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This paper argues for a reconsideration of social cohesion as an analytical concept and a policy goal in response to increasing levels of religious diversity in contemporary Australia. In recent decades, Australian has seen a revitalization of religion, increasing numbers of those who do not identify with a religion (the “nones”), and the growth of religious minorities, including Islam, Buddhism, Hinduism, and Sikhism. These changes are often understood as problematic for social cohesion. In this paper, we review some conceptualizations of social cohesion and religious diversity in Australia, arguing that the concept of social cohesion, despite its initial promise, is ultimately problematic, particularly when it is used to defend privilege. We survey Australian policy responses to religious diversity, noting that these are varied, often piecemeal, and that the hyperdiverse state of Victoria generally has the most sophisticated set of public policies. We conclude with a call for more nuanced and contextualized analyses of religious diversity and social cohesion in Australia. Religious diversity presents both opportunities as well as challenges to social cohesion. Both these aspects need to be considered in the formation of policy responses.

This paper analyzes the contours of religious and nonreligious diversity in the Canadian public sphere. The ever-changing (non)religious landscape offers an opportunity to consider the flow of ideas from this new diversity to responses and choices at the individual, group, and state levels to inclusion and exclusion. The paper first begins with a descriptive approach to religious diversity, identifying the normatively-charged nature inherent to measures of religion. It then turns to the notion of choices, considering the somewhat uniquely Canadian contributions of multiculturalism, reasonable accommodation, and the recent complication of nonreligion as a category of religious identity. The paper then considers three case studies which reveal the tensions embedded in the new diversity and responses to it in Canada, including (1) the Saint-Sacrement Hospital crucifix incident; (2) Zunera Ishaq’s challenge to the citizenship ceremony niqab ban; and (3) school controversies in Ontario’s Peel Region.

Sustainable development goal (SDG) 5 focuses on gender equality and empowerment and it is considered as one of the most important SDGs. Therefore, this article presented a time series prediction model that predicts gender-related educational results in the US, Saudi Arabia, China, Egypt, and Sweden. By analyzing gender-disaggregated demographic, socioeconomic, and educational data, the 1 DCNN can reveal temporal patterns and discrepancies. The main reason for selecting 1D-CNN as a deep learning model is its ability to model sequential data and detect minor changes. Through implementing the 1 DCNN with verified historical data, realistic progress trajectories have been predicted, which are suited to the particular circumstances of each country. The results obtained from the proposed model show that the model can produce important predictions in a range of gender-focused educational measures. In addition, it provides useful information that helps organizations develop, educators, politicians, and gender activists. In Conclusion, the results presented in this paper improve evidence-based planning and focused interventions, which hasten the advancement of gender equity in education and other fields.

Datafication is simultaneously becoming a means and a goal of modern marketdriven uses of technologies. The optimisation of the “consumer experience” shapes a data-driven consumer subject, which does not encompass all practices and identities. The article aims to problematise datafication, which overlooks complex “citizen experiences” that also include gender and sexual identity. At the same time, former and existing gender inequalities remain fundamental learning data, based on which algorithms and artificial intelligence generate models of future sociality. We encounter at least three interconnected types of inequality (on the levels of culture, data and technologies) that can create a self-sustaining and self-learning process that reproduces future inequalities.

