Search results for: cross layer optimization

Authors: Yu-Lin Chen, Kimberly Koester, Marissa Raymond-Flesh, Anika Thapar, Jay Thapar

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Purpose: Effectively communicating adolescent health topics to teens and their parents is crucial. This study emphasizes critically evaluating the optimal use of artificial intelligence tools (AI), which are increasingly prevalent in disseminating health information. By fostering a deeper understanding of AI voice preference in the context of health, the research aspires to have a ripple effect, enhancing the collective health literacy and decision-making capabilities of both teenagers and their parents. This study explores AI voices' potential within health learning modules for annual well-child visits. We aim to identify preferred voice characteristics and understand factors influencing perceived trustworthiness, ultimately aiming to improve health literacy and decision-making in both demographics. Methods: A cross-sectional study assessed preferences and trust perceptions of AI voices in learning modules among teens (11-18) and their parents/guardians in Northern California. The study involved the development of four distinct learning modules covering various adolescent health-related topics, including general communication, sexual and reproductive health communication, parental monitoring, and well-child check-ups. Participants were asked to evaluate eight AI voices across the modules, considering a set of six factors such as intelligibility, naturalness, prosody, social impression, trustworthiness, and overall appeal, using Likert scales ranging from 1 to 10 (the higher, the better). They were also asked to select their preferred choice of voice for each module. Descriptive statistics summarized participant demographics. Chi-square/t-tests explored differences in voice preferences between groups. Regression models identified factors impacting the perceived trustworthiness of the top-selected voice per module. Results: Data from 104 participants (teen=63; adult guardian = 41) were included in the analysis. The mean age is 14.9 for teens (54% male) and 41.9 for the parent/guardian (12% male). At the same time, similar voice quality ratings were observed across groups, and preferences varied by topic. For instance, in general communication, teens leaned towards young female voices, while parents preferred mature female tones. Interestingly, this trend reversed for parental monitoring, with teens favoring mature male voices and parents opting for mature female ones. Both groups, however, converged on mature female voices for sexual and reproductive health topics. Beyond preferences, the study delved into factors influencing perceived trustworthiness. Interestingly, social impression and sound appeal emerged as the most significant contributors across all modules, jointly explaining 71-75% of the variance in trustworthiness ratings. Conclusion: The study emphasizes the importance of catering AI voices to specific audiences and topics. Social impression and sound appeal emerged as critical factors influencing perceived trustworthiness across all modules. These findings highlight the need to tailor AI voices by age and the specific health information being delivered. Ensuring AI voices resonate with both teens and their parents can foster their engagement and trust, ultimately leading to improved health literacy and decision-making for both groups. Limitations and future research: This study lays the groundwork for understanding AI voice preferences for teenagers and their parents in healthcare settings. However, limitations exist. The sample represents a specific geographic location, and cultural variations might influence preferences. Additionally, the modules focused on topics related to well-child visits, and preferences might differ for more sensitive health topics. Future research should explore these limitations and investigate the long-term impact of AI voice on user engagement, health outcomes, and health behaviors.

Keywords: artificial intelligence, trustworthiness, voice, adolescent

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Authors: Gertraud Koch, Teresa Stumpf, Alejandra Tijerina García

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

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

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Authors: Tim Crocker-Buque, Sandra Mounier-Jack, Natasha Howard

