korea, and Japan. The study identifies Maharashtra, Tamil Nadu, Mumbai, and Delhi as prominent contributors to India's e-waste crisis. This issue is contextualized within the broader framework of the United Nations' 2030 Agenda for Sustainable Development, which encompasses 17 Sustainable Development Goals (SDGs) and 169 associated targets to address poverty, environmental preservation, and universal prosperity. The study underscores the interconnectedness of e-waste management with several SDGs, including health, clean water, economic growth, sustainable cities, responsible consumption, and ocean conservation. Central Pollution Control Board (CPCB) data reveals that e-waste generation surpasses that of plastic waste, increasing annually at a rate of 31%. However, only 20% of electronic waste is recycled through organized and regulated methods in underdeveloped nations. In Europe, efficient e-waste management stands at just 35%. E-waste pollution poses serious threats to soil, groundwater, and public health due to toxic components such as mercury, lead, bromine, and arsenic. Long-term exposure to these toxins, notably arsenic in microchips, has been linked to severe health issues, including cancer, neurological damage, and skin disorders. Lead exposure, particularly concerning for children, can result in brain damage, kidney problems, and blood disorders. The study highlights the problematic transboundary movement of e-waste, with approximately 352,474 metric tonnes of electronic waste illegally shipped from Europe to developing nations annually, mainly to Africa, including Nigeria, Ghana, and Tanzania. Effective e-waste management, underpinned by appropriate infrastructure, regulations, and policies, offers opportunities for job creation and aligns with the objectives of the 2030 Agenda for SDGs, especially in the realms of decent work, economic growth, and responsible production and consumption. E-waste represents hazardous pollutants and valuable secondary resources, making it a focal point for anthropogenic resource exploitation. The United Nations estimates that e-waste holds potential secondary raw materials worth around 55 billion Euros. The study also identifies numerous challenges in e-waste management, encompassing the sheer volume of e-waste, child labor, inadequate legislation, insufficient infrastructure, health concerns, lack of incentive schemes, limited awareness, e-waste imports, high costs associated with recycling plant establishment, and more. To mitigate these issues, the study offers several solutions, such as providing tax incentives for scrap dealers, implementing reward and reprimand systems for e-waste management compliance, offering training on e-waste handling, promoting responsible e-waste disposal, advancing recycling technologies, regulating e-waste imports, and ensuring the safe disposal of domestic e-waste. A mechanism, Buy-Back programs, will compensate customers in cash when they deposit unwanted digital products. This E-waste could contain any portable electronic device, such as cell phones, computers, tablets, etc. Addressing the e-waste predicament necessitates a multi-faceted approach involving government regulations, industry initiatives, public awareness campaigns, and international cooperation to minimize environmental and health repercussions while harnessing the economic potential of recycling and responsible management.

Keywords: e-waste management, sustainable development goal, e-waste disposal, recycling technology, buy-back policy

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3 Femicide: The Political and Social Blind Spot in the Legal and Welfare State of Germany

Authors: Kristina F. Wolff

Abstract:

