Relative Importance Research Articles

Social protection strategies in relations between Ukraine and the European Union

In today’s world, social protection is becoming an increasingly important topic that combines economic, political, and social aspects. Regardless of the level of development of a country, people are constantly looking for ways to ensure their well-being and protect themselves from negative influences. Social protection strategies are of particular importance in relations between Ukraine and the European Union. Ukraine, as a sovereign state, monitors the needs of its population and tries to adapt its social system to European standards. Therefore, the purpose of the study is to analyze the current state and prospects for the development of social protection strategies in Ukraine in the context of cooperation with the European Union to identify possible areas for improving the social sphere and ensuring a high level of social protection for the Ukrainian population. The study uses a variety of methods, including analysis, synthesis, induction, deduction, comparative legal, dialectical, and others. Considering cooperation with the European Union helps to solve socioeconomic problems and ensure a high level of social protection.

The relation of clinical governance climate on quality of care mediated by patient safety culture

The hospital organization determines quality of care (QOC) from health services; however, there are many challenges due to the different backgrounds of healthcare workers. Essentially, governance is needed to guarantee a process oriented toward clinical outcomes. Unfortunately, research on clinical management with dimensional measurements conducted in private hospitals is still scanty. This study aimed to investigate the relationship between clinical governance climate (CGC) on QOC mediated by a patient safety culture (PSC) and the control variable adaptation to workload in relation to QOC. Participants were healthcare workers in two private hospitals that have been fully accredited; 416 participants met the requirements. Data were collected by distributing questionnaires in March 2023. Data were analyzed through partial least square – structural equation model (PLS-SEM). The study result indicated a significant positive relationship between CGC and PSC (β=0.851, p-value<0.05). Further, a positive relationship between PSC to QOC (β=0.654, p-value<0.05) was established. However, insufficient evidence indicates a direct relation between CGC on QOC (p-value>0.05). The role of PSC as a full mediating was confirmed (β=0.557, p-value<0.05, CI 95% 0.441-0.677). The finding of this study is the importance of CGC relation to QOC mediated by PSC in private hospitals.

Ethnopharmacological Survey of Medicinal Plants Used by Local Herbalists and Traditional Healers for the Treatment of Cancer in Jordan

Background: As many Jordanians include herbs in their treatment, an ethnopharmacological survey was conducted to identify the most prescribed plants for the treatment of cancer by local herbalists and traditional healers in Jordan, aiming to encourage the prescription that is based on scientific evidence, to tackle some important practices in traditional healing, and to provide candidates for the isolation of new anticancer agents. Methods: Thirty-two Jordanian herbalists and traditional healers were interviewed. Both the use value and frequency of citation were implemented as quantitative methods to demonstrate the relative importance of a chosen species for the treatment of cancer. Furthermore, literature was screened for evidences that supported or opposed the use of the plants of interest Results: It was revealed that 31 plants are currently used in Jordan for the treatment of cancer, with Curcuma longa and Ephedra foeminea being the most used ones. Conclusions: It was noticed that the use of many prescribed plants could be rationalised by in vitro and/or in vivo studies. However, more attention should be paid by practitioners to some important aspects, such as the method of use and preparation of plants, their interaction with chemotherapeutic agents and the differences in their efficacy against different cancer types.

HelloTalk Application as an Alternative for Building Students’ Reading Ability on Narative Texts

English was regarded as a foreign language in Indonesia and holds significant importance in various domains, including education, economy, international relations, and technology. Consequently, the Indonesian government has designated English as the primary foreign language, mandatory for learning in both schools and universities. Thus, English has incorporated into the curriculum from elementary level up to university. This research aimed to determine if there is a significant difference in the reading abilities of students taught using the Hellotalk application compared to those taught through conventional methods.in this school most of students still low to read the English text so the Reseacher interesting to give new method for them. The method used Quantitative research, with an experimental method and quasi-experimental design. The target population consisted of seventh-grade students. Purposive sampling was utilized to select a sample of 25 students for the experimental group and 25 students for the control group. Data collection involved the use of a multiple-choice test, which was subsequently analyzed using the independent t-test in SPSS 25. The research findings revealed a significant distinction between the experimental group and the control group. This meant that Hellotalk Application was suitable to use in teaching reading on narrative texts at the seventh grade.

