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Most statistical and machine learning models used for binary data modeling and classification assume that the data are balanced. However, this assumption can lead to poor predictive performance and bias in parameter estimation when there is an imbalance in the data due to the threshold election for the binary classification. To address this challenge, several authors suggest using asymmetric link functions in binary regression, instead of the traditional symmetric functions such as logit or probit, aiming to highlight characteristics that would help the classification task. Therefore, this study aims to introduce new classification functions based on the Lomax distribution (and its variations; including power and reverse versions). The proposed Bayesian functions have proven asymmetry and were implemented in a Stan program into the R workflow. Additionally, these functions showed promising results in real-world data applications, outperforming classical link functions in terms of metrics. For instance, in the first example, comparing the reverse power double Lomax (RPDLomax) with the logit link showed that, regardless of the data imbalance, the RPDLomax model assigns effectively lower mean posterior predictive probabilities to failure and higher probabilities to success (21.4% and 63.7%, respectively), unlike Logistic regression, which does not clearly distinguish between the mean posterior predictive probabilities for these two classes (36.0% and 39.5% for failure and success, respectively). That is, the proposed asymmetric Lomax approach is a competitive model for differentiating binary data classification in imbalanced tasks against the Logistic approach. [ABSTRACT FROM AUTHOR]

This study evaluates the links between representative indices of companies with high environmental performance and the propensity of such indices to economic and financial shocks. Five indices, representing environmental segments and four global macroeconomic and financial variables, were analyzed over a thirteen-year period, which included various crisis moments, such as the sovereign debt crisis, the COVID-19 pandemic and the onset of the Russia/Ukraine conflict. Using dynamic and nonlinear models, our research reveals statistically significant and consistent relationships between the variables under investigation, particularly during periods of global financial and pandemic crises. The analysis revealed that the VIXCLS is the most influential global risk factor, with certain risk factors being influenced by environmental segments, particularly Alternative Energy. This influence can create conditions conducive to contagion risk and diminish the benefits of portfolio diversification. This study contributes to a deeper understanding of the connection between environmental investments and their vulnerability to significant global events and risks. [ABSTRACT FROM AUTHOR]

Piecewise models have gained popularity as a useful tool in reliability and quality control/monitoring, particularly when the process data deviates from a normal distribution. In this study, we develop maximum likelihood estimators (MLEs) for the process capability indices, denoted as $ C_{pk} $ C pk , $ C_{pm} $ C pm , $ C^{*}_{pm} $ C pm ∗ and $ C_{pmk} $ C pmk , using a semiparametric model. To remove the bias in the MLEs with small sample sizes, we propose a bias-correction approach to obtain improved estimates. Furthermore, we extend the proposed method to situations where the change-points in the density function are unknown. To estimate the model parameters efficiently, we employ the profiled maximum likelihood approach. Our simulation study reveals that the suggested method yields accurate estimates with low bias and mean squared error. Finally, we provide real-world data applications to demonstrate the superiority of the proposed procedure over existing ones. [ABSTRACT FROM AUTHOR]

This study investigated the impact of the people category of the Sustainable Development Goals (SDGs) on sustainable and conventional economic growth in Asia and the Pacific region, using a sample of 52 selected countries between 2000 and 2023. Employing two distinct models, model A1 for conventional economic growth and model A2 for sustainable economic growth, we explained the relationships between five SDG indicators: employed poverty rate, stunted children, expenditure on health, expenditure of education, and % of women MNAs on economic growth. This study employed a fixed-effect model and random-effect model to investigate the impact of the people category SDGs on traditional and sustainable economic growth. The comparative analysis of each SDG in both models revealed valuable insights. SDG 1, "employed poverty rate", has a positive impact on economic growth in both models, while SDG 2, "percentage of stunted child", did not significantly influence economic growth in either model. Moreover, SDG 3 and SDG 4, relating to "government's health expenditure per capita" and "government's Education education expenditure per capita", respectively, exhibited a positive impact on traditional and sustainable economic growth. Conversely, SDG 5, "percentage of women members of national parliament", displayed an insignificant impact on traditional and sustainable economic growth models. In conclusion, this study suggests that policymakers should prioritize targeted interventions to alleviate employed poverty, enhance healthcare, and boost education spending. Moreover, promoting women's representation in national parliaments should be approached with context-specific strategies to maximize its impact on economic growth. [ABSTRACT FROM AUTHOR]

