Relative Importance Research Articles

Fcgr2b and Fcgr3 are the major genetic factors for cartilage antibody-induced arthritis, overriding the effect of Hc encoding complement C5.

Like rheumatoid arthritis (RA) in humans, collagen-induced arthritis (CIA) in mice is associated with not only MHC class II genetic polymorphism but also, to some extent, with other loci including genes encoding Fc gamma receptors (FCGRs) and complement C5. In this study, we used a cartilage antibody-induced arthritis (CAIA) model in which arthritis develops within a 12-h timeframe, to determine the relative importance of FCGRs and C5 (Hc). In CAIA, inhibiting or deleting FCGR3 substantially hindered arthritis development, underscoring the crucial role of this receptor. Blocking FCGR3 also reduced the levels of FCGR4, and vice versa. When employing an IgG1 arthritogenic cocktail that exclusively interacts with FCGR2B and FCGR3, joint inflammation was promptly initiated in Fcgr2b--mice but not in Fcgr3--mice, suggesting that FCGR3 is sufficient for CAIA development. Regarding complement activation, Fcgr2b++.Hc** mice with C5 mutated were fully resistant to CAIA, whereas Fcgr2b--.Hc** mice developed arthritis rapidly. We conclude that FCGR3 is essential and sufficient for CAIA development, particularly when induced by IgG1 antibodies. The human ortholog of mouse FCGR3, FCGR2A, may be associated with RA pathogenesis. FCGR2B deficiency allows for rapid arthritis progression and overrides the resistance conferred by C5 deficiency.

BENTHIC MACROINVERTEBRATE COMMUNITY IN TWO AMAZONIAN UPLAND LAKES

Studies of biological communities in Amazonian lakes are limited to floodplains of large rivers. However, the high-altitude lakes of the Serra dos Carajás differ from other lakes in the region due to the high natural concentration of iron and manganese. An important component of this biological community are the macroinvertebrates, some of which are sensitive to environmental and chemical variables. However, little is known about the influence of heavy metal concentrations on this community component in Amazonian lakes. In our study, we observed the importance of variables such as water depth and concentration of chemical elements in sediments on the macroinvertebrate community. Through a redundancy analysis, we found that the depth of the lake affects the number of species and the composition of the benthic macroinvertebrate community. We also found a relative importance of the concentration of manganese in the sediment for the community studied. Our results indicate that the macroinvertebrate community is differentiated in the marginal and central regions of the lake, since the deposition of organic matter and heavy metals in the sediment is different in these two regions of the lake. The relationship found has implications for the management and restoration of upland lakes in the Amazon, helping to preserve this unique ecosystem.

Habitat utilization of the Eurasian spoonbill (Platalea leucorodia) wintering in the Yancheng National Nature Reserve: relative importance of artificial habitats

Coastal wetlands are among the most modified habitats because of the loss and degradation of tidal flats, resulting in a rapid decline in waterbirds migrating along flyways. Understanding the relative importance of multiple types of wetlands as habitats for waterbirds and the factors influencing their utilization could improve management effectiveness. During the wintering seasons of 2021-2022 and 2022-2023, we documented the distribution of Eurasian spoonbills (Platalea leucorodia), a wetland specialist, in the Yancheng National Nature Reserve (YNNR) and quantified the surrounding environments as influencing factors to assess the relationship between their habitat use patterns and environmental characteristics. Our results showed that spoonbills inhabit common seepweed (Suaeda glauca) marshes, reed (Phragmites australis) ponds, aquaculture ponds, and agricultural channels. Although natural wetlands supported a greater number of spoonbills in the YNNR, spoonbills were able to forage in artificial wetlands. The environmental features where the spoonbills were distributed were found to influence their habitat use, and the most important factor was water depth, followed by species richness and vegetation cover. These results demonstrated that spoonbills rely on both natural and artificial wetlands in the core and buffer zones of the YNNR. Our research thus underlined that conservation interventions of natural and artificial wetlands, such as controlling the water depth and diminishing human activities, might maximize the effects of total conservation outcomes for the Eurasian spoonbills, as well as for various coastal waterbirds with similar ecological requirements.