MHGCN+: Multiplex Heterogeneous Graph Convolutional Network

Heterogeneous graph convolutional networks have gained great popularity in tackling various network analytical tasks on heterogeneous graph data, ranging from link prediction to node classification. However, most existing works ignore the relation heterogeneity with multiplex networks between multi-typed nodes and the different importance of relations in meta-paths for node embedding, which can hardly capture the heterogeneous structure signals across different relations. To tackle this challenge, this work proposes a M ultiplex H eterogeneous G raph C onvolutional N etwork (MHGCN+) for multiplex heterogeneous network embedding. Our MHGCN+ can automatically learn the useful heterogeneous meta-path interactions of different lengths with different importance in multiplex heterogeneous networks through multi-layer convolution aggregation. Additionally, we effectively integrate both multi-relation structural signals and attribute semantics into the learned node embeddings with both unsupervised and semi-supervised learning paradigms. Extensive experiments on seven real-world datasets with various network analytical tasks demonstrate the significant superiority of MHGCN+ against state-of-the-art embedding baselines in terms of all evaluation metrics. The source code of our method is available at: https://github.com/FuChF/MHGCN-plus .

An improved habitat suitability index for the great crested newt Triturus cristatus

An improved habitat suitability index for the great crested newt Triturus cristatus

Analysis of Factors Affecting the Implementation of Sustainable Building Projects

Abstract: Sustainability concept can be defined as “meeting the needs of the present without compromising the needs of the future” [7]. Conventional buildings approximately consumes more than 30% of energy while utilising around 40% of resources while also simultaneously generating 40% of wastes and 35% of harmful green-house gases [8]. The sustainable building construction approach has the potential to make a significant contribution to sustainable development, especially considering the building industry’s considerable influence. Based on our literature assessment, we discovered that multiple research reveal a general lack of consistency across outcomes in different geographical locations regarding factors impacting the implementation of sustainable building projects. Therefore this study is based on the analysis of factors that impact the implementation of sustainable building projects and the effects of sustainable building projects on various critical factors. For the result of the research analysis, the Reliability analysis which was conducted based on Cronbach's Alpha Coefficient for the factors affecting the implementation of sustainable building projects were found to be 0.76658442 which can conclude that the reliability level of the questionnaires responses was good while based on Relative Importance Index (RII) analysis factors affecting the implementation of sustainable building projects were ranked, with material related factors being the most significant (RII 0.705) among other factors. Additionally, the impact of implementing sustainable building projects on different critical factors was determined, with RII analysis indicating that the most significant impact will occur in terms of economic benefits (RII 0.767). Overall, the study tried fulfilling all the objectives which were stated.

Information and analytical support for economic evaluation and digital indication of innovative development of a developer enterprise in construction

In the conditions of functioning of construction enterprises, the importance of relations between the development of a construction and investment project and its stakeholders (stakeholders), which influence various aspects of project activities in order to make a profit, is growing. Reducing the effectiveness of interaction between construction developers and their partners, such as customers, contractors, design organizations, competitors and public organizations, requires the development of theoretical and methodological foundations for the implementation of a stakeholder-oriented strategy for managing construction enterprises. This strategy includes the organization of financing and implementation of a real estate development project, ta king into account the constraints and with the aim of obtaining commercial benefits. In today's world, construction development is a n area that is constantly being influenced by innovative technologies and strategies. The economic development of a country is determined by the efficiency of construction enterprises, which are an important indicator of the status and trends of the internal and external economic environment. The article explores innovative directions aimed at updating business processes and organizational structures of enterprises in the field of construction development. By analyzing and systematizing modern approaches to management and the use of advanced technologies, the article considers such innovative areas as the introduction of the Building Information Modeling (BIM) system, the use of intelligent management systems, the development of digital platforms, and others. Coverage of these areas will allow to provide an economic assessment and determine the criteria for qualimetric and factor analysis of indicators of innovative development of enterprises in the construction industry and their impact on the efficiency of business processes and competitiveness of enterprises. The economic assessment of innovative development in the development system is an important tool for enterprises seeking to achieve sustainable growth and success. Innovations have become a key success factor in the modern economy, especially in the field of construction and real estate development. Ukraine, as a country with active construction activity, has a great potential for innovative changes in this sector. However, for the effective implementation of innovations in the activities of construction enterprises, a deep economic assessment and economic and managerial analysis are required. This article serves as a source for studying and understanding innovative trends in construction development and considers the possibilities of their implementation to improve the efficiency of management and economic diagnostics and digital administration of directive indicators for assessing the innovative development of a construction developer enterprise.