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Background: Due to both the increasing scale and speed of urbanisation, urban areas in low and middle-income countries (LMICs) host increasingly large populations of under-immunized children, with the additional associated risks of rapid disease transmission in high-density living environments. Multiple interdependent factors are associated with these coverage disparities in urban areas and most evidence comes from relatively few countries, e.g., predominantly India, Kenya, Nigeria, and some from Pakistan, Iran, and Brazil. This study aimed to identify, describe, and assess the main tools used to measure or improve coverage of immunisation services in poor urban areas. Methods: Authors used a qualitative review design, including academic and non-academic literature, to identify tools used to improve coverage of public health interventions in urban areas. Authors selected and extracted sources that provided good examples of specific tools, or categories of tools, used in a context relevant to urban immunization. Diagnostic (e.g., for data collection, analysis, and insight generation) and programme tools (e.g., for investigating or improving ongoing programmes) and interventions (e.g., multi-component or stand-alone with evidence) were selected for inclusion to provide a range of type and availability of relevant tools. These were then prioritised using a decision-analysis framework and a tool selection guide for programme managers developed. Results: Authors reviewed tools used in urban immunisation contexts and tools designed for (i) non-immunization and/or non-health interventions in urban areas, and (ii) immunisation in rural contexts that had relevance for urban areas (e.g., Reaching every District/Child/ Zone). Many approaches combined several tools and methods, which authors categorised as diagnostic, programme, and intervention. The most common diagnostic tools were cross-sectional surveys, key informant interviews, focus group discussions, secondary analysis of routine data, and geographical mapping of outcomes, resources, and services. Programme tools involved multiple stages of data collection, analysis, insight generation, and intervention planning and included guidance documents from WHO (World Health Organisation), UNICEF (United Nations Children's Fund), USAID (United States Agency for International Development), and governments, and articles reporting on diagnostics, interventions, and/or evaluations to improve urban immunisation. Interventions involved service improvement, education, reminder/recall, incentives, outreach, mass-media, or were multi-component. The main gaps in existing tools were an assessment of macro/policy-level factors, exploration of effective immunization communication channels, and measuring in/out-migration. The proposed framework uses a problem tree approach to suggest tools to address five common challenges (i.e. identifying populations, understanding communities, issues with service access and use, improving services, improving coverage) based on context and available data. Conclusion: This study identified many tools relevant to evaluating urban LMIC immunisation programmes, including significant crossover between tools. This was encouraging in terms of supporting the identification of common areas, but problematic as data volumes, instructions, and activities could overwhelm managers and tools are not always suitably applied to suitable contexts. Further research is needed on how best to combine tools and methods to suit local contexts. Authors’ initial framework can be tested and developed further.

Keywords: health equity, immunisation, low and middle-income countries, poverty, urban health

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Authors: Volker Wannack

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

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

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Authors: Faruk Ozdemir, Roy Kalawsky, Peter Hubbard

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

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

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Authors: Rohini Das, Subhasish Das, Smruti Rekha Sahoo, Shagupta Yesmin

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The Paleoproterozoic Kolhan Group (Purana) ensemble constitutes the youngest lithostratigraphic 'outlier' in the Singhbhum Archaean craton. The Kolhan unconformably overlies both the Singhbhum granite and the Iron Ore Group (IOG). Representing a typical sandstone-shale ( +/- carbonates) sequence, the Kolhan is characterized by the development of thin and discontinuous patches of basal conglomerates draped by sandstone beds. The IOG-fault limits the western 'distal' margin of the Kolhan basin showing evidence of passive subsidence subsequent to the initial rifting stage. The basin evolved as a half-graben under the influence of an extensional stress regime. The assumption of a tectonic setting for the NE-SW trending Kolhan basin possibly relates to the basin opening to the E-W extensional stress system that prevailed during the development of the Newer Dolerite dyke. The Paleoproterozoic age of the Kolhan basin is based on the consideration of the conformable stress pattern responsible both for the basin opening and the development of the conjugate fracture system along which the Newer Dolerite dykes intruded the Singhbhum Archaean craton. The Kolhan sandstones show progressive change towards greater textural and mineralogical maturity in its upbuilding. The trend of variations in different mineralogical and textural attributes, however, exhibits inflections at different lithological levels. Petrological studies collectively indicate that the sandstones were dominantly derived from a weathered granitic crust under a humid climatic condition. Provenance-derived variations in sandstone compositions are therefore a key in unraveling regional tectonic histories. The basin axis controlled the progradation direction which was likely driven by climatically induced sediment influx, a eustatic fall, or both. In the case of the incongruent shift, increased sediment supply permitted the rivers to cross the basinal deep. Temporal association of the Kolhan with tectonic structures in the belt indicates that syn-tectonic thrust uplift, not isostatic uplift or climate, caused the influx of quartz. The sedimentation pattern in the Kolhan reflects a change from braided fluvial-ephemeral pattern to a fan-delta-lacustrine type. The channel geometries and the climate exerted a major control on the processes of sediment transfer. Repeated fault controlled uplift of the source followed by subsidence and forced regression, generated multiple sediment cyclicity that led to the fluvial-fan delta sedimentation pattern. Intermittent uplift of the faulted blocks exposed fresh bedrock to mechanical weathering that generated a large amount of detritus and resulted to forced regressions, repeatedly disrupting the cycles which may reflect a stratigraphic response of connected rift basins at the early stage of extension. The marked variations in the thickness of the fan delta succession and the stacking pattern in different measured profiles reflect the overriding tectonic controls on fan delta evolution. The accumulated fault displacement created higher accommodation and thicker delta sequences. Intermittent uplift of fault blocks exposed fresh bedrock to mechanical weathering, generated a large amount of detritus, and resulted in forced closure of the land-locked basin, repeatedly disrupting the fining upward pattern. The control of source rock lithology or climate was of secondary importance to tectonic effects. Such a retrograding fan delta could be a stratigraphic response of connected rift basins at the early stage of extension.

