Search results for: shared-decision making

Authors: Manuel I. Capel, Antonio Tomeu, Alberto Salguero

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Tumor growth from a transformed cancer-cell up to a clinically apparent mass spans through a range of spatial and temporal magnitudes. Through computer simulations, Cellular Automata (CA) can accurately describe the complexity of the development of tumors. Tumor development prognosis can now be made -without making patients undergo through annoying medical examinations or painful invasive procedures- if we develop appropriate CA-based software tools. In silico testing mainly refers to Computational Biology research studies of application to clinical actions in Medicine. To establish sound computer-based models of cellular behavior, certainly reduces costs and saves precious time with respect to carrying out experiments in vitro at labs or in vivo with living cells and organisms. These aim to produce scientifically relevant results compared to traditional in vitro testing, which is slow, expensive, and does not generally have acceptable reproducibility under the same conditions. For speeding up computer simulations of cellular models, specific literature shows recent proposals based on the CA approach that include advanced techniques, such the clever use of supporting efficient data structures when modeling with deterministic stochastic cellular automata. Multiparadigm and multiscale simulation of tumor dynamics is just beginning to be developed by the concerned research community. The use of stochastic cellular automata (SCA), whose parallel programming implementations are open to yield a high computational performance, are of much interest to be explored up to their computational limits. There have been some approaches based on optimizations to advance in multiparadigm models of tumor growth, which mainly pursuit to improve performance of these models through efficient memory accesses guarantee, or considering the dynamic evolution of the memory space (grids, trees,…) that holds crucial data in simulations. In our opinion, the different optimizations mentioned above are not decisive enough to achieve the high performance computing power that cell-behavior simulation programs actually need. The possibility of using multicore and GPU parallelism as a promising multiplatform and framework to develop new programming techniques to speed-up the computation time of simulations is just starting to be explored in the few last years. This paper presents a model that incorporates parallel processing, identifying the synchronization necessary for speeding up tumor growth simulations implemented in Java and C++ programming environments. The speed up improvement that specific parallel syntactic constructs, such as executors (thread pools) in Java, are studied. The new tumor growth parallel model is proved using implementations with Java and C++ languages on two different platforms: chipset Intel core i-X and a HPC cluster of processors at our university. The parallelization of Polesczuk and Enderling model (normally used by researchers in mathematical oncology) proposed here is analyzed with respect to performance gain. We intend to apply the model and overall parallelization technique presented here to solid tumors of specific affiliation such as prostate, breast, or colon. Our final objective is to set up a multiparadigm model capable of modelling angiogenesis, or the growth inhibition induced by chemotaxis, as well as the effect of therapies based on the presence of cytotoxic/cytostatic drugs.

Keywords: cellular automaton, tumor growth model, simulation, multicore and manycore programming, parallel programming, high performance computing, speed up

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Authors: Claire Williams

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Randomised controlled Trials (RCTs) of efficacy are still perceived as the gold standard for the generation of evidence, and whilst advances in data collection methods are well developed, this progress has not been matched for the reporting of adverse events (AEs). Assessment and reporting of AEs in clinical trials are fraught with human error and inefficiency and are extremely time and resource intensive. Recent research conducted into the quality of reporting of AEs during clinical trials concluded it is substandard and reporting is inconsistent. Investigators commonly send reports to sponsors who are incorrectly categorised and lacking in critical information, which can complicate the detection of valid safety signals. In our presentation, we will describe an electronic data capture system, which has been designed to support clinical trial processes by reducing the resource burden on investigators, improving overall trial efficiencies, and making trials safer for patients. This proprietary technology was developed using expertise proven in the delivery of the world’s first prospective, phase 3b real-world trial, ‘The Salford Lung Study, ’ which enabled robust safety monitoring and reporting processes to be accomplished by the remote monitoring of patients’ EHRs. This technology enables safety alerts that are pre-defined by the protocol to be detected from the data extracted directly from the patients EHR. Based on study-specific criteria, which are created from the standard definition of a serious adverse event (SAE) and the safety profile of the medicinal product, the system alerts the investigator or study team to the safety alert. Each safety alert will require a clinical review by the investigator or delegate; examples of the types of alerts include hospital admission, death, hepatotoxicity, neutropenia, and acute renal failure. This is achieved in near real-time; safety alerts can be reviewed along with any additional information available to determine whether they meet the protocol-defined criteria for reporting or withdrawal. This active surveillance technology helps reduce the resource burden of the more traditional methods of AE detection for the investigators and study teams and can help eliminate reporting bias. Integration of multiple healthcare data sources enables much more complete and accurate safety data to be collected as part of a trial and can also provide an opportunity to evaluate a drug’s safety profile long-term, in post-trial follow-up. By utilising this robust and proven method for safety monitoring and reporting, a much higher risk of patient cohorts can be enrolled into trials, thus promoting inclusivity and diversity. Broadening eligibility criteria and adopting more inclusive recruitment practices in the later stages of drug development will increase the ability to understand the medicinal products risk-benefit profile across the patient population that is likely to use the product in clinical practice. Furthermore, this ground-breaking approach to AE detection not only provides sponsors with better-quality safety data for their products, but it reduces the resource burden on the investigator and study teams. With the data taken directly from the source, trial costs are reduced, with minimal data validation required and near real-time reporting enables safety concerns and signals to be detected more quickly than in a traditional RCT.

Keywords: more comprehensive and accurate safety data, near real-time safety alerts, reduced resource burden, safer trials

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Authors: Rafael Carlos C. Aniceto, Bryce Abraham M. Anos, Don Christian A. Cornel, Marjerie Brianna S. Go, Samantha Nicole U. Roque, Earl Christian C. Te

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Indigenous peoples (IPs) in the Philippines are a vulnerable, marginalized group in terms of health and overall well-being due to social inequities and cultural differences. National standards regarding maternal healthcare are geared towards facility-based delivery with modern medicine, health services, and skilled birth attendants. Standards and procedures of care for pregnant mothers do not take into account cultural differences between indigenous people and the majority of the population. There do exist, however, numerous other factors that cause relatively poorer health outcomes among indigenous peoples (IPs). This analytic cross-sectional study sought to determine the association between social determinants of health (SDH), focusing on status as indigenous peoples, and maternal health-related knowledge and attitudes (KA), and health behavior of the Dumagat-Agta indigenous people of Barangay Catablingan and Barangay San Marcelino, General Nakar, Quezon Province, and their utilization of health facilities for antenatal care, facility-based delivery and postpartum care, which would affect their health outcomes (that were not within the scope of this study). To quantitatively measure the primary/secondary exposures and outcomes, a total of 90 face-to-face interviews with IP and non-IP mothers were done. For qualitative information, participant observation among 6 communities (5 IP and 1 non-IP), 11 key informant interviews (traditional and modern health providers) and 4 focused group discussions among IP mothers were conducted. Primary quantitative analyses included chi-squared, T-test and binary logistic regression, while secondary qualitative analyses involved thematic analysis and triangulation. The researchers spent a total of 15 days in the community to learn the culture and participate in the practices of the Dumagat-Agta more intensively and deeply. Overall, utilization of all MNCHN services measured in the study was lower for IP mothers compared to their non-IP counterparts. After controlling for confounders measured in the study, IP status (primary exposure) was found to be significantly correlated with utilization of and adherence to two MNCHN-prescribed services: number of antenatal care check-ups and place of delivery (secondary outcomes). Findings show that being an indigenous mother leads to unfavorable social determinants of health, and if compounded by a difference in knowledge and attitudes, would then lead to poor levels of utilization of MNCHN-prescribed services. Key themes from qualitative analyses show that factors that affected utilization were: culture, land alienation, social discrimination, socioeconomic status, and relations between IPs and non-IPs, specifically with non-IP healthcare providers. The findings of this study aim to be used to help and guide in policy-making, to provide healthcare that is not only adequate and of quality, but more importantly, that addresses inequities stemming from various social determinants, and which is socio-culturally acceptable to indigenous communities. To address the root causes of health problems of IPs, there must be full recognition and exercise of their collective rights to communal assets, specifically land, and self-determination. This would improve maternal and child health outcomes to one of the most vulnerable and neglected sectors in society today.

