Complex Drivers Research Articles

Age-related skull fracture patterns in infants after low-height falls.

Prior research and experience has increased physician understanding of infant skull fracture prediction. However, patterns related to fracture length, nonlinearity, and features of complexity remain poorly understood, and differences across infant age groups have not been previously explored. To determine how infant and low-height fall characteristics influence fracture patterns, we collected data from 231 head CT 3D reconstructions and quantified length and nonlinearity using a custom image processing code. Regression analysis was used to determine the effects of age and fall characteristics on nonlinearity, length, and features of fracture complexity. While impact surface had an important role in the number of cracks present in a fracture, younger infants and greater fall heights significantly affected most features of fracture complexity, including suture-to-suture spanning and biparietal involvement. In addition, increasing fracture length with increasing fall height supports trends identified by prior finite-element modeling. Finally, this study yielded results supporting the presence of soft tissue swelling as a function of fracture location rather than impact site. Age-related properties of the infant skull confer unique fracture patterns following head impact. Further characterization of these properties, particularly in infants <4 months of age, will improve our understanding of the infant skull's response to trauma. Younger infant age and greater fall heights have significant effects on many features of fracture complexity resulting from low-height falls. Incorporating multiple crack formation and multiple bone involvement into computational models of young infant skull fractures may result in increased biofidelity. Drivers of skull fracture complexity are not well understood, and skull fracture patterns in real-world data across infant age groups have not been previously described. Understanding fracture complexity relative to age in accidental falls will improve the understanding of accidental and abusive head trauma.

The continuation of criminalization by other means: the role of judicial agency in the Italian policing of humanitarian assistance at sea

ABSTRACT Over the last few years, many of the civil society organizations engaged in search and rescue activities in the Central Mediterranean have been targeted in different ways by public authorities. This phenomenon, widely described in terms of ‘policing’, has been central in the EU’s and member states’ migration governance. Scholars have increasingly considered various aspects of that, mostly focusing on legislation, practices and consequences of policing. This article contributes to the existing scholarship by shifting attention to the policy dimension and specifically considering the policy-making process. I focus on the Italian case, in the context of the broader EU policing dynamics, adopting an actor-centred institutionalist perspective, with a view to explaining how and why such policies emerged and evolved over time. To do so, I focus on the policy influence of the judiciary, as enabler of both expansive and repressive dynamics, in the broader context of European and national migration policy-making dynamics. Based on extensive research encompassing different governance layers, the case at hand offers interesting empirical and analytical reflections related to the policing of humanitarian assistance and on the role of the judiciary as a complex and ambivalent driver of the policy process.

Quantifying maerl (rhodolith) habitat complexity along an environmental gradient at regional scale in the Northeast Atlantic

Maerl beds are ecologically important marine biogenic habitats founded on a few species of free-living coralline algae that aggregate and form highly complex rhodoliths. The high biodiversity found in these habitats have been mainly justified by the structural complexity that they provide. However, few attempts to quantify this complexity have been made. Maerl species distribution, density, rhodolith growth forms, and shapes vary with environmental conditions. Hydrodynamics and depth have been shown to drive morphology. Using species-specific metrics such as sphericity and branching density, as well as diameter and fractal dimension at the rhodolith level, and maerl density at the habitat level, we quantified the habitat complexity within ten maerl beds at a regional scale (along ∼400 km of the coastline of Brittany in Western France). Using both long-term monitoring data and environmental models, we investigated how maerl habitat complexity varies among beds and which environmental conditions drive those differences. The effects of currents, exposure to wind-generated waves, temperature and sediment granulometry were evaluated. We confirmed variations in complexity in maerl beds at the habitat and rhodolith levels at local and regional scales, which might have ecological and conservational implications for their associated biodiversity. The analysed environmental conditions drive around a third of the variance in habitat complexity. Sediment granulometry is the main driver of maerl habitat complexity in Brittany, while the isolated effects of depth and hydrodynamics accounted for less than 5% of the variability each. Our results have important implications for paleoecology, and we suggest that maerl facies should be interpreted carefully. Our study provides a first attempt at explicitly quantifying maerl habitat complexity, and further contributes to the understanding of this fundamental ecological question.