Keywords: Kolhan basin, petrology, sandstone, tectonics

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Authors: Fatima Saeed, Abdullah Mudassar

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Introduction: Patient safety remains a global priority in the ever-evolving healthcare landscape. At the forefront of this endeavor are the International Patient Safety Goals (IPSGs), a standardized framework designed to mitigate risks and elevate the quality of care. Doctors, positioned as primary caregivers, wield a pivotal role in upholding and adhering to IPSGs, underscoring the critical significance of their knowledge and understanding of these goals. This research embarks on a comprehensive exploration into the depth of Doctors ' comprehension of IPSGs, aiming to unearth potential gaps and provide insights for targeted educational interventions. Established by influential healthcare bodies, including the World Health Organization (WHO), IPSGs represent a universally applicable set of objectives spanning crucial domains such as medication safety, infection control, surgical site safety, and patient identification. Adherence to these goals has exhibited substantial reductions in adverse events, fostering an overall enhancement in the quality of care. This study operates on the fundamental premise that an informed Doctors workforce is indispensable for effectively implementing IPSGs. A nuanced understanding of these goals empowers Doctors to identify potential risks, advocate for necessary changes, and actively contribute to a safety-centric culture within healthcare institutions. Despite the acknowledged importance of IPSGs, there is a growing concern that nurses may need more knowledge to integrate these goals into their practice seamlessly. Methodology: A Comprehensive research methodology covering study design, setting, duration, sample size determination, sampling technique, and data analysis. It introduces the philosophical framework guiding the research and details material, methods, and the analysis framework. The descriptive quantitative cross-sectional study in teaching care hospitals utilized convenient sampling over six months. Data collection involved written informed consent and questionnaires, analyzed with SPSS version 23, presenting results graphically and descriptively. The chapter ensures a clear understanding of the study's design, execution, and analytical processes. Result: The survey results reveal a substantial distribution across hospitals, with 34.52% in MTIKTH and 65.48% in HMC MTI. There is a notable prevalence of patient safety incidents, emphasizing the significance of adherence to IPSGs. Positive trends are observed, including 77.0% affirming the "time-out" procedure, 81.6% acknowledging effective healthcare provider communication, and high recognition (82.7%) of the purpose of IPSGs to improve patient safety. While the survey reflects a good understanding of IPSGs, areas for improvement are identified, suggesting opportunities for targeted interventions. Discussion: The study underscores the need for tailored care approaches and highlights the bio-socio-cultural context of 'contagion,' suggesting areas for further research amid antimicrobial resistance. Shifting the focus to patient safety practices, the survey chapter provides a detailed overview of results, emphasizing workplace distribution, patient safety incidents, and positive reflections on IPSGs. The findings indicate a positive trend in patient safety practices with areas for improvement, emphasizing the ongoing need for reinforcing safety protocols and cultivating a safety-centric culture in healthcare. Conclusion: In summary, the survey indicates a positive trend in patient safety practices with a good understanding of IPSGs among participants. However, identifying areas for potential improvement suggests opportunities for targeted interventions to enhance patient safety further. Ongoing efforts to reinforce adherence to safety protocols, address identified gaps, and foster a safety culture will contribute to continuous improvements in patient care and outcomes.