Background: In the Federal Republic of Germany, violence against women is deeply embedded in society. Germany is, as of March 2020, the most populous member state of the European Union with 83.2 million inhabitants and, although more than half of its inhabitants are women, gender equality was not certified in the Basic Law until 1957. Women have only been allowed to enter paid employment without their husband's consent since 1977 and have marital rape prosecuted only since 1997. While the lack of equality between men and women is named in the preamble of the Istanbul Convention as the cause of gender-specific, structural, traditional violence against women, Germany continues to sink on the latest Gender Equality Index. According to Police Crime Statistics (PCS), women are significantly more often victims of lethal violence, emanating from men than vice versa. The PCS, which, since 2015, also collects gender-specific data on violent crimes, is kept by the Federal Criminal Police Office, but without taking into account the relevant criteria for targeted prevention, such as the history of violence of the perpetrator/killer, weapon, motivation, etc.. Institutions such as EIGE or the World Health Organization have been asking Germany for years in vain for comparable data on violence against women in order to gain an overview or to develop cross-border synergies. The PCS are the only official data collection on violence against women. All players involved are depend on this data set, which is published only in November of the following year and is thus already completely outdated at the time of publication. In order to combat German femicides causally, purposefully and efficiently, evidence-based data was urgently needed. Methodology: Beginning in January 2019, a database was set up that now tracks more than 600 German femicides, broken down by more than 100 crime-related individual criteria, which in turn go far beyond the official PCS. These data are evaluated on the one hand by daily media research, and on the other hand by case-specific inquiries at the respective public prosecutor's offices and courts nationwide. This quantitative long-term study covers domestic violence as well as a variety of different types of gender-specific, lethal violence, including, for example, femicides committed by German citizens abroad. Additionallyalcohol/ narcotic and/or drug abuse, infanticides and the gender aspect in the judiciary are also considered. Results: Since November 2020, evidence-based data from a scientific survey have been available for the first time in Germany, supplementing the rudimentary picture of reality provided by PCS with a number of relevant parameters. The most important goal of the study is to identify "red flags" that enable general preventive awareness, that serve increasingly precise hazard assessment in acute hazard situations, and from which concrete instructions for action can be identified. Already at a very early stage of the study it could be proven that in more than half of all femicides with a sexual perpetrator/victim constellation there was an age difference of five years or more. Summary: Without reliable data and an understanding of the nature and extent, cause and effect, it is impossible to sustainably curb violence against girls and women, which increasingly often culminates in femicide. In Germany, valid data from a scientific survey has been available for the first time since November 2020, supplementing the rudimentary reality picture of the official and, to date, sole crime statistics with several relevant parameters. The basic research provides insights into geo-concentration, monthly peaks and the modus operandi of male violent excesses. A significant increase of child homicides in the course of femicides and/or child homicides as an instrument of violence against the mother could be proven as well as a danger of affected persons due to an age difference of five years and more. In view of the steadily increasing wave of violence against women, these study results are an eminent contribution to the preventive containment of German femicides.

Keywords: femicide, violence against women, gender specific data, rule Of law, Istanbul convention, gender equality, gender based violence

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2 Tool for Maxillary Sinus Quantification in Computed Tomography Exams

Authors: Guilherme Giacomini, Ana Luiza Menegatti Pavan, Allan Felipe Fattori Alves, Marcela de Oliveira, Fernando Antonio Bacchim Neto, José Ricardo de Arruda Miranda, Seizo Yamashita, Diana Rodrigues de Pina

Abstract:

The maxillary sinus (MS), part of the paranasal sinus complex, is one of the most enigmatic structures in modern humans. The literature has suggested that MSs function as olfaction accessories, to heat or humidify inspired air, for thermoregulation, to impart resonance to the voice and others. Thus, the real function of the MS is still uncertain. Furthermore, the MS anatomy is complex and varies from person to person. Many diseases may affect the development process of sinuses. The incidence of rhinosinusitis and other pathoses in the MS is comparatively high, so, volume analysis has clinical value. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure, which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust, and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression, and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to quantify MS volume proved to be robust, fast, and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases. Providing volume values for MS could be helpful in evaluating the presence of any abnormality and could be used for treatment planning and evaluation of the outcome. The computed tomography (CT) has allowed a more exact assessment of this structure which enables a quantitative analysis. However, this is not always possible in the clinical routine, and if possible, it involves much effort and/or time. Therefore, it is necessary to have a convenient, robust and practical tool correlated with the MS volume, allowing clinical applicability. Nowadays, the available methods for MS segmentation are manual or semi-automatic. Additionally, manual methods present inter and intraindividual variability. Thus, the aim of this study was to develop an automatic tool to quantity the MS volume in CT scans of paranasal sinuses. This study was developed with ethical approval from the authors’ institutions and national review panels. The research involved 30 retrospective exams of University Hospital, Botucatu Medical School, São Paulo State University, Brazil. The tool for automatic MS quantification, developed in Matlab®, uses a hybrid method, combining different image processing techniques. For MS detection, the algorithm uses a Support Vector Machine (SVM), by features such as pixel value, spatial distribution, shape and others. The detected pixels are used as seed point for a region growing (RG) segmentation. Then, morphological operators are applied to reduce false-positive pixels, improving the segmentation accuracy. These steps are applied in all slices of CT exam, obtaining the MS volume. To evaluate the accuracy of the developed tool, the automatic method was compared with manual segmentation realized by an experienced radiologist. For comparison, we used Bland-Altman statistics, linear regression and Jaccard similarity coefficient. From the statistical analyses for the comparison between both methods, the linear regression showed a strong association and low dispersion between variables. The Bland–Altman analyses showed no significant differences between the analyzed methods. The Jaccard similarity coefficient was > 0.90 in all exams. In conclusion, the developed tool to automatically quantify MS volume proved to be robust, fast and efficient, when compared with manual segmentation. Furthermore, it avoids the intra and inter-observer variations caused by manual and semi-automatic methods. As future work, the tool will be applied in clinical practice. Thus, it may be useful in the diagnosis and treatment determination of MS diseases.