Knowledge Sharing in the Supply Chain Networks: A Perspective of Supply Chain Complexity Drivers

Background: Knowledge transfer has been an important aspect in supply chain systems; however, there are many factors that affect the impact of transfer effectiveness. In previous studies, less attention has been given to the process of knowledge transfer and therefore, this paper highlights the significance of the process of knowledge transfer in supply chain processes. Enhanced supply chain networks have better performance when knowledge sharing is present, and it is important to identify and eliminate any supply chain complexity to improve the supply chain processes. Methods: A systematic review on the literature has been conducted to critically identify and evaluate the factors of supply chain complexity which impact knowledge transfer. Findings: The findings highlight the key benefits of effective knowledge transfer in supply chain systems by identifying risks associated with supply chain networks. Conclusion: The balanced power of facilitating knowledge transfer in supply chain processes helps in supply chain partnerships and reduces the supply chain complexity. This paper has both theoretical and practical contributions as it adds to the literature by identifying the factors of supply chain complexity drivers which are impacting the knowledge transfer.

Evaluation of failure risks for manual tightening operations in automotive assembly lines

PurposeThe tightening operations are one of the most critical operations in automotive assembly lines because of its direct impact on customer safety. This study aims to evaluate the major complexity drivers for manual tightening operations, correlate with real tightening failure data and propose mitigations to improve the complexity.Design/methodology/approachIn the first stage, the complexity drivers for manual tightening operations were identified. Then, the relative importance of the risk attributes was defined by using pairwise comparisons questionnaire. Further, failure mode effect analysis–analytic hierarchy process (FMEA–AHP) and AHP ratings methods were applied to 20 manual tightening operations in automotive assembly lines. Finally, the similarities between the revealed results and the real failure rates of a Turkish automotive factory were examined and a sensitivity analysis was conducted.FindingsThe correlation between the proposed methods and manual tightening failure data was calculated as 83%–86%. On the other hand, the correlation between FMEA–AHP and AHP ratings was found as 92%. Poor ergonomics, operator competency and training, operator concentration-loose attention fatigue, manual mouthing before the tightening operation, frequent task changes, critical tightening sequence, positioning of the part and/or directional assembly were found relatively critical for the selected 20 tightening operations.Originality/valueThis is a unique study for the evaluation of the attributes for manual tightening complexity in automotive assembly lines. The output of this study can be used to improve manual tightening failures in manual assembly lines and to create low complexity assembly lines in new model launches.

Rule-breaking in terrestrial protected areas of sub-Saharan Africa: A review of drivers, deterrent measures and implications for conservation

Nature conservation relies largely on peoples' rule adherence. Nevertheless, non-compliance with regulations threatens in situ conservation in nearly every protected area (PA) and remains an intractable issue. We reviewed the available published scholarly literature on non-compliant biological resource-use in terrestrial protected areas (TPAs) of sub-Saharan Africa. The focus is on two objectives, firstly, to disentangle the complex drivers behind the various types of deviant behaviour observed in these PAs, and secondly, to assess the strategies deployed on the ground to deter such illegalities. Using 72 selected journal articles published between 2001 and 2021, we recorded nine types of deviant behaviour or illegal resource extraction that were reported. Poaching activity overshadowed all other criminal behaviours. Drivers varied according to the type of crime perpetrated or resources targeted. Poverty was the most cited driver of non-compliance, particularly for illegal bushmeat hunting. PA resentment prompted by destructive errant wildlife was almost as strong a motivation as material poverty. To deter offenders from committing a crime, a combination of interventions, i.e., law enforcement and a spectrum of non-enforcement approaches, such as Reformed Poachers Associations, long-term research sites and resource-access agreements, were deployed. Our synthesis demonstrates that the growing sub-Saharan African literature on non-compliant biological resource-use in TPAs is dominated by bushmeat poaching drivers. Other motives for PA offences by border villagers are scarcely dealt with in the peer-reviewed literature. Future studies of wildlife crime need to address PA transgression multidimensionality, not just bushmeat poaching, to reveal further drivers of transgressive behaviour and ultimately allow for evidence-informed conservation intervention design.