Keywords: child health, indigenous people, knowledge-attitudes-practices, maternal health, social determinants of health

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Authors: Stefano Scippo, Damiana Luzzi, Stefano Cuomo, Maria Ranieri

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Background: In response to the rise in natural disasters linked to climate change, numerous studies on Disaster Risk Reduction Education (DRRE) have emerged since the '90s, mainly using a didactic transmission-based approach. Effective DRRE should align with an interactive, experiential, and participatory educational model, which can be costly and risky. A potential solution is using simulations facilitated by eXtended Reality (XR). Research Question: This study aims to conduct a scoping review to explore educational methodologies that use XR to enhance knowledge among teachers, students, and citizens about environmental risks, natural disasters (including climate-related ones), and their management. Method: A search string of 66 keywords was formulated, spanning three domains: 1) education and target audience, 2) environment and natural hazards, and 3) technologies. On June 21st, 2023, the search string was used across five databases: EBSCOhost, IEEE Xplore, PubMed, Scopus, and Web of Science. After deduplication and removing papers without abstracts, 2,152 abstracts (published between 2013 and 2023) were analyzed and 2,062 papers were excluded, followed by the exclusion of 56 papers after full-text scrutiny. Excluded studies focused on unrelated technologies, non-environmental risks, and lacked educational outcomes or accessible texts. Main Results: The 34 reviewed papers were analyzed for context, risk type, research methodology, learning objectives, XR technology use, outcomes, and educational affordances of XR. Notably, since 2016, there has been a rise in scientific publications, focusing mainly on seismic events (12 studies) and floods (9), with a significant contribution from Asia (18 publications), particularly Japan (7 studies). Methodologically, the studies were categorized into empirical (26) and non-empirical (8). Empirical studies involved user or expert validation of XR tools, while non-empirical studies included systematic reviews and theoretical proposals without experimental validation. Empirical studies were further classified into quantitative, qualitative, or mixed-method approaches. Six qualitative studies involved small groups of users or experts, while 20 quantitative or mixed-method studies used seven different research designs, with most (17) employing a quasi-experimental, one-group post-test design, focusing on XR technology usability over educational effectiveness. Non-experimental studies had methodological limitations, making their results hypothetical and in need of further empirical validation. Educationally, the learning objectives centered on knowledge and skills for surviving natural disaster emergencies. All studies recommended XR technologies for simulations or serious games but did not develop comprehensive educational frameworks around these tools. XR-based tools showed potential superiority over traditional methods in teaching risk and emergency management skills. However, conclusions were more valid in studies with experimental designs; otherwise, they remained hypothetical without empirical evidence. The educational affordances of XR, mainly user engagement, were confirmed by the studies. Authors’ Conclusions: The analyzed literature lacks specific educational frameworks for XR in DRRE, focusing mainly on survival knowledge and skills. There is a need to expand educational approaches to include uncertainty education, developing competencies that encompass knowledge, skills, and attitudes like risk perception.

Keywords: disaster risk reduction education, educational technologies, scoping review, XR technologies

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Authors: Gousilin Leandra Rocha Da Silva, Stéfani T. A. Dantas, Bruna F. Rossi, Erika R. Bonsaglia, Ivana G. Castilho, Terue Sadatsune, Ary Fernandes Júnior, Vera l. M. Rall

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Kidney failure causes decreased diuresis and accumulation of nitrogenous substances in the body. To increase patient survival, hemodialysis is used as a partial substitute for renal function. However, contamination of the water used in this treatment, causing bacteremia in patients, is a worldwide concern. The Burkholderia cepacia complex (Bcc), a group of bacteria with more than 20 species, is frequently isolated from hemodialysis water samples and comprises opportunistic bacteria, affecting immunosuppressed patients, due to its wide variety of virulence factors, in addition to innate resistance to several antimicrobial agents, contributing to the permanence in the hospital environment and to the pathogenesis in the host. The objective of the present work was to characterize molecularly and phenotypically Bcc isolates collected from the water and dialysate of the Hemodialysis Unit and from the blood of patients at a Public Hospital in Botucatu, São Paulo, Brazil, between 2019 and 2021. We used 33 Bcc isolates, previously obtained from blood cultures from patients with bacteremia undergoing hemodialysis treatment (2019-2021) and 24 isolates obtained from water and dialysate samples in a Hemodialysis Unit (same period). The recA gene was sequenced to identify the specific species among the Bcc group. All isolates were tested for the presence of some genes that encode virulence factors such as cblA, esmR, zmpA and zmpB. Considering the epidemiology of the outbreak, the Bcc isolates were molecularly characterized by Multi Locus Sequence Type (MLST) and by pulsed-field gel electrophoresis (PFGE). The verification and quantification of biofilm in a polystyrene microplate were performed by submitting the isolates to different incubation temperatures (20°C, average water temperature and 35°C, optimal temperature for group growth). The antibiogram was performed with disc diffusion tests on agar, using discs impregnated with cefepime (30µg), ceftazidime (30µg), ciprofloxacin (5µg), gentamicin (10µg), imipenem (10µg), amikacin 30µg), sulfametazol/trimethoprim (23.75/1.25µg) and ampicillin/sulbactam (10/10µg). The presence of ZmpB was identified in all isolates, while ZmpA was observed in 96.5% of the isolates, while none of them presented the cblA and esmR genes. The antibiogram of the 33 human isolates indicated that all were resistant to gentamicin, colistin, ampicillin/sulbactam and imipenem. 16 (48.5%) isolates were resistant to amikacin and lower rates of resistance were observed for meropenem, ceftazidime, cefepime, ciprofloxacin and piperacycline/tazobactam (6.1%). All isolates were sensitive to sulfametazol/trimethoprim, levofloxacin and tigecycline. As for the water isolates, resistance was observed only to gentamicin (34.8%) and imipenem (17.4%). According to PFGE results, all isolates obtained from humans and water belonged to the same pulsotype (1), which was identified by recA sequencing as B. cepacia¸, belonging to sequence type ST-767. By observing a single pulse type over three years, one can observe the persistence of this isolate in the pipeline, contaminating patients undergoing hemodialysis, despite the routine disinfection of water with peracetic acid. This persistence is probably due to the production of biofilm, which protects bacteria from disinfectants and, making this scenario more critical, several isolates proved to be multidrug-resistant (resistance to at least three groups of antimicrobials), turning the patient care even more difficult.

Keywords: hemodialysis, burkholderia cepacia, PFGE, MLST, multi drug resistance

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Authors: Yannick Willemin

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Carbon fibre-reinforced plastic (CFRP) offers outstanding value. However, like all materials, CFRP also has its challenges. Many forming processes are largely manual and hard to automate, making it challenging to control repeatability and reproducibility (R&R); they generate significant scrap and are too slow for high-series production; fibre costs are relatively high and subject to supply and cost fluctuations; the supply chain is fragmented; many forms of CFRP are not recyclable, and many materials have yet to be fully characterized for accurate simulation; shelf life and outlife limitations add cost; continuous-fibre forms have design limitations; many materials are brittle; and small and/or thick parts are costly to produce and difficult to automate. A majority of small structural parts are metal due to high CFRP fabrication costs for the small-size class. The fact that CFRP manufacturing processes that produce the highest performance parts also tend to be the slowest and least automated is another reason CFRP parts are generally higher in cost than comparably performing metal parts, which are easier to produce. Fortunately, business is in the midst of a major manufacturing evolution—Industry 4.0— one technology seeing rapid growth is additive manufacturing/3D printing, thanks to new processes and materials, plus an ability to harness Industry 4.0 tools. No longer limited to just prototype parts, metal-additive technologies are used to produce tooling and mold components for high-volume manufacturing, and polymer-additive technologies can incorporate fibres to produce true composites and be used to produce end-use parts with high aesthetics, unmatched complexity, mass customization opportunities, and high mechanical performance. A new hybrid manufacturing process combines the best capabilities of additive—high complexity, low energy usage and waste, 100% traceability, faster to market—and post-consolidation—tight tolerances, high R&R, established materials, and supply chains—technologies. The platform was developed by Zürich-based 9T Labs AG and is called Additive Fusion Technology (AFT). It consists of a design software offering the possibility to determine optimal fibre layup, then exports files back to check predicted performance—plus two pieces of equipment: a 3d-printer—which lays up (near)-net-shape preforms using neat thermoplastic filaments and slit, roll-formed unidirectional carbon fibre-reinforced thermoplastic tapes—and a post-consolidation module—which consolidates then shapes preforms into final parts using a compact compression press fitted with a heating unit and matched metal molds. Matrices—currently including PEKK, PEEK, PA12, and PPS, although nearly any high-quality commercial thermoplastic tapes and filaments can be used—are matched between filaments and tapes to assure excellent bonding. Since thermoplastics are used exclusively, larger assemblies can be produced by bonding or welding together smaller components, and end-of-life parts can be recycled. By combining compression molding with 3D printing, higher part quality with very-low voids and excellent surface finish on A and B sides can be produced. Tight tolerances (min. section thickness=1.5mm, min. section height=0.6mm, min. fibre radius=1.5mm) with high R&R can be cost-competitively held in production volumes of 100 to 10,000 parts/year on a single set of machines.