Over the past years, transport mode recognition has become a large field of research. However, flight as a type of transportation has been mostly overlooked. A system for flight detection might be useful for context-aware applications, but more importantly, it can be used to automatically manage airplane mode on smartphones. Smartphones transmit radio frequency signals which could potentially interfere with aircraft systems, and it is therefore important that devices enable airplane mode to avoid this problem. This paper proposes flyDetect, a method for automatic flight mode detection and an embodiment in the form of an app that demonstrates the viability of the method. Thus, the system uses the accelerometer and barometer in an Android smartphone, can detect the start and end of a flight, and notify other apps or systems on the device when this happens. Our evaluation shows that flyDetect meets the requirements set for the solution, and the results are very promising. [ABSTRACT FROM AUTHOR]

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The objective of this study was to evaluate the effect of incorporating different concentrations of graphene oxide (GO) nanoparticles on the mechanical properties of a resin-modified glass ionomer cement (RMGIC). A commercial RMGIC (Resiglass R, Biodinâmica) was modified by incorporating 0.1% and 0.5% (by weight) of GO into the powder's material. An unmodified RMGIC was used as a control group. Powder samples were characterized using Scanning Electron Microscopy (SEM) and Energy Dispersive Spectroscopy (EDS). Specimens were fabricated and subjected to flexural strength (n = 15), modulus of elasticity (n = 15), Vicker's microhardness (n = 10), and surface roughness tests (n = 10). Data were analyzed using one-way ANOVA and Tukey's post hoc test (α = 5%). Experimental groups' powder demonstrated a homogeneous dispersion of GO. No statistically significant difference was observed in flexural strength (p = 0.067) and modulus of elasticity (p = 0.143) tests. The groups containing 0.1% and 0.5% GO showed significantly higher microhardness and lower surface roughness values (p < 0.001) compared to the control group. The incorporation of GO nanoparticles at concentrations of 0.1% and 0.5% improved the microhardness and surface roughness without negatively affecting the flexural strength and modulus of elasticity of an RMGIC. [ABSTRACT FROM AUTHOR]

This study aims to examine the influence of individual and organizational factors on the implementation of circular economy (CE) practices in SMEs in Bangladesh. A non-probability sampling technique is utilized to select a sample of 280 respondents from the textile and leather industries. Data are collected through a survey assessing individual factors such as environmental consciousness and innovation propensity, as well as organizational factors including leadership commitment and training and development programs. A frequency table is used to give the respondents' details, and skewness and kurtosis are conducted to find the data normality. Reliability and validity analyses are conducted to ensure the robustness of the measurement instruments. A correlation matrix is generated to examine the relationships between variables, followed by a multiple regression analysis to test the hypothesized relationships. The preliminary findings indicate a significant correlation between individual and organizational factors and the implementation of CE practices. The multiple regression analysis reveals that both sets of factors contribute significantly to explaining the variance in CE implementation. The results indicate that environmental consciousness, innovation propensity, leadership commitment, and training and development programs emerge as significant predictors of CE implementation within these industries. This study offers valuable insights and sheds light on the role of individual and organizational factors in shaping sustainable practices. The findings contribute to the explanatory literature on CE implementation, providing empirical evidence to inform policymaking and business strategies aimed at promoting sustainability in the SME sector and beyond. [ABSTRACT FROM AUTHOR]

