Search results for: water supply systems

Authors: Frank Adusah-Poku, John Bosco Dramani, Prince Boakye Frimpong

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Climate change is considered a principal threat to human existence and livelihood. The persistence and intensity of droughts and floods in recent years have adversely affected food production systems and value chains, making it impossible to end global hunger by 2030. Thus, this study aims to examine the effect of climate change on food consumption for both farm and non-farm households in Ghana. An important focus of the analysis is to investigate how climate change affects alternative dimensions of food security, examine the extent to which these effects vary across heterogeneous groups, and explore the channels through which climate change affects food consumption. Finally, we conducted a pilot study to understand the significance of farm and non-farm diversification measures in reducing the harmful impact of climate change on farm households. The approach of this article is to use two secondary and one primary datasets. The first secondary dataset is the Ghana Socioeconomic Panel Survey (GSPS). The GSPS is a household panel dataset collected during the period 2009 to 2019. The second dataset is monthly district rainfall and temperature gridded data from the Ghana Meteorological Agency. This data was matched to the GSPS dataset at the district level. Finally, the primary data was obtained from a survey of farm and non-farm adaptation practices used by farmers in three regions in Northern Ghana. The study employed the household fixed effects model to estimate the effect of climate change (measured by temperature and rainfall) on food consumption in Ghana. Again, it used the spatial and temporal variation in temperature and rainfall across the districts in Ghana to estimate the household-level model. Evidence of potential mechanisms through which climate change affects food consumption was explored using two steps. First, the potential mechanism variables were regressed on temperature, rainfall, and the control variables. In the second and final step, the potential mechanism variables were included as extra covariates in the first model. The results revealed that extreme average temperature and drought had caused a decrease in food consumption as well as reduced the intake of important food nutrients such as carbohydrates, protein and vitamins. The results further indicated that low rainfall increased food insecurity among households with no education compared with those with primary and secondary education. Again, non-farm activity and silos have been revealed as the transmission pathways through which the effect of climate change on farm households can be moderated. Finally, the results indicated over 90% of the small-holder farmers interviewed had no farm diversification adaptation strategies for climate change, and a little over 50% of the farmers owned unskilled or manual non-farm economic ventures. This makes it very difficult for the majority of the farmers to withstand climate-related shocks. These findings suggest that achieving the Sustainable Development Goal of Zero Hunger by 2030 needs an integrated approach, such as reducing the over-reliance on rainfed agriculture, educating farmers, and implementing non-farm interventions to improve food consumption in Ghana.

Keywords: climate change, food consumption, Ghana, non-farm activity

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Authors: Rachel Barker

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The exponential velocity in the truly knowledge-intensive world today has increasingly bombarded organizations with unfathomable challenges. Hence organizations are introduced to strange lexicons of descriptors belonging to a new paradigm of who, what and how knowledge at individual and organizational levels should be managed. Although organizational knowledge has been recognized as a valuable intangible resource that holds the key to competitive advantage, little progress has been made in understanding how knowledge sharing at individual level could benefit knowledge use at collective level to ensure added value. The research problem is that a lack of research exists to measure knowledge sharing through a multi-layered structure of ideas with at its foundation, philosophical assumptions to support presuppositions and commitment which requires actual findings from measured variables to confirm observed and expected events. The purpose of this paper is to address this problem by presenting a theoretical approach to measure knowledge sharing in emerging knowledge organizations. The research question is that despite the competitive necessity of becoming a knowledge-based organization, leaders have found it difficult to transform their organizations due to a lack of knowledge on who, what and how it should be done. The main premise of this research is based on the challenge for knowledge leaders to develop an organizational culture conducive to the sharing of knowledge and where learning becomes the norm. The theoretical constructs were derived and based on the three components of the knowledge management theory, namely technical, communication and human components where it is suggested that this knowledge infrastructure could ensure effective management. While it is realised that it might be a little problematic to implement and measure all relevant concepts, this paper presents effect of eight critical success factors (CSFs) namely: organizational strategy, organizational culture, systems and infrastructure, intellectual capital, knowledge integration, organizational learning, motivation/performance measures and innovation. These CSFs have been identified based on a comprehensive literature review of existing research and tested in a new framework adapted from four perspectives of the balanced score card (BSC). Based on these CSFs and their items, an instrument was designed and tested among managers and employees of a purposefully selected engineering company in South Africa who relies on knowledge sharing to ensure their competitive advantage. Rigorous pretesting through personal interviews with executives and a number of academics took place to validate the instrument and to improve the quality of items and correct wording of issues. Through analysis of surveys collected, this research empirically models and uncovers key aspects of these dimensions based on the CSFs. Reliability of the instrument was calculated by Cronbach’s a for the two sections of the instrument on organizational and individual levels.The construct validity was confirmed by using factor analysis. The impact of the results was tested using structural equation modelling and proved to be a basis for implementing and understanding the competitive predisposition of the organization as it enters the process of knowledge management. In addition, they realised the importance to consolidate their knowledge assets to create value that is sustainable over time.

Keywords: innovation, intellectual capital, knowledge sharing, performance measures

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Authors: Chris J. Boreham, Dianne S. Edwards, Amber Jarrett, Justin Davies, Robert Poreda, Alex Sessions, John Eiler

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The origins of natural gases in the Amadeus Basin have been assessed using molecular and stable isotope (C, H, N, He) systematics. A dominant end-member thermogenic, oil-associated gas is considered for the Ordovician Pacoota−Stairway sandstones of the Mereenie gas and oil field. In addition, an abiogenic end-member is identified in the latest Proterozoic lower Arumbera Sandstone of the Dingo gasfield, being most likely associated with radiolysis of methane with polymerisation to wet gases. The latter source assignment is based on a similar geochemical fingerprint derived from the laboratory gamma irradiation experiments on methane. A mixed gas source is considered for the Palm Valley gasfield in the Ordovician Pacoota Sandstone. Gas wetness (%∑C₂−C₅/∑C₁−C₅) decreases in the order Mereenie (19.1%) > Palm Valley (9.4%) > Dingo (4.1%). Non-produced gases at Magee-1 (23.5%; Late Proterozoic Heavitree Quartzite) and Mount Kitty-1 (18.9%; Paleo-Mesoproterozoic fractured granitoid basement) are very wet. Methane thermometry based on clumped isotopes of methane (¹³CDH₃) is consistent with the abiogenic origin for the Dingo gas field with methane formation temperature of 254ᵒC. However, the low methane formation temperature of 57°C for the Mereenie gas suggests either a mixed thermogenic-biogenic methane source or there is no thermodynamic equilibrium between the methane isotopomers. The shallow reservoir depth and present-day formation temperature below 80ᵒC would support microbial methanogenesis, but there is no accompanying alteration of the C- and H-isotopes of the wet gases and CO₂ that is typically associated with biodegradation. The Amadeus Basin gases show low to extremely high inorganic gas contents. Carbon dioxide is low in abundance (< 1% CO₂) and becomes increasing depleted in ¹³C from the Palm Valley (av. δ¹³C 0‰) to the Mereenie (av. δ¹³C -6.6‰) and Dingo (av. δ¹³C -14.3‰) gas fields. Although the wide range in carbon isotopes for CO₂ is consistent with multiple origins from inorganic to organic inputs, the most likely process is fluid-rock alteration with enrichment in ¹²C in the residual gaseous CO₂ accompanying progressive carbonate precipitation within the reservoir. Nitrogen ranges from low−moderate (1.7−9.9% N₂) abundance (Palm Valley av. 1.8%; Mereenie av. 9.1%; Dingo av. 9.4%) to extremely high abundance in Magee-1 (43.6%) and Mount Kitty-1 (61.0%). The nitrogen isotopes for the production gases have δ¹⁵N = -3.0‰ for Mereenie, -3.0‰ for Palm Valley and -7.1‰ for Dingo, suggest all being mixed inorganic and thermogenic nitrogen sources. Helium (He) abundance varies over a wide range from a low of 0.17% to one of the world’s highest at 9% (Mereenie av. 0.23%; Palm Valley av. 0.48%, Dingo av. 0.18%, Magee-1 6.2%; Mount Kitty-1 9.0%). Complementary helium isotopes (R/Ra = ³He/⁴Hesample / ³He/⁴Heair) range from 0.013 to 0.031 R/Ra, indicating a dominant crustal origin for helium with a sustained input of radiogenic 4He from the decomposition of U- and Th-bearing minerals, effectively diluting any original mantle helium input. The high helium content in the non-produced gases compared to the shallower producing wells most likely reflects their stratigraphic position relative to the Tonian Bitter Springs Group with the former below and the latter above an effective carbonate-salt seal.

