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Managing the level-of-detail (LOD) in architectural models is crucial yet challenging, particularly for effective representation and visualization of buildings. Traditional approaches often fail to deliver controllable detail alongside semantic consistency, especially when dealing with noisy and inconsistent inputs. We address these limitations with Co-LOD, a new approach specifically designed for effective LOD management in architectural modeling. Co-LOD employs shape co-analysis to standardize geometric structures across multiple buildings, facilitating the progressive and consistent generation of LODs. This method allows for precise detailing in both individual models and model collections, ensuring semantic integrity. Extensive experiments demonstrate that Co-LOD effectively applies accurate LOD across a variety of architectural inputs, consistently delivering superior detail and quality in LOD representations. [ABSTRACT FROM AUTHOR]

Cyber-physical systems are becoming more intelligent with the adoption of heterogeneous sensor networks and machine learning capabilities that deal with an increasing amount of input data. While this complexity aims to solve problems in various domains, it adds new challenges for the system assurance. One issue is the rise in the number of abnormal behaviors that affect system performance due to possible sensor faults and attacks. The combination of safety risks, which are usually caused by random sensor faults and security risks that can happen during any random system state, makes the full coverage testing of the cyber-physical system challenging. Existing techniques are inadequate to deal with complex safety and security co-risks against cyber-physical systems. In this paper, we propose AST-SafeSec, an analysis methodology for both safety and security aspects that utilizes reinforcement learning to identify the most likely adversarial paths at various normal or failure states of a cyber-physical system that can influence system behavior through its sensor data. The methodology is evaluated using an autonomous vehicle scenario by incorporating a security attack into the stochastic sensor elements of a vehicle. Evaluation results show that the methodology analyzes the interaction of malicious attacks with random faults and identifies the incident caused by the interactions and the most likely path that leads to the incident. [ABSTRACT FROM AUTHOR]

In this article, I explore collaborative ethnography as a means to bridge theory and practice, knowledge and action, in social movement research, and to produce knowledge that is relevant and useful both inside and outside academia. For this purpose, I will present a group of interconnected dimensions and challenges that shape the practice of research collaboration with social movements: a situated, artisanal and experimental ethos regarding method and outcomes; elements of shared authority, co-decision, co-analysis, and co-theorization in fieldwork; the decentered role of scholars; the tension between academic and extra-academic relevance; the link between trust, access, and collaboration; epistemic and methodological questions of writing and representation; the significance of time for weaving and sustaining collaboration; and the ways in which the actors involved relate to knowledge-practices and theory production. These eight dimensions illustrate how ethnographic collaboration takes place (or fails to materialize) in actual research projects, highlighting elements that will facilitate or hinder the co-production of knowledge with our co-researchers. [ABSTRACT FROM AUTHOR]

In this article, I explore collaborative ethnography as a means to bridge theory and practice, knowledge and action, in social movement research, and to produce knowledge that is relevant and useful for both the academic and the non-academic public. For this purpose, I will present a group of interconnected dimensions and challenges that shape the practice of research collaboration with social movements: a situated, artisanal and experimental ethos regarding method and outcomes; elements of shared authority, co-decision, co-analysis, and co-theorization in fieldwork; the decentered role of scholars; the tension between academic and extra-academic relevance; the link between trust, access, and collaboration; epistemic and methodological questions of writing and representation; the significance of time for weaving and sustaining collaboration; and the ways in which the actors involved relate to knowledge-practices and theory production. These eight dimensions illustrate how ethnographic collaboration takes place (or fails to materialize) in actual research projects, highlighting elements that will facilitate or hinder the co-production of knowledge with our co-researchers.

The purpose of this exploratory study is to highlight, in the context of initial teacher training, the possible transformations brought by a training environment based on a situation of peer co-analysis, and thus to find out whether it can offer opportunities for professional learning. The approach seeks to identify the traces of re-elaboration of the experience that emerge from the exchanges carried out by the students during the time of co-analysis. It then consists of identifying the traces of learning in the teaching activity of the trainees. Two students in their second year of the Master’s degree in teaching and training, who had previously been trained in the role of tutor (observer/analyst), took part in the study. The results show that the situation allows them, under certain conditions, to appropriate and consolidate professional knowledge. In particular, the co-constructed proposals should relate to the students’ concerns, respond to problems raised by the tutor, and be formulated by the tutor. The instructor’s assistance also seems necessary. Impacts on training are then envisaged.

This article reflects on the praxis of collaborative research with social movements, taken here as reflexive/epistemic communities that develop their own para-ethnographic knowledge- practices. What does it entail to do research with subjects that conceive and conduct research as a key dimension of their political praxis? How does this affect the ethnographic encounter? How does it modify fieldwork? Drawing on my own research experience with social movement networks, I will discuss two challenges in collaborative research: a) the question of power, the (a)symmetry -- the hierarchy -- among actors; and, b) the concerns regarding the analytical autonomy of scholars. Within this framework, the article will advocate for establishing logics of co-presence and shared authority with our co-researchers. [ABSTRACT FROM AUTHOR]