Keywords: additive manufacturing, composites, thermoplastic, hybrid manufacturing

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Authors: Muhammad Bilal Shaikh

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

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

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Authors: Farhana Alam Bhuiyan, Saad Khan, Tanveer Hassan, Jhalok Ranjon Talukder, Syeda Farjana Ahmed, Rahil Roodsaz, Els Rommes, Sabina Faiz Rashid

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Breaking the shame’ is a 3 year (2015-2018) qualitative implementation research project which investigates several aspects of sexual and reproductive health and rights (SRHR) issues for adolescents living in Bangladesh. Scope of learning SRHR issues for adolescents is limited here due to cultural and religious taboos. This study adds to the ongoing discussions around adolescent’s SRHR needs and aims to, 1) understand the overall SRHR needs of urban and rural unmarried female and male adolescents and the challenges they face, 2) explore existing gaps in the content of SRHR curriculum and 3) finally, addresses some critical knowledge gaps by developing and implementing innovative SRHR educational materials. 18 in-depth interviews (IDIs) and 10 focus-group discussions (FGDs) with boys and 21 IDIs and 14 FGDs with girls of ages 13-19, from both urban and rural setting took place. Curriculum materials from two leading organizations, Unite for Body Rights (UBR) Alliance Bangladesh and BRAC Adolescent Development Program (ADP) were also reviewed, with discussions with 12 key program staff. This paper critically analyses the relevance of some of the SRHR topics that are covered, the challenges with existing pedagogic approaches and key sexuality issues that are not covered in the content, but are important for adolescents. Adolescents asked for content and guidance on a number of topics which remain missing from the core curriculum, such as emotional coping mechanisms particularly in relationships, bullying, impact of exposure to porn, and sexual performance anxiety. Other core areas of concern were effects of masturbation, condom use, sexual desire and orientation, which are mentioned in the content, but never discussed properly, resulting in confusion. Due to lack of open discussion around sexuality, porn becomes a source of information for the adolescents. For these reasons, several myths and misconceptions regarding SRHR issues like body, sexuality, agency, and gender roles still persist. The pedagogical approach is very didactic, and teachers felt uncomfortable to have discussions on certain SRHR topics due to cultural taboos or shame and stigma. Certain topics are favored- such as family planning, menstruation- and presented with an emphasis on biology and risk. Rigid formal teaching style, hierarchical power relations between students and most teachers discourage questions and frank conversations. Pedagogy approaches within classrooms play a critical role in the sharing of knowledge. The paper also describes the pilot approaches to implementing new content in SRHR curriculum. After a review of findings, three areas were selected as critically important, 1) myths and misconceptions 2) emotional management challenges, and 3) how to use condom, that have come up from adolescents. Technology centric educational materials such as web page based information platform and you tube videos are opted for which allow adolescents to bypass gatekeepers and learn facts and information from a legitimate educational site. In the era of social media, when information is always a click away, adolescents need sources that are reliable and not overwhelming. The research aims to ensure that adolescents learn and apply knowledge effectively, through creating the new materials and making it accessible to adolescents.

Keywords: adolescents, Bangladesh, media, sexuality education, unmet needs

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Authors: Leo Byrne, Neil Watts

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In the complex and evolving landscape of global trade, maritime sanctions emerge as a critical tool wielded by the international community to curb illegal activities and alter the behavior of non-compliant states and entities. These sanctions, designed to restrict or prohibit trade by sea with sanctioned jurisdictions, entities, or individuals, face continuous challenges due to the sophisticated evasion tactics employed by countries like North Korea. As the Democratic People's Republic of Korea (DPRK) diverts significant resources to circumvent these measures, understanding the nuances of their methodologies becomes imperative for maintaining the integrity of global trade systems. The DPRK, one of the most sanctioned nations globally, has developed an intricate network to facilitate its trade in illicit goods, ensuring the flow of revenue from designated activities continues unabated. Given its geographic and economic conditions, North Korea predominantly relies on maritime routes, utilizing foreign ports to route its illicit trade. This reliance on the sea is exploited through various sophisticated methods, including the use of front companies, falsification of documentation, commingling of bulk cargos, and physical alterations to vessels. These tactics enable the DPRK to navigate through the gaps in regulatory frameworks and lax oversight, effectively undermining international sanctions regimes Maritime sanctions carry significant implications for global trade, imposing heightened risks in the maritime domain. The deceptive practices employed not only by the DPRK but also by other high-risk jurisdictions, necessitate a comprehensive understanding of UN targeted sanctions. For stakeholders in the maritime sector—including maritime authorities, vessel owners, shipping companies, flag registries, and financial institutions serving the shipping industry—awareness and compliance are paramount. Violations can lead to severe consequences, including reputational damage, sanctions, hefty fines, and even imprisonment. To mitigate risks associated with these deceptive practices, it is crucial for maritime sector stakeholders to employ rigorous due diligence and regulatory compliance screening measures. Effective sanctions compliance serves as a protective shield against legal, financial, and reputational risks, preventing exploitation by international bad actors. This requires not only a deep understanding of the sanctions landscape but also the capability to identify and manage risks through informed decision-making and proactive risk management practices. As the DPRK and other sanctioned entities continue to evolve their sanctions evasion tactics, the international community must enhance its collective efforts to demystify and counter these practices. By leveraging more stringent compliance measures, stakeholders can safeguard against the illicit use of the maritime domain, reinforcing the effectiveness of maritime sanctions as a tool for global security. This paper seeks to dissect North Korea's adaptive strategies in the face of maritime sanctions. By examining up-to-date, geographically, and temporally relevant case studies, it aims to shed light on the primary nodes through which Pyongyang evades sanctions and smuggles goods via third-party ports. The goal is to propose multi-level interaction strategies, ranging from governmental interventions to localized enforcement mechanisms, to counteract these evasion tactics.

Keywords: maritime, maritime sanctions, international sanctions, compliance, risk

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Authors: V. Howard, R. Maguire, S. Corrigan

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Background: Type 1 Diabetes (T1D) is a chronic autoimmune disease, typically diagnosed in childhood. T1D puts an enormous strain on families; controlling blood-glucose in children is difficult and the consequences of poor control for patient health are significant. Successful illness management and better health outcomes can be dependent on quality of caregiving. On diagnosis, parent-caregivers face a steep learning curve as T1D care requires a significant level of knowledge to inform complex decision making throughout the day. The majority of illness management is carried out in the home setting, independent of clinical health providers. Parent-caregivers vary in their level of knowledge and their level of engagement in applying this knowledge in the practice of illness management. Enabling researchers to quantify these aspects of the caregiver experience is key to identifying targets for psychosocial support interventions, which are desirable for reducing stress and anxiety in this highly burdened cohort, and supporting better health outcomes in children. Currently, there are limited tools available that are designed to capture this information. Where tools do exist, they are not comprehensive and do not adequately capture the lived experience. Objectives: Development of quantitative tools, informed by lived experience, to enable researchers gather data on parent-caregiver knowledge and engagement, which accurately represents the experience/cohort and enables exploration of questions that are of real-world value to the cohort themselves. Methods: This research employed an engaged approach to address the problem of quantifying two key aspects of caregiver diabetes management: Knowledge and engagement. The research process was multi-staged and iterative. Stage 1: Working from a constructivist standpoint, literature was reviewed to identify relevant questionnaires, scales and single-item measures of T1D caregiver knowledge and engagement, and harvest candidate questionnaire items. Stage 2: Aggregated findings from the review were circulated among a PPI (patient and public involvement) expert panel of caregivers (n=6), for discussion and feedback. Stage 3: In collaboration with the expert panel, data were interpreted through the lens of lived experience to create a long-list of candidate items for novel questionnaires. Items were categorized as either ‘knowledge’ or ‘engagement’. Stage 4: A Delphi-method process (iterative surveys) was used to prioritize question items and generate novel questions that further captured the lived experience. Stage 5: Both questionnaires were piloted to refine wording of text to increase accessibility and limit socially desirable responding. Stage 6: Tools were piloted using an online survey that was deployed using an online peer-support group for caregivers for Juveniles with T1D. Ongoing Research: 123 parent-caregivers completed the survey. Data analysis is ongoing to establish face and content validity qualitatively and through exploratory factor analysis. Reliability will be established using an alternative-form method and Cronbach’s alpha will assess internal consistency. Work will be completed by early 2024. Conclusion: These tools will enable researchers to gain deeper insights into caregiving practices among parents of juveniles with T1D. Development was driven by lived experience, illustrating the value of engaged research at all levels of the research process.