Keywords: amadeus gas, thermogenic, abiogenic, C, H, N, He isotopes

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Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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Authors: Maryam Fallahpoor, Biswajeet Pradhan

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Background: Artificial intelligence (AI) serves as a valuable tool in mitigating the scarcity of human resources required for the evaluation and categorization of vast quantities of medical imaging data. When AI operates with optimal precision, it minimizes the demand for human interpretations and, thereby, reduces the burden on radiologists. Among various AI approaches, deep learning (DL) stands out as it obviates the need for feature extraction, a process that can impede classification, especially with intricate datasets. The advent of DL models has ushered in a new era in medical imaging, particularly in the context of COVID-19 detection. Traditional 2D imaging techniques exhibit limitations when applied to volumetric data, such as Computed Tomography (CT) scans. Medical images predominantly exist in one of two formats: neuroimaging informatics technology initiative (NIfTI) and digital imaging and communications in medicine (DICOM). Purpose: This study aims to employ DL for the classification of COVID-19-infected pulmonary patients and normal cases based on 3D CT scans while investigating the impact of image format. Material and Methods: The dataset used for model training and testing consisted of 1245 patients from IranMehr Hospital. All scans shared a matrix size of 512 × 512, although they exhibited varying slice numbers. Consequently, after loading the DICOM CT scans, image resampling and interpolation were performed to standardize the slice count. All images underwent cropping and resampling, resulting in uniform dimensions of 128 × 128 × 60. Resolution uniformity was achieved through resampling to 1 mm × 1 mm × 1 mm, and image intensities were confined to the range of (−1000, 400) Hounsfield units (HU). For classification purposes, positive pulmonary COVID-19 involvement was designated as 1, while normal images were assigned a value of 0. Subsequently, a U-net-based lung segmentation module was applied to obtain 3D segmented lung regions. The pre-processing stage included normalization, zero-centering, and shuffling. Four distinct 3D CNN models (ResNet152, ResNet50, DensNet169, and DensNet201) were employed in this study. Results: The findings revealed that the segmentation technique yielded superior results for DICOM images, which could be attributed to the potential loss of information during the conversion of original DICOM images to NIFTI format. Notably, ResNet152 and ResNet50 exhibited the highest accuracy at 90.0%, and the same models achieved the best F1 score at 87%. ResNet152 also secured the highest Area under the Curve (AUC) at 0.932. Regarding sensitivity and specificity, DensNet201 achieved the highest values at 93% and 96%, respectively. Conclusion: This study underscores the capacity of deep learning to classify COVID-19 pulmonary involvement using real 3D hospital data. The results underscore the significance of employing DICOM format 3D CT images alongside appropriate pre-processing techniques when training DL models for COVID-19 detection. This approach enhances the accuracy and reliability of diagnostic systems for COVID-19 detection.

Keywords: deep learning, COVID-19 detection, NIFTI format, DICOM format

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Authors: Adrian Priceputu, Elena Mihaela Stan

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Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.

Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations

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Authors: Ayse Collins

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The Agenda 2030 puts Higher Education Institutions (HEIs) in the situation where they should emphasize ways to promote sustainability accordingly. However, it is still unclear: a) how sustainability is understood, and b) which actions have been taken in both discourse and practice by HEIs regarding the three pillars of sustainability, society, environment, and economy. There are models of sustainable universities developed by different authors from different countries; For Example, The Global Reporting Initiative (GRI) methodology which offers a variety of indicators to diagnose performance. However, these models have never been developed for universities in particular. Any model, in this sense, cannot be completed adequately without defining the appropriate tools to measure, analyze and control the performance of initiatives. There is a need to conduct researches in different universities from different countries to understand where we stand in terms of sustainable higher education. Therefore, this study aims at exploring the actions taken by a university in Ankara, Turkey, since Agenda 2030 should consider localizing its objectives and targets according to a certain geography. This university just announced 2021-2022 as “Sustainability Year.” Therefore, this research is a multi-methodology longitudinal study and uses the theoretical framework of the organization and transition management (TM). It is designed to examine the activities as being strategic, tactical, operational, and reflexive in nature and covers the six main aspects: academic community, administrative staff, operations and services, teaching, research, and extension. The preliminary research will answer the role of the top university governance, perception of the stakeholders (students, instructors, administrative and support staff) regarding sustainability, and the level of achievement at the mid-evaluation and final, end of year evaluation. TM Theory is a multi-scale, multi-actor, process-oriented approach with the analytical framework to explore and promote change in social systems. Therefore, the stages and respective methodology for collecting data in this research is: Pre-development Stage: a) semi-structured interviews with university governance, c) open-ended survey with faculty, students, and administrative staff d) Semi-structured interviews with support staff, and e) analysis of current secondary data for sustainability. Take-off Stage: a) semi-structured interviews with university governance, faculty, students, administrative and support staff, b) analysis of secondary data. Breakthrough stabilization a) survey with all stakeholders at the university, b) secondary data analysis by using selected indicators for the first sustainability report for universities The findings from the predevelopment stage highlight how stakeholders, coming from different faculties, different disciplines with different identities and characteristics, face the sustainability challenge differently. Though similar sustainable development goals ((social, environmental, and economic) are set in the institution, there are differences across disciplines and among different stakeholders, which need to be considered to reach the optimum goal. It is believed that the results will help changes in HEIs organizational culture to embed sustainability values in their strategic planning, academic and managerial work by putting enough time and resources to be successful in coping with sustainability.

Keywords: higher education, sustainability, sustainability auditing, transition management

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Authors: Matthew Arnaouti, Michael Baird, Gabrielle Cahill, Tamara Worlton, Michelle Joseph

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Introduction: Over ten years after the 7.0 magnitude Earthquake struck the capital of Haiti, impacting over three million people and leading to the deaths of over two hundred thousand, the multinational humanitarian response remains the largest disaster relief effort to date. This study critically evaluates the multi-sector and multinational disaster response to the Earthquake, looking at how the lessons learned from this analysis can be applied to future disaster response efforts. We put particular emphasis on assessing the interaction between civilian and military sectors during this humanitarian relief effort, with the hopes of highlighting how concrete guidelines are essential to improve future responses. Methods: An extensive scoping review of the relevant literature was conducted - where library scientists conducted reproducible, verified systematic searches of multiple databases. Grey literature and hand searches were utilised to identify additional unclassified military documents, for inclusion in the study. More than 100 documents were included for data extraction and analysis. Key domains were identified, these included: Humanitarian and Military Response, Communication, Coordination, Resources, Needs Assessment and Pre-Existing Policy. Corresponding information and lessons-learned pertaining to these domains was then extracted - detailing the barriers and facilitators to an effective response. Results: Multiple themes were noted which stratified all identified domains - including the lack of adequate pre-existing policy, as well as extensive ambiguity of actors’ roles. This ambiguity was continually influenced by the complex role the United States military played in the disaster response. At a deeper level, the effects of neo-colonialism and concern about infringements on Haitian sovereignty played a substantial role at all levels: setting the pre-existing conditions and determining the redevelopment efforts that followed. Furthermore, external factors significantly impacted the response, particularly the loss of life within the political and security sectors. This was compounded by the destruction of important infrastructure systems - particularly electricity supplies and telecommunication networks, as well as air and seaport capabilities. Conclusions: This study stands as one of the first and most comprehensive evaluations, systematically analysing the civilian and military response - including their collaborative efforts. This study offers vital information for improving future combined responses and provides a significant opportunity for advancing knowledge in disaster relief efforts - which remains a more pressing issue than ever. The categories and domains formulated serve to highlight interdependent factors that should be applied in future disaster responses, with significant potential to aid the effective performance of humanitarian actors. Further studies will be grounded in these findings, particularly the need for greater inclusion of the Haitian perspective in the literature, through additional qualitative research studies.