Landslide susceptibility zonation using the analytical hierarchy process (AHP) in the Great Xi’an Region, China

This study aims to delineate landslide susceptibility maps using the Analytical Hierarchy Process (AHP) method for the Great Xi’an Region, China, which is a key planning project for urban construction in Shaanxi Province, China from 2021 to 2035. Multiple data as elevation, slope, aspect, curvature, river density, soil, lithology, and land use have been considered for delineating the landslide susceptibility maps. Spatially thematic layers and distributed maps of all the aforementioned parameters were created in a GIS environment. Determine the relative importance of these thematic layers in the occurrence of landslides in the study area concerning historical landslide data to assign appropriate weights. Landslide sensitivity maps were generated by a weighted combination in a GIS environment after being analyzed by the AHP method. The sensitivity maps were categorized as “very high (11.06%), high (19.41%), moderate (23.03%), low (28.70%), and very low (17.80%)”. Overlay analysis of the test data with the LSM showed that the moderate to very high landslide susceptibility zones were able to contain 82.58% of the historic landslides. The results of the study help determine the landslide-prone areas in the area and provide a reference for subsequent construction. In addition, the analysis of landslide susceptibility in the area contributes to the study of landslides in similar loess sites.

Decomposing Uncertainty in Macro-Finance Term Structure Models

Abstract This paper studies the extent to which macro-finance term structure models are susceptible to predictive uncertainty. We propose a general form of arbitrage-free models and quantify the relative importance of unpredictable priced risk variance, as well as macro-finance model uncertainty and learning uncertainty in predictability. Predictive performance and relative contributions of uncertainty sources are dynamically measured based on Bayesian methods, revealing dominating priced risk variance and other important uncertainty sources at different points in time. Macro-finance model uncertainty is high for near-term forward spread forecasts and contributes up to 87% of predictive uncertainty prior to recessions, implying strong dispersion in the information content of macro variables when forming near-term monetary policy expectations. (JEL C1, C3, C5, D8, E4, G1)

Exploring the relative importance of sustainable competitiveness pillars

While the acknowledged significance of pillars such as economic sustainability, intellectual capital, resource efficiency, natural capital, social capital, and governance in contributing to a nation’s long-term economic and social prosperity forms the basis of this research, our primary aim is to undertake a more nuanced exploration. Instead of reiterating their broad contributions, we seek to investigate the specific and individual roles of these pillars and the intricate interdependencies among them. To accomplish this, a Bayesian Belief Network (BBN) model was developed using a dataset by SolAbility covering sustainable competitiveness scores for 180 countries, which demonstrated a predictive accuracy of 88.9%. Sensitivity analysis uncovered the critical role played by ‘governance’, ‘social capital’, ‘economic sustainability’, and ‘intellectual capital’ in influencing overall sustainable competitiveness. Notably, ‘governance’ and ‘intellectual capital’ were found to have a far-reaching impact on multiple competitiveness pillars within the BBN model. Highly competitive countries consistently demonstrated strong performance in the ‘governance’, ‘social capital’, and ‘economic sustainability’ pillars, whereas low competitiveness was associated with a deficiency in ‘intellectual capital’. Notably, ‘governance’, ‘social capital’, ‘intellectual capital’, and ‘economic sustainability’ emerged as the most informative factors concerning the sustainable competitiveness variable. ‘Natural capital’ and ‘resource intensity’ were relatively less critical factors. This is the first study to quantify the relative significance of individual sustainable competitiveness pillars within a probabilistic network model, thus providing valuable insights for policymakers regarding resource allocation. Researchers can also leverage these findings to delve deeper into the importance of sub-pillars associated with the critical pillars identified in this research.