Keywords: caregiving, engaged research, juvenile type 1 diabetes, quantified engagement and knowledge

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Authors: E. O. Aluta, C. A. Booth, D. G. Proverbs, T. Appleby

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Challenges in the effective management of potable water have attracted global attention in recent years and remain many world regions’ major priorities. Scarcity and unavailability of potable water may potentially escalate poverty, obviate democratic expression of views and militate against inter-sectoral development. These challenges contra-indicate the inherent potentials of the resource. Thus, while creation of poverty may be regarded as a broad-based problem, it is capable of reflecting life-span reduction diseases, the friction of interests manifesting in threats and warfare, the relegation of democratic principles for authoritarian definitions and Human Rights abuse. The challenges may be identified as manifestations of ineffective management of potable water resource and therefore, regarded as major problems in environmental protection. In reaction, some nations have re-examined their laws and policies, while others have developed innovative projects, which seek to ameliorate difficulties of providing sustainable potable water. The problems resonate in Nigeria, where the legal framework supporting the supply and management of potable water has been criticized as ineffective. This has impacted more on rural community members, often regarded as ‘voiceless’. At that level, the participation of non-state actors has been identified as an effective strategy, which can improve water supply. However, there are indications that there is no pragmatic application of this, resulting in over-centralization and top-down management. Thus, this study focuses on how the participatory process may enable the development of participatory water governance framework, for use in Nigeria rural communities. The Rural Advisory Board (RAB) is proposed as a governing body to promote proximal relationships, institute democratisation borne out of participation, while enabling effective accountability and information. The RAB establishes mechanisms for effectiveness, taking into consideration Transparency, Accountability and Participation (TAP), advocated as guiding principles of decision-makers. Other tools, which may be explored in achieving these are, Laws and Policies supporting the water sector, under the direction of the Ministries and Law Courts, which ensure non-violation of laws. Community norms and values, consisting of Nigerian traditional belief system, perceptions, attitude and reality (often undermined in favour of legislations), are relied on to pave the way for enforcement. While the Task Forces consist of community members with specific designation of duties, which ensure compliance and enforceability, a cross-section of community members are assigned duties. Thus, the principle of participation is pragmatically reflected. A review of the literature provided information on the potentials of the participatory process, in potable water governance. Qualitative methodology was explored by using the semi-structured interview as strategy for inquiry. The purposive sampling strategy, consisting of homogeneous, heterogeneous and criterion techniques was applied to enable sampling. The samples, sourced from diverse positions of life, were from the study area of Delta State of Nigeria, involving three local governments of Oshimili South, Uvwie and Warri South. From the findings, there are indications that the application of the participatory process is inhered with empowerment of the rural community members to make legitimate demands for TAP. This includes the obviation of mono-decision making for the supply and management of potable water. This is capable of restructuring the top-down management to a top-down/bottom-up system.

Keywords: participation, participatory process, participatory water governance, rural advisory board

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Authors: Harold M. Carag, April Charmaine D. Camacho, Girlie Nora A. Abrigo, Florencia G. Palis, Ma. Larissa Lelu P. Gata

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A technology impact assessment on the use of microbial inoculants in the reforestation and rehabilitation of forest ancestral lands of the Magbukün Aytas in Morong, Bataan was conducted. This two-year rainforestation technology aimed to determine the optimum condition for the improvement of seedling survival rate in the nursery and in the field to hasten the process of forest regeneration of Magbukün Ayta’s ancestral land. A combination of qualitative methods (key informant interviews, focus groups and participant observation), participated by the farmers who were directly involved in the project, community men and women, the council of elders and the project staff, was employed to complete this impact assessment. The recorded data were transcribed, and the accounts were broadly categorized on the following aspects: social (gender, institutional, anthropological), economic and environmental. The Australian Center for International Agricultural Research (ACIAR) framework was primarily used for the impact analysis while the Harvard Analytical Framework was specifically used for the gender impact analysis. Through this technology, a wildling nursery with more than one thousand seedlings was successfully established and served as a good area for the healthy growth of seedlings that would be planted in the forest. Results showed that this technology affected positively and negatively the various gender roles present in the community although household work remained to be the women’s responsibility. The technology introduced directly added up to the workload done by the men and women (preparing and applying fertilizer, making pots etc.) but this, in turn, provided ways to increase their sources of livelihood. The gender roles that were already present were further strengthened after the project and men remained to be in control. The technology or project in turn also benefited from the already present roles since they no longer have to assign things to them, the execution of the various roles was smoothly executed. In the anthropological aspect, their assigned task to manage the nursery was an easy responsibility because of their deep connection to the environment and their fear and beliefs on ‘engkato’ and ‘anito’ was helpful in guarding the forest. As the cultural value of these trees increases, their mindset of safeguarding the forest also heightens. Meanwhile, the welfare of the whole tribe is the ultimate determinant of the swift entry of projects. The past institutions brought ephemeral reliefs on the subsistence of the Magbukün Aytas. These were good ‘conditioning’ factors for the adoption of the technology of the project. As an attempt to turn away from the dependent of harmful chemical, the project’s way of introducing organic inputs was slowly gaining popularity in the community. Economically, the project was able to provide additional income to the farmers. However, the slow mode of payment dismayed other farmers and abandoned their roles. Lastly, major environmental effects weren’t that much observed after the application of the technology. The minor effects concentrated more on the improved conditions of the soil and water in the community. Because of the introduced technology, soil conditions became more favorable specifically for the species that were planted. The organic fertilizers used were in turn not harmful for the residents living in Sitio Kanawan. There were no human diseases caused by the technology. The conservation of the biodiversity of the forest is clearly the most evident long-term result of the project.

Keywords: ancestral lands, impact assessment, microbial inculants, reforestation

Procedia PDF Downloads 142

Authors: Manon Frédout, Laëtitia Bucari, Mathias Aloui, Gaëtan Duhamel, Olivier Rovellotti, Javier Blanco

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Ecosystems must be resilient to ensure cleaner air, better water and soil quality, and thus healthier citizens. Technology can be an excellent tool to support urban ecosystem restoration projects, especially when based on Open Source and promoting Open Data. This is the goal of the ecoTeka application: one single digital tool for tree management which allows decision-makers to improve their urban forestry practices, enabling more responsible urban planning and climate change adaptation. EcoTeka provides city councils with three main functionalities tackling three of their challenges: easier biodiversity inventories, better green space management, and more efficient planning. To answer the cities’ need for reliable tree inventories, the application has been first built with open data coming from the websites OpenStreetMap and OpenTrees, but it will also include very soon the possibility of creating new data. To achieve this, a multi-source algorithm will be elaborated, based on existing artificial intelligence Deep Forest, integrating open-source satellite images, 3D representations from LiDAR, and street views from Mapillary. This data processing will permit identifying individual trees' position, height, crown diameter, and taxonomic genus. To support urban forestry management, ecoTeka offers a dashboard for monitoring the city’s tree inventory and trigger alerts to inform about upcoming due interventions. This tool was co-constructed with the green space departments of the French cities of Alès, Marseille, and Rouen. The third functionality of the application is a decision-making tool for urban planning, promoting biodiversity and landscape connectivity metrics to drive ecosystem restoration roadmap. Based on landscape graph theory, we are currently experimenting with new methodological approaches to scale down regional ecological connectivity principles to local biodiversity conservation and urban planning policies. This methodological framework will couple graph theoretic approach and biological data, mainly biodiversity occurrences (presence/absence) data available on both international (e.g., GBIF), national (e.g., Système d’Information Nature et Paysage) and local (e.g., Atlas de la Biodiversté Communale) biodiversity data sharing platforms in order to help reasoning new decisions for ecological networks conservation and restoration in urban areas. An experiment on this subject is currently ongoing with Montpellier Mediterranee Metropole. These projects and studies have shown that only 26% of tree inventory data is currently geo-localized in France - the rest is still being done on paper or Excel sheets. It seems that technology is not yet used enough to enrich the knowledge city councils have about biodiversity in their city and that existing biodiversity open data (e.g., occurrences, telemetry, or genetic data), species distribution models, landscape graph connectivity metrics are still underexploited to make rational decisions for landscape and urban planning projects. This is the goal of ecoTeka: to support easier inventories of urban biodiversity and better management of urban spaces through rational planning and decisions relying on open databases. Future studies and projects will focus on the development of tools for reducing the artificialization of soils, selecting plant species adapted to climate change, and highlighting the need for ecosystem and biodiversity services in cities.

