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An 8-week jump training did not boost effort value or the willingness to exert effort in a student sample

Physical inactivity remains highly prevalent, partly driven by the aversive nature of effort. However, effort can also be experienced as rewarding, which is associated with greater overall physical activity. Accordingly, the present study investigates whether regular physical exercise alters the self-reported value of physical effort, neural activation during exercise, and the willingness to exert effort. Sixty-two young adults were assigned to either an eight-week high-intensity jump training or a control group. Participants completed a two-task cycling ergometer exercise before and after the intervention. The first task assessed the value of effort at three pre-determined intensity levels, whereas the second task allowed participants to self-select the intensity to measure their willingness to exert effort. Participants’ perceived exertion and state value of physical effort were assessed, along with neural activation in the ventromedial prefrontal cortex and pre-supplementary motor area using functional near-infrared spectroscopy. Bayesian analyses provided evidence against main effects of condition, time, as well as their interaction, for self-reported value of physical effort, willingness to exert effort, and neural activity. This suggests that the value of effort may be relatively stable, as an eight-week training intervention did not alter the value of physical effort or the willingness to exert effort.

Support technology for weakly cemented roof roadways under alkaline water infiltration

A global map of seagrass ecosystems

Factors associated with low-density lipoprotein control in outpatients with myocardial infarction: A hospital-based study

Discrepancies in factors influencing low-density lipoprotein cholesterol (LDL-C) control in patients with myocardial infarction have been documented in existing literature. Assessing LDL-C control and the associated factors is a crucial initial measure for guiding future interventions aimed at enhancing health outcomes in patients with myocardial infarction (MI). This study aimed to evaluate LDL-C control status and explore the predictors of uncontrolled LDL-C in patients with myocardial infarction. Data were collected by a research pharmacist from medical records, including sociodemographic and clinical characteristics, comorbidities, prescribed medications, and biomedical parameters such as LDL-C levels among patients attending an outpatient cardiology clinic. The validated Arabic versions of the 4-item medication adherence scale and the medication beliefs questionnaire were used to evaluate medication adherence and beliefs, respectively. Binary logistic regression was implemented to investigate the predictors of LDL-C control. The results showed most of the patients (n = 255) had uncontrolled LDL-C (76.6%). Regression results revealed that smoking (OR= 2.006; 95% CI: 1.054–3.816; P = 0.034), receiving beta blockers (OR=2.211; 95% CI: 1.024–4.775; P = 0.043), and having uncontrolled blood pressure (OR=1.940; 95% CI: 1.069–3.520; P = 0.029) were independently associated with higher odds of uncontrolled LDL-C. In conclusion, in MI patients with poor LDL-C control, lowering the risk of cardiac complications and improving health outcomes require the development of focused and efficient LDL-C level management strategies. Achieving this goal will require putting strategies like smoking cessation counselling into practice and improving BP control.

Hybrid quantum-classical machine learning for industrial multi-anomaly detection via