Improvement of Industrial Maintenance Plans through Assistance-Driven Reliability-Centered Maintenance and Case-Based Reasoning Design

The present work builds on studies where the industrial market is currently characterized by a highly variable demand in terms of the quantities and flexibility of manufacturing or mass customization, which translates into a more demanding production context in terms of the continuous changes that are required in the production systems, the effect of which results in an increase in the fatigue of the machines that make up the production systems. However, current production systems tend to use highly communicative and sensorized cyber–physical systems; these characteristics can be used to integrate them into decision-assisted systems to improve the availability of the industrial plant. The developed assisted system focuses on collecting and taking advantage of historical knowledge of industrial plant failures and breakdowns. By ideally integrating the reliability-centered maintenance (RCM) methodology and case-based reasoning (CBR) algorithms implemented in a Java application, it is possible to design maintenance plans that are adjusted to the real and changing operational context of any industrial plant. As a result, faster and more accurate decisions are made, because they are based on data. This article focuses on improving certain aspects of the developed assisted system by adding more value by incorporating fuzzy logic (FL) techniques. The aim is to improve the way of entering information about risk factors and their relative importance by incorporating natural language instead of a numerical score, resulting in increased precision in the calculation of the risk priority number (RPN) of the new cases that are incorporated into the assisted system. On the other hand, an attempt has been made to correct two of the main inherent and recognized weaknesses in the classic RPN calculation method by implementing an appropriate mix of fuzzy logic techniques.

Vendor Selection Criteria and Construction Project Performance in Rivers Nigeria.

The study focused on Vendor Selection Criteria and Construction Project Performance in Rivers Nigeria. It adopted a survey approach; utilized structured questionnaire to collect data from 71 on-site construction project managers and engineers; data obtained were ranked according to their priority using Relative Importance Index (RII), and Chi-Square Analysis. Linear regression coefficients were drawn as estimates of construction project performance. The results showed that 22 criteria, grouped into four supplier selection dimensions: capability, quality, costs and sustainability. These indicators showed significant interaction with construction project performance. However, supplier flexibility did not yield significant outcome on construction project performance. The results suggest that supplier capability, supplier quality, supplier costs, and supplier sustainability selection variables are important sources of enhanced performance for construction project management. Keywords: Construction management; Vendor selection; Project performance; Relative importance index; Sustainable supplier selection.

Circular Economy in the Building Sector: Investigating Awareness, Attitudes, Barriers, and Enablers through a Case Study in Saudi Arabia

The adoption of circular economy (CE) holds significant potential to mitigate the challenges posed by the conventional linear economic model. The building sector in Saudi Arabia continues experiencing rapid growth, often marked by a consistent annual rise in the number of projects. The incorporation of CE principles into this expansion presents opportunities to optimize resource utilization, minimize waste generation, and enhance overall environmental sustainability. This study explores the current levels of awareness, perception, and implementation of CE principles among local building sector stakeholders and assesses the potential for CE expansion in the region. Additionally, it seeks to rank the identified barriers and enablers while exploring the interconnected relationships between such barriers. A literature review was conducted to explore the CE barriers and enablers. This was followed by an online survey which was conducted amongst 139 respondents from diverse stakeholder groups. A relative importance index (RII) was employed to rank the barriers and enablers, and the findings were subjected to statistical analysis using the Statistical Package for Social Sciences (SPSS). The outcomes of this study highlight a significant lack of awareness regarding CE principles among stakeholders, with a very low implementation rate. To break this inertia and encourage the adoption of CE practices, this study suggests the need for CE- supportive policy and legislation, and the provision of financial incentives.

Modeling variation in mixture effects over space with a Bayesian spatially varying mixture model.