Sustainable Consumption Behaviour and Common Goods: Education, Culture, Rule of Law, Work, and Solidarity

It is increasingly imperative to foster consumption behaviours that are more environmentally responsible. In order to design impact and sustainable actions that promote a transition to a more sustainable society, it is crucial to understand the underlying motivators that drive this change. Within this framework, this study sought to demonstrate how the comprehensive experience of common goods (solidarity, work, rule of law, culture, and education) is linked to such consumption behaviours. In order to test this hypothesis, a hypothetical-deductive quantitative approach was utilised, employing the second-generation statistical technique of partial least squares structural equation modeling (PLS-SEM) for data analysis. The results revealed that only the common good of Solidarity exhibits a significant relationship with Sustainable Consumption Behaviour. Additionally, Work and Education as common goods demonstrate a relationship of relative importance with this behaviour. Additionally, relationships were found between the common good, showcasing the interconnectedness rooted in cultural norms that strengthen individuals' experiences and, thus, cultivate a sense of community - an essential component for promoting consciousness and modifying behaviours. The novelty of this work is that it was not only focused on governing the commons, but also on how they are distributed and maintained for the long term. The theoretical basis was that natural resources are finite goods to which everyone should have access; however, not everyone enjoys them. That is why a limitation in agency impedes the experience of common goods and, therefore, in sustainable consumption. This study demonstrated that prioritising the welfare of others in addition to oneself, known as altruism, enhances the satisfaction derived from selfless consumption. The implications of this research include the development of instructional interventions incorporating motivational aspects to encourage sustainable consumption practices, ultimately supporting the shift necessary for the well-being of future generations.

Explainable machine learning for predicting stomatal conductance across multiple plant functional types

Stomatal conductance (gs) is a key leaf-level function controlling water, carbon, and energy exchange between vegetation and the surrounding environment. Conventionally, semi-empirical models have been used to model gs, but these models require re-parameterization as ecosystems undergo phenological changes over the growing season. In contrast, machine learning (ML) models offer a potential path to overcome this problem but are less interpretable than process-based models. This study explores ML as an approach to develop flexible and robust models of gs for a range of plant functional types (PFTs), including C3 crops, C3 grasses, shrubs, and tree species across different continents. An explainable machine-learning approach (eXML) was used here to provide novel interpretations and insights into the ML model formulations and relative predictor importance. We contrast the performance of three ML architectures: extreme gradient boosting, random forests, and neural networks. Models were developed and examined using many combinations of environmental and physiological predictors. The results demonstrated that ML models significantly outperform conventional semi-empirical models in predicting gs responses to the environment, while not requiring re-parameterization as is required in the semi-empirical paradigm. Particular focus is placed on models formulated around predictor sets that are: (a) relevant to gs estimation in modern terrestrial biophysical simulation models, and (b) composed of variables describing environmental and physiological drivers that can be remotely sensed non-invasively. “Generalized” models developed using data from all four PFTs demonstrated strong predictive performance using only three predictor variables, capturing 63–80 % of the variability in stomatal conductance across all ML architectures. Four predictor variables resulted in models capturing 79–83 % of gs variability, and models developed using all five predictor variables examined here were able to capture as much as 87 % of gs variability across all PFTs. Uncertainty in gs predictions was quantified using quantile regression. Shapley additive explanations was applied to unravel instance-based positive and negative contributions of environmental and physiological predictors to gs modeling, while illustrating that the models are consistent with the underlying ecophysiology. This work demonstrates the power of ML to introduce a new paradigm in the simulation of highly dynamic ecophysiological processes critical to environmental prediction.

Community Preferences for the Care of Older People at the End of Life: How Important is the Disease Context?

