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Development of the Semi-Implicit Self-Report to assess Attitudes Toward Immigration (SISRATI): Psychometric properties and convergence
Attitudes toward immigration in Spain represent a pressing social concern, particularly in the context of increasing reports of racism and public rejection and concern. However, assessing these attitudes is complicated by social desirability bias inherent in self-report measures. This study aimed to develop and validate a semi-implicit instrument using news headlines—half pro-immigration and half anti-immigration—which participants (N = 616, divided into two sub-samples) judged as true or false. Psychometric properties were evaluated through Exploratory and Confirmatory Factor Analyses, revealing a two-factor structure comprising 12 items: “Pro-Immigration Statements” and “Anti-Immigration Statements.” Based on these dimensions, participants were clustered into four groups: “Favorable to Immigration,” “Unfavorable to Immigration,” “Non-Discriminant Believers,” and “Non-Discriminant Unbelievers.” These groups were then compared on emotional responses (valence and intensity) to immigration-related content, Big Five personality traits, and reflective cognitive style. Significant differences in emotional responses across groups supported the tool’s convergent validity. The results highlight the utility of semi-implicit measures in capturing nuanced attitudes toward immigration and avoiding the biases of traditional self-report methods. Implications for future research and social intervention are discussed, along with study limitations and potential improvements for the proposed tool.
Infrared thermography to assess fatigue, injury risk factors and recovery in soccer: a systematic review of original studies
Background: Recovery after a training session or match is a key factor in injury prevention and sports performance. The purpose of this systematic review was to analyze and consolidate the available scientific evidence from the main databases on the use of infrared thermography in the assessment of fatigue, injury risk factors, and recovery in soccer players.Methods: The literature search was conducted following the PRISMA guidelines and the PICOS model until June 30, 2025, in the main scientific databases (ScienceDirect, EMBASE, Web of Science (WOS), Cochrane Library, SciELO, MEDLINE/PubMed, SPORTDiscus, and Scopus). The risk of bias and methodological quality were assessed using the Cochrane Handbook guidelines and the PEDro scale.”Results: The initial literature search yielded a total of 510 records. After applying the inclusion and exclusion criteria, the final sample consisted of 20 studies, which were of high methodological quality. The results showed the effects of infrared thermography in assessing fatigue, identifying injury risk factors, and monitoring recovery processes in soccer players. The studies also systematically reported the characterization of the population, the assessment methods used, the variables analyzed, the methodological design, the main results, and the effects of the intervention.Conclusions: Infrared thermography shows promise as a valid, reliable, and non-invasive tool for assessing skin temperature, reflecting temperature changes in response to physiological processes. It allows for the analysis of structural or metabolic fatigue and thermal asymmetries. Therefore, thermography could be used to design individualized recovery protocols.
Advanced Wafer Hotspot Detection through Image Segmentation and Stacked Model
The wafer map is a data visualization of a thin semiconductor fabric made of crystalline silicon, such as defects or test results. The wafer map is a base for creating electronic coordinate circuits and photovoltaic cells. During the wafer map production, any fault results in a product failure. The wafer map faults are undetectable to the naked eye, which is a big challenge. Hotspot detection in wafer maps is significantly important to evaluate the manufacturing process and. improve product yield. The hotspot detection in the wafer maps is the primary aim of this research. A novel wafer map hotspot detector (WHD) is proposed based on three stack fully connected conventional neural network layers and a dense layer. Data augmentation uses the segmented images of the wafers to build the proposed model. The proposed model is evaluated through several evalua-tion parameters and state-of-the-art studies comparative analysis. The proposed model achieved a 94% training and 90% testing performance accuracy for hotspot detection and shows better results than existing approaches. This study helps semiconductor engineers improve wafer manufacturing designs and efficiency in the semiconductor industry.
Consumption of ultra-processed foods is associated with cognitive status in elderly patients
Background: Emerging evidence suggests that there might be an association between excess consumption of ultra-processed foods (UPFs) on cognitive health. UPF intake could promote systemic inflammation, oxidative stress phenomena, and metabolic dysregulation, contributing to neurodegeneration onset and cognitive decline in elderly population.Aim: The aim of this cross-sectional study was to examine the relation between UPF dietary pattern on MCI status in elderly patients taking into account the contribution of inflammatory markers.Design: The dietary intake was assessed using a validated food frequency questionnaire in ninety-two participants. All reported food items were categorized according to the NOVA system, classifying foods on the basis of the extent and purpose of industrial processing. Plasmatic concentrations of TGF-β1 and TNF-ɑ were measured by ELISA assay at the time of baseline neuropsychological evaluation. The Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) were administered to evaluate the cognitive function in all participants. Non-parametric tests, correlation analysis, and logistic regression models were performed to assess the relations between variables of interest.Results: No significant associations were observed for unprocessed/minimally processed foods, culinary processed foods, or processed foods across the different regression models. In contrast, higher consumption of UPF was associated with increased odds of MCI (adjusted OR = 4.24, 95% CI: 1.05–17.13). However, after additional adjustment for inflammatory biomarkers (TGF-β and TNF-α), the association was attenuated and no longer statistically significant (OR = 4.79, 95% CI: 0.73–31.24), although the direction of the association remained positive.Conclusion: UPF consumption may be associated with increased likelihood of MCI, and inflammatory status may potentially play a role in this association.
Association between socioeconomic and health variables and community-acquired pneumonia mortality rates in Chile from 1990 to 2021
Objectives To describe long-term trends in mortality attributed to community-acquired pneumonia (CAP) in Chile from 1990 to 2021, stratified by age group, and to evaluate associations with selected socioeconomic and demographic indicators. Study design Ecological, observational, longitudinal study using national secondary data. Methods CAP mortality rates were analyzed for the total population and by age group. Associations with the Human Development Index (HDI), poverty rate, aging index, and life expectancy at birth were examined using a hierarchical analytical approach. This included Spearman's rank correlation for initial exploration, multivariable linear regression to assess adjusted associations, and Prais–Winsten generalized least squares regression to account for first-order autocorrelation and shared temporal trends. Stationarity was evaluated using augmented Dickey–Fuller tests, with supplementary analyses using first-differenced variables. Missing data were imputed using time-based regression or interpolation, with sensitivity analyses performed. Results CAP mortality declined substantially across all age groups over the study period. Strong bivariate correlations were observed between mortality and all socioeconomic indicators; however, these associations were attenuated after adjustment for confounding and temporal autocorrelation. In multivariable and time-series models, HDI and the aging index remained significantly associated with CAP mortality in children (0–9 years) and older adults (≥65 years), whereas associations in intermediate age groups were not robust after accounting for shared secular trends. Poverty and life expectancy did not demonstrate independent associations in adjusted models. Conclusions CAP mortality in Chile has decreased markedly over the past three decades. Associations with socioeconomic indicators are strongest at the extremes of age and persist after accounting for temporal structure, although the ecological design precludes causal inference. These findings highlight the importance of considering demographic and socioeconomic context in population-level analyses of infectious disease outcomes.