Common Frame Of Reference Research Articles

Operational resilience implementation: Challenges and opportunities for UK building societies

Operational resilience is the preparedness and existence of resilient IT systems, processes and resources to provide services continuously during a disruption. This study examines the operational resilience implementation challenges and opportunities for UK building societies and wider financial institutions. The key challenges are resource constraints, understanding regulatory requirements, supplier concerns, domain knowledge, legacy systems and manual-driven processes. Some challenges are being addressed with awareness and training, improved governance and risk management, recruitment and industry support networks. The opportunities include realising the actual state of IT systems, adopting cloud solutions, resources and capabilities, as well as improved domain knowledge and a better understanding of services and markets. Regulators need to be more explicit about their expectations and requirements, while the industry needs to collaborate on setting up common frames of reference for operational resilience frameworks. Lastly, the study provides a holistic view of operational resilience, including its implementation and management challenges, control measures and emerging opportunities.

Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing

Spiking neural networks and neuromorphic hardware platforms that simulate neuronal dynamics are getting wide attention and are being applied to many relevant problems using Machine Learning. Despite a well-established mathematical foundation for neural dynamics, there exists numerous software and hardware solutions and stacks whose variability makes it difficult to reproduce findings. Here, we establish a common reference frame for computations in digital neuromorphic systems, titled Neuromorphic Intermediate Representation (NIR). NIR defines a set of computational and composable model primitives as hybrid systems combining continuous-time dynamics and discrete events. By abstracting away assumptions around discretization and hardware constraints, NIR faithfully captures the computational model, while bridging differences between the evaluated implementation and the underlying mathematical formalism. NIR supports an unprecedented number of neuromorphic systems, which we demonstrate by reproducing three spiking neural network models of different complexity across 7 neuromorphic simulators and 4 digital hardware platforms. NIR decouples the development of neuromorphic hardware and software, enabling interoperability between platforms and improving accessibility to multiple neuromorphic technologies. We believe that NIR is a key next step in brain-inspired hardware-software co-evolution, enabling research towards the implementation of energy efficient computational principles of nervous systems. NIR is available at neuroir.org

Spiritual care competencies in pre-graduate medical and nursing education

Abstract Context: Current research in the field of spiritual care (SC) is constantly encouraging pre- and postgraduate training, particularly in medicine and nursing. Several reference frameworks have been produced to support this teaching since the 2000’s. Methods: This narrative review first identifies the spiritual care competencies (SCCs) currently taught during pre-graduate nursing and medical science education in state-of-research studies. The competencies mentioned in the two reference frameworks identified as authoritative are then compared with this current and actual teaching. Specificities of each discipline are highlighted through this comparison. Results: Similar competencies form a mainstream of SC teaching in the literature. For the vast majority, it appears to be a set of transdisciplinary competencies. Intrapersonal spirituality competencies are considered decisive. Some particularities of the medical framework open up a very specific field of reflection, including the role of the physician (identity development) and the meaning (and spirituality) of work. Conclusion: Adding a complement to the competencies reference frameworks that includes identity development would be better suited to sustain students’ inner growth. A common frame of reference for nursing and medical education is conceivable, although the aims of SC in both fields need to be clarified.

Automated extrinsic calibration of solid-state frame LiDAR sensors with non-overlapping field of view for monitoring indoor stockpile storage facilities