Mixture analysis is an emerging statistical tool in epidemiological research that seeks to estimate the health effects associated with mixtures of several exposures. This approach acknowledges that individuals experience many simultaneous exposures and it can estimate the relative importance of components in the mixture. Health effects due to mixtures may vary over space driven by to political, demographic, environmental, or other differences. In such cases, estimating a global mixture effect without accounting for spatial variation would induce bias in effect estimates and potentially lower statistical power. To date, no methods have been developed to estimate spatially varying chemical mixture effects. We developed a Bayesian spatially varying mixture model that estimates spatially varying mixture effects and the importance weights of components in the mixture, while adjusting for covariates. We demonstrate the efficacy of the model through a simulation study that varies the number of mixtures (one and two) and spatial pattern (global, one-dimensional, radial) and magnitude of mixture effects, showing that the model is able to accurately reproduce the spatial pattern of mixture effects across a diverse set of scenarios. Finally, we apply our model to a multi-center case-control study of non-Hodgkin lymphoma (NHL) in Detroit, Iowa, Los Angeles, and Seattle. We identify significant spatially varying positive and inverse associations with NHL for two mixtures of pesticides in Iowa and do not find strong spatial effects at the other three centers. In conclusion, the Bayesian spatially varying mixture model represents a novel method for modeling spatial variation in mixture effects.

Exploring the importance of mobile app attributes based on consumers' voices using structured and unstructured data

PurposeThis exploratory study examines and comprehends the relative importance of mobile app attributes from a consumer perspective. Both quantitative and qualitative analysis approaches explore users' behavior and attitudes toward the priorities of mobile app attributes and preferences, identifying correlations between attributes and aggregating individual attributes into groups.Design/methodology/approachOnline convenience sampling and snowball sampling resulted in 417 valid responses. The numerical data are analyzed using the relative to an identified distribution (RIDIT) scoring system and gray relational analysis (GRA), and qualitative responses are investigated using text-mining techniques.FindingsThis study finds enhanced nuances of user preferences and provides data-driven insights that might help app developers and marketers create a distinct app that will add value to consumers. The latent semantic analysis indicates relationship structure among the attributes, and text-based cluster analysis determines the subsets of attributes that represent the unique functions of the mobile app.Practical implicationsThis study reveals the essential components of mobile apps, paying particular attention to the consumer value component, which boosts user approval and encourages prolonged use. Overall, the results demonstrate that developers must concentrate on its functional, technical and esthetic features to make an app more exciting and practical for potential users.Originality/valueMost scholarly research on apps has focused on their technological merits, aesthetics and usability from the user's perspective. A post-adoption multi-attribute app analysis using both structured and unstructured data is conducted in this study.

Low body mass index as a predictor of sputum culture conversion and treatment outcomes among patients receiving treatment for multidrug-resistant tuberculosis in Lesotho

ABSTRACT Background A low body mass index (BMI) at the start of treatment for rifampicin- or multidrug-resistant tuberculosis (MDR/RR-TB) is associated with poor treatment outcomes and may contribute to delayed sputum culture conversion, thereby prolonging the period of potential transmission to others. Whether the relative importance of low BMI in predicting treatment outcomes differs by HIV status is unclear. Objectives We evaluated the association between low BMI and two dependent variables, sputum culture conversion and end-of-treatment outcome, among patients receiving treatment for MDR/RR-TB in Lesotho, a setting with a high prevalence of HIV infection. Methods Secondary data from a prospective cohort of patients initiating a longer (18–20 months) treatment containing bedaquiline and/or delamanid under routine programmatic conditions in Lesotho were analysed. Risk ratios and differences were adjusted for potential confounders using multivariable logistic regression, and estimates were stratified by HIV status. Results Of 264 patients, 105 and 250 were eligible for culture conversion and end-of-treatment analyses, respectively. Seventy-one per cent of patients (74/105) experienced culture conversion within six months, while 74% (184/250) experienced a favourable end-of-treatment outcome. Low BMI was associated with a lower frequency of culture conversion at six months among those who were not living with HIV (relative risk [RR]: 0.50 [95% CI: 0.21, 0.79]); this association was attenuated among those living with HIV (RR: 0.88 [95% CI: 0.68, 1.23]). A low BMI was moderately associated with a lower frequency of treatment success (RR = 0.89 [95% CI: 0.77, 1.03]), regardless of HIV status. Conclusions Low BMI was common and associated with the frequency of six-month culture conversion and end-of-treatment outcomes. The association with culture conversion was more pronounced among those not living with HIV. Addressing the myriad factors that drive low BMI in this setting could hasten culture conversion and improve end-of-treatment outcomes. This will require a multipronged approach focused on alleviating food insecurity and enabling prompt diagnosis and treatment of HIV and TB.