The aim of the current study is to identify grapevine rootstocks with the potential to tolerate excessive Cu concentrations. Four grapevine rootstock genotypes were tested: Paulsen 1103, IAC 572, SO4 and Isabel. The plants were cultivated in nutrition solution added to the following treatments: 0.3 µM Cu and 80 µM Cu. Growth, nutrient concentration in tissue and the physiological and biochemical parameters were assessed. Rootstocks showed different growth responses to Cu excess in the solution. SO4, IAC 572 and Isabel markedly reduced growth under Cu excess compared to plants in the control solution, whereas genotype Paulsen 1103 showed a less pronounced effect. The root system of all genotypes presented a Cu increase under a high Cu concentration, as well as higher POD activity and H2O2 concentration than the control. Isabel presented the greatest sensitivity to Cu excess, as shown by leaf wilting and yellowing. Paulsen 1103 rootstock presented smaller changes in the observed parameters in the high Cu concentration solution than in the control solution. Our results indicate that Paulsen 1103 is the most tolerant to Cu excess, whereas Isabel is the most sensitive. There are natural genetic variations in tolerance to this abiotic stress that typically affect grapevine plants. [ABSTRACT FROM AUTHOR]

Kaposi sarcoma (KS) is a neoplasm of vascular origin that promotes angiogenesis and the growth of endothelial cells triggered by the Kaposi Sarcoma‐associated Herpes Virus (KSHV). When associated with HIV, KSHV becomes more aggressive and rapidly evolves. The HIV‐1 TAT protein can be essential in developing AIDS‐associated KS by promoting angiogenesis and increasing KSHV replication. Therefore, we evaluated the genetic profile of the first exon of tat gene among groups of people living with HIV (PLHIV) with (case group, n = 36) or without KS, this later with (positive control group, n = 46) and without KSHV infection (negative control group, n = 24); all individuals under antiretroviral therapy. The genetic diversity, the DN/DS ratio, and the genetic entropy of the first exon of tat were higher in the case group, followed by the positive control group, which was higher than the negative control group. The number of tat codons under positive selection was seven in the case group, six in the positive control group, and one in the negative control group. The prevalence of HIV viral loads below the detection limit was equal in the case and positive control groups, which were lower than in the negative control group. The mean CD4+ T cell counts were higher in the negative control group, followed by the positive control group, and followed by the case group. These results emphasize the negative influence of KSHV in antiretroviral treatment, as well as the HIV‐specific TAT profile among PLHIV who developed KS. [ABSTRACT FROM AUTHOR]

Contribution: An analysis of the extent to which sustainability is present in the syllabi, project briefs, report templates, and student final reports of the three Iberian European project semester (EPS) providers, over a five-year period. Background: EPS is a one-semester capstone project framework that adopts project-based learning and multicultural, multidisciplinary teamwork. Educating engineers for sustainable development requires fostering critical and ethical thinking and a desire for equity, solidarity and preservation of natural resources, and cultural and genetic diversity. Existing engineering capstone design programs emphasize solving real world problems, hands-on training, and soft skills, but few focus on sustainability aspects of engineering design. The three Iberian EPS providers adopt project-based learning and teamwork methodologies, promoting the development of transversal skills and addressing sustainability in a multicultural and multidisciplinary background. Intended Outcomes: To show that the three Iberian EPS providers follow these recommendations and contribute to raising students' awareness of sustainable development. Application Design: The proposed sustainability learning assessment method collects evidence from syllabi, project briefs, report templates, and final reports to extract faculty and student perspectives. The sustainability-related terms collected were processed into word cloud format, allowing a simple and intuitive interpretation of students' understanding of sustainability, and in co-occurrence network format, to understand if sustainability has a pervasive or confined presence within the reports. Findings: Iberian EPS faculty and students are aware of the social, economic, and environmental impact of their projects, in terms of quality of life, social responsibility, the use of resources, and environmentally friendly technology.

Citrus sinensis orange juice is an excellent dietary source of β-carotene, a well-known antioxidant. However, β-carotene concentrations are relatively low in most cultivars. We developed a new orange through metabolic engineering strategy (GS) with 33.72-fold increase in β-carotene content compared to its conventional counterpart (CV). Using Caenorhabditis elegans, we found that animals treated with GS showed a greater reduction in intracellular reactive oxygen species (ROS) which is associated with a greater resistance to oxidative stress and induction of the expression of antioxidant genes. Moreover, animals treated with GS orange showed a more effective protection against β-amyloid proteotoxicity and greater hypolipidemic effect under high glucose diet compared to animals treated with CV. These data demonstrate that the increased amount of β-carotene in orange actually provides a greater beneficial effect in C. elegans and a valuable proof of principle to support further studies in mammals and humans.