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Measuring change and location of informal settlements at a national level:The Argentinian case
No full textToday, there is a consensus that informal settlements continue to expand in both area and population. These settlements are often associated with large cities, such as Dharavi in Mumbai and Kibera in Nairobi. However, secondary cities, rather than megacities, are the epicenters of population growth and urban expansion. The lack of reliable and consistent data, both globally and nationally, has hindered accurate measurement of whether informal settlements are also growing rapidly in secondary cities. This research project analyzes the growth rates of informal settlement areas and populations in Argentina at the national scale from 2016 to 2023, using RENABAP's quantitative and qualitative survey data combined with Earth Observation-based data. We found that the entire sample of informal settlements in Argentina continues to grow at an annual rate of 1.79%. More importantly, informal areas are more prominent and expanding at a larger scale in the less populated cities of the country. Our study confirms, at a national scale, that secondary and smaller cities have a higher number of informal settlements and faster growth rates than primary and larger cities. The scale of this difference should be alarming, prompting a reevaluation of how this compares to global trends in informal settlements. This is fundamental for allocating resources and shaping urban policy globally, especially to meet the needs of informal dwellers
Conceptualizing a Capability-Mapping Method for Systems Engineering Readiness in SMEs
No full textThis paper introduces a capability-driven mapping method designed to bridge SMEs challenges to SE knowledge. This enables SMEs to adopt SE within the context of Systems of Systems (SoS) environments. The method uses a self-assessment tool to identify challenges in SMEs' Design and Development Processes, focusing on challenges caused by characteristics such as uncertainty and ambiguity. These challenges are mapped to SE knowledge, practices, and methodologies, offering actionable advice to improve SMEs' technical capabilities, process maturity, and strategic alignment. Although the method is currently theoretical, future work will focus on empirical validation to refine and adapt this for diverse SME contexts. This paper proposes a practical solution for SMEs to systematically assess, improve, and integrate SE practices, ultimately strengthening their ability to participate in complex SoS projects
Effect of noise control treatments on surfaces near a non-uniform inflow propeller
Full text linkWith the advent of urban air mobility and distributed electric propulsion in aviation, effective noise mitigation for propeller systems has become critical. This study explores the application of noise-mitigating materials in the bottom wall of UTwente's wind tunnel test section, beneath a non-shrouded propeller subject to non-uniform inflow. The objective was to assess the impact of these materials on tonal noise reduction, emitted noise levels, and directivity. Two materials were tested: arrays of additive-manufactured quarter-wavelength resonators (band-stop mitigator) and a slab of metal foam (broadband mitigator). Various geometrical configurations were investigated for the resonators, with the optimal configuration placing resonators everywhere except directly beneath the propeller blades. Applying resonators immediately underneath the propeller, with a critical clearance, induced a spurious hydrodynamic interaction, amplifying tonal noise at higher frequencies. The efficiency of the quarter-wavelength-resonator solution depends heavily on configuration. Performance was compared with a flat plate and the metal foam, with the tuned resonators outperforming the broadband material in noise reduction. The polar directivity of the emitted sound is influenced by the configuration, and the presence of any sound-mitigating material underneath the propeller consistently degrades upstream azimuthal directivity
Unpacking productive dialogues as building blocks of dynamic capabilities for sustainability-oriented innovation
No full textFirms are increasingly pursuing Sustainability-Oriented Innovation (SOI) in response to stakeholder and regulatory pressures. Achieving SOI depends on dynamic capabilities (DCs)—the abilities to sense, seize, and transform. Although previous research highlights the role of productive dialogues in enabling DCs, it has focused primarily on intrafirm interactions and emphasized dialogue quality over content, overlooking the importance of interorganizational exchanges. This study addresses these gaps through a qualitative case study of four European manufacturing firms. We identify three types of productive dialogues—with external stakeholders, within the supply chain and within the organization—that support different phases of the SOI process. Each type centers on specific issues and contributes uniquely to sensing, seizing, and transforming. Our findings refine the concept of productive dialogue by explicitly focusing on interfirm dialogues, the contents of these dialogues, and the necessary outcomes of these dialogues to foster SOI
Common European Data Spaces in Health Care:A Privacy-Preserving Ecosystem for Cancer Research
No full textThe Dutch healthcare system faces significant challenges, including rising costs, administrative inefficiencies, and increasing pressure on the workforce. The European Health Data Space (EHDS) offers a promising solution to support data sharing for research and innovation while preserving data privacy and sovereignty. This paper outlines a technical and organizational framework for implementing privacy-preserving data sharing in cancer research. The proposed infrastructure leverages a combination of federated learning, multi-party computation, and FAIR Data Points to enable decentralized analysis of real-world health data. Key challenges, such as balancing data utility and privacy, are addressed through governance structures, including data permit management, certification processes, and rigorous identity management. The approach also considers the difficulties in sharing high-dimensional data while maintaining both privacy and usability. By integrating standardization efforts, privacy-enhancing technologies, and robust governance models, the framework aligns with the EHDS vision for a secure, interoperable, and patient-centric data ecosystem. This paper thus contributes to advancing cancer research through responsible secondary use of health data, fostering trust among stakeholders, and enabling the development of innovative healthcare solutions while ensuring compliance with GDPR and other relevant regulations.</p