Keywords: civilian and military collaboration, combined response, disaster, disaster response, earthquake, Haiti, humanitarian response

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Authors: G. M. Vlasceanu, H. Iovu, E. Vasile, M. Ionita

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Herein, the synthesis and characterization of chitosan-gelatin highly porous scaffold reinforced with graphene oxide, and hydroxyapatite (HAp), crosslinked with genipin was targeted. In tissue engineering, chitosan and gelatin are two of the most robust biopolymers with wide applicability due to intrinsic biocompatibility, biodegradability, low antigenicity properties, affordability, and ease of processing. HAp, per its exceptional activity in tuning cell-matrix interactions, is acknowledged for its capability of sustaining cellular proliferation by promoting bone-like native micro-media for cell adjustment. Genipin is regarded as a top class cross-linker, while graphene oxide (GO) is viewed as one of the most performant and versatile fillers. The composites with natural bone HAp/biopolymer ratio were obtained by cascading sonochemical treatments, followed by uncomplicated casting methods and by freeze-drying. Their structure was characterized by Fourier Transform Infrared Spectroscopy and X-ray Diffraction, while overall morphology was investigated by Scanning Electron Microscopy (SEM) and micro-Computer Tomography (µ-CT). Ensuing that, in vitro enzyme degradation was performed to detect the most promising compositions for the development of in vivo assays. Suitable GO dispersion was ascertained within the biopolymer mix as nanolayers specific signals lack in both FTIR and XRD spectra, and the specific spectral features of the polymers persisted with GO load enhancement. Overall, correlations between the GO induced material structuration, crystallinity variations, and chemical interaction of the compounds can be correlated with the physical features and bioactivity of each composite formulation. Moreover, the HAp distribution within follows an auspicious density gradient tuned for hybrid osseous/cartilage matter architectures, which were mirrored in the mice model tests. Hence, the synthesis route of a natural polymer blend/hydroxyapatite-graphene oxide composite material is anticipated to emerge as influential formulation in bone tissue engineering. Acknowledgement: This work was supported by the project 'Work-based learning systems using entrepreneurship grants for doctoral and post-doctoral students' (Sisteme de invatare bazate pe munca prin burse antreprenor pentru doctoranzi si postdoctoranzi) - SIMBA, SMIS code 124705 and by a grant of the National Authority for Scientific Research and Innovation, Operational Program Competitiveness Axis 1 - Section E, Program co-financed from European Regional Development Fund 'Investments for your future' under the project number 154/25.11.2016, P_37_221/2015. The nano-CT experiments were possible due to European Regional Development Fund through Competitiveness Operational Program 2014-2020, Priority axis 1, ID P_36_611, MySMIS code 107066, INOVABIOMED.

Keywords: biopolymer blend, ectopic osteoinduction, graphene oxide composite, hydroxyapatite

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Authors: Leigha C. Crout

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This paper will investigate the categorical disregard of the People’s Republic of China (PRC) in establishing and maintaining a baseline standard of civil guarantees for economic migrant women and their dependents. In light of the relative forward strides in terms of policy facilitating the ascension of female workers in China, this oft-invisible subgroup of women remains neglected from the modern-day “iron rice bowl” of the self-identified communist state. This study is being undertaken to rectify the absence of data on this subject and provide a baseline for future studies on the matter, as the human rights of migrants has become an established facet of transnational dialogue and debate. The basic methodology of this research will consist of the evaluation of China’s compliance with its own national guidelines, and the eight international human rights law treaties it has ratified. Data will be extracted and cross-checked from a number of relevant sources to monitor the extent of compliance, including but by no means limited to the United Nations Human Rights Council (UNHRC) Universal Periodic Review (UPR) reports and responses, submissions and responses of international human rights treaty bodies, local and international nongovernmental organizations (NGOs) and their annual reports, and articles and commentaries authored by specialists on the modern state and implementation of Chinese law. Together, these data will illuminate the vast network of compliance that has forced many migrant women to work within situations of extreme economic precarity. The structure will proceed as follows: first, an outline of the current status of migrant workers and the enforcement of stipulated protections will be provided; next, the analysis of the oft-debated regulations directing and the outline of mandatory services guaranteed to external and internal migrants; and finally, a conclusion incorporating various recommendations to improve transparency and gradually decrease the amount of migrant work turned forced labor that typifies the economic migrant experience, especially in the case of women. The internal and international migrant workers in China are bound by different and uncomplimentary systems. The first, which governs Chinese citizens moving to different regions or provinces to find more sustainable employment (internal migrants), is called the hukou (or huji) residency system. This law enforces strict regulation of the movement of peoples, while ensuring that residents of urban areas receive preferential benefits to those received by their so-called “agricultural” resident counterparts. Given the overwhelming presence of the Communist Party of China throughout the vast state, the management of internal migrants and the disregard for foreign domestic workers is, at minimum, a surprising oversight. This paper endeavors to provide a much-needed foundation for future commentary and discussion on the treatment of female migrant workers and their families in the People’s Republic of China.

Keywords: female migrant worker’s rights, the People’s Republic of China, forced labor, Hukou residency system

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Authors: Mohanad Elemary, Imose Itua, Rajeswari B. Matam

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Virologists and public health experts have been predicting potential pandemics from coronaviruses for decades. The viruses which caused the SARS and MERS pandemics and the Nipah virus led to many lost lives, but still, the COVID-19 pandemic caused by the SARS-CoV2 virus surprised many scientific communities, experts, and governments with its ease of transmission and its pathogenicity. Governments of various countries reacted by locking down entire populations to their homes to combat the devastation caused by the virus, which led to a loss of livelihood and economic hardship to many individuals and organizations. To revive national economies and support their citizens in resuming their lives, governments focused on the development and use of contact tracing apps as a digital way to track and trace exposure. Google and Apple introduced the Exposure Notification Systems (ENS) framework. Independent organizations and countries also developed different frameworks for contact tracing apps. The efficiency, popularity, and adoption rate of these various apps have been different across countries. In this paper, we present a critical analysis of the different contact tracing apps with respect to their efficiency, adoption rate and general perception, and the governmental strategies and policies, which led to the development of the applications. When it comes to the European countries, each of them followed an individualistic approach to the same problem resulting in different realizations of a similarly functioning application with differing results of use and acceptance. The study conducted an extensive review of existing literature, policies, and reports across multiple disciplines, from which a framework was developed and then validated through interviews with six key stakeholders in the field, including founders and executives in digital health startups and corporates as well as experts from international organizations like The World Health Organization. A framework of best practices and tactics is the result of this research. The framework looks at three main questions regarding the contact tracing apps; how to develop them, how to deploy them, and how to regulate them. The findings are based on the best practices applied by governments across multiple countries, the mistakes they made, and the best practices applied in similar situations in the business world. The findings include multiple strategies when it comes to the development milestone regarding establishing frameworks for cooperation with the private sector and how to design the features and user experience of the app for a transparent, effective, and rapidly adaptable app. For the deployment section, several tactics were discussed regarding communication messages, marketing campaigns, persuasive psychology, and the initial deployment scale strategies. The paper also discusses the data privacy dilemma and how to build for a more sustainable system of health-related data processing and utilization. This is done through principles-based regulations specific for health data to allow for its avail for the public good. This framework offers insights into strategies and tactics that could be implemented as protocols for future public health crises and emergencies whether global or regional.

Keywords: contact tracing apps, COVID-19, digital health applications, exposure notification system

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Authors: Tiziana Ferrero-Regis, Marissa Lindquist

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Circular Economy (CE) is increasingly seen as the reorganisation of production and consumption, and cities are acknowledged as the sources of many ecological and social problems; at the same time, they can be re-imagined through an ecologically and socially resilient future. The concept of the CE has received pointed critiques for its techno-deterministic orientation, focus on science and transformation by the policy. At the heart of our local re-imagining of the CE into circularity through contact zones there is the acknowledgment of collective, spontaneous and shared imaginations of alternative and sustainable futures through the creation of networks of community initiatives that are transformative, creating opportunities that simultaneously make cities rich and enrich humans. This paper presents a mapping project of the fashion and textile ecosystem in Brisbane, Queensland, Australia. Brisbane is currently the most aspirational city in Australia, as its population growth rate is the highest in the country. Yet, Brisbane is considered the least “fashion city” in the country. In contrast, the project revealed a greatly enhanced picture of distinct fashion and textile clusters across greater Brisbane and the adjacency of key services that may act to consolidate CE community contact zones. Clusters to the north of Brisbane and several locales to the south are zones of a greater mix between public/social amenities, walkable zones and local transport networks with educational precincts, community hubs, concentration of small enterprises, designers, artisans and waste recovery centers that will help to establish knowledge of key infrastructure networks that will support enmeshing these zones together. The paper presents two case studies of independent designers who work on new and re-designed clothing through recovering pre-consumer textiles and that operate from within creative precincts. The first case is designer Nelson Molloy, who recently returned to the inner city suburb of West End with their Chasing Zero Design project. The area was known in the 1980s and 1990s for its alternative lifestyle with creative independent production, thrifty clothing shops, alternative fashion and a socialist agenda. After 30 years of progressive gentrification of the suburb, which has dislocated many of the artists, designers and artisans, West End is seeing the return and amplification of clusters of artisans, artists, designers and architects. The other case study is Practice Studio, located in a new zone of creative growth, Bowen Hills, north of the CBD. Practice Studio combines retail with a workroom, offers repair and remaking services, becoming a point of reference for young and emerging Australian designers and artists. The paper demonstrates the spatial politics of the CE and the way in which new cultural capital is produced thanks to cultural specificities and resources. It argues for the recognition of contact zones that are created by local actors, communities and knowledge networks, whose grass-roots agency is fundamental for the co-production of CE’s systems of local governance.