Several industrial and commercial bulk material management applications rely on accurate, current stockpile volume estimation. Proximal imaging and LiDAR sensing modalities can be used to derive stockpile volume estimates in outdoor and indoor storage facilities. Among available imaging and LiDAR sensing modalities, the latter is more advantageous for indoor storage facilities due to its ability to capture scans under poor lighting conditions. Evaluating volumes from such sensing modalities requires the pose (i.e., position and orientation) parameters of the used sensors relative to a common reference frame. For outdoor facilities, a Global Navigation Satellite System (GNSS) combined with an Inertial Navigation System (INS) can be used to derive the sensors’ pose relative to a global reference frame. For indoor facilities, GNSS signal outages will not allow for such capability. Prior research has developed strategies for establishing the sensor position and orientation for stockpile volume estimation while relying on multi-beam spinning LiDAR units. These approaches are feasible due to the large range and Field of View (FOV) of such systems that can capture the internal surfaces of indoor storage facilities.The mechanical movement of multi-beam spinning LiDAR units together with the harsh conditions within indoor facilities (e.g., excessive humidity, wide range of temperature variation, dust, and corrosive environment in deicing salt storage facilities) limit the use of such systems. With the increasing availability of solid-state LiDAR units, there is an interest in exploring their potential for stockpile volume estimation. Despite their higher robustness to harsh conditions, solid-state LiDAR units have shorter distance measurement range and limited FOV when compared with multi-beam spinning LiDAR. This research presents a strategy for the extrinsic calibration (i.e., estimating the relative pose parameters) of installed solid-state LiDAR units inside stockpile storage facilities. The extrinsic calibration is made possible using deployed spherical targets and a complete, reference scan of the facility from another LiDAR sensing modality. The proposed research introduces strategies for: 1) automated extraction of the spherical targets; 2) automated matching of these targets in the solid-state LiDAR and reference scans using invariant relationships among them; and 3) coarse-to-fine estimation of the calibration parameters. Experimental results in several facilities have shown the feasibility of using the proposed methodology to conduct the extrinsic calibration and volume evaluation with an error percentage less than 3.5% even with occlusion percentages reaching up to 50%.

Hawala in criminal court: the role of law and commercial culture in informal financial exchange

A historically informed understanding of ḥawāla and other varieties of informal value transfer systems (IVTS) requires consideration of the normative and cultural elements which structure and facilitate transactions in globalized financial markets. This paper argues that the Sharia-based normative and cultural framework of ḥawāla is created in the social relations of Muslim networks and that, in a criminal law context, this normativity can be used as a tool to discern between legitimate and illegitimate transactions. The new institutional economists’ (NIE) explanation of ḥawāla, which predominates in scholarly work, neglects this common frame of reference built on community, shared belief, and normative rules and expectations. The NIE views economic institutions through the lens of profitmaking and self-interest centred institutional development. Moreover, in a criminal law context, the profit-oriented perspective of law overlooks the normative characteristics that sometimes appear in the transactional characteristics of these transactions. When evidence of these characteristics is presented to the court, they offer a useful tool to differentiate legitimate from illegitimate transfers of value. Legitimate transfers will frequently be facilitated through dense networks in which the normativity and culture of ḥawāla frame the rules and expectations of parties to the transaction. Criminal transactions, on the other hand, typically involve fewer participants, sometimes from different ethnic and linguistic backgrounds, are profit-orientated, and involve means of enforcement such as the use of violence which traditional networks do not employ. The NIE perspective does not fully account for non-western legal orders or for commercial practices in which exchange remains culturally, historically, and socially embedded.

Consumer Protection Safeguards after the AI Act

The long-awaited introduction of the AI Act, notwithstanding its originality, does not introduce any regulation outside the existing framework. It supplements the safeguards provided in numerous sectors of the EU legislation, inter alia, consumer protection. An examination of the basic EU law along with national legislation of the most influential legal orders, i.e. the French and German one, and model rules of the Draft Common Frame of Reference (DCFR)confirms that the new AI Act sheds light on pre-existing vague legal concepts. In this respect, this novel piece of legislation promotes a better understanding of traditional notions of law applicable to the modern digital reality without introducing totally new rules. Accordingly, certainty of law is reinforced where consumer protection had languished, not because of legislative shortage, but for facts and situations described as necessary conditions of certain rights were contested on the basis of contrary possible interpretations of decisive terms. Ultimately, the very importance of the AI act regarding consumer protection lies not in the introduction of new rights and obligations, but in a multiple practical assistance to the implementation of existing rules adjusting thus the traditional legal concepts with technological development beyond their original scope.

Is inclusive education for children with special educational needs and disabilities an impossible dream?

Countries have been implementing inclusive educational practices for children with special educational needs and disabilities (SEND) for at least 30 years. Some issues continue to present as unresolved and will be examined in this paper with possible ways forward suggested. 1. There is still a lack of clarity around the definition of inclusion, its theoretical underpinnings, its implementation in practice and evaluation of success. 2. Teachers often still report the same problems of insufficient resources and express the same concerns about lack of skills and knowledge as reported in the early days. 3. A key question is, do children with SEND achieve better outcomes in inclusive educational settings? The paper argues that an overarching executive framework applied to the education of children with SEND is needed to provide a common frame of reference that can be shared by educators, policymakers and researchers. New ways of resourcing inclusion are discussed including supporting collaboration between mainstream and special schools to better utilize the expertise located in special schools. The paper examines the evidence for improved academic and social outcomes for learners with SEND in inclusive schools and proposes that psychological outcomes now need to be measured too. It further suggests that future research needs to drill down to the level of teacher classroom instruction rather than rely on the broader mainstream school-special school comparison.