Keywords: digital software, ecological design of urban landscapes, sustainable urban development, urban ecological corridor, urban forestry, urban planning

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Authors: Daniel Stabler, Anne-Laure Mention, Henri Hakala, Ahmad Alaassar

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In Europe, 2.2 billion tons of waste annually generate severe environmental damage and economic burdens, and negatively impact human health. A stark illustration of the problem is found within the consumer electronics industry, which reflects one of the most complex global waste streams. Of the 5.3 billion globally discarded mobile phones in 2022, only 17% were properly recycled. To address these pressing issues, Europe has made significant strides in developing waste management strategies, Circular Economy initiatives, and Right to Repair policies. These endeavors aim to make product repair and maintenance more accessible, extend product lifespans, reduce waste, and promote sustainable resource use. European countries have introduced Right to Repair policies, often in conjunction with extended producer responsibility legislation, repair subsidies, and consumer repair indices, to varying degrees of regulatory rigor. Changing societal trends emphasizing sustainability and environmental responsibility have driven consumer demand for more sustainable and repairable products, benefiting repair-focused consumer electronics businesses. In academic research, much of the literature in Management studies has examined the European Circular Economy and the Right to Repair from firm-level perspectives. These studies frequently employ a business-model lens, emphasizing innovation and strategy frameworks. However, this study takes an institutional perspective, aiming to understand the adoption of Circular Economy and repair-focused business models within the European consumer electronics market. The concepts of the Circular Economy and the Right to Repair align with institutionalism as they reflect evolving societal norms favoring sustainability and consumer empowerment. Regulatory institutions play a pivotal role in shaping and enforcing these concepts through legislation, influencing the behavior of businesses and individuals. Compliance and enforcement mechanisms are essential for their success, compelling actors to adopt sustainable practices and consider product life extension. Over time, these mechanisms create a path for more sustainable choices, underscoring the influence of institutions and societal values on behavior and decision-making. Institutionalism, particularly 'neo-institutionalism,' provides valuable insights into the factors driving the adoption of Circular and repair-focused business models. Neo-institutional pressures can manifest through coercive regulatory initiatives or normative standards shaped by socio-cultural trends. The Right to Repair movement has emerged as a prominent and influential idea within academic discourse and sustainable development initiatives. Therefore, understanding how macro-level societal shifts toward the Circular Economy and the Right to Repair trigger firm-level responses is imperative. This study aims to answer a crucial question about the impact of European Right to Repair initiatives had on the financial and environmental performance of European consumer electronics companies at the firm level. A quantitative and statistical research design will be employed. The study will encompass an extensive sample of consumer electronics firms in Northern and Western Europe, analyzing their financial and environmental performance in relation to the implementation of Right to Repair mechanisms. The study's findings are expected to provide valuable insights into the broader implications of the Right to Repair and Circular Economy initiatives on the European consumer electronics industry.

Keywords: circular economy, right to repair, institutionalism, environmental management, european union

Procedia PDF Downloads 82

Authors: Eunjung Lee

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

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

Procedia PDF Downloads 47

Authors: Subhash Nerella, Ziyuan Guan, Azra Bihorac, Parisa Rashidi

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Intensive care units (ICUs) provide care to critically ill patients in severe and life-threatening conditions. However, patient monitoring in the ICU is limited by the time and resource constraints imposed on healthcare providers. Many critical care indices such as mobility are still manually assessed, which can be subjective, prone to human errors, and lack granularity. Other important aspects, such as environmental factors, are not monitored at all. For example, critically ill patients often experience circadian disruptions due to the absence of effective environmental “timekeepers” such as the light/dark cycle and the systemic effect of acute illness on chronobiologic markers. Although the occurrence of delirium is associated with circadian disruption risk factors, these factors are not routinely monitored in the ICU. Hence, there is a critical unmet need to develop systems for precise and real-time assessment through novel enabling technologies. We have developed the mobility and circadian disruption quantification system (Mobi-DiQ) by augmenting biomarker and clinical data with pervasive sensing data to generate mobility and circadian cues related to mobility, nightly disruptions, and light and noise exposure. We hypothesize that Mobi-DiQ can provide accurate mobility and circadian cues that correlate with bedside clinical mobility assessments and circadian biomarkers, ultimately important for delirium risk assessment and prevention. The collected multimodal dataset consists of depth images, Electromyography (EMG) data, patient extremity movement captured by accelerometers, ambient light levels, Sound Pressure Level (SPL), and indoor air quality measured by volatile organic compounds, and the equivalent CO₂ concentration. For delirium risk assessment, the system recognizes mobility cues (axial body movement features and body key points) and circadian cues, including nightly disruptions, ambient SPL, and light intensity, as well as other environmental factors such as indoor air quality. The Mobi-DiQ system consists of three major components: the pervasive sensing system, a data storage and analysis server, and a data annotation system. For data collection, six local pervasive sensing systems were deployed, including a local computer and sensors. A video recording tool with graphical user interface (GUI) developed in python was used to capture depth image frames for analyzing patient mobility. All sensor data is encrypted, then automatically uploaded to the Mobi-DiQ server through a secured VPN connection. Several data pipelines are developed to automate the data transfer, curation, and data preparation for annotation and model training. The data curation and post-processing are performed on the server. A custom secure annotation tool with GUI was developed to annotate depth activity data. The annotation tool is linked to the MongoDB database to record the data annotation and to provide summarization. Docker containers are also utilized to manage services and pipelines running on the server in an isolated manner. The processed clinical data and annotations are used to train and develop real-time pervasive sensing systems to augment clinical decision-making and promote targeted interventions. In the future, we intend to evaluate our system as a clinical implementation trial, as well as to refine and validate it by using other data sources, including neurological data obtained through continuous electroencephalography (EEG).

Keywords: deep learning, delirium, healthcare, pervasive sensing

Procedia PDF Downloads 93

Authors: Nayer Mofidtabatabaei

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

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

Procedia PDF Downloads 71

Authors: Georgina Cherry, Taranpreet Rai, Luke Boyden, Sitira Williams, Andrea Wright, Richard Brown, Viva Chu, Alasdair Cook, Kevin Wells

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Estimating population-level burden, abilities of pet-parents to identify disease and demand for veterinary services worldwide is challenging. The purpose of this study is to compare a feline pruritus survey with social media listening (SML) data discussing this condition. Surveys are expensive and labour intensive to analyse, but SML data is freeform and requires careful filtering for relevancy. This study considers data from a survey of owner-observed symptoms of 156 pruritic cats conducted using Pet Parade® and SML posts collected through web-scraping to gain insights into the characterisation and management of feline pruritus. SML posts meeting a feline body area, behaviour and symptom were captured and reviewed for relevance representing 1299 public posts collected from 2021 to 2023. The survey involved 1067 pet-parents who reported on pruritic symptoms in their cats. Among the observed cats, approximately 18.37% (n=196) exhibited at least one symptom. The most frequently reported symptoms were hair loss (9.2%), bald spots (7.3%) and infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin (8.2%). Notably, bald spots were the primary symptom reported for short-haired cats, while other symptoms were more prevalent in medium and long-haired cats. Affected body areas, according to pet-parents, were primarily the head, face, chin, neck (27%), and the top of the body, along the spine (22%). 35% of all cats displayed excessive behaviours consistent with pruritic skin disease. Interestingly, 27% of these cats were perceived as non-symptomatic by their owners, suggesting an under-identification of itch-related signs. Furthermore, a significant proportion of symptomatic cats did not receive any skin disease medication, whether prescribed or over the counter (n=41). These findings indicate a higher incidence of pruritic skin disease in cats than recognized by pet owners, potentially leading to a lack of medical intervention for clinically symptomatic cases. The comparison between the survey and social media listening data revealed bald spots were reported in similar proportions in both datasets (25% in the survey and 28% in SML). Infection, crusting, scaling, redness, scabbing, scaling, or bumpy skin accounted for 31% of symptoms in the survey, whereas it represented 53% of relevant SML posts (excluding bumpy skin). Abnormal licking or chewing behaviours were mentioned by pet-parents in 40% of SML posts compared to 38% in the survey. The consistency in the findings of these two disparate data sources, including a complete overlap in affected body areas for the top 80% of social media listening posts, indicates minimal biases in each method, as significant biases would likely yield divergent results. Therefore, the strong agreement across pruritic symptoms, affected body areas, and reported behaviours enhances our confidence in the reliability of the findings. Moreover, the small differences identified between the datasets underscore the valuable insights that arise from utilising multiple data sources. These variations provide additional depth in characterising and managing feline pruritus, allowing for more comprehensive understanding of the condition. By combining survey data and social media listening, researchers can obtain a nuanced perspective and capture a wider range of experiences and perspectives, supporting informed decision-making in veterinary practice.