Keywords: infection control, international patient safety, patient safety practices, proper medication

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Authors: Veenapani Rajeev Verma

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Context: Assessing facility readiness is paramount as it can indicate capacity of facilities to provide essential care for resilience to health challenges. In the context of decentralization, estimation of supply side readiness indices at sub national level is imperative for effective evidence based policy but remains a colossal challenge due to lack of dependable and representative data sources. Setting: District Poonch of Jammu and Kashmir was selected for this study. It is remote, rural district with unprecedented topographical barriers and is identified as high priority by government. It is also a fragile area as is bounded by Line of Control with Pakistan bearing the brunt of cease fire violations, military skirmishes and sporadic militant attacks. Hilly geographical terrain, rudimentary/absence of road network and impoverishment are quintessential to this area. Objectives: Objective of the study is to a) Evaluate the service readiness of health facilities and create a concise index subsuming plethora of discrete indicators and b) Ascertain supply side barriers in service provisioning via stakeholder’s analysis. Study also strives to expand analytical domain unravelling context and area specific intricacies associated with service delivery. Methodology: Mixed method approach was employed to triangulate quantitative analysis with qualitative nuances. Facility survey encompassing 90 Subcentres, 44 Primary health centres, 3 Community health centres and 1 District hospital was conducted to gauge general service availability and service specific availability (depth of coverage). Compendium of checklist was designed using Indian Public Health Standards (IPHS) in form of standard core questionnaire and scorecard generated for each facility. Information was collected across dimensions of amenities, equipment, medicines, laboratory and infection control protocols as proposed in WHO’s Service Availability and Readiness Assesment (SARA). Two stage polychoric principal component analysis employed to generate a parsimonious index by coalescing an array of tracer indicators. OLS regression method used to determine factors explaining composite index generated from PCA. Stakeholder analysis was conducted to discern qualitative information. Myriad of techniques like observations, key informant interviews and focus group discussions using semi structured questionnaires on both leaders and laggards were administered for critical stakeholder’s analysis. Results: General readiness score of health facilities was found to be 0.48. Results indicated poorest readiness for subcentres and PHC’s (first point of contact) with composite score of 0.47 and 0.41 respectively. For primary care facilities; principal component was characterized by basic newborn care as well as preparedness for delivery. Results revealed availability of equipment and surgical preparedness having lowest score (0.46 and 0.47) for facilities providing secondary care. Presence of contractual staff, more than 1 hr walk to facility, facilities in zone A (most vulnerable) to cross border shelling and facilities inaccessible due to snowfall and thick jungles was negatively associated with readiness index. Nonchalant staff attitude, unavailability of staff quarters, leakages and constraint in supply chain of drugs and consumables were other impediments identified. Conclusions/Policy Implications: It is pertinent to first strengthen primary care facilities in this setting. Complex dimensions such as geographic barriers, user and provider behavior is not under precinct of this methodology.

Keywords: effective coverage, principal component analysis, readiness index, universal health coverage

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Authors: Chiu-Yin Leung

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This research investigates a complex assemblage among indigenous identities, socio-political organization and national apparatus in the border landscape of post-colonial Hong Kong. This former British colony had designated a transient mode of governance in its New Territories and particularly the northernmost borderland in 1951-2012. With a discriminated system of land provisions for the indigenous villagers, the place has been inherited with distinctive village-based culture, historic monuments and agrarian practices until its sovereignty return into the People’s Republic of China. In its latest development imperatives by the national strategic planning, the frontier area of Hong Kong has been identified as a strategy site for regional economic integration in South China, with cross-border projects of innovation and technology zones, mega-transport infrastructure and inter-jurisdictional arrangement. Contemporary literature theorizes borders as the material and discursive production of territoriality, which manifest in state apparatus and the daily lives of its citizens and condense in the contested articulations of power, security and citizenship. Drawing on the concept of assemblage, this paper attempts to tract how the border regime and infrastructure in Hong Kong as a city are deeply ingrained in the everyday lived spaces of the local communities but also the changing urban and regional strategies across different longitudinal moments. Through an intensive ethnographic fieldwork among the borderland villages since 2008 and the extensive analysis of colonial archives, new development plans and spatial planning frameworks, the author navigates the genealogy of the border landscape in Ta Kwu Ling frontier area and its implications as the milieu for new state space, covering heterogeneous fields particularly in indigenous rights, heritage preservation, rural sustainability and regional economy. Empirical evidence suggests an apparent bias towards indigenous power and colonial representation in classifying landscape values and conserving historical monuments. Squatter and farm tenants are often deprived of property rights, statutory participation and livelihood option in the planning process. The postcolonial bureaucracies have great difficulties in mobilizing resources to catch up with the swift, political-first approach of the mainland counterparts. Meanwhile, the cultural heritage, lineage network and memory landscape are not protected altogether with any holistic view or collaborative effort across the border. The enactment of land resumption and compensation scheme is furthermore disturbed by lineage-based customary law, technocratic bureaucracy, intra-community conflicts and multi-scalar political mobilization. As many traces of colonial misfortune and tyranny have been whitewashed without proper management, the author argues that postcolonial justice is yet reconciled in this fragmented border landscape. The assemblage of border in mainstream representation has tended to oversimplify local struggles as a collective mist and setup a wider production of schizophrenia experiences in the discussion of further economic integration among Hong Kong and other mainland cities in the Pearl River Delta Region. The research is expected to shed new light on the theorizing of border regions and postcolonialism beyond Eurocentric perspectives. In reassembling the borderland experiences with other arrays in state governance, village organization and indigenous identities, the author also suggests an alternative epistemology in reconciling socio-spatial differences and opening up imaginaries for positive interventions.