Inconsistent results from trait-based analyses of moth trends point to complex drivers of change

Inconsistent results from trait-based analyses of moth trends point to complex drivers of change

Keeping policy commitments: An organizational capability approach to local green housing equity

AbstractAffordable housing that incorporates sustainability goals into its design has the potential to address both health and economic disparities via enhanced energy‐efficiency, structural durability and indoor environmental quality. Despite the potential for these win‐win advances, survey data of U.S. local governments indicate these types of equity investments remain rare. This study explores barriers and pathways to distributional equity via energy‐efficient housing. Using archival city sustainability survey data collected during a period of heightened U.S. federal investment in local government energy‐efficiency programs, we combine machine learning (ML) and process‐tracing approaches for modeling the complex drivers and barriers underlying these decisions. First, we ask, how do characteristics of a city's organizational learning methods—its administrative structure, past experience with housing programs, resources, stakeholder engagement and planning—predict policy commitments to green affordable housing? Using ensemble ML methods, we find that three specific modes of organizational learning—past experience with affordable housing programs, seeking assistance from neighborhood groups and the technical expertise of professional green organizations—are the most impactful features in determining city commitments to constructing green affordable housing. Our second stage uses process‐tracing within a specific case identified by the ML models to determine the ordering of these factors and to provide more nuance on green‐housing policy implementation.

Towards a Taxonomy of The 21st century Architectural Practices in the age of Sustainability and Technology

The architectural practices witness drastic transformations in the 21st century globally, which put the architectural community in a situation of crisis; facing challenges to identify different trajectories and their characteristics for a reliable evaluation of the approaches and strategies. Conferences and research laboratories started to seek a philosophy interpreting new practices, mostly known is the 2003 Pompidou exhibition in France discussing “Non-standard Architectures”. This research investigates the interrelation between architecture, and the most-two dialectic terms of the age “sustainability and technology”, linking influencing beliefs and philosophies with the design approaches and strategies through a comprehensive design theory. It emphasizes the paradigm shift from modernism architecture that tied the design to craft to a richer knowledge paradigm ties design, technology and craft in a complex-system. This has more impressive and complex drivers corresponding to the reflects of “The Knowledge Power” coined by Foucault that shapes the whole cultural paradigm and its sub-systems of any society across history. Such a philosophy can reach a meta-theory about current practices of architecture seen as isolated islands or fragmented practices through revealing the radical drivers of current iconic projects and identifying hypothetical boundaries that interprets these typologies and their relevancy to each other promoting a new holistic paradigm of architecture.

Issue-Based Complexity: Digitally Supported Negotiation in Geodesign Linking Planning and Implementation

Research regarding the complex issues in planning negotiation is sparse. This article aims to shed light on the characteristics of “the negotiation issue” in planning and how to deal with negotiation-related complexity towards planning implementation. It conceptualizes processes of negotiation that are represented/implemented via graphic and geographic elements, where the topology is a crucial factor. Our case study of the CAMKOX corridor at UCL’s geodesign workshop provides new insights into the potential of digital negotiations for assessing the characteristics of planning negotiation issues and their associated complexity drivers to enhance the quality of spatiality. The findings provide a detailed description of issue-based planning complexity. A shift of focus away from the products of planning to the negotiation process—as the most important consideration in planning—opens the possibility of implementing “shared” interventions on which there is consensus.