Keywords: contact zones, circular citities, fashion and textiles, circular neighbourhoods, australia

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Authors: Mohua Dutta

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The primary aim of this research paper is to investigate the forced urban migration of Dalits in India who are fleeing caste persecution in rural areas. This paper examines the relationship between caste and rural-to-urban internal migration in India using a literary text, Rohinton Mistry’s A Fine Balance, highlighting the challenges faced by Dalits in rural areas that force them to migrate to urban areas. Despite the prevalence of such discussions in Dalit autobiographies written in vernacular languages, there is a lack of discussion regarding caste migration in Indian English Literature, including this present text, as evidenced by the existing critical interpretations of the novel, which this paper seeks to rectify. The primary research question is how urban migration affects caste system in India and why rural-to-urban caste migration occurs. The purpose of this paper is to better understand the reasons for Dalit migration, the challenges they face in rural and urban areas, and the lingering influence of caste in both rural and urban areas. The study reveals that the promise of mobility and emancipation provided by class operations drives rural-to-urban caste migration in India, but it also reveals that caste marginalization in rural areas is closely linked to class marginalization and other forms of subalternity in urban areas. Moreover, the caste system persists in urban areas as well, making Dalit migrants more vulnerable to social, political, and economic discrimination. The reason for this is that, despite changes in profession and urban migration, the trapped structure of caste capital and family networks exposes migrants to caste and class oppressions. To reach its conclusion, this study employs a variety of methodologies. Discourse analysis is used to investigate the current debates and narratives surrounding caste migration. Critical race theory, specifically intersectional theory and social constructivism, aids in comprehending the complexities of caste, class, and migration. Mistry's novel is subjected to textual analysis in order to identify and interpret references to caste migration. Secondary data, such as theoretical understanding of the caste system in operation and scholarly works on caste migration, are also used to support and strengthen the findings and arguments presented in the paper. The study concludes that rural-to-urban caste migration in India is primarily motivated by the promise of socioeconomic mobility and emancipation offered by urban spaces. However, the caste system persists in urban areas, resulting in the continued marginalisation and discrimination of Dalit migrants. The study also highlights the limitations of urban migration in providing true emancipation for Dalit migrants, as they remain trapped within caste and family network structures. Overall, the study raises awareness of the complexities surrounding caste migration and its impact on the lives of India's marginalised communities. This study contributes to the field of Migration Studies by shedding light on an often-overlooked issue: Dalit migration. It challenges existing literary critical interpretations by emphasising the significance of caste migration in Indian English Literature. The study also emphasises the interconnectedness of caste and class, broadening understanding of how these systems function in both rural and urban areas.

Keywords: rural-to-urban caste migration in india, internal migration in india, caste system in india, dalit movement in india, rooster coop of caste and class, urban poor as subalterns

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Authors: Chevonne Reynolds, Res Altwegg, Andrew Balmford, Claire N. Spottiswoode

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Modern agriculture has revolutionised the planet’s capacity to support humans, yet has simultaneously had a greater negative impact on biodiversity than any other human activity. Balancing the demand for food with the conservation of biodiversity is one of the most pressing issues of our time. Biodiversity-friendly farming (‘land sharing’), or alternatively, separation of conservation and production activities (‘land sparing’), are proposed as two strategies for mediating the trade-off between agriculture and biodiversity. However, there is much debate regarding the efficacy of each strategy, as this trade-off has typically been addressed by short term studies at fine spatial scales. These studies ignore processes that are relevant to biodiversity at larger scales, such as meta-population dynamics and landscape connectivity. Therefore, to better understand species response to agricultural land-use and provide evidence to underpin the planning of better production landscapes, we need to determine the merits of each strategy at larger scales. In South Africa, a remarkable citizen science project - the South African Bird Atlas Project 2 (SABAP2) – collates an extensive dataset describing the occurrence of birds at a 5-min by 5-min grid cell resolution. We use these data, along with fine-resolution data on agricultural land-use, to determine which strategy optimises the agriculture-biodiversity trade-off in a southern African context, and at a spatial scale never considered before. To empirically test this trade-off, we model bird species population density, derived for each 5-min grid cell by Royle-Nicols single-species occupancy modelling, against both the amount and configuration of different types of agricultural production in the same 5-min grid cell. In using both production amount and configuration, we can show not only how species population densities react to changes in yield, but also describe the production landscape patterns most conducive to conservation. Furthermore, the extent of both the SABAP2 and land-cover datasets allows us to test this trade-off across multiple regions to determine if bird populations respond in a consistent way and whether results can be extrapolated to other landscapes. We tested the land sparing/sharing trade-off for 281 bird species across three different biomes in South Africa. Overall, a higher proportion of species are classified as losers, and would benefit from land sparing. However, this proportion of loser-sparers is not consistent and varies across biomes and the different types of agricultural production. This is most likely because of differences in the intensity of agricultural land-use and the interactions between the differing types of natural vegetation and agriculture. Interestingly, we observe a higher number of species that benefit from agriculture than anticipated, suggesting that agriculture is a legitimate resource for certain bird species. Our results support those seen at smaller scales and across vastly different agricultural systems, that land sparing benefits the most species. However, our analysis suggests that land sparing needs to be implemented at spatial scales much larger than previously considered. Species persistence in agricultural landscapes will require the conservation of large tracts of land, and is an important consideration in developing countries, which are undergoing rapid agricultural development.

Keywords: agriculture, birds, land sharing, land sparing

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Authors: Marcin Zieliński, Marcin Dębowski, Mirosław Krzemieniewski

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The anaerobic degradation of substrates is limited especially by the rate and effectiveness of the first (hydrolytic) stage of fermentation. This stage may be intensified through pre-treatment of substrate aimed at disintegration of the solid phase and destruction of substrate tissues and cells. The most frequently applied criterion of disintegration outcomes evaluation is the increase in biogas recovery owing to the possibility of its use for energetic purposes and, simultaneously, recovery of input energy consumed for the pre-treatment of substrate before fermentation. Hydrodynamic cavitation is one of the methods for organic substrate disintegration that has a high implementation potential. Cavitation is explained as the phenomenon of the formation of discontinuity cavities filled with vapor or gas in a liquid induced by pressure drop to the critical value. It is induced by a varying field of pressures. A void needs to occur in the flow in which the pressure first drops to the value close to the pressure of saturated vapor and then increases. The process of cavitation conducted under controlled conditions was found to significantly improve the effectiveness of anaerobic conversion of organic substrates having various characteristics. This phenomenon allows effective damage and disintegration of cellular and tissue structures. Disintegration of structures and release of organic compounds to the dissolved phase has a direct effect on the intensification of biogas production in the process of anaerobic fermentation, on reduced dry matter content in the post-fermentation sludge as well as a high degree of its hygienization and its increased susceptibility to dehydration. A device the efficiency of which was confirmed both in laboratory conditions and in systems operating in the technical scale is a hydrodynamic generator of cavitation. Cavitators, agitators and emulsifiers constructed and tested worldwide so far have been characterized by low efficiency and high energy demand. Many of them proved effective under laboratory conditions but failed under industrial ones. The only task successfully realized by these appliances and utilized on a wider scale is the heating of liquids. For this reason, their usability was limited to the function of heating installations. Design of the presented cavitation generator allows achieving satisfactory energy efficiency and enables its use under industrial conditions in depolymerization processes of biomass with various characteristics. Investigations conducted on the laboratory and industrial scale confirmed the effectiveness of applying cavitation in the process of biomass destruction. The use of the cavitation generator in laboratory studies for disintegration of sewage sludge allowed increasing biogas production by ca. 30% and shortening the treatment process by ca. 20 - 25%. The shortening of the technological process and increase of wastewater treatment plant effectiveness may delay investments aimed at increasing system output. The use of a mechanical cavitator and application of repeated cavitation process (4-6 times) enables significant acceleration of the biogassing process. In addition, mechanical cavitation accelerates increases in COD and VFA levels.