The ways of creating a trust

This article explores the ways of creating a trust, according to Article 2074 of the Civil Code of the Republic of Moldova. To shed light on the legislative inspiration and the distinct characteristics of various methods of establishment, a comparative analysis is conducted concerning the provisions outlined in Book X (Trusts) of the Draft Common Frame of Reference, as well as the Civil Codes of the Province of Quebec, France, Romania, and the Republic of Moldova. The discussion emphasizes the ways for voluntarily creating a trust, namely by contract, unilateral declaration, and will, all of which are comprehensively regulated. Additionally, the article addresses the mechanism of creating a trust through administrative act or court decision, situations that necessitate explicit legislative regulation before implementation. The paper also delves into the relationship between ‘law’ and ‘administrative act’ as sources of trusts, presenting a hypothesis that the legislator intentionally substituted this term in the legislation of the Republic of Moldova.

Disentangling reference frames in the neural compass.

Abstract The neural system that encodes heading direction in humans can be found in the medial and superior parietal cortex and the entorhinal-retrosplenial circuit. However, it is still unclear whether heading direction in these different regions is represented within an allocentric or egocentric coordinate system. To investigate this problem, we first asked whether regions encoding (putatively) allocentric facing direction also encode (unambiguously) egocentric goal direction. Second, we assessed whether directional coding in these regions scaled with the preference for an allocentric perspective during everyday navigation. Before the experiment, participants learned different object maps in two geometrically similar rooms. In the MRI scanner, their task was to retrieve the egocentric position of a target object (e.g., Front, Left) relative to an imagined facing direction (e.g., North, West). Multivariate analyses showed, as predicted, that facing direction was encoded bilaterally in the superior parietal lobule (SPL), the retrosplenial complex (RSC), and the left entorhinal cortex (EC), a result that could be interpreted both allocentrically and egocentrically. Crucially, we found that the same voxels in the SPL and RSC also coded for egocentric goal direction but not for allocentric goal direction. Moreover, when facing directions were expressed as egocentric bearings relative to a reference vector, activities for facing direction and egocentric goal direction were correlated, suggesting a common reference frame. Besides, only the left EC coded allocentric goal direction as a function of the subject’s propensity to use allocentric strategies. Altogether, these results suggest that heading direction in the superior and medial parietal cortex is mediated by an egocentric code, whereas the entorhinal cortex encodes directions according to an allocentric reference frame.

Case-Based Collaborative Learning in Undergraduate Radiology Teaching—Are Essential Conditions for Group Discussions Met?

BackgroundDelivering case-based collaborative learning (cCBL) at scale using technology that both presents the clinical problem authentically and seeks to foster quality group discussion is a challenge, especially argumentation which is critical for effective learning. The aim of this study was to investigate the presence of essential conditions to capitalise on a technology-enhanced cCBL scenario for teaching radiology and facilitating quality group discussion. MethodsA questionnaire was administered to 114 fourth-year medical students who completed a technology-enhanced cCBL scenario for teaching neuroradiology. It consisted of individual online pre-class work and face-to-face in-class work, where group discussion followed individual work at a workstation. Items from the ‚Heedful Interrelating in Collaborative Educational Settings‘ scale and ‚positive emotional engagement‘ questionnaire assessed the quality of social-cognitive processes and emotional engagement during the group discussions. Structured interviews were used to explore the teachers’ awareness of and engagement with the technology. ResultsThe mean scores of most,heedfulness’ items were below 3.5 (7-point scale), suggesting that participants did not enter the debriefing with a mindset conducive for argumentation. However, for the affective states 'interest' and 'enjoyment' the mean scores were above 5. Free text comments suggested participants enjoyed the superficial interactions, but did not necessarily engage in argumentation. Structured interviews revealed teachers were aware of the possibilities of the learning dashboard and used it as a common frame of reference, but didn't really succeed to use it as a springboard for discussion. ConclusionsA technology-enhanced cCBL scenario is useful for teaching radiology in undergraduate medical education, but the added value of acquiring in-depth knowledge will only be achieved when students are aware of the importance of an ‚heedful’ mind-set.