Keywords: social media listening, feline pruritus, surveys, felines, cats, pet owners

Procedia PDF Downloads 127

Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

Procedia PDF Downloads 373

Authors: Xue Bai, Ranran He, Chang Liu

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Care planning before the onset of intensive care needs can benefit older adults’ psychological well-being and increases families’ ability to manage caregiving crises and cope with care transitions. Effective care planning requires collaborative ‘team-work’ in families. However, future care planning has not been substantially examined in intergenerational or family contexts, let alone among immigrant families who have to face particular challenges in parental caregiving. From a family systems perspective, this study intends to explore the extent, processes, and contents of intergenerational care planning of Mainland immigrant ageing families in Hong Kong and to examine the intergenerational congruence and discrepancies in the care planning process. Adopting a qualitative research design, semi-structured in-depth interviews were conducted with 17 adult child-older parent pairs and another 33 adult children. In total, 50 adult children who migrated to Hong Kong after the age of 18 with more than three years’ work experience in Hong Kong had at least one parent aged over 55 years old who was not a Hong Kong resident and considered his/herself as the primary caregiver of the parent were recruited. Seventeen ageing parents of the recruited adult children were invited for dyadic interviews. Scarcity of caregiving resources in the context of cross-border migration, intergenerational discrepancies in care planning stages, both generations’ struggle and ambivalence toward filial care, intergenerational transmission of care values, and facilitating role of accumulated family capital in care preparation were primary themes concluded from participants’ narratives. Compared with ageing parents, immigrant adult children generally displayed lower levels of care planning. Although with a strong awareness of parents’ future care needs, few adult children were found engaged in concrete planning activities. This is largely due to their uncertainties toward future life and career, huge work and living pressure, the relatively good health status of their parents, and restrictions of public welfare policies in the receiving society. By contrast, children’s cross-border migration encouraged ageing parents to have early and clear preparation for future care. Ageing parents mostly expressed low filial care expectations when realizing the scarcity of family caregiving resources in the cross-border context. Even though they prefer in-person support from children, most of them prepare themselves for independent ageing to prioritize the next generation’s needs or choose to utilize paid services, welfare systems, friend networks, or extended family networks in their sending society. Adult children were frequently found caught in the dilemma of desiring to provide high quality and in-person support for their parents but lacking sufficient resources. Notably, a salient pattern of intergenerational transmission in terms of family and care values and ideal care arrangement emerged from intergenerational care preparation. Moreover, the positive role of accumulated family capital generated by a reunion in care preparation and joint decision-making were also identified. The findings of the current study will enhance professionals’ and service providers’ awareness of intergenerational care planning in cross-border migration contexts, inform services to alleviate unpreparedness for elderly care and intergenerational discrepancies concerning care arrangements and broaden family services to encompass intergenerational care planning interventions. Acknowledgment: This study is supported by a General Research Grant from the Research Grants Council of the HKSAR, China (Project Number: 15603818).

Keywords: intergenerational care planning, mainland immigrants in Hong Kong, migrant family, older adults

Procedia PDF Downloads 126

Authors: Justin Woulfe

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

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

Procedia PDF Downloads 160

Authors: Philipp Sommer, Amgad Agoub

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The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Sofia Horjales, Florencia Palma

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Our society is currently experiencing a profound transformation, demanding a proactive response from governmental bodies and higher education institutions to empower the next generation as catalysts for change. Environmental sustainability is rooted in the critical need to maintain the equilibrium and integrity of natural ecosystems, ensuring the preservation of precious natural resources and biodiversity for the benefit of both present and future generations. It is an essential cornerstone of sustainable development, complementing social and economic sustainability. In this evolving landscape, active methodologies take a central role, aligning perfectly with the principles of the 2030 Agenda for Sustainable Development and emerging as a pivotal element of teacher education. The emphasis on active learning methods has been driven by the urgent need to nurture sustainability and instill social responsibility in our future leaders. The Universidad Tecnológica of Uruguay (UTEC) is a public, technologically-oriented institution established in 2012. UTEC is dedicated to decentralization, expanding access to higher education throughout Uruguay, and promoting inclusive social development. Operating through Regional Technological Institutes (ITRs) and associated centers spread across the country, UTEC faces the challenge of remote student populations. To address this, UTEC utilizes e-learning for equal opportunities, self-regulated learning, and digital skills development, enhancing communication among students, teachers, and peers through virtual classrooms. The Interdisciplinary Continuing Education Program is part of the Innovation and Entrepreneurship Department of UTEC. The main goal is to strengthen innovation skills through a transversal and multidisciplinary approach. Within this Program, we have developed a Case of Study and Project-Based Learning Virtual Course designed for university students and open to the broader UTEC community. The primary aim of this course is to establish a strong foundation for comprehending and addressing environmental sustainability issues from an interdisciplinary perspective. Upon completing the course, we expect students not only to understand the intricate interactions between social and ecosystem environments but also to utilize their knowledge and innovation skills to develop projects that offer enhancements or solutions to real-world challenges. Our course design centers on innovative learning experiences, rooted in active methodologies. We explore the intersection of these methods with sustainability and social responsibility in the education of university students. A paramount focus lies in gathering student feedback, empowering them to autonomously generate ideas with guidance from instructors, and even defining their own project topics. This approach underscores that when students are genuinely engaged in subjects of their choice, they not only acquire the necessary knowledge and skills but also develop essential attributes like effective communication, critical thinking, and problem-solving abilities. These qualities will benefit them throughout their lifelong learning journey. We are convinced that education serves as the conduit to merge knowledge and cultivate interdisciplinary collaboration, igniting awareness and instigating action for environmental sustainability. While systemic changes are undoubtedly essential for society and the economy, we are making significant progress by shaping perspectives and sparking small, everyday actions within the UTEC community. This approach empowers our students to become engaged global citizens, actively contributing to the creation of a more sustainable future.

Keywords: active learning, environmental education, project-based learning, soft skills development

Procedia PDF Downloads 71

Authors: Haruka Ando

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Undernutrition of children is a critical issue, especially for people in the remote areas of the Republic of Djibouti, since household food insecurity, inadequate child caring and feeding, unhealthy environment and lack of clean water, as well as insufficient maternal and child healthcare, are underlying causes which affect. Nomadic pastoralists living in the Dikhil region (Dikhil) are socio-economically and geographically more vulnerable due to displacement, which in turn worsens the situation of child stunting. A high prevalence of inappropriate complementary feeding among pastoral mothers might be a significant barrier to child growth. This study aims to identify health promotion intervention strategies that would support an increase in optimal complementary feeding among pastoral mothers of children aged 6-23 months in Dikhil. There are four objectives; to explore and to understand the existing practice of complementary feeding among pastoral mothers in Dikhil; to identify the barriers in appropriate complementary feeding among the mothers; to critically explore and analyse the strategies for an increase in complementary feeding among the mothers; to make pragmatic recommendations to address the barriers in Djibouti. This is an in-depth study utilizing a conceptual framework, the behaviour change wheel, to analyse the determinants of complementary feeding and categorize health promotion interventions for increasing optimal complementary feeding among pastoral mothers living in Dikhil. The analytical tool was utilized to appraise the strategies to mitigate the selected barriers against optimal complementary feeding. The data sources were secondary literature from both published and unpublished sources. The literature was systematically collected. The findings of the determinants including the barriers of optimal complementary feeding were identified: heavy household workload, caring for multiple children under five, lack of education, cultural norms and traditional eating habits, lack of husbands' support, poverty and food insecurity, lack of clean water, low media coverage, insufficient health services on complementary feeding, fear, poor personal hygiene, and mothers' low decision-making ability and lack of motivation for food choice. To mitigate selected barriers of optimal complementary feeding, four intervention strategies based on interpersonal communication at the community-level were chosen: scaling up mothers' support groups, nutrition education, grandmother-inclusive approach, and training for complementary feeding counseling. The strategies were appraised through the criteria of effectiveness and feasibility. Scaling up mothers' support groups could be the best approach. Mid-term and long-term recommendations are suggested based on the situation analysis and appraisal of intervention strategies. Mid-term recommendations include complementary feeding promotion interventions are integrated into the healthcare service providing system in Dikhil, and donor agencies advocate and lobby the Ministry of Health Djibouti (MoHD) to increase budgetary allocation on complementary feeding promotion to implement interventions at a community level. Moreover, the recommendations include a community health management team in Dikhil training healthcare workers and mother support groups by using complementary feeding communication guidelines and monitors behaviour change of pastoral mothers and health outcome of their children. Long-term recommendations are the MoHD develops complementary feeding guidelines to cover sector-wide collaboration for multi-sectoral related barriers.