Population preferences for care at the end of life can inform palliative care policy and direction. Research investigating preferences for care at the end of life has focused predominantly on the context of advanced cancer, with relatively little attention to other life-limiting illnesses that are common causes of death. We aimed to investigate preferences for the care of older people at the end of life in three different disease contexts. The purpose was to understand if population preferences for care in the last 3 weeks of life would differ for patients dying from cancer, heart failure or dementia. Three discrete choice experiments were conducted in Australia with a general population sample using similar methods but different end-of-life disease contexts. Some attributes were common across the three experiments and others differed to accommodate the specific disease context. Each survey was completed by a different panel sample aged ≥45years (cancer, n=1548; dementia, n=1549; heart failure, n=1003). Analysis was by separate mixed logit models. The most important attributes across all three surveys were costs to the patient and family, patient symptoms and informal carer stress. The probability of choosing an alternative was lowest (0.18-0.29) when any one of these attributes was at the least favourable level, holding other attributes constant across alternatives. The cancer survey explored symptoms more specifically and found patient anxiety with a higher relative importance score than the symptom attribute of pain. Dementia was the only context where most respondents preferred to not have a medical intervention to prolong life; the probability of choosing an alternative with a feeding tube was 0.40 (95% confidence interval 0.36-0.43). This study suggests a need for affordable services that focus on improving patient and carer well-being irrespective of the location of care, and this message is consistent across different disease contexts, including cancer, heart failure and dementia. It also suggests some different considerations in the context of people dying from dementia where medical intervention to prolong life was less desirable.

An integrated conceptual model for enhancing refugee education

AbstractThis paper introduces a unified conceptual framework for understanding refugee identity construction within educational contexts, drawing on theories of social justice (Fraser, 2008), affective relations (Lynch, 2012), the resumption of ordinary life (Kohli, 2011) and ecological systems (Bronfenbrenner, 1977). Addressing a gap in the existing scholarship, the model emphasises the importance of affective relations in shaping refugee identities in education alongside other factors. The study examines the macro constructs of redistribution, recognition, representation and relational affect, highlighting their impact on refugee children's educational experiences. Further, it considers the micro constructs of safety, sense of belonging and success in integration and attainment in educational environments. The constructs are examined across various levels of Bronfenbrenner's ecological system, demonstrating the complexity of refugees’ needs. This model aims to facilitate a holistic, justice‐oriented approach to refugee education, which is crucial given the rise in global displacement. The study has significant implications for refugee education research and policymaking, potentially informing targeted interventions and programmes that foster academic success, overall well‐being, and practice in refugee education.

How Segregation Ruins Inference: A Sociological Simulation of the Inequality Equilibrium

Abstract Why do many people underestimate economic and racial inequality and maintain that theirs is a meritocratic society? Existing work suggests that people are rationalizing, misinformed, or misled. This article proposes an additional explanation: Inequality itself makes economic and racial disparities difficult to understand. In unequal societies, individuals establish their networks at formative institutions patterned by class and race. As a result, they unwittingly condition on key causal pathways when making descriptive and causal inferences about inequality. We use a simple agent-based model to show that, under circumstances typical to highly stratified societies, individuals will underestimate the extent of economic and racial inequality, downplay the importance of inherited advantages, and overestimate the relative importance of individual ability. Moreover, we show that they will both underestimate the extent of racial discrimination and overestimate its relative importance. Because segregated social worlds bias inference in these ways, all individuals (rich and poor) have principled reasons to favor less redistribution than they would if their social worlds were more integrated.

Interpreting biogeochemical processes through the relationship between total alkalinity and dissolved inorganic carbon: Theoretical basis and limitations

AbstractThe marine carbonate system is influenced by anthropogenic CO2 uptake, biogeochemical processes, and physical changes that involve freshwater input and removal. Two frequently used parameters to quantify seawater carbonate system are total alkalinity (TA) and total dissolved inorganic carbon (DIC). To account for the physical changes, both TA and DIC are usually normalized to a reference salinity (i.e., nTA and nDIC), and then the relationship between nTA and nDIC is used to identify major biogeochemical processes that regulate the carbonate system, based on process‐specific reaction stoichiometry. However, the theoretical basis of this interpretation has not been holistically examined. In this study, we validated this method under idealized conditions and discussed the associated assumptions and limitations. Furthermore, we applied this method to interpret field TA and DIC data from a lagoonal estuary in the northwestern Gulf of Mexico. Our results demonstrated that evaluating field data that encompass multiple stations and time periods could be problematic. In addition, various combinations of biogeochemical processes can lead to the same nTA–nDIC relationship, even though the relative importance of each individual process may vary significantly. Therefore, the stoichiometric relationship relying solely on TA and DIC data is not a definitive approach for uncovering dominant biogeochemical processes. Instead, measurements of process‐specific parameters are necessary.