Macaque Brainnetome Atlas: A multifaceted brain map with parcellation, connection, and histology

The rhesus macaque (Macaca mulatta) is a crucial experimental animal that shares many genetic, brain organizational, and behavioral characteristics with humans. A macaque brain atlas is fundamental to biomedical and evolutionary research. However, even though connectivity is vital for understanding brain functions, a connectivity-based whole-brain atlas of the macaque has not previously been made. In this study, we created a new whole-brain map, the Macaque Brainnetome Atlas (MacBNA), based on the anatomical connectivity profiles provided by high angular and spatial resolution ex vivo diffusion MRI data. The new atlas consists of 248 cortical and 56 subcortical regions as well as their structural and functional connections. The parcellation and the diffusion-based tractography were evaluated with invasive neuronal-tracing and Nissl-stained images. As a demonstrative application, the structural connectivity divergence between macaque and human brains was mapped using the Brainnetome atlases of those two species to uncover the genetic underpinnings of the evolutionary changes in brain structure. The resulting resource includes: (1) the thoroughly delineated Macaque Brainnetome Atlas (MacBNA), (2) regional connectivity profiles, (3) the postmortem high-resolution macaque diffusion and T2-weighted MRI dataset (Brainnetome-8), and (4) multi-contrast MRI, neuronal-tracing, and histological images collected from a single macaque. MacBNA can serve as a common reference frame for mapping multifaceted features across modalities and spatial scales and for integrative investigation and characterization of brain organization and function. Therefore, it will enrich the collaborative resource platform for nonhuman primates and facilitate translational and comparative neuroscience research.

Redefining Hallin and Mancini’s Media System: Cross-Border Investigative Networks in Europe

This article analyses how cross-border investigative journalism (CBIJ) has expanded the parameters of the media system described by Hallin and Mancini (2004), with the addition of new indicators to adapt it to the paradigm of global convergent media. To this end, it examines how this type of journalism has been conceptualised in Europe as a result of the forums articulated at Dataharvest (the European Investigative Journalism Conference). A quantitative method is applied with text mining techniques to analyse the frequency, associations, and groupings of terms mentioned in the sessions offered from 2014 to 2023. To classify the language units, the variables of CBIJ’s economic model, its thematic relationship with national contexts, and its professional practices are used. The results reveal a clear predominance of the word “data,” reflecting Dataharvest’s particular interest in the dynamics of data processing, which has become an essential part of the work in these networks. An analysis of organisational culture reveals that high-profile associations play a more important role in collaborative projects than less institutionalised networks. The business model encourages non-profit organisations that depend on foundations to support their work. In thematic terms, CBIJ projects address topics emerging in the supranational space, offered with a common frame of reference for multiple countries. These networks necessitate a redefinition of the model defined in 2004, as they have developed qualities of their own in relation to the business model they adopt, the transnational orientation of reporters, the issues addressed, and, to a lesser extent, professional practices.

The dynamics of racism and antiracism in a Scottish charity

This research explored how staff and families using a Scottish trauma-informed charity, striving to enact antiracism, understand and approach race and antiracism in services for families of colour. Thematic analysis was applied to data from ten interviews with six staff participants and four families. Six interlinking themes emerged. Staff identified the charity as a ‘white organisation’ and sought ‘a common frame of reference’ with families, while families expressed overwhelming ‘gratitude’ to staff. ‘Identities were owned and disowned’, with participants using ‘colour-blind’ racial ideologies. Staff ‘located responsibility’ for bridging cultural gaps in families of colour. White staff, while well-intentioned, did not express a fundamental understanding of racism, impeding their ability to enact antiracism. This reflected wider Scottish policy and lay beliefs of being a post-racist society, and challenged organisational attempts to fully embody trauma-informed practice. Challenges and recommendations for researching racism in the third sector are discussed.