Keywords: Afar, child food, child nutrition, complementary feeding, complementary food, developing countries, Djibouti, East Africa, hard-to-reach areas, Horn of Africa, nomad, pastoral, rural area, Somali, Sub-Saharan Africa

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Authors: Sitira Williams, Georgina Cherry, Andrea Wright, Kevin Wells, Taran Rai, Richard Brown, Travis Street, Alasdair Cook

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Social media sources (50) were identified, keywords defined by veterinarians and organised into 6 topics known to be indicative of feline pruritus: body areas, behaviors, symptoms, diagnosis, and treatments. These were augmented using academic literature, a cat owner survey, synonyms, and Google Trends. The content was collected using a social intelligence solution, with keywords tagged and filtered. Data were aggregated and de-duplicated. SL content matching body areas, behaviors and symptoms were reviewed manually, and posts were marked relevant if: posted by a pet owner, identifying an itchy cat and not duplicated. A sub-set of 493 posts published from 2009-2022 was used for reflexive thematic analysis in NVIVO (Burlington, MA) to identify themes. Five themes were identified: allergy, pruritus, additional behaviors, unusual or undesirable behaviors, diagnosis, and treatment. Most (258) posts reported the cat was excessively licking, itching, and scratching. The majority were indoor cats and were less playful and friendly when itchy. Half of these posts did not indicate a known cause of pruritus. Bald spots and scabs (123) were reported, often causing swelling and fur loss, and 56 reported bumps, lumps, and dry patches. Other impacts on the cat’s quality of life were ear mites, cat self-trauma and stress. Seven posts reported their cats’ symptoms caused them ongoing anxiety and depression. Cats with food allergies to poultry (often chicken and beef) causing bald spots featured in 23 posts. Veterinarians advised switching to a raw food diet and/or changing their bowls. Some cats got worse after switching, leaving owners’ needs unmet. Allergic reactions to flea bites causing excessive itching, red spots, scabs, and fur loss were reported in 13 posts. Some (3) posts indicated allergic reactions to medication. Cats with seasonal and skin allergies, causing sneezing, scratching, headshaking, watery eyes, and nasal discharge, were reported 17 times. Eighty-five posts identified additional behaviors. Of these, 13 reported their cat’s burst pimple or insect bite. Common behaviors were headshaking, rubbing, pawing at their ears, and aggressively chewing. In some cases, bites or pimples triggered previously unseen itchiness, making the cat irritable. Twenty-four reported their cat had anxiety: overgrooming, itching, losing fur, hiding, freaking out, breathing quickly, sleeplessness, hissing and vocalising. Most reported these cats as having itchy skin, fleas, and bumps. Cats were commonly diagnosed with an ear infection, ringworm, acne, or kidney disease. Acne was diagnosed in cats with an allergy flare-up or overgrooming. Ear infections were diagnosed in itchy cats with mites or other parasites. Of the treatments mentioned, steroids were most frequently used, then anti-parasitics, including flea treatments and oral medication (steroids, antibiotics). Forty-six posts reported distress following poor outcomes after medication or additional vet consultations. SL provides veterinarians with unique insights. Verbatim comments highlight the detrimental effects of pruritus on pets and owner quality of life. This study demonstrates the need for veterinarians to communicate management and treatment options more effectively to relieve owner frustrations. Data analysis could be scaled up using machine learning for topic modeling.

Keywords: content analysis, feline, itch, pruritus, social media, thematic analysis, veterinary dermatology

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Authors: Ramazan Bakir, Gizem Kayar

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It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

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Authors: A. Chandra, M. Arthur, L. Mize, A. Pomeroy-Stevens

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Background: Lower and middle-income countries (LMICs) in Asia face rapid urbanization resulting in both economic opportunities (the urban advantage) and emerging health challenges. Urban health risks are magnified in informal settlements and include infectious disease outbreaks, inadequate access to health services, and poor air quality. Over the coming years, urban spaces in Asia will face accelerating public health risks related to migration, climate change, and environmental health. These challenges are complex and require multi-sectoral and multi-stakeholder solutions. The Building Health Cities (BHC) program is funded by the United States Agency for International Development (USAID) to work with smart city initiatives in the Asia region. BHC approaches urban health challenges by addressing policies, planning, and services through a health equity lens, with a particular focus on informal settlements and migrant communities. The program works to develop data-driven decision-making, build inclusivity through stakeholder engagement, and facilitate the uptake of appropriate technology. Methodology: The BHC program has partnered with the smart city initiatives of Indore in India, Makassar in Indonesia, and Da Nang in Vietnam. Implementing partners support municipalities to improve health delivery and equity using two key approaches: political economy analysis and participatory systems mapping. Political economy analyses evaluate barriers to collective action, including corruption, security, accountability, and incentives. Systems mapping evaluates community health challenges using a cross-sectoral approach, analyzing the impact of economic, environmental, transport, security, health system, and built environment factors. The mapping exercise draws on the experience and expertise of a diverse cohort of stakeholders, including government officials, municipal service providers, and civil society organizations. Results: Systems mapping and political economy analyses identified significant barriers for health care in migrant populations. In Makassar, migrants are unable to obtain the necessary card that entitles them to subsidized health services. This finding is being used to engage with municipal governments to mitigate the barriers that limit migrant enrollment in the public social health insurance scheme. In Indore, the project identified poor drainage of storm and wastewater in migrant settlements as a cause of poor health. Unsafe and inadequate infrastructure placed residents of these settlements at risk for both waterborne diseases and injuries. The program also evaluated the capacity of urban primary health centers serving migrant communities, identifying challenges related to their hours of service and shortages of health workers. In Da Nang, the systems mapping process has only recently begun, with the formal partnership launched in December 2019. Conclusion: This paper explores lessons learned from BHC’s systems mapping, political economy analyses, and stakeholder engagement approaches. The paper shares progress related to the health of migrants in informal settlements. Case studies feature barriers identified and mitigating steps, including governance actions, taken by local stakeholders in partner cities. The paper includes an update on ongoing progress from Indore and Makassar and experience from the first six months of program implementation from Da Nang.