Defective Subviral Particles Modify Ecological Equilibria and Enhance Viral Coexistence

Cooperation is a main driver of biological complexity at all levels. In the viral world, gene sharing among viral genomes, complementation between genomes or interactions within quasispecies are frequently observed. In this contribution, we explore the effects of flexible associations between fully fledged viruses and subviral entities, such as virus satellites, in viral dynamics and, in particular, in stable viral coexistence. We devise a mathematical model to compare different situations of competition between two viruses and to quantify how the association with a satellite qualitatively modifies dynamical equilibria. The relevant parameter is the invasion fitness of each virus or of the virus-satellite tandem, which in the model depends on the transmission rate of viruses and on their effect on host survival. In a virus-virus competition, one of the viruses becomes eventually extinct, recasting the competitive exclusion law of ecology. However, an association with a satellite might change the outcome of the competition in two ways, either to favor the less competitive virus (regardless of whether it is the helper virus or not) or to allow for the stable coexistence of the two viruses and the satellite. The virus-satellite association differs from other mechanisms proposed in ecology to date to enhance species coexistence. We hypothesize that such an association constitutes a parsimonious evolutionary pathway towards more stable cooperative associations, such as bipartite viral forms, a collaborative association unique to viruses.

Visual complexity of egg patterns predicts egg rejection according to Weber's law.

Visual complexity is ubiquitous in nature. Drivers of complexity include selection in coevolutionary arms races between antagonists. However, the causes and consequences of biological complexity and its perception are largely understudied, partly because complexity is difficult to quantify. Here, we address this by studying egg pattern complexity and its perception in hosts (tawny-flanked prinia Prinia subflava), which visually recognize and reject mimetic eggs of their virulent brood parasite (cuckoo finch Anomalospiza imberbis). Using field data and an optimization algorithm, we compute a complexity metric which predicts rejection of experimentally placed conspecific eggs in prinia nests. Real cuckoo finch eggs exhibit significantly lower pattern complexity than prinia eggs, suggesting that high complexity benefits hosts because it distinguishes host eggs from parasitic eggs. We show that prinias perceive complexity differences according to Weber's law of proportional processing (i.e. relative, rather than absolute, differences between stimuli are processed in discrimination, such that two eggs with simple patterns are more easily discriminable than two with complex patterns). This may influence coevolutionary trajectories of hosts and parasites. The new methods presented for quantifying complexity and its perception can help us to understand selection pressures driving the evolution of complexity and its consequences for species interactions.

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features

Cancers of unknown primary (CUP) origin account for ∼3% of all cancer diagnoses, whereby the tumor tissue of origin (TOO) cannot be determined. Using a uniformly processed dataset encompassing 6756 whole-genome sequenced primary and metastatic tumors, we develop Cancer of Unknown Primary Location Resolver (CUPLR), a random forest TOO classifier that employs 511 features based on simple and complex somatic driver and passenger mutations. CUPLR distinguishes 35 cancer (sub)types with ∼90% recall and ∼90% precision based on cross-validation and test set predictions. We find that structural variant derived features increase the performance and utility for classifying specific cancer types. With CUPLR, we could determine the TOO for 82/141 (58%) of CUP patients. Although CUPLR is based on machine learning, it provides a human interpretable graphical report with detailed feature explanations. The comprehensive output of CUPLR complements existing histopathological procedures and can enable improved diagnostics for CUP patients.

Peracarid Assemblages in a Human-Disturbed Location from South-Western Mediterranean Sea: Role of Surface Orientation and Phytal Structure of the Habitat

The goal of this investigation was to assess the role of a number of environmental variables on the traits of a peracarid population inhabiting turfs of Ellisolandia elongata in a Mediterranean disturbed location. Samples were collected from a vertical and a horizontal surface to assess the role of orientation, and several structural traits of the turf (number of fronds, their height and width, available phytal area for colonization, and dry weight) were measured. The samples were characterized by their species composition, relative abundance of constant species, total abundance of individuals, and α-diversity (species richness, Shannon index and Pielou’s evenness). Generalized linear models were used to relate environmental variables with ecological descriptors, whereas a cluster plot and a principal correspondence analysis, both based on the Bray-Curtis coefficient, were conducted to detect the presence of distinct assemblages. Results showed orientation to be a key factor governing the assemblages, since samples from vertical and horizontal surfaces formed definite groups based on Bray-Curtis similarities. Moreover, GLMs pointed out that orientation influenced relative abundance of the majority of constant species, as well as species richness and Shannon index. Phytal height had a positive effect on the relative abundances of Hexapleomera bultidactyla, Coxischyrocerus inexpectatus and Hyale stebbingi, and a negative one on Shannon index and evenness, whereas available phytal area influenced positively evenness and negatively the relative abundance of Elasmopus pocillimanus. Thus, it can be inferred that although species composition depended on surface orientation, the spatial structure of the turf was the main driver for assemblage complexity.