Privacy preserving image registration

Image registration is a key task in medical imaging applications, allowing to represent medical images in a common spatial reference frame. Current approaches to image registration are generally based on the assumption that the content of the images is usually accessible in clear form, from which the spatial transformation is subsequently estimated. This common assumption may not be met in practical applications, since the sensitive nature of medical images may ultimately require their analysis under privacy constraints, preventing to openly share the image content. In this work, we formulate the problem of image registration under a privacy preserving regime, where images are assumed to be confidential and cannot be disclosed in clear. We derive our privacy preserving image registration framework by extending classical registration paradigms to account for advanced cryptographic tools, such as secure multi-party computation and homomorphic encryption, that enable the execution of operations without leaking the underlying data. To overcome the problem of performance and scalability of cryptographic tools in high dimensions, we propose several techniques to optimize the image registration operations by using gradient approximations, and by revisiting the use of homomorphic encryption trough packing, to allow the efficient encryption and multiplication of large matrices. We focus on registration methods of increasing complexity, including rigid, affine, and non-linear registration based on cubic splines or diffeomorphisms parameterized by time-varying velocity fields. In all these settings, we demonstrate how the registration problem can be naturally adapted for accounting to privacy-preserving operations, and illustrate the effectiveness of PPIR on a variety of registration tasks.

Chapitre 6. Des éthiques collectives à une gestion adaptative des conflits organisationnels

The idea of collaborative governance is gaining popularity. However, how can it be truly collaborative? Decision-making systems with diverse stakeholders must deal with different positions, roles, interests, missions, observations, and values. The co P·R·I·M·O·V (Position, Role, Interest, Mission, Observation, Values) bioethics tool aims to improve the practice of sustainable, collaborative, and democratic development of technosocial initiatives through its user-friendly format for professional ethicists. The tool follows the logic of Conflict of Interest (CoI) analysis used in organizational ethics frameworks. CoI, as an analytical unit in ethics, allows the anticipation and management of problems that may compromise the short- and long-term activities of a program and its governance. This tool was built on a case study for the implementation of monitoring of antibiotic use in animal health in Quebec, Canada. The use of this bioethics tool is strategic and can help negotiate positions and thus co-construct a common frame of reference between the stakeholders in view of a collaborative governance favoring cooperation.

Designing ecosystems of intelligence from first principles

This white paper lays out a vision of research and development in the field of artificial intelligence for the next decade (and beyond). Its denouement is a cyber-physical ecosystem of natural and synthetic sense-making, in which humans are integral participants—what we call “shared intelligence.” This vision is premised on active inference, a formulation of adaptive behavior that can be read as a physics of intelligence, and which inherits from the physics of self-organization. In this context, we understand intelligence as the capacity to accumulate evidence for a generative model of one’s sensed world—also known as self-evidencing. Formally, this corresponds to maximizing (Bayesian) model evidence, via belief updating over several scales, that is, inference, learning, and model selection. Operationally, this self-evidencing can be realized via (variational) message passing or belief propagation on a factor graph. Crucially, active inference foregrounds an existential imperative of intelligent systems; namely, curiosity or the resolution of uncertainty. This same imperative underwrites belief sharing in ensembles of agents, in which certain aspects (i.e., factors) of each agent’s generative world model provide a common ground or frame of reference. Active inference plays a foundational role in this ecology of belief sharing—leading to a formal account of collective intelligence that rests on shared narratives and goals. We also consider the kinds of communication protocols that must be developed to enable such an ecosystem of intelligences and motivate the development of a shared hyper-spatial modeling language and transaction protocol, as a first—and key—step towards such an ecology.

Transfer of Contracts under German Law

The paper analyses the historical development of the transfer of contracts under German Law, regarding the principle of succession for the assignment of claims and the assumption of debts and the influence of the German Federal Court of Justice on the transfer of shares in a company. It also provides a dogmatic framing of the subject and shows the prerequisites for a valid transfer of contracts under German Law. Additionally, the paper outlines the protection of succession in contract law and how the Draft Common Frame of Reference codified the transfer of contracts. Finally, the author argues for the statutory addition of a third variant, of private assumption of debt, which is effective without the creditor’s consent.