Keywords: maxillary sinus, support vector machine, region growing, volume quantification

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1 “MaxSALIVA”: A Nano-Sized Dual-Drug Delivery System for Salivary Gland Radioprotection and Repair in Head and Neck Cancer

Authors: Ziyad S. Haidar

Abstract:

Background: Saliva plays a major role in maintaining oral and dental health (consequently, general health and well-being). Where it normally bathes the oral cavity and acts as a clearing agent. This becomes more apparent when the amount and quality of salivare significantly reduced due to medications, salivary gland neoplasms, disorders such as Sjögren’s syndrome, and especially ionizing radiation therapy for tumors of the head and neck, the fifth most common malignancy worldwide, during which the salivary glands are included within the radiation field or zone. Clinically, patients affected by salivary gland dysfunction often opt to terminate their radiotherapy course prematurely because they become malnourished and experience a significant decrease in their quality of life. Accordingly, the development of an alternative treatment to restore or regenerate damaged salivary gland tissue is eagerly awaited. Likewise, the formulation of a radioprotection modality and early damage prevention strategy is also highly desirable. Objectives: To assess the pre-clinical radio-protective effect as well as the reparative/regenerative potential of layer-by-layer self-assembled lipid-polymer-based core-shell nanocapsules designed and fine-tuned in this experimental work for the sequential (ordered) release of dual cytokines, following a single local administration (direct injection) into a murine sub-mandibular salivary gland model of irradiation. Methods: The formulated core-shell nanocapsules were characterized by physical-chemical-mechanically pre-/post-loading with the drugs (in solution and powder formats), followed by optimizing the pharmaco-kinetic profile. Then, nanosuspensions were administered directly into the salivary glands, 24hrs pre-irradiation (PBS, un-loaded nanocapsules, and individual and combined vehicle-free cytokines were injected into the control glands for an in-depth comparative analysis). External irradiation at an elevated dose of 18Gy (revised from our previous 15Gy model) was exposed to the head-and-neck region of C57BL/6 mice. Salivary flow rate (un-stimulated) and salivary protein content/excretion were regularly assessed using an enzyme-linked immunosorbent assay (3-month period). Histological and histomorphometric evaluation and apoptosis/proliferation analysis followed by local versus systemic bio-distribution and immuno-histochemical assays were then performed on all harvested major organs (at the distinct experimental end-points). Results: Monodisperse, stable, and cytocompatible nanocapsules capable of maintaining the bioactivity of the encapsulant within the different compartments with the core and shell and with controlled/customizable pharmaco-kinetics, resulted, as is illustrated in the graphical abstract (Figure) below. The experimental animals demonstrated a significant increase in salivary flow rates when compared to the controls. Herein, salivary protein content was comparable to the pre-irradiation (baseline) level. Histomorphometry further confirmed the biocompatibility and localization of the nanocapsules, in vivo, into the site of injection. Acinar cells showed fewer vacuoles and nuclear aberration in the experimental group, while the amount of mucin was higher in controls. Overall, fewer apoptotic activities were detected by a Terminal deoxynucleotidyl Transferase (TdT) dUTP Nick-End Labeling (TUNEL) assay and proliferative rates were similar to the controls, suggesting an interesting reparative and regenerative potential of irradiation-damaged/-dysfunctional salivary glands. The Figure below exemplifies some of these findings. Conclusions: Biocompatible, reproducible, and customizable self-assembling layer-by-layer core-shell delivery system is formulated and presented. Our findings suggest that localized sequential bioactive delivery of dual cytokines (in specific dose and order) can prevent irradiation-induced damage via reducing apoptosis and also has the potential to promote in situ proliferation of salivary gland cells; maxSALIVA is scalable (Good Manufacturing Practice or GMP production for human clinical trials) and patent-pending.

Keywords: saliva, head and neck cancer, nanotechnology, controlled drug delivery, xerostomia, mucositis, biopolymers, innovation

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