Disentangling the evolutionary drivers of social complexity: A comprehensive test of hypotheses.

During the Holocene, the scale and complexity of human societies increased markedly. Generations of scholars have proposed different theories explaining this expansion, which range from broadly functionalist explanations, focusing on the provision of public goods, to conflict theories, emphasizing the role of class struggle or warfare. To quantitatively test these theories, we develop a general dynamical model based on the theoretical framework of cultural macroevolution. Using this model and Seshat: Global History Databank, we test 17 potential predictor variables proxying mechanisms suggested by major theories of sociopolitical complexity (and >100,000 combinations of these predictors). The best-supported model indicates a strong causal role played by a combination of increasing agricultural productivity and invention/adoption of military technologies (most notably, iron weapons and cavalry in the first millennium BCE).

Developing a model for health determinants research within local government: lessons from a large, urban local authority.

Background: Socio-economic, cultural and environmental conditions strongly affect health across the life course. Local government plays a key role in influencing these wider determinants of health and levels of inequality within their communities. However, they lack the research infrastructure and culture that would enable them to develop an evidence-based approach to tackling the complex drivers of those conditions. Methods: We undertook a scoping project using some research methods and some descriptive summaries to explore the potential for, and what would be needed to develop a local authority research system for the City of Bradford, UK. This included identifying the current research landscape and any barriers and enablers to research activity within the local authority using qualitative individual and focus group interviews, a rapid review of existing local research system models, scoping and description of the use of evidence in decision making and training opportunities and existing support for local government research. Results: We identified four key themes important to developing and sustaining a research system: leadership, resource and capacity, culture, partnerships. Some use of research in decision making was evident but research training opportunities within the local authority were limited. Health research funders are slowly adapting to the local government environment, but this remains limited and more work is needed to shift the centre of gravity towards public health, local government and the community more generally. Conclusions: We propose a model for a local authority research system that can guide the development of an exemplar whole system research framework that includes research infrastructure, data sharing, research training and skills, and co-production with local partners, to choose, use, generate, and deliver research in local government.

Abstract 2167: Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features

Abstract Tumor tissue of origin (TOO) is an important factor for guiding treatment decisions. However, TOO cannot be determined for ~3% of metastatic cancer patients that present in the clinic and are categorized as cancers of unknown primary (CUP). As whole genome sequencing (WGS) of tumors is now transitioning from the research domain to diagnostic practice in order to address the increasing demand for biomarker detection, its use for detection of TOO in routine diagnostics also starts becoming within reach. While proof of concept for the use of genome-wide features has been demonstrated before, more complex WGS mutation features, including structural variant (SV) driver and passenger events, have never been integrated into TOO-classifiers even though they bear highly characteristic links with tumor TOO. Using a uniformly processed dataset containing 6820 whole-genome sequenced primary and metastatic tumors (ICGC/PCAWG and Hartwig cohors), we have developed Cancer of Unknown Primary Location Resolver (CUPLR), a random forest based TOO classifier that employs 502 genome-wide features based on simple and complex somatic driver and passenger mutations. Our model is able to distinguish 33 cancer (sub)types with an overall accuracy of 91% and 89% based on cross-validation (n=6139) and hold out set (n=681) predictions, respectively. We found that SV derived features increase the accuracy and utility of TOO classification for specific cancer types. To ensure that predictions are human-interpretable and suited for use in routine diagnostics, CUPLR reports the top contributing features and their values compared to cohort averages. The comprehensive output of CUPLR is complementary to existing histopathological procedures and may thus improve diagnostics for patients with CUP. CUP is the first reimbursed indication for WGS in The Netherlands. We will report on the prospective use and clinical utility of WGS for CUP patients in routine diagnostics but also highlight the added value of CUPLR for unsolved differential diagnosis cases and incidental cases where the independent WGS analysis was discrepant with the original tumor diagnosis. Citation Format: Luan Nguyen, Luuk Schipper, Paul Roepman, Kim Monkhorst, Arne van Hoeck, Petur Snaebjornsson, Edwin Cuppen. Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2167.