Keywords: heritage conservation, indigenous communities, post-colonial borderland, regional development, rural sustainability

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Authors: Kristina F. Wolff

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

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

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

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

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

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Authors: Alba Prats-Bisbe, Jaume López-Carballo, David Leno-Colorado, Alberto García Molina, Alicia Romero Marquez, Elena Hernández Pena, Eloy Opisso Salleras, Raimon Jané Campos

Abstract:

Neurological disorders are a leading cause of disability and premature mortality worldwide. Neurorehabilitation (NRHB) is a clinical process aimed at reducing functional impairment, promoting societal participation, and improving the quality of life for affected individuals. Virtual reality (VR) technology is emerging as a promising NRHB support tool. Its immersive nature fosters a strong sense of agency and embodiment, motivating patients to engage in meaningful tasks and increasing adherence to therapy. However, the clinical benefits of VR interventions are challenging to determine due to the high heterogeneity among health applications. This study explores a stepwise development approach for creating VR-based tools to assist individuals with neurological disorders in medical practice, aiming to enhance reproducibility, facilitate comparison, and promote the generalization of findings. Building on previous research, the step-by-step methodology encompasses: Needs Identification– conducting cross-disciplinary meetings to brainstorm problems, solutions, and address barriers. Intervention Definition– target population, set goals, and conceptualize the VR system (equipment and environments). Material Selection and Placement– choose appropriate hardware and software, place the device within the hospital setting, and test equipment. Co-design– collaboratively create VR environments, user interfaces, and data management strategies. Prototyping– develop VR prototypes, conduct user testing, and make iterative redesigns. Usability and Feasibility Assessment– design protocols and conduct trials with stakeholders in the hospital setting. Efficacy Assessment– conduct clinical trials to evaluate outcomes and long-term effects. Cost-Effectiveness Validation– assess reproducibility, sustainability, and balance between costs and benefits. NRHB is complex due to the multifaceted needs of patients and the interdisciplinary healthcare architecture. VR has the potential to support various applications, such as motor skill training, cognitive tasks, pain management, unilateral spatial neglect (diagnosis and treatment), mirror therapy, and ecologically valid activities of daily living. Following this methodology was crucial for launching a VR-based system in a real hospital environment. Collaboration with neuropsychologists lead to develop A) a VR-based tool for cognitive rehabilitation in patients with acquired brain injury (ABI). The system comprises a head-mounted display (HTC Vive Pro Eye) and 7 tasks targeting attention, memory, and executive functions. A desktop application facilitates session configuration, while database records in-game variables. The VR tool's usability and feasibility were demonstrated in proof-of-concept trials with 20 patients, and effectiveness is being tested through a clinical protocol with 12 patients completing 24-session treatment. Another case involved collaboration with nurses and paediatric physiatrists to create B) a VR-based distraction tool during invasive techniques. The goal is to alleviate pain and anxiety associated with botulinum toxin (BTX) injections, blood tests, or intravenous placements. An all-in-one headset (HTC Vive Focus 3) deploys 360º videos to improve the experience for paediatric patients and their families. This study presents a framework for developing clinically relevant and technologically feasible VR-based support tools for hospital settings. Despite differences in patient type, intervention purpose, and VR system, the methodology demonstrates usability, viability, reproducibility and preliminary clinical benefits. It highlights the importance approach centred on clinician and patient needs for any aspect of NRHB within a real hospital setting.

Keywords: neurological disorders, neurorehabilitation, stepwise development approach, virtual reality

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