Morphological ant mimics: constrained to imperfection?

Adaptive evolution relies on both heritable variation and selection. Variation is the raw material upon which selection acts, so any mechanism that limits or prevents the generation of heritable variation reduces the power of selection to lead to adaptation. Such limitations are termed evolutionary constraints. While it is widely accepted that constraints play an important role in shaping evolutionary outcomes, their relative importance, as opposed to adaptation, in determining evolutionary outcomes remains a subject of debate. Evolutionary constraints are often evoked as the reason behind the persistence of inaccurate mimicry. Here, we compared the variation and accuracy of body-shape mimicry in ant-mimicking spiders with that of ant-mimicking insects, predicting greater constraints, and hence inaccuracy, in spiders mimicking ants, due to their evolutionary distance from the ant model. We found high inter-species variation in mimetic accuracy, but dorsally, no overall difference in mimetic accuracy between spider and insect mimics, which is inconsistent with a constraint causing inaccurate mimicry. Our study provides empirical evidence suggesting that imperfect mimicry in spiders and insects is predominantly shaped by adaptive processes rather than constraints or chance. Our findings contribute to our understanding of the mechanisms underlying evolutionary diversity and the processes that shape phenotypic outcomes.

Validation of the Donabedian Model of Health Service Quality in Selected States in Nigeria.

Every citizen of a nation has the basic constitutional right to quality health care. However, there is a dearth of literature on the validity and reliability of the Donabedian conceptual model of health service quality in Nigeria. The current paper focused on validating the Donabedian model of quality health service in selected states in Nigeria. This is a prospective study of 479 health workforce consisting of 204 physicians, 180 nurses, and 95 health information management officers in three geopolitical zones in Nigeria. A multistage sampling technique was used to select respondents. Data were collected through a semi-structured questionnaire with a response rate of 87%. The overall reliability test of the variables yielded α =0.938. Data gathered was analyzed descriptively for the socio-demographic characteristics and Relative Importance Index (RII) to rank the criteria according to their relative importance. Findings from the study reveal that the (RII) of all the items in the study instrument exceeded the universally acceptable threshold of 0.5, indicating a high level of care in Federal Tertiary Hospitals in Nigeria with regards to structure, process, and outcomes. The study underscored the need for the adoption of the Donabedian model in the three other geopolitical zones in Nigeria for a generalized conclusion on the validity and reliability of the Donabedian conceptual model of health service quality. We recommended that research studies on health service quality should be anchored on Donabedian conceptual model as a way to increase awareness of the relevance of the model in improving clinical care in Nigeria.

Use of machine learning to identify characteristics associated with severe hypoglycemia in older adults with type 1 diabetes: a post-hoc analysis of a case–control study

IntroductionSevere hypoglycemia (SH) in older adults (OAs) with type 1 diabetes is associated with profound morbidity and mortality, yet its etiology can be complex and multifactorial. Enhanced tools to identify...

Half a Century of Controversy: The Neutralist/Selectionist Debate in Molecular Evolution.

The neutral and nearly neutral theories, introduced more than 50 yr ago, have raised and still raise passionate discussion regarding the forces governing molecular evolution and their relative importance. The debate, initially focused on the amount of within-species polymorphism and constancy of the substitution rate, has spread, matured, and now underlies a wide range of topics and questions. The neutralist/selectionist controversy has structured the field and influences the way molecular evolutionary scientists conceive their research.