Background The current understanding of brain aging and dementia diagnostics relies heavily on standardized data from homogeneous populations in the Global North, which creates challenges in assessing diverse populations. Critical gaps exist in understanding how geographical, socioeconomic, and demographic factors impact accelerated brain aging across global populations, particularly in underserved regions. Method We developed three approaches: (1) A computer‐vision DenseNet classifier analyzing raw structural MRI data from 3,000 participants with behavioral variant frontotemporal dementia (bvFTD), Alzheimer's disease (AD), and healthy controls; and (2) A graph‐based deep learning architecture analyzing High‐Order Interactions from fMRI and EEG data from 5,306 participants across 15 countries to study the difference between predicted age and chronological age (brain‐age gaps, BAGs); and (3) By analyzing associations between BAGs and exposomes using nonlinear Generalized Additive Models (GAMs) in a multimodal approach combining atrophy, fMRI and EEG. Result (1) The DenseNet classifier demonstrated robust performance across standardized 3T and non‐standardized 1.5T clinical images, with disease‐specific patterns identified in key brain regions of AD and FTD pathology. (2) The BAGs analysis revealed significantly older brain ages in Latin American and Caribbean (LAC) populations compared to non‐LAC regions. Structural socioeconomic inequality, pollution, and health disparities strongly predicted increased BAGs, particularly in LAC. We observed larger BAGs in females within LAC control and AD groups and an ascending BAG pattern from healthy controls to mild cognitive impairment to AD. (3) Our GAM results so far showed significant associations between BAGs and various factors including Human Development Index, economic equality, air pollution, and communicable disease death ratios, with all models showing high statistical significance (p <0.0001). A meta‐model combining GAM predictions demonstrated enhanced predictive power compared to individual models, suggesting that aggregate‐level environmental factors have meaningful effects on brain health globally. Conclusion These findings can provide scalable solutions to address accelerated aging disparities, particularly in underserved settings. GAM multimodal meta‐models increase the performance of BAGs estimations. Personalized AI tools can study accelerated brain aging trajectories and their modifiable risk factors.

The results of an experiment conducted in the Sea of Japan in August 2023 on an acoustic path with a length of 144.4 km under summer–fall hydrological conditions are discussed. The case of the propagation of pseudorandom pulse signals from an extended shelf into the deep sea upon reception at depths of 69, 126, 680, and 914 m is examined. The analysis of the experimentally obtained pulse characteristics has shown that a group of ray arrivals with a duration of approximately 0.5 s, with the maximum in the center, is recorded at all depths. The experiment on reception of broadband pulse signals with a central frequency of 400 Hz has been conducted at a distance of 144.4 km from the source of navigation signals (SNSs) located on the shelf at a depth of 30 m and a sea depth of 45 m. Signal information has been received using a system equipped with hydrophones distributed up to a depth of 1000 m, enabling long-term signal recording at fixed depths or during submersion. The experimental findings have made it possible to study pulse characteristics of the acoustic waveguide, to calculate the effective propagation velocities of signals received at different depths, and to conclude about the potential of using measuring autonomous underwater vehicles (AUVs) at depths up to 1000 m to solve the problems of climate monitoring of marine areas.

Recently, ecological damage and environmental pollution have become increasingly serious. Experts in various fields have started to study related issues from diverse points of view. To prevent the accelerated deterioration of the ecological environment, ecolinguistics emerged. Eco-critical discourse analysis is one of the important parts of ecolinguistics research, that is, it is a critical discourse analysis of the use of language from the perspective of the language’s ecological environment. Firstly, an ecological tone and modality system are constructed from an ecological perspective. Under the guidance of the ecological philosophy of \"equality, harmony, and symbiosis\", this study conducts an ecological discourse analysis on the Sino-US trade friction reports, aiming to present the similarities and differences between the two newspapers’ trade friction discourses and to reveal the ecological significance of international ecological factors in the discourse. Secondly, this method establishes a vector expression of abstract words based on emotion dictionary resources and introduces emotion polarity and part-of-speech features of words. Then the word vector is formed into the text feature matrix, which is used as the input of the Convolutional Neural Network (CNN) model, and the Back Propagation algorithm is adopted to train the model. Finally, in the light of the trained CNN model, the unlabeled news is predicted, and the experimental results are analyzed. The results reveal that during the training process of Chinese and English datasets, the accuracy of the training set can reach nearly 100%, and the loss rate can be reduced to 0. On the test set, the classification accuracy of Chinese text can reach 83%, while that of English text can reach 90%, and the experimental results are ideal. This study provides an explanatory approach for ecological discourse analysis on the news reports of Sino-US trade frictions and has certain guiding significance for the comparative research on political news reports under different ideologies between China and the United States.