Body condition and diet of the dyeing poison frog Dendrobates tinctorius (Cuvier 1797) (Amphibia: Dendrobatidae) from the eastern Brazilian Amazonia

The present study adds new data on the natural history of Dendrobatestinctorius. We conducted our fieldwork during the rainy season of the years2018 and 2019 in two protected areas (Parque Natural Municipal do Cancão–PNMC and Reserva Extrativista Beija-Flor Brilho de Fogo–REBFBF) in the state of Amapá, Brazil. Through active visual searches we sampled 22 individuals of D. tinctorius, of which 10 were countedfor the population of PNMC and 12 for the population of REBFBF. We calculatedthe Body Condition Index (BCI) for all individuals and, for dietary data, each frog’s stomach was flushed. Females from the REBFBF were larger than males whencompared to the PNMC population. BCI of females from the REBFBF showed higher values than males. Gravid females of both populations showed higher BCI. Retrievedstomachs revealed a total of 290 prey items divided into four main taxonomiccategories of Arthropods. The Index of Relative Importance revealed that antsof the genus Solenopsis were the majority of the diet, and mites represented only 4.86%. The niche breadth for both populations was narrow, indicating a specialist diet, as expected for the species. Our study evidences the importance of integration between BCI and dietary aspects.

Understanding Clinician Preferences for Treatment Attributes in Oncology: A Discrete Choice Experiment of Oncologists' and Urologists' Preferences for First-Line Treatment of Locally Advanced/Unresectable Metastatic Urothelial Carcinoma in Five European Countries.

Prior discrete choice experiments (DCE) in oncology found that, on average, clinicians rank survival as the most important treatment attribute. We investigate heterogeneity in clinician preferences within the context of first-line treatment for advanced urothelial carcinoma in Spain, France, Italy, Germany, and the UK. The online DCE included 12 treatment choice tasks, each comparing two hypothetical therapy profiles defined by treatment attributes: grade 3/4 treatment-related adverse events (TRAEs), induction and maintenance administration schedules, progression-free survival, and overall survival (OS). We used a random parameters logit model to estimate attribute relative importance (RI) (0-100%) and generate preference shares for four treatment profiles. Results were stratified by country. Preference heterogeneity was evaluated by latent class analysis. In August and September 2022, 498 clinicians (343 oncologists and 155 urologists) completed the DCE. OS had the strongest influence on clinicians' preferences [RI = 62%; range, 51.6% (Germany) to 63.7% (Spain)] followed by frequency of grade 3/4 TRAEs (RI = 27%). Among treatment profiles, the chemotherapy plus immune checkpoint inhibitor maintenance therapy profile had the largest preference share [51%; range, 38% (Italy) to 56% (UK)]. Four latent classes of clinicians were identified (N = 469), with different treatment profile preferences: survival class (30.1%), trade-off class (22.4%), no strong preference class (40.9%), and aggressive treatment class (6.6%). OS was not the most important attribute for 30.0% of clinicians. While average sample results were consistent with those of prior DCEs, this study found heterogeneity in clinician preferences within and across countries, highlighting the diversity in clinician decision making in oncology.

Environmental harshness does not affect the propensity for social learning in great tits, Parus major

According to the harsh environment hypothesis, natural selection should favour cognitive mechanisms to overcome environmental challenges. Tests of this hypothesis to date have largely focused on asocial learning and memory, thus failing to account for the spread of information via social means. Tests in specialized food-hoarding birds have shown strong support for the effects of environmental harshness on both asocial and social learning. Whether the hypothesis applies to non-specialist foraging species remains largely unexplored. We evaluated the relative importance of social learning across a known harshness gradient by testing generalist great tits, Parus major, from high (harsh)- and low (mild)-elevation populations in two social learning tasks. We showed that individuals use social learning to find food in both colour-associative and spatial foraging tasks and that individuals differed consistently in their use of social learning. However, we did not detect a difference in the use or speed of implementing socially observed information across the elevational gradient. Our results do not support predictions of the harsh environment hypothesis suggesting that context-dependent costs and benefits as well as plasticity in the use of social information may play an important role in the use of social learning across environments. Finally, this study adds to the accumulating evidence that the harsh environment hypothesis appears to have more pronounced effects on specialists compared to generalist species.