AutoSV-Annotator:Integrating Deductive and Automatic Software Verification
No full textSoftware model checking and deductive software verification have complementary strengths and weaknesses: software model checkers are more straight-forward to use, as they analyze the program without user input; but they do not yet support complicated data structures and expressive specifications. In contrast, deductive verifiers can verify expressive specifications and complex data structures modularly, but they require the user to specify the program behavior in detail, which is a time-consuming process. Due to their differing nature, the two approaches usually remain separate. However, for industrial usage, one requires both: ease of use as well as expressiveness. Therefore, we present AutoSV-Annotator, a toolchain that integrates the two approaches for C programs. The toolchain allows a user to iteratively refine the deductive annotations in a C program, calling a model checker to supplement the annotations at each iteration, guided by the already existing annotations. We show that our tool is able to annotate and prove many tasks from the SV-Benchmarks set. Our results show that the two strategies can indeed benefit from each other
Electrically Tunable Capacitor for EMC Band-Stop Filters
No full textBand-Stop filters can be used to replace bulky low-pass filters in specific applications, particularly with frequencies up to 150 kHz. The use of a tunable capacitor could greatly improve the performance of such band-stop filters by tuning its resonant frequency. Tunable capacitors are widely utilized in radio-communication systems but are therefore designed specifically for high-frequency and low-power applications. However, the use of these specific components for EMC applications below 150 kHz is not possible since it focuses on low-frequency and high-power systems. Multilayer ceramic capacitors could be well suited for such applications because they can provide high capacitance values, high voltage ratings, and exhibit significant reduction in capacitance when a DC bias voltage is applied. This generally unwanted capacitor property will be explored in this study for its potency to influence the resonance frequency of a tunable band-stop filter. The capacitors showed a reduction in capacitance of up to 70% using a bias voltage ranging from 0 V to 40 V. This reduction in capacitance allowed the band-stop filter to achieve a resonance frequency ranging from 87 kHz to 134 kHz with insertion loss of 17 dB to 23 dB.</p
Ethical Considerations in AI-Based Brain Tumour Diagnosis
No full textArtificial intelligence has really transformed medical diagnosis in brain tumours by changing the direction of medical imaging. This study compares the performances of two AI models, YOLO and Roboflow, in the detection and classification of tumours. YOLO showed high accuracy and speed in tumour detection but faced difficulties when it came to small or irregularly shaped tumours, especially low-grade gliomas. Roboflow did very well in multi label classification which is necessary to distinguish types of tumors. That is good, for example, to differentiate between meningiomas versus pituitary tumours, whereas not so good in the case of heterogeneous gliomas. Hence, these are complementary strengths that can be combined to help improve diagnostic workflows. Besides the technical performances, important ethical challenges were pointed out such as biased dataset imbalances, risks to patient privacy, unclear accountability in the case of diagnostic errors, and opacity of model decision-making. Proposed solutions include diversification of datasets, privacy-preserving techniques such as federated learning, accountability frameworks, and explainable AI. These findings emphasize the need for a multidisciplinary approach that integrates technical innovation with ethical safeguards, ensuring the equitable and trustworthy application of AI in clinical practice, while improving diagnostic accuracy and patient outcomes in neuro-oncology.<br/
Emergence of Intrinsic One-Dimensional Excitons in Colloidal Bi13S18I2 Nanocrystals
No full textWe present a synthesis method for colloidal nanocrystals exhibiting a one-dimensional Peierls-like distortion in the form of size-tunable colloidal and monodisperse Bi13S18I2 nanorods. The Bi13S18I2 nanorods exhibit an absorption onset around 1.6 eV and an excitonic transition around 1.1 eV. First-principles calculations demonstrate that this intrinsic excitonic transition originates from one-dimensional excitons localized in the Bi2+ columns formed within the Bi13S18I2 lattice. In these columns, a Peierls-like distortion results in Bi2+ dimerization and the formation of a Peierls bandgap, which is intrinsic to Bi13S18I2. This work demonstrates an exciting approach to induce excitonic properties in semiconductors without relying on traditional quantum confinement strategies, as well as opportunities to explore the spontaneous inherent symmetry breaking in nanocrystals. The Bi13S18I2 nanorods also highlight the important role of colloidal chemistry in the discovery of complex materials and their optical properties and motivate further exploration of metal chalcohalide nanocrystals
Applying (semi-)automatic metadata to early modern normative texts. :Annif and <i>Policeygesetzgebung</i> from the City-State of Bern (1528–1798)
No full textThis study investigates the application of modern digital tools to analyze handwritten normative texts from the City-State of Bern (1528-1798). By leveraging the Simple Knowledge Organization System (SKOS) and automatic metadata generation tools such as Transkribus for Handwritten Text Recognition (HTR) and Annif for automated subject indexing, we aim to enhance the efficiency and accuracy of historical text analysis. Our methodology involves digitizing 4,550 police ordinances, manually segmenting them, and employing a hierarchical SKOS framework with 1,830 distinct labels (Rhonda Organisation 2024). Annif’s backends, including TF-IDF, Umikuji Parabel, Umikuji Bonsai, and Machine Learning Language Model, were evaluated using Normalized Discounted Cumulative Gain (NDCG) metrics to generate relevant metadata. The results demonstrate that the Umikuji backends achieved high NDCG scores, highlighting their effectiveness. This research highlights the transformative potential of integrating digital tools in the humanities, providing a scalable solution for managing large historical datasets and enhancing access to historical texts. The findings advocate for broader adoption of these technologies in historical research, promoting greater collaboration and innovation. Future research will explore the application of these methods to other historical corpora and additional backend systems