Developing a proof-of-concept curriculum foundation model for industry 5.0: A primary data survey of built environment academics

Purpose: Higher education curriculum development in the construction industry has historically received scant academic attention and often, courses/programmes are largely developed using the tacit knowledge of individual tutors. This research investigates the core interpersonal and technical skills and competencies required of a contemporary construction management graduate. Specifically, the work culminates in the development of a proof-of-concept model that could be incorporated into higher education curriculum development. Methodology: A mixed philosophical stance is implemented using both postpositivism and interpretivism together with inductive and abductive reasoning to examine built environment academics’ perceptions of the phenomena under investigation. Descriptive and inferential statistics (i.e., weighted average, relative importance index, one sample t test, Chi-square test and Kruskal-Wallis test) are utilised to formulate a foundational set of core interpersonal skills for construction management curricula. Such knowledge provides a strong foundation for building an optimised course curriculum. Findings: Research findings demonstrate that, whilst technical skills are relatively important for the construction manager’s role, they significantly pale in comparison to interpersonal skills. Furthermore, an aggregate ranking of skills and competencies suggests that a substantial number of interpersonal skills and competencies out-rank numerous technical skills and competencies. Surprisingly, digital-esque themes rank towards the bottom of the table, with ‘traditional’ skills competencies (i.e., workflow, budgeting and costing) ranking higher. Originality: This research constitutes the first attempt to: understand the core interpersonal and technical skills and competencies required of a contemporary construction manager; and premised upon this, generate a construction management education curriculum foundation model. Nascent findings pinpoint the core interpersonal skills and competencies that serve as the curriculum’s foundation and expose the inadequacies of digital technical skills in core construction management teaching.

Factors influencing deceased organ donation rates in OECD countries: a panel data analysis

ObjectivesThis study aims to investigate factors with a significant influence on deceased organ donation rates in Organisation for Economic Co-operation and Development (OECD) countries and determine their relative importance. It...

The trajectory of contemporary cryoplanation literature: A bibliometric assessment

AbstractThe origin of cryoplanation landforms has long been a subject of controversy in the literature on periglacial geomorphology. Multiple hypotheses have been advanced over the past century, but by the early 1970s only two had survived: geological structure and climate‐driven nivation processes. To determine whether some publications may be playing a “gate‐keeping” role through selective citation, we conducted a co‐citation analysis of the cryoplanation literature for the 1971–2018 period preceding a resurgence of publications by the authors of the present paper. The results indicate that there has been no overt attempt to influence the trajectory of the cryoplanation literature. Although consensus now exists that cryoplanation landforms are erosional phenomena, the roles of structure and nivation and their relative importance are still contested. We suggest that terminological complexity and ambiguity can be reduced by treating “nivation” as a process term and “cryoplanation terrace” as a morphological descriptor.

Temperature and nutrients alter the relative importance of stochastic and deterministic processes in the coastal macroinvertebrates biodiversity assembly on long-time scales.

Macroinvertebrates play a vital role in coastal ecosystems and are an important indicator of ecosystem quality. Both anthropogenic activity and environmental changes may lead to significant changes in the marine macroinvertebrate community. However, the assembly process of benthic biodiversity and its mechanism driven by environmental factors at large scales remains unclear. Here, using the benthic field survey data of 15 years at large spatial and temporal scales from the Yellow Sea Large Marine Ecosystem, we investigated the relative importance of environmental selection, dispersal processes, random-deterministic processes of macroinvertebrates community diversity assembly, and the responses of this relative importance driven by temperature and nutrients. Results showed that the macroinvertebrates community diversity is mainly affected by dispersal. Nitrogen and phosphorus are the most important negative factors among environmental variables, while geographical distance is the main limiting factor of β diversity. Within the range of 0.35-0.70 mg/L of nutrients, increasing nutrient concentration can significantly facilitate the contribution of the decay effect to β diversity. Within the temperature range studied (15.0-18.0°C), both warming and cooling can lead to a greater tendency for species diversity assembly processes to be dominated by deterministic processes. The analysis contributes to a better understanding of the assembly process of the diversity of coastal marine macroinvertebrates communities and how they adapt to global biogeochemical processes.