Keywords: hydrodynamic cavitation, pretreatment, biomass, methane fermentation, Virginia fanpetals

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Authors: Eleftheria Atta, Yianna Vovides, Marios Katsioloudes

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In the fusion of neoliberalism and globalization, Higher Education (HE) is becoming increasingly complex. The changing patterns of the economy worldwide caused the development of high value-added economy HE has been viewed as a social investment, significant for the development of knowledge-based societies and economies. In order to contribute to economic competitiveness universities are required to produce local and employable workers in order to fit into the neoliberal economic environment. The emergence of neoliberal performativity, which measures outcomes, is a key aspect in a neoliberal era. It facilitates the redesign of institutions making organizations and individuals to think about themselves in relation to their performance. Performativity and performance management systems lead academics to become more effective, professionally advance, improve and become better than others and therefore act competitively. Besides the aforementioned complexities, universities also encounter the challenge of maintaining a set of values to guide an institution’s actions and which have always been highly respected in developing a HE institution. The formulation of a clear set of values also determines the institutional culture which will be maintained. It is evident that values create a significant framework for the workplace and may determine positive institutional results. Universities are required to engage in activities for capacity building which will improve their students’ competence as well as offer opportunities to administrative and academic staff to professionally develop in light of neoliberal performativity. Additionally, the University is now considered as an innovation ecosystem playing a significant role in providing education, research and innovation to help create solutions to meet social, environmental and economic challenges. Thus, Universities become central in orchestrating multi-actor innovation networks. This presentation will discuss the establishment of an institutional unit entitled ‘Human Development Unit’ (HDU) in a European start-up university. The activities of the HDU are envisioned as drivers for innovation that would enable the university as a whole to maintain its position in a fast-changing world and be ready to face adaptive challenges. In addition, the HDU provides its students, staff, and faculty with opportunities to advance their academic and professional development through engagement in programs that align with institutional values. It also serves as a connector with the broader community. The presentation will highlight the functions of three centers which the unit will coordinate namely, the Student Development Center (SDC), the Faculty & Staff Development Center (FSDC) and the Continuing Education Center (CEC). The presentation aligns with the aim of the conference as it welcomes presentations to discuss innovations and challenges encountered in HE. Particularly, this presentation seeks to discuss the establishment of an innovative unit at a start-up university which will contribute to creating an institutional culture shaped by the value of academic excellence for students as well as for staff, shaping and defining the functions and activities of the unit. The establishment of the proposed unit is crucial in a start-up university both to differentiate from other competitors but also to sustain its presence given the pressures in a neoliberal HE context.

Keywords: academic excellence, globalization, human development unit, neoliberalism

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Authors: O. Squillace, R. L. Thompson

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Migration of small molecules to, and across the surface of polymer matrices is a little-studied problem with important industrial applications. Tackifiers in adhesives, flavors in foods and binding agents in paints all present situations where the function of a product depends on the ability of small molecules to migrate through a polymer matrix to achieve the desired properties such as softness, dispersion of fillers, and to deliver an effect that is felt (or tasted) on a surface. It’s been shown that the chemical and molecular structure, surface free energies, phase behavior, close environment and compatibility of the system, influence the migrants’ motion. When differences in behavior, such as occurrence of segregation to the surface or not, are observed it is then of crucial importance to identify and get a better understanding of the driving forces involved in the process of molecular migration. In this aim, experience is meant to be allied with theory in order to deliver a validated theoretical and computational toolkit to describe and predict these phenomena. The systems that have been chosen for this study aim to address the effect of polarity mismatch between the migrants and the polymer matrix and that of a second migrant over the first one. As a non-polar resin polymer, polyvinyl acetate is used as the material to which more or less polar migrants (sorbitol, carvone, octanoic acid (OA), triacetin) are to be added. Through contact angle measurement a surface excess is seen for sorbitol (polar) mixed with PVAc as the surface energy is lowered compare to the one of pure PVAc. This effect is increased upon the addition of carvon or triacetin (non-polars). Surface micro-structures are also evidenced by atomic force microscopy (AFM). Ion beam analysis (Nuclear Reaction Analysis), supplemented by neutron reflectometry can accurately characterize the self-organization of surfactants, oligomers, aromatic molecules in polymer films in order to relate the macroscopic behavior to the length scales that are amenable to simulation. The nuclear reaction analysis (NRA) data for deuterated OA 20% shows the evidence of a surface excess which is enhanced after annealing. The addition of 10% triacetin, as a second migrant, results in the formation of an underlying layer enriched in triacetin below the surface excess of OA. The results show that molecules in polarity mismatch with the matrix tend to segregate to the surface, and this is favored by the addition of a second migrant of the same polarity than the matrix. As studies have been restricted to materials that are model supported films under static conditions in a first step, it is also wished to address the more challenging conditions of materials under controlled stress or strain. To achieve this, a simple rig and PDMS cell have been designed to stretch the material to a defined strain and to probe these mechanical effects by ion beam analysis and atomic force microscopy. This will make a significant step towards exploring the influence of extensional strain on surface segregation, flavor release in cross-linked rubbers.

Keywords: polymers, surface segregation, thin films, molecular migration

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Authors: Shilpa Murthy, Hazlina Binti Abu Bakar, Juliet Mathew, Chandrashekhar Thummala Hlly Sreerama Reddy, Pathiyil Ravi Shankar

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Simulation is defined as a technique that replaces or expands real experiences with guided experiences that interactively imitate real-world processes or systems. Simulation enables learners to train in a safe and non-threatening environment. For decades, simulation has been considered an integral part of clinical teaching and learning strategy in medical education. The several types of simulation used in medical education and the clinical environment can be applied to several models, including full-body mannequins, task trainers, standardized simulated patients, virtual or computer-generated simulation, or Hybrid simulation that can be used to facilitate learning. Simulation allows healthcare practitioners to acquire skills and experience while taking care of patient safety. The recent COVID pandemic has also led to an increase in simulation use, as there were limitations on medical student placements in hospitals and clinics. The learning is tailored according to the educational needs of students to make the learning experience more valuable. Simulation in the pre-clinical years has challenges with resource constraints, effective curricular integration, student engagement and motivation, and evidence of educational impact, to mention a few. As instructors, we may have more reliance on the use of simulation for pre-clinical students while the students’ confidence levels and perceived competence are to be evaluated. Our research question was whether the implementation of simulation-based learning positively influences preclinical medical students' confidence levels and perceived competence. This study was done to align the teaching activities with the student’s learning experience to introduce more low-fidelity simulation-based teaching sessions for pre-clinical years and to obtain students’ input into the curriculum development as part of inclusivity. The study was carried out at International Medical University, involving pre-clinical year (Medical) students who were started with low-fidelity simulation-based medical education from their first semester and were gradually introduced to medium fidelity, too. The Student Satisfaction and Self-Confidence in Learning Scale questionnaire from the National League of Nursing was employed to collect the responses. The internal consistency reliability for the survey items was tested with Cronbach’s alpha using an Excel file. IBM SPSS for Windows version 28.0 was used to analyze the data. Spearman’s rank correlation was used to analyze the correlation between students’ satisfaction and self-confidence in learning. The significance level was set at p value less than 0.05. The results from this study have prompted the researchers to undertake a larger-scale evaluation, which is currently underway. The current results show that 70% of students agreed that the teaching methods used in the simulation were helpful and effective. The sessions are dependent on the learning materials that are provided and how the facilitators engage the students and make the session more enjoyable. The feedback provided inputs on the following areas to focus on while designing simulations for pre-clinical students. There are quality learning materials, an interactive environment, motivating content, skills and knowledge of the facilitator, and effective feedback.

Keywords: low-fidelity simulation, pre-clinical simulation, students satisfaction, self-confidence

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Authors: Iris Alkaher, Nurit Carmi

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It is widely agreed among scientists that population growth (PG) is a major factor that drives the global environmental crisis. Many researchers recognize that explicitly addressing the impact of PG on the environment and human quality of life through education systems worldwide could play a significant role in improving understanding regarding the links between rapid PG and environmental degradation and changing perceptions, attitudes, and behaviors concerning the necessity to reduce the fertility rate. However, the issue of PG is still rarely included in schools' curricula, mainly because of its complexity and controversiality. This study aims to explore the perspectives of teachers with an academic background in environmental and sustainability education (ESEteachers) and teachers with no such background (non-ESE teachers) regarding PG as an environmental risk. The study also explores the teachers’ willingness to include PG in their teaching and identifies what predicts their inclusion of it. In this mixed-methods research study, data were collected using questionnaires and interviews. The findings portray a complex picture concerning the debate aboutPG as a major factor that drives the global environmental crisis in the Israeli context. Consistent with other countries, we found that the deep-rooted pronatalist culture in the Israeli society, as well as a robust national pronatalist agenda and policies, have a tremendous impact on the education system. Therefore, we found that an academic background in ESE had a limited impact on teachers' perceptions concerning PG as a problem and on their willingness to include it in their teaching and discuss its controversiality. Teachers' attitudes related to PG demonstrated social, cultural, and politically oriented disavowal justification regarding the negative impacts of rapid PG, identified in the literature as population-skepticism and population-fatalism. Specifically, factors such as the ongoing Israeli-Palestinian conflict, the Jewish anxiety of destruction, and the religious command to“be fruitful and multiply”influenced the perceptions of both ESE and non-ESE teachers. While these arguments are unique to the Israeli context, pronatalist policies are international. In accordance with the pronatalist policy, we also found that the absence of PG from both school curricula and the Israeli public discourse was reported by ESE and non-ESE teachers as major reasons for their disregarding PG in their teaching. Under these circumstances, the role of the education system to bring the population question to the front stage in Israel and elsewhere is more challenging. To encourage science and social studies teachers to incorporate the controversial issue of PG in their teaching and successfully confront dominant pronatalist cultures, they need strong and ongoing scaffolding and support. In accordance with scientists' agreement regarding the role of PG as a major factor that drives the global environmental crisis, we call on stakeholders and policymakers in the education system to bring the population debate into schools' curricula, the sooner, the better. And not only as part of human efforts to mitigate environmental degradation but also to use this controversial topic as a platform for shaping critical learners and responsible and active citizens who are tolerant of different people’s opinions.