Latest technological trends lead toward systems connected to public networks even in critical domains. Bringing together safety and security work is becoming imperative, as a connected safety-critical system is not safe if it is not secure. The main objective of this study is to investigate the current status of safety and security co-analysis in system engineering by conducting a systematic literature review. The steps of the review are the following: the research questions identification; agreement upon a search string; applying the search string to chosen databases; a selection criterion formulation for the relevant publications filtering; selected papers categorization and analysis. We focused on the early system development stages and identified 33 relevant publications categorized as follows: combined safety and security approaches that consider the mutual influence of safety and security; safety-informed security approaches that consider influence of safety on security; and security-informed safety approaches that consider influence of security on safety. The results showed that a number of identified approaches are driven by needs in fast developing application areas, e.g., automotive, while works focusing on combined analysis are mostly application area independent. Overall, the study shows that safety and security co-analysis is still a developing domain. [ABSTRACT FROM AUTHOR]

The involvement of “people with experience” in research has developed considerably in the last decade. However, involvement as co-analysts at the point of data analysis and synthesis has received very little attention—in particular, there is very little work that involves people living with dementia as co-analysts. In this qualitative secondary data analysis project, we (a) analyzed data through two theoretical lenses: Douglas’s cultural theory of risk and Tronto’s Ethic of Care, and (b) analyzed data in workshops with people living with dementia. The design involved cycles of presenting, interpreting, representing and reinterpreting the data, and findings between multiple stakeholders. We explore ways of involving people with experience as co-analysts and explore the role of reflexivity, multiple voicing, literary styling, and performance in participatory data analysis. [ABSTRACT FROM AUTHOR]

Hitherto, the effect of vanadium on higher plant growth remains an open topic. Therefore, nontargeted metabolomic and RNA-Seq profiling were implemented to unravel the possible alteration in alfalfa seedlings subjected to 0.1 mg L−1 (B group) and 0.5 mg L−1 (C group) pentavalent vanadium [(V(V)] versus control (A group) in this study. Results revealed that vanadium exposure significantly altered some pivotal transcripts and metabolites. The number of differentially expressed genes (DEGs) markedly up- and down-regulated was 21 and 23 in B_vs_A, 27 and 33 in C_vs_A, and 24 and 43 in C_vs_B, respectively. The number for significantly up- and down-regulated differential metabolites was 17 and 15 in B_vs_A, 43 and 20 in C_vs_A, and 24 and 16 in C_vs_B, respectively. Metabolomics and transcriptomics co-analysis characterized three significantly enriched metabolic pathways in C_vs_A comparing group, viz., α -linolenic acid metabolism, flavonoid biosynthesis, and phenylpropanoid biosynthesis, from which some differentially expressed genes and differential metabolites participated. The metabolite of traumatic acid in α -linolenic acid metabolism and apigenin in flavonoid biosynthesis were markedly upregulated, while phenylalanine in phenylpropanoid biosynthesis was remarkably downregulated. The genes of allene oxide cyclase (AOC) and acetyl-CoA acyltransferase (fadA) in α -linolenic acid metabolism, and chalcone synthase (CHS), flavonoid 3′-monooxygenase (CYP75B1), and flavonol synthase (FLS) in flavonoid biosynthesis, and caffeoyl-CoA O -methyltransferase (CCoAOMT) in phenylpropanoid biosynthesis were significantly downregulated. While shikimate O -hydroxycinnamoyltransferase (HCT) in flavanoid and phenylpropanoid biosynthesis were conspicuously upregulated. Briefly, vanadium exposure induces a readjustment yielding in metabolite and the correlative synthetic precursors (transcripts/unigenes) in some branched metabolic pathways. This study provides a practical and in-depth perspective from transcriptomics and metabolomics in investigating the effects conferred by vanadium on plant growth and development. [Display omitted] • There exist three significantly enriched KEGG pathways at 0.5 mg L−1 V. • Raffinose was markedly upregulated at all vanadium exposed compare groups. • Traumatic acid was obviously upregulated at α -linolenic acid metabolism. • Apigenin was distinctly upregulated in flavonoid biosynthesis. [ABSTRACT FROM AUTHOR]

We introduce a co-analysis method which learns a functionality model for an object category, e.g., strollers or backpacks. Like previous works on functionality, we analyze object-to-object interactions and intra-object properties and relations. Differently from previous works, our model goes beyond providing a functionality-oriented descriptor for a single object; it prototypes the functionality of a category of 3D objects by co-analyzing typical interactions involving objects from the category. Furthermore, our co-analysis localizes the studied properties to the specific locations, or surface patches, that support specific functionalities, and then integrates the patch-level properties into a category functionality model. Thus our model focuses on the how, via common interactions, and where, via patch localization, of functionality analysis. Given a collection of 3D objects belonging to the same category, with each object provided within a scene context, our co-analysis yields a set of proto-patches, each of which is a patch prototype supporting a specific type of interaction, e.g., stroller handle held by hand. The learned category functionality model is composed of proto-patches, along with their pairwise relations, which together summarize the functional properties of all the patches that appear in the input object category. With the learned functionality models for various object categories serving as a knowledge base, we are able to form a functional understanding of an individual 3D object, without a scene context. With patch localization in the model, functionality-aware modeling, e.g, functional object enhancement and the creation of functional object hybrids, is made possible. [ABSTRACT FROM AUTHOR]