American idle: the relative importance of dispositional and environmental predictors of state labor force participation rates in the USA

This is the first study to determine the capacity of state-level IQ and Big Five personality to predict total, male, and female state labor force participation rates (LFPRs). It is based on residents aged 20–64 years in the 48 contiguous American states from 2013 to 2017. Five state environmental variables—White population percent, urban population percent, per capita personal income, political preference, and age distribution—were statistically controlled. Multiple regression analysis revealed that IQ independently predicted total, male, and female LFPRs with β coefficients of 0.67, 0.71, and 0.59, respectively. Neuroticism also independently predicted total LFPRs and male LFPRs with βs of − 0.20 and − 0.29. As well, lower Openness to Experience and higher liberal political preference were associated with higher female LFPRs, producing βs of − 0.37 and 0.47, respectively. No other variables emerged as independent predictors. Regarding total LFPR variance, the six dispositional variables jointly accounted for 23.0% with the five environmental variables controlled and 74.2% without. Corresponding values were 25.9% and 74.3% for male LFPRs, and 19.6% and 66.5% for female LFPRs. With the six dispositional variables controlled, the five environmental variables together could only account for 11.0% in total LFPRs, 10.8% in male LFPRs, and 16.5% in female LFPRs. Spatial autocorrelation was tested and found to be nonsignificant. These previously overlooked dispositional predictors of state LFPRs are especially important given the salience of LFPRs in economic functioning, declines in American LFPRs since 2000, and the 35th-place standing of the USA on LFPRs among nations by 2022.

Modelling of the Flame Surface Density Transport During Flame-Wall Interaction of Premixed Flames within Turbulent Boundary Layers

ABSTRACT A priori Direct Numerical Simulation (DNS) analysis of the modelling of the generalised flame surface density (FSD) transport equation in the framework of Reynolds Averaged Navier-Stokes (RANS) simulations has been conducted with a focus on flame-wall interaction (FWI) within turbulent boundary layers. The analysis was performed using two different scenarios: one involving the unsteady head-on interaction of a statistically planar premixed flame as it propagates through a turbulent boundary layer, and the other addressing statistically stationary oblique-wall interaction of a V-shaped premixed flame within a turbulent channel flow. Flame-wall interaction has been observed to exert a significant influence on the statistical behavior of the terms in the FSD transport equation. Throughout all phases of flame-wall interaction in both configurations, the primary source and sink terms in the FSD transport equation are consistently associated with the tangential strain rate and curvature terms. The relative importance of the contributions of the propagation and turbulent transport terms in the FSD transport equation have been found to be influenced by the flame-wall interaction configuration. Existing models for the tangential strain rate term in the FSD transport equation have been identified as inadequate based on a priori DNS assessment. Hence, adjustments to these models have been proposed to address the impact of flame orientation and near-wall effects specifically in the context of flame-wall interaction within turbulent boundary layers. The alignment between the flame normal vector and the wall normal vector has been identified as a crucial factor in modelling the contributions of unresolved dilatation rate and unresolved normal strain rate to the FSD transport equation. New models for these terms have been demonstrated to exhibit satisfactory agreement with the corresponding terms extracted from DNS data.

Landscape determinants of aquatic estuarine habitat use by juvenile Chinook salmon

Habitat restoration planning and design can be informed by information on spatial patterns in habitat use, which can be obtained from temporally and spatially extensive monitoring efforts. Using records from long-term monitoring in four tidal deltas, we modelled how landscape features (channel types, wetland vegetation types, and a channel network connectivity index) influenced juvenile natural-origin (NOr) and hatchery-origin (HOr) Chinook salmon presence/absence and density when present. Models detected strong effects of landscape characteristics on either presence/absence or density, although the directionality and relative importance of these features differed between NOr and HOr fish. In addition, while interannual differences were stronger for NOr juveniles, seasonal pattern was much stronger for HOr fish and was in fact the strongest predictor of density. For both types of fish, interactions of landscape features existed with seasonal pattern, indicating that habitat use changed dynamically from the beginning to the end of the rearing period. These findings help provide general principles for prioritizing location and designing of habitat restoration projects.