Developing a model for health determinants research within local government: lessons from a large, urban local authority

Background: Socio-economic, cultural and environmental conditions strongly affect health across the life course. Local government plays a key role in influencing these wider determinants of health and levels of inequality within their communities. However, they lack the research infrastructure and culture that would enable them to develop an evidence-based approach to tackling the complex drivers of those conditions. Methods: We undertook a scoping project using some research methods and some descriptive summaries to explore the potential for, and what would be needed to develop a local authority research system for the City of Bradford, UK. This included identifying the current research landscape and any barriers and enablers to research activity within the local authority using qualitative individual and focus group interviews, a rapid review of existing local research system models, scoping and description of the use of evidence in decision making and training opportunities and existing support for local government research. Results: We identified four key themes important to developing and sustaining a research system: leadership, resource and capacity, culture, partnerships. Some use of research in decision making was evident but research training opportunities within the local authority were limited. Health research funders are slowly adapting to the local government environment, but this remains limited and more work is needed to shift the centre of gravity towards public health, local government and the community more generally. Conclusions: We propose a model for a local authority research system that can guide the development of an exemplar whole system research framework that includes research infrastructure, data sharing, research training and skills, and co-production with local partners, to choose, use, generate, and deliver research in local government.

The importance of S&amp;OP, collaboration and process discipline in a complex business environment: A case study from the canned seafood industry

Supply chains are usually faced with a considerable number of external and internal drivers of complexity. They can originate from diverse sources such as a big product variety to produce, difficulties in raw material sourcing, a vertically disintegrated production network, ever-changing customer needs, or strong regulatory requirements. Those drivers typically correlate to each other and are mutually dependent. For example, a widespread production network makes raw material sourcing a complex task. In reverse, varying raw material availability across regions determines the design of a production network that is then not necessarily trimmed on leanness. Some industry supply chains are more complex than others, meaning they are exposed to more complexity drivers than supply chains in other industries. Thai Union Europe (TUE) predominantly operates in the canned seafood industry, and the related supply chain with its multitude of complexity drivers can be considered very complex. The way TUE manages sales and operations planning (S&amp;OP) in this environment is key to its market success. The company’s execution of S&amp;OP is inevitably linked to its corporate culture of collaboration and process discipline. Focus is not only on an S&amp;OP programme with best practice processes but also on achieving the necessary cultural change. The way TUE plans and manages its complex supply chain is the subject of this case study.

A rural community's perspective on the causes of and solutions to the opioid crisis in southern Virginia: a qualitative study.

Introduction:Opioid use disorder is a leading public health issue in the USA, with complex drivers requiring a multi-level response. Rural communities are particularly affected by opioid misuse. Due to variability in local conditions and resources, they require community-specific responses. The aim of this study was to gain insight into the perceptions, knowledge, and experiences of members of a rural community impacted by the opioid crisis to inform the development of local strategies to address the crisis.Methods:Stakeholder focus groups were conducted by a participatory research team as part of a larger project using the Stakeholder Engagement in Question Development and Prioritization (SEED) Method.Results:Key findings from the focus groups included the importance of family dynamics and social networks as risk and resiliency factors, addressing hopelessness as a preventive strategy, the need for holistic approaches to treatment, childhood exposure resulting in intergenerational substance use, the needs of overburdened healthcare providers, the expansion of long-term rehabilitation programs, and the need for judicial reform towards those with opioid use disorder. Specific and well-defined strategies are needed for more comprehensive methods to address the complexity of opioid use disorder. Understanding factors that contribute to opioid use disorder in rural communities through a stakeholder engagement process should be the first responsive strategy in developing actions.Conclusion:This study shows that rural community stakeholders provide important perspectives that can be useful in solving the drug epidemic in their neighborhoods. Their understanding of the internal dynamics of the communities’ needs offers a unique roadmap in which prioritized actions can be customized and adapted for improving health outcomes.