Many academics and experts focus on portfolio optimization and risk budgeting as a topic of study. Streamlining a portfolio using machine learning methods and elements is examined, as well as a strategy for portfolio expansion that relies on the decay of a portfolio’s risk into risk factor commitments. There is a more vulnerable relationship between commonly used trademarked portfolios and neural organizations based on variables than famous dimensionality decrease strategies, as we have found. Machine learning methods also generate covariance and portfolio weight structures that are more difficult to assess. The least change portfolios outperform simpler benchmarks in minimizing risk. During periods of high instability, risk-adjusted returns are present, and these effects are amplified for investors with greater sensitivity to chance changes in returns R.

Hormone assessment is typically recommended for awake, unsedated dogs. However, one of the most commonly asked questions from veterinary practitioners to the endocrinology laboratory is how sedation impacts cortisol concentrations and the adrenocorticotropic hormone (ACTH) stimulation test. Butorphanol, dexmedetomidine, and trazodone are common sedatives for dogs, but their impact on the hypothalamic-pituitary-adrenal axis (HPA) is unknown. The objective of this study was to evaluate the effects of butorphanol, dexmedetomidine, and trazodone on serum cortisol concentrations. Twelve healthy beagles were included in a prospective, randomized, four-period crossover design study with a 7-day washout. ACTH stimulation test results were determined after saline (0.5 mL IV), butorphanol (0.3 mg/kg IV), dexmedetomidine (4 µg/kg IV), and trazodone (3-5 mg/kg PO) administration. Compared to saline, butorphanol increased basal (median 11.75 µg/dL (range 2.50-23.00) (324.13 nmol/L; range 68.97-634.48) 1.27 µg/dL (0.74-2.10) (35.03 nmol/L; 20.41-57.93); < 0.0001) and post-ACTH cortisol concentrations (17.05 µg/dL (12.40-26.00) (470.34 nmol/L; 342.07-717.24) 13.75 µg/dL (10.00-18.90) (379.31 nmol/L; 275.96-521.38); ≤ 0.0001). Dexmedetomidine and trazodone did not significantly affect basal (1.55 µg/dL (range 0.75-1.55) (42.76 nmol/L; 20.69-42.76); = 0.33 and 0.79 µg/dL (range 0.69-1.89) (21.79 nmol/L; 19.03-52.14); = 0.13, respectively, saline 1.27 (0.74-2.10) (35.03 nmol/L; 20.41-57.93)) or post-ACTH cortisol concentrations (14.35 µg/dL (range 10.70-18.00) (395.86 nmol/L; 295.17-496.55); (P = 0.98 and 12.90 µg/dL (range 8.94-17.40) (355.86 nmol/L; 246.62-480); = 0.65), respectively, saline 13.75 µg/dL (10.00-18.60) (379.31 nmol/L; 275.86-513.10). Butorphanol administration should be avoided prior to ACTH stimulation testing in dogs. Further evaluation of dexmedetomidine and trazodone's effects on adrenocortical hormone testing in dogs suspected of HPA derangements is warranted to confirm they do not impact clinical diagnosis.

Does women's empowerment strengthen global good citizenship? We test theories of democratic foreign policy and feminist international relations that suggest that more deeply democratic countries with greater gender equity will be stronger international human rights promoters. First, the direct empowerment of women as policymakers and civil society constituencies may shift states' incentives and ability to pursue international human rights initiatives. Second, greater sexual equality may lead to feminist socialization of the wider society to promote human rights values. We test these predictions by measuring the relationship between five different measures of sexual equality and a country's propensity to support 30 international human rights outcomes, including legal commitments, humanitarian assistance, and sanctions, controlling for previously established contributing factors such as level of development and democratic regime type. We find that more sexually equal countries are more likely to support international commitments to constrain state violence against individuals, international measures to combat gender and sexual orientation discrimination, and more and higher quality development assistance. However, sexual equality appears to yield less benefit for more costly human rights initiatives: yielding sovereignty to international legal institutions, promoting economic rights through concessionary trade policies, or adopting diplomatic sanctions against pariah states. These effects are stronger in democratic states, where citizen empowerment translates more readily into foreign policy, and are also found in a sample that excludes the Western powers.