FOREST FEATURE LIDAR SLAM (F2-LSLAM) AND INTEGRATED SCAN SIMULTANEOUS TRAJECTORY ENHANCEMENT AND MAPPING (IS2-TEAM) FOR ACCURATE FOREST INVENTORY USING BACKPACK SYSTEMS

Abstract. Under-canopy mapping is desired to derive critical forest biometrics, such as diameter at breast height (DBH), merchantable height, and debris volume. The main challenge of such under-canopy mapping is the intermittent access to the global navigation satellite system (GNSS) signal, which is crucial to deriving accurately georeferenced mapping products. In this study, we propose two frameworks – Forest Feature LiDAR Simultaneous Localization and Mapping (F2-LSLAM) and Integrated Scan Simultaneous Trajectory Enhancement and mapping (IS2-TEAM) – for 3D LiDAR unit mounted on backpack systems to achieve accurate forest inventory. In the F2-LSLAM strategy, ground/tree trunk features are extracted from individual LiDAR scans. On the other hand, when trajectory information provided by navigation sensors is available, these semantic features are derived from LiDAR points within several scans (i.e., integrated scan) for the IS2-TEAM strategy. Then, local/global least squares adjustment (LSA) using derived features is performed to register LiDAR scans to a common reference frame for both strategies. To evaluate the performance of the proposed strategies, three in-house developed backpack systems with varying specifications were used to collect data in complicated forest environments. Through the comparison with point clouds acquired by a commercial backpack LiDAR system, the proposed frameworks are capable of generating point clouds with satisfactory intra-dataset alignment quality (in the range of 2–4 cm) for all backpack systems in natural forest areas with relatively flat terrain. However, for more challenging areas with dense undergrowth vegetation and/or large height differences, F2-LSLAM framework cannot extract sufficient features, while IS2-TEAM still exhibits good performance.

Phased Array Radio Navigation System on UAVs: In-Flight Calibration

Global Navigation Satellite Systems (GNSS) has been the primary positioning solution for Unmanned Aerial Vehicles (UAVs) due to their worldwide coverage, high precision and lightweight receivers. However, GNSS is prone to electromagnetic interference and malicious assaults, including jamming or spoofing because of its low signal-to-noise ratio (SNR). To ensure the continuity and protection of UAV operations, using redundant navigation systems is essential. In recent years, the phased array radio system (PARS) has established itself as a local navigation solution. PARS is robust towards malicious assaults because of an much higher SNR than GNSS regarding directed and encrypted transmission. An essential factor of PARS is that the orientation of the radio antenna at a ground station needs to be precisely determined to obtain the correct positioning of UAVs. This paper presents a method for extending a previously proposed calibration algorithm to estimate the ground antenna orientation with an inertial navigation system (INS) aided by redundant positioning sensors (GNSS, PARS or barometer) using a multiplicative extended Kalman filter (MEKF) so that the calibration can be activated during flights whenever GNSS is available. In other words, the proposed navigation system is essentially an aided-INS which switches between two modes depending on the availability of GNSS: calibration and GNSS aiding mode when GNSS is available (Mode 1) and PARS and barometer aiding mode when GNSS is unavailable (Mode 2). Considering that the navigation system needs to include the effect of Earth’s curvature for a long-distance flight, PARS horizontal measurement and the barometer measurement were treated independently, and the navigation equations were propagated in Earth Centred Earth Fixed (ECEF) frame. The independent treatment of barometer measurement, and the propagation in ECEF frame were also beneficial when using multiple ground antennas to have a common reference point and reference frame. The proposed method was validated using data (Inertial Measurement Unit (IMU), GNSS, PARS, Pixhawk autopilot (including barometer) measurements) collected during a field test. In the validation, GNSS was made available at the middle of the flight and the calibration mode was activated for 200s. The proposed navigation system successfully estimated the precise orientation of multiple ground antennas and the navigation solutions were verified using GNSS and Pixhawk autopilot solutions as ground truth.

DeepSlice: rapid fully automatic registration of mouse brain imaging to a volumetric atlas

Registration of data to a common frame of reference is an essential step in the analysis and integration of diverse neuroscientific data. To this end, volumetric brain atlases enable histological datasets to be spatially registered and analyzed, yet accurate registration remains expertise-dependent and slow. In order to address this limitation, we have trained a neural network, DeepSlice, to register mouse brain histological images to the Allen Brain Common Coordinate Framework, retaining registration accuracy while improving speed by >1000 fold.