Keywords: informal settlements, migration, stakeholder engagement mapping, urban health

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Authors: Lina Wu

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The excessive discharge of nitrogen in sewage greatly intensifies the eutrophication of water bodies and threatens water quality. Nitrogen pollution control has become a global concern. The concentration of nitrogen in water is reduced by converting ammonia nitrogen, nitrate nitrogen and nitrite nitrogen into nitrogen-containing gas through biological treatment, physicochemical treatment and oxidation technology. However, some wastewater containing high ammonia nitrogen including landfill leachate, is difficult to be treated by traditional nitrification and denitrification because of its high COD content. The core process of denitrification is that denitrifying bacteria convert nitrous acid produced by nitrification into nitrite under anaerobic conditions. Still, its low-carbon nitrogen does not meet the conditions for denitrification. Many studies have shown that the natural autotrophic anammox bacteria can combine nitrous and ammonia nitrogen without a carbon source through functional genes to achieve total nitrogen removal, which is very suitable for removing nitrogen from leachate. In addition, the process also saves a lot of aeration energy consumption than the traditional nitrogen removal process. Therefore, anammox plays an important role in nitrogen conversion and energy saving. The short-range nitrification and denitrification coupled with anaerobic ammoX ensures total nitrogen removal. It improves the removal efficiency, meeting the needs of society for an ecologically friendly and cost-effective nutrient removal treatment technology. In recent years, research has found that the symbiotic system has more water treatment advantages because this process not only helps to improve the efficiency of wastewater treatment but also allows carbon dioxide reduction and resource recovery. Microalgae use carbon dioxide dissolved in water or released through bacterial respiration to produce oxygen for bacteria through photosynthesis under light, and bacteria, in turn, provide metabolites and inorganic carbon sources for the growth of microalgae, which may lead the algal bacteria symbiotic system save most or all of the aeration energy consumption. It has become a trend to make microalgae and light-avoiding anammox bacteria play synergistic roles by adjusting the light-to-dark ratio. Microalgae in the outer layer of light particles block most of the light and provide cofactors and amino acids to promote nitrogen removal. In particular, myxoccota MYX1 can degrade extracellular proteins produced by microalgae, providing amino acids for the entire bacterial community, which helps anammox bacteria save metabolic energy and adapt to light. As a result, initiating and maintaining the process of combining dominant algae and anaerobic denitrifying bacterial communities has great potential in treating landfill leachate. Chlorella has a brilliant removal effect and can withstand extreme environments in terms of high ammonia nitrogen, high salt and low temperature. It is urgent to study whether the algal mud mixture rich in denitrifying bacteria and chlorella can greatly improve the efficiency of landfill leachate treatment under an anaerobic environment where photosynthesis is stopped. The optimal dilution concentration of simulated landfill leachate can be found by determining the treatment effect of the same batch of bacteria and algae mixtures under different initial ammonia nitrogen concentrations and making a comparison. High-throughput sequencing technology was used to analyze the changes in microbial diversity, related functional genera and functional genes under optimal conditions, providing a theoretical and practical basis for the engineering application of novel bacteria-algae symbiosis system in biogas slurry treatment and resource utilization.

Keywords: nutrient removal and recovery, leachate, anammox, Partial nitrification, Algae-bacteria interaction

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Authors: Aastha Arora, Vikas Bhuria, Saurabh Singh, Uma Pathak, Shweta Mathur, Puja P. Hazari, Rajat Sandhir, Ravi Soni, Anant N. Bhatt, Bilikere S. Dwarakanath

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Radiotherapy is an effective curative and palliative option for patients with thoracic malignancies. However, lung injury, comprising of pneumonitis and fibrosis, remains a significant clin¬ical complication of thoracic radiation, thus making it a dose-limiting factor. Also, injury to the lung is often reported as part of multi-organ failure in victims of accidental radiation exposures. Radiation induced inflammatory response in the lung, characterized by leukocyte infiltration and vascular changes, is an important contributing factor for the injury. Therefore, countermeasure agents to attenuate radiation induced inflammatory response are considered as an important approach to prevent chronic lung damage. Although Amifostine, the widely used, FDA approved radio-protector, has been found to reduce the radiation induced pneumonitis during radiation therapy of non-small cell lung carcinoma, its application during mass and field exposure is limited due to associated toxicity and ineffectiveness with the oral administration. The amifostine analogue (DRDE-30) overcomes this limitation as it is orally effective in reducing the mortality of whole body irradiated mice. The current study was undertaken to investigate the potential of DRDE-30 to ameliorate radiation induced lung damage. DRDE-30 was administered intra-peritoneally, 30 minutes prior to 13.5 Gy thoracic (60Co-gamma) radiation in C57BL/6 mice. Broncheo- alveolar lavage fluid (BALF) and lung tissues were harvested at 12 and 24 weeks post irradiation for studying inflammatory and fibrotic markers. Lactate dehydrogenase (LDH) leakage, leukocyte count and protein content in BALF were used as parameters to evaluate lung vascular permeability. Inflammatory cell signaling (p38 phosphorylation) and anti-oxidant status (MnSOD and Catalase level) was assessed by Western blot, while X-ray CT scan, H & E staining and trichrome staining were done to study the lung architecture and collagen deposition. Irradiation of the lung increased the total protein content, LDH leakage and total leukocyte count in the BALF, reflecting endothelial barrier dysfunction. These disruptive effects were significantly abolished by DRDE-30, which appear to be linked to the DRDE-30 mediated abrogation of activation of the redox-sensitive pro- inflammatory signaling cascade, the MAPK pathway. Concurrent administration of DRDE-30 with radiation inhibited radiation-induced oxidative stress by strengthening the anti-oxidant defense system and abrogated p38 mitogen-activated protein kinase activation, which was associated with reduced vascular leak and macrophage recruitment to the lungs. Histopathological examination (by H & E staining) of the lung showed radiation-induced inflammation of the lungs, characterized by cellular infiltration, interstitial oedema, alveolar wall thickening, perivascular fibrosis and obstruction of alveolar spaces, which were all reduced by pre-administration of DRDE-30. Structural analysis with X-ray CT indicated lung architecture (linked to the degree of opacity) comparable to un-irradiated mice that correlated well with the lung morphology and reduced collagen deposition. Reduction in the radiation-induced inflammation and fibrosis brought about by DRDE-30 resulted in a profound increase in animal survival (72 % in the combination vs 24% with radiation) observed at the end of 24 weeks following irradiation. These findings establish the potential of the Amifostine analogue, DRDE-30, in reducing radiation induced pulmonary injury by attenuating the inflammatory and fibrotic responses.

Keywords: amifostine, fibrosis, inflammation, lung injury radiation

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Authors: Priyanka Botny Srinath, Alessandro Suglia, Mel McKendrick

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Background: Organizational cultural studies integrate sociology and anthropology, portraying man as a creator of symbols, languages, beliefs, and ideologies -essentially, a creator and manager of meaning. In our research, we leverage analytical measures to discern whether an organization embodies a singular culture or a myriad of subcultures. Fast-forward to 2023, our research thesis focuses on digitally measuring culture, coining it as the "Work Culture Quotient." This entails conceptually mapping common experiential patterns to provide executives insights into the digital organization journey, aiding in understanding their current position and identifying future steps. Objectives: Finding the new age skills that help in defining the culture; understand the implications of post-COVID effects; derive a digital framework for measuring skillsets. Method: We conducted two comprehensive Delphi studies to distill essential insights. Delphi 1: Through a thematic analysis of interviews with 20 high-level leaders representing companies across diverse regions -India, Japan, the US, Canada, Morocco, and Uganda- we identified 20 key skills critical for cultivating a robust organizational culture. The skills are -influence, self-confidence, optimism, empathy, leadership, collaboration and cooperation, developing others, commitment, innovativeness, leveraging diversity, change management, team capabilities, self-control, digital communication, emotional awareness, team bonding, communication, problem solving, adaptability, and trustworthiness. Delphi 2: Subject matter experts were asked to complete a questionnaire derived from the thematic analysis in stage 1 to formalise themes and draw consensus amongst experts on the most important workplace skills. Results: The thematic analysis resulted in 20 workplace employee skills being identified. These skills were all included in the Delphi round 2 questionnaire. From the outputs, we analysed the data using R Studio for arriving at agreement and consensus, we also used sum of squares method to compare various agreements to extract various themes with a threshold of 80% agreements. This yielded three themes at over 80% agreement (leadership, collaboration and cooperation, communication) and three further themes at over 60% agreement (commitment, empathy, trustworthiness). From this, we selected five questionnaires to be included in the primary data collection phase, and these will be paired with the digital footprints to provide a workplace culture quotient. Implications: The findings from these studies bear profound implications for decision-makers, revolutionizing their comprehension of organizational culture. Tackling the challenge of mapping the digital organization journey involves innovative methodologies that probe not only external landscapes but also internal cultural dynamics. This holistic approach furnishes decision-makers with a nuanced understanding of their organizational culture and visualizes pivotal skills for employee growth. This clarity enables informed choices resonating with the organization's unique cultural fabric. Anticipated outcomes transcend mere individual cultural measurements, aligning with organizational goals to unveil a comprehensive view of culture, exposing artifacts and depth. Armed with this profound understanding, decision-makers gain tangible evidence for informed decision-making, strategically leveraging cultural strengths to cultivate an environment conducive to growth, innovation, and enduring success, ultimately leading to measurable outcomes.

Keywords: leadership, cooperation, collaboration, teamwork, work culture

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