Keywords: population growth, environmental and sustainability education, controversial environmental sustainability issues, pronatalism

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Authors: A. Augustyn, M. Florek, M. Herezniak

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Since the public authorities are constantly pressured by the public opinion to showcase the tangible and measurable results of their efforts, the evaluation of place brand-related activities becomes a necessity. Given the political and social character of place branding process, the legitimization of the branding efforts requires the compliance of the objectives set out in the city brand strategy with the actual needs, expectations, and aspirations of various internal stakeholders. To deliver on the diverse promises, city authorities and brand managers need to translate them into the measurable indicators against which the brand strategy effectiveness will be evaluated. In concert with these observations are the findings from branding and marketing literature with a widespread consensus that places should adopt a more systematic and holistic approach in order to ensure the performance of their brands. However, the measurement of the effectiveness of place branding remains insufficiently explored in theory, even though it is considered a significant step in the process of place brand management. Therefore, the aim of the research presented in the current paper was to collect insights on the nature of effectiveness measurement of city brand strategies and to juxtapose these findings with the theoretical assumptions formed on the basis of the state-of-the-art literature review. To this end, 15 international academic experts (out of 18 initially selected) with affiliation from ten countries (five continents), were individually interviewed. The standardized set of 19 open-ended questions was used for all the interviewees, who had been selected based on their expertise and reputation in the fields of place branding/marketing. Findings were categorized into four modules: (i) conceptualizations of city brand effectiveness, (ii) methodological issues of city brand effectiveness measurement, (iii) the nature of measurement process, (iv) articulation of key performance indicators (KPIs). Within each module, the interviewees offered diverse insights into the subject based on their academic expertise and professional activity as consultants. They proposed that there should be a twofold understanding of effectiveness. The narrow one when it is conceived as the aptitude to achieve specific goals, and the broad one in which city brand effectiveness is seen as an increase in social and economic reality of a place, which in turn poses diverse challenges for the measurement concepts and processes. Moreover, the respondents offered a variety of insights into the methodological issues, particularly about the need for customization and flexibility of the measurement systems, for the employment of interdisciplinary approach to measurement and implications resulting therefrom. Considerable emphasis was put on the inward approach to measurement, namely the necessity to monitor the resident’s evaluation of brand related activities instead of benchmarking cities against the competitive set. Other findings encompass the issues of developing appropriate KPIs for the city brand, managing the measurement process and the inclusion of diverse stakeholders to produce a sound measurement system. Furthermore, the interviewees enumerated the most frequently made mistakes in measurement mainly resulting from the misunderstanding of the nature of city brands. This research was financed by the National Science Centre, Poland, research project no. 2015/19/B/HS4/00380 Towards the categorization of place brand strategy effectiveness indicators – findings from strategic documents of Polish district cities – theoretical and empirical approach.

Keywords: city branding, effectiveness, experts’ insights, measurement

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Authors: Natàlia Garcia Soler, Timothy Moss

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Despite the multiple benefits of sustainable urban drainage, as demonstrated in numerous case studies across the world, urban rainwater harvesting techniques are generally restricted to isolated model projects. The leap from niche to mainstream has, in most cities, proved an elusive goal. Why policies promoting rainwater harvesting are limited in their widespread implementation has seldom been subjected to systematic analysis. Much of the literature on the policy, planning and institutional contexts of these techniques focus either on their potential benefits or on project design, but very rarely on a critical-constructive analysis of past experiences of implementation. Moreover, the vast majority of these contributions are restricted to single-case studies. There is a dearth of knowledge with respect to, firstly, policy implementation processes and, secondly, multi-case analysis. Insights from both, the authors argue, are essential to inform more effective rainwater harvesting in cities in the future. This paper presents preliminary findings from a research project on rainwater harvesting in cities from a social science perspective that is funded by the Swedish Research Foundation (Formas). This project – UrbanRain – is examining the challenges and opportunities of mainstreaming rainwater harvesting in three European cities. The paper addresses two research questions: firstly, what lessons can be learned on suitable policy incentives and planning instruments for rainwater harvesting from a meta-analysis of the relevant international literature and, secondly, how far these lessons are reflected in a study of past and ongoing rainwater harvesting projects in a European forerunner city. This two-tier approach frames the structure of the paper. We present, first, the results of the literature analysis on policy and planning issues of urban rainwater harvesting. Here, we analyze quantitatively and qualitatively the literature of the past 15 years on this topic in terms of thematic focus, issues addressed and key findings and draw conclusions on research gaps, highlighting the need for more studies on implementation factors, actor interests, institutional adaptation and multi-level governance. In a second step we focus in on the experiences of rainwater harvesting in Berlin and present the results of a mapping exercise on a wide variety of projects implemented there over the last 30 years. Here, we develop a typology to characterize the rainwater harvesting projects in terms of policy issues (what problems and goals are targeted), project design (which kind of solutions are envisaged), project implementation (how and when they were implemented), location (whether they are in new or existing urban developments) and actors (which stakeholders are involved and how), paying particular attention to the shifting institutional framework in Berlin. Mapping and categorizing these projects is based on a combination of document analysis and expert interviews. The paper concludes by synthesizing the findings, identifying how far the goals, governance structures and instruments applied in the Berlin projects studied reflect the findings emerging from the meta-analysis of the international literature on policy and planning issues of rainwater harvesting and what implications these findings have for mainstreaming such techniques in future practice.

Keywords: institutional framework, planning, policy, project implementation, urban rainwater management

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Alaa Fezai, Anuj Sharma, Wolfgang Mueller-Hirsch, André Zimmermann

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Viscoelastic materials have been widely used in the automotive industry over the last few decades with different functionalities. Besides their main application as a simple and efficient surface damping treatment, they may ensure optimal operating conditions for on-board electronics as thermal interface or sealing layers. The dynamic behavior of viscoelastic materials is generally dependent on many environmental factors, the most important being temperature and strain rate or frequency. Prior to the reliability analysis of systems including viscoelastic layers, it is, therefore, crucial to accurately predict the dynamic and lifetime behavior of these materials. This includes the identification of the dynamic material parameters under critical temperature and frequency conditions along with a precise damage localization and identification methodology. The goal of this work is twofold. The first part aims at applying an inverse viscoelastic material-characterization approach for a wide frequency range and under different temperature conditions. For this sake, dynamic measurements are carried on a single lap joint specimen using an electrodynamic shaker and an environmental chamber. The specimen consists of aluminum beams assembled to adapter plates through a viscoelastic adhesive layer. The experimental setup is reproduced in finite element (FE) simulations, and frequency response functions (FRF) are calculated. The parameters of both the generalized Maxwell model and the fractional derivatives model are identified through an optimization algorithm minimizing the difference between the simulated and the measured FRFs. The second goal of the current work is to guarantee an on-line detection of the damage, i.e., delamination in the viscoelastic bonding of the described specimen during frequency monitored end-of-life testing. For this purpose, an inverse technique, which determines the damage location and size based on the modal frequency shift and on the change of the mode shapes, is presented. This includes a preliminary FE model-based study correlating the delamination location and size to the change in the modal parameters and a subsequent experimental validation achieved through dynamic measurements of specimen with different, pre-generated crack scenarios and comparing it to the virgin specimen. The main advantage of the inverse characterization approach presented in the first part resides in the ability of adequately identifying the material damping and stiffness behavior of soft viscoelastic materials over a wide frequency range and under critical temperature conditions. Classic forward characterization techniques such as dynamic mechanical analysis are usually linked to limitations under critical temperature and frequency conditions due to the material behavior of soft viscoelastic materials. Furthermore, the inverse damage detection described in the second part guarantees an accurate prediction of not only the damage size but also its location using a simple test setup and outlines; therefore, the significance of inverse numerical-experimental approaches in predicting the dynamic behavior of soft bonding layers applied in automotive electronics.

Keywords: damage detection, dynamic characterization, inverse approaches, vibration testing, viscoelastic layers

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Authors: Laverne Seales

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When most people think of Panama, they immediately think of the Canal; however, the construction and the people who made it possible are often omitted and seldom acknowledged. The reality is that the construction of this waterway was achieved through forced migration and discriminatory practices toward people of African descent, specifically black people from the Caribbean. From the colonial period to the opening and subsequent operation of the Panama Canal by the United States, this paper goes through the rich layers of Panamanian history to examine the life of Afro-Caribbeans and their descendants in Panama. It also considers the role of the United States in Panama; it explores how the United States in Panama forged a racially complex country that made the integration of Afro-Caribbeans and their descendants difficult. After laying a historical foundation, the exploration of Afro-Caribbean people and Panamanians of Afro-Caribbean descent are analyzed through Afro-Panamanian writer Carlos Guillermo ‘Cubena’ Wilson's novels, short stories, and poetry. This study focuses on how Cubena addresses racism, discrimination, inequality, and social justice issues towards Afro-Caribbeans and their descendants who traveled to Panama to construct the Canal. Content analysis methodology can yield several significant contributions, and analyzing Carlos Guillermo Wilson's literature under this framework allows us to consider social commentary and critique of Panamanian society. It identifies the social issues and concerns of Afro-Caribbeans and people of Afro-Caribbean descent, such as inequality, corruption, racism, political oppression, and cultural identity. Analysis methodology allows us to explore how Cubena's literature engages with questions of cultural identity and belonging in Panamanian society. By examining themes related to race, ethnicity, language, and heritage, this research uncovers the complexities of Panamanian cultural identity, allowing us to interrogate power dynamics and social hierarchies in Panamanian society. Analyzing the portrayal of different social groups, institutions, and power structures helps uncover how power is wielded, contested, and resisted; Cubena's fictional world allows us to see how it functions in Panama. Content analysis methodology also provides for critiquing political systems and governance in Panama. By examining the representation and presentation of political figures, institutions, and events in Cubena's literature, we uncover his commentary on corruption, authoritarianism, governance, and the role of the United States in Panama. Content analysis highlights how Wilson's literature amplifies the voices and experiences of marginalized individuals and communities in Panamanian society. By centering the narratives of Afro-Panamanians and other marginalized groups, this researcher uncovers Cubena's commitment to social justice and inclusion in his writing and helps the reader engage with historical narratives and collective memory in Panama. Overall, analyzing Carlos Guillermo ‘Cubena’ Wilson's literature as a platform for social commentary and critique of Panamanian society using content analysis methodology provides valuable insights into the cultural, social, and political dimensions of Afro-Panamanians during and after the construction of the Panama Canal.

Keywords: Afro-Caribbean, Panama Canal, race, Afro-Panamanian, identity, history

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Authors: Antonio Boggia, Luisa Paolotti, Gianluca Massei, Lucia Rocchi, Elaine Pace, Maria Attard

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The aim of this paper is to present a methodology and a computer model for sustainability assessment based on the integration of Multi-criteria Decision Analysis (MCDA) with a Geographic Information System (GIS). It presents the result of a study for the implementation of a model for measuring sustainability to address the policy actions for the improvement of sustainability at territory level. The aim is to rank areas in order to understand the specific technical and/or financial support that is required to develop sustainable growth. Assessing sustainable development is a multidimensional problem: economic, social and environmental aspects have to be taken into account at the same time. The tool for a multidimensional representation is a proper set of indicators. The set of indicators must be integrated into a model, that is an assessment methodology, to be used for measuring sustainability. The model, developed by the Environmental Laboratory of the University of Perugia, is called GeoUmbriaSUIT. It is a calculation procedure developed as a plugin working in the open-source GIS software QuantumGIS. The multi-criteria method used within GeoUmbriaSUIT is the algorithm TOPSIS (Technique for Order Preference by Similarity to Ideal Design), which defines a ranking based on the distance from the worst point and the closeness to an ideal point, for each of the criteria used. For the sustainability assessment procedure, GeoUmbriaSUIT uses a geographic vector file where the graphic data represent the study area and the single evaluation units within it (the alternatives, e.g. the regions of a country, or the municipalities of a region), while the alphanumeric data (attribute table), describe the environmental, economic and social aspects related to the evaluation units by means of a set of indicators (criteria). The use of the algorithm available in the plugin allows to treat individually the indicators representing the three dimensions of sustainability, and to compute three different indices: environmental index, economic index and social index. The graphic output of the model allows for an integrated assessment of the three dimensions, avoiding aggregation. The presence of separate indices and graphic output make GeoUmbriaSUIT a readable and transparent tool, since it doesn’t produce an aggregate index of sustainability as final result of the calculations, which is often cryptic and difficult to interpret. In addition, it is possible to develop a “back analysis”, able to explain the positions obtained by the alternatives in the ranking, based on the criteria used. The case study presented is an assessment of the level of sustainability in the six regions of Malta, an island state in the middle of the Mediterranean Sea and the southernmost member of the European Union. The results show that the integration of MCDA-GIS is an adequate approach for sustainability assessment. In particular, the implemented model is able to provide easy to understand results. This is a very important condition for a sound decision support tool, since most of the time decision makers are not experts and need understandable output. In addition, the evaluation path is traceable and transparent.

Keywords: GIS, multi-criteria analysis, sustainability assessment, sustainable development

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Authors: Amenah Dhannoon, Ciaran Martin Hurley, Laura Wrafter, Podraic J. Regan

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Introduction: The COVID-19 pandemic continues to present unprecedented challenges for healthcare systems. This has resulted in the pragmatic shift in the practice of plastic surgery units worldwide. During this period, many units reported a significant fall in urgent melanoma referrals, leading to patients presenting with advanced disease requiring more extensive surgery and inferior outcomes. Our objective was to evaluate our unit's experience with both non-invasive and invasive melanoma during the COVID-19 pandemic and characterize our experience and contrast it to that experienced by our neighbors in the UK, mainland Europe and North America. Methods: a retrospective chart review was performed on all patients diagnosed with invasive and non-invasive cutaneous melanoma between March to December of 2019 (control) compared to 2020 (COVID-19 pandemic) in a single plastic surgery unit in Ireland. Patient demographics, referral source, surgical procedures, tumour characteristics, radiological findings, oncological therapies and follow-up were recorded. All data were anonymized and stored in Microsoft Excel. Results: A total of 589 patients were included in the study. Of these, 314 (53%) with invasive melanoma, compared to 275 (47%) with the non-invasive disease. Overall, more patients were diagnosed with both invasive and non-invasive melanoma in 2020 than in 2019 (p<0.05). However, significantly longer waiting times in 2020 (64 days) compared to 2019 (28 days) (p<0.05), with the majority of the referral being from GP in 2019 (83%) compared to 61% in 2020. Positive sentinel lymph node were higher in 2019 at 56% (n=28) compared to 24% (n=22) in 2020. There was no statistically significant difference in the tutor characteristics or metastasis status. Discussion: While other countries have noticed a fall in the melanoma diagnosis. Our units experienced a higher number of disease diagnoses. This can be due to multiple reasons. In Ireland, the government reached an early agreement with the private sector to continue elective surgery on an urgent basis in private hospitals. This allowed access to local anesthetic procedures and local skin cancer cases were triaged to non-COVID-19 provider centers. Our unit also adapted a fast, effective and minimal patient contact strategy for triaging skin cancer based on telemedicine. Thirdly, a skin cancer nurse specialist maintained patient follow-ups and triaging a dedicated email service. Finally, our plastic surgery service continued to maintain a virtual complex skin cancer multidisciplinary team meeting during the pandemic, ensuring local clinical governance has adhered to each clinical case. Conclusion: Our study highlights that with the prompt efficient restructuring of services, we could reserve successful management of skin cancer even in the most devastating times. It is important to reflect on the success during the pandemic and emphasize the importance of preparation for a potentially difficult future

Keywords: malignant melanoma, skin cancer, COVID-19, triage

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Authors: Reggie Chandra

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Trafficaccidents and traffic signal optimization are correlated. However, 70-90% of the traffic signals across the USA are not synchronized. The reason behind that is insufficient resources to create and implement timing plans. In this work, we will discuss the use of a breakthrough Artificial Intelligence (AI) technology to optimize traffic flow and collect 24/7/365 accurate traffic data using a vehicle detection system. We will discuss what are recent advances in Artificial Intelligence technology, how does AI work in vehicles, pedestrians, and bike data collection, creating timing plans, and what is the best workflow for that. Apart from that, this paper will showcase how Artificial Intelligence makes signal timing affordable. We will introduce a technology that uses Convolutional Neural Networks (CNN) and deep learning algorithms to detect, collect data, develop timing plans and deploy them in the field. Convolutional Neural Networks are a class of deep learning networks inspired by the biological processes in the visual cortex. A neural net is modeled after the human brain. It consists of millions of densely connected processing nodes. It is a form of machine learning where the neural net learns to recognize vehicles through training - which is called Deep Learning. The well-trained algorithm overcomes most of the issues faced by other detection methods and provides nearly 100% traffic data accuracy. Through this continuous learning-based method, we can constantly update traffic patterns, generate an unlimited number of timing plans and thus improve vehicle flow. Convolutional Neural Networks not only outperform other detection algorithms but also, in cases such as classifying objects into fine-grained categories, outperform humans. Safety is of primary importance to traffic professionals, but they don't have the studies or data to support their decisions. Currently, one-third of transportation agencies do not collect pedestrian and bike data. We will discuss how the use of Artificial Intelligence for data collection can help reduce pedestrian fatalities and enhance the safety of all vulnerable road users. Moreover, it provides traffic engineers with tools that allow them to unleash their potential, instead of dealing with constant complaints, a snapshot of limited handpicked data, dealing with multiple systems requiring additional work for adaptation. The methodologies used and proposed in the research contain a camera model identification method based on deep Convolutional Neural Networks. The proposed application was evaluated on our data sets acquired through a variety of daily real-world road conditions and compared with the performance of the commonly used methods requiring data collection by counting, evaluating, and adapting it, and running it through well-established algorithms, and then deploying it to the field. This work explores themes such as how technologies powered by Artificial Intelligence can benefit your community and how to translate the complex and often overwhelming benefits into a language accessible to elected officials, community leaders, and the public. Exploring such topics empowers citizens with insider knowledge about the potential of better traffic technology to save lives and improve communities. The synergies that Artificial Intelligence brings to traffic signal control and data collection are unsurpassed.

Keywords: artificial intelligence, convolutional neural networks, data collection, signal control, traffic signal

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Authors: Pierobon Enrico, Missiaggia Marta, Castelluzzo Michele, Tommasino Francesco, Ricci Leonardo, Scifoni Emanuele, Vincezo Monaco, Boscardin Maurizio, La Tessa Chiara

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Clinical outcomes collected over the past three decades have suggested that ion therapy has the potential to be a treatment modality superior to conventional radiation for several types of cancer, including recurrences, as well as for other diseases. Although the results have been encouraging, numerous treatment uncertainties remain a major obstacle to the full exploitation of particle radiotherapy. To overcome therapy uncertainties optimizing treatment outcome, the best possible radiation quality description is of paramount importance linking radiation physical dose to biological effects. Microdosimetry was developed as a tool to improve the description of radiation quality. By recording the energy deposition at the micrometric scale (the typical size of a cell nucleus), this approach takes into account the non-deterministic nature of atomic and nuclear processes and creates a direct link between the dose deposited by radiation and the biological effect induced. Microdosimeters measure the spectrum of lineal energy y, defined as the energy deposition in the detector divided by most probable track length travelled by radiation. The latter is provided by the so-called “Mean Chord Length” (MCL) approximation, and it is related to the detector geometry. To improve the characterization of the radiation field quality, we define a new quantity replacing the MCL with the actual particle track length inside the microdosimeter. In order to measure this new quantity, we propose a two-stage detector consisting of a commercial Tissue Equivalent Proportional Counter (TEPC) and 4 layers of Low Gain Avalanche Detectors (LGADs) strips. The TEPC detector records the energy deposition in a region equivalent to 2 um of tissue, while the LGADs are very suitable for particle tracking because of the thickness thinnable down to tens of micrometers and fast response to ionizing radiation. The concept of HDM has been investigated and validated with Monte Carlo simulations. Currently, a dedicated readout is under development. This two stages detector will require two different systems to join complementary information for each event: energy deposition in the TEPC and respective track length recorded by LGADs tracker. This challenge is being addressed by implementing SoC (System on Chip) technology, relying on Field Programmable Gated Arrays (FPGAs) based on the Zynq architecture. TEPC readout consists of three different signal amplification legs and is carried out thanks to 3 ADCs mounted on a FPGA board. LGADs activated strip signal is processed thanks to dedicated chips, and finally, the activated strip is stored relying again on FPGA-based solutions. In this work, we will provide a detailed description of HDM geometry and the SoC solutions that we are implementing for the readout.

Keywords: particle tracking, ion therapy, low gain avalanche diode, tissue equivalent proportional counter, microdosimetry

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Authors: Su Yen Chen

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ChatGPT has shown both strengths and limitations in clinical, educational, and research settings, raising important concerns about accuracy, transparency, and ethical use. Despite an improved understanding of user acceptance and satisfaction, there is still a gap in how general AI perceptions translate into practical applications within healthcare. This study focuses on examining the perceptions of ChatGPT's impact among 266 healthcare majors in Taiwan, exploring its implications for their career development, as well as its utility in clinical practice, medical education, and research. By employing a structured survey with precisely defined subscales, this research aims to probe the breadth of ChatGPT's applications within healthcare, assessing both the perceived benefits and the challenges it presents. Additionally, to further enhance the comprehensiveness of our methodology, we have incorporated qualitative data collection methods, which provide complementary insights to the quantitative findings. The findings from the survey reveal that perceptions and usage of ChatGPT among healthcare majors vary significantly, influenced by factors such as its perceived utility, risk, novelty, and trustworthiness. Graduate students and those who perceive ChatGPT as more beneficial and less risky are particularly inclined to use it more frequently. This increased usage is closely linked to significant impacts on personal career development. Furthermore, ChatGPT's perceived usefulness and novelty contribute to its broader impact within the healthcare domain, suggesting that both innovation and practical utility are key drivers of acceptance and perceived effectiveness in professional healthcare settings. Trust emerges as an important factor, especially in clinical settings where the stakes are high. The trust that healthcare professionals place in ChatGPT significantly affects its integration into clinical practice and influences outcomes in medical education and research. The reliability and practical value of ChatGPT are thus critical for its successful adoption in these areas. However, an interesting paradox arises with regard to the ease of use. While making ChatGPT more user-friendly is generally seen as beneficial, it also raises concerns among users who have lower levels of trust and perceive higher risks associated with its use. This complex interplay between ease of use and safety concerns necessitates a careful balance, highlighting the need for robust security measures and clear, transparent communication about how AI systems work and their limitations. The study suggests several strategic approaches to enhance the adoption and integration of AI in healthcare. These include targeted training programs for healthcare professionals to increase familiarity with AI technologies, reduce perceived risks, and build trust. Ensuring transparency and conducting rigorous testing are also vital to foster trust and reliability. Moreover, comprehensive policy frameworks are needed to guide the implementation of AI technologies, ensuring high standards of patient safety, privacy, and ethical use. These measures are crucial for fostering broader acceptance of AI in healthcare, as the study contributes to enriching the discourse on AI's role by detailing how various factors affect its adoption and impact.

Keywords: ChatGPT, healthcare, survey study, IT adoption, behaviour, applcation, concerns

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Authors: Rachel S. Chang, Samuel P. Massion, Alan Z. Grusky, Heather A. Ridinger

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Introduction Health advocacy is defined as activities that improve access to care, utilize resources, address health disparities, and influence health policy. Advocacy is increasingly being recognized as a critical component of a physician’s role, as understanding social determinants of health and improving patient care are important aspects within the American Medical Association’s Health Systems Science framework. However, despite this growing prominence, educational interventions that address advocacy topics are limited and variable across medical school curricula. Furthermore, few recent studies have evaluated attitudes toward health advocacy among physicians-in-training in the United States. This study examines medical student attitudes towards health advocacy, along with perceived knowledge, ability, and current level of engagement with health advocacy during their clerkships. Methods This study employed a cross-sectional survey design using a single anonymous, self-report questionnaire to all second-year medical students at Vanderbilt University School of Medicine (n=96) in December 2020 during clerkship rotations. The survey had 27 items with 5-point Likert scale (15), multiple choice (11), and free response questions (1). Descriptive statistics and thematic analysis were utilized to analyze responses. The study was approved by the Vanderbilt University Institutional Review Board. Results There was an 88% response rate among second-year clerkship medical students. A majority (83%) agreed that formal training in health advocacy should be a mandatory part of the medical student curriculum Likewise, 83% of respondents felt that acting as a health advocate or patients should be part of their role as a clerkship student. However, a minority (25%) felt adequately prepared. While 72% of respondents felt able to identify a psychosocial need, 18% felt confident navigating the healthcare system and only 9% felt able to connect a patient to a psychosocial resource to fill that gap. 44% of respondents regularly contributed to conversations with their medical teams when discussing patients’ social needs, such as housing insecurity, financial insecurity, or legal needs. On average, respondents reported successfully connecting patients to psychosocial resources 1-2 times per 8-week clerkship block. Barriers to participating in health advocacy included perceived time constraints, lack of awareness of resources, lower emphasis among medical teams, and scarce involvement with social work teams. Conclusions In this single-institutional study, second-year medical students on clerkships recognize the importance of advocating for patients and support advocacy training within their medical school curriculum. However, their perceived lack of ability to navigate the healthcare system and connect patients to psychosocial resources, result in students feeling unprepared to advocate as effectively as they hoped during their clerkship rotations. Our results support the ongoing need to equip medical students with training and resources necessary for them to effectively act as advocates for patients.

Keywords: clerkships, medical students, patient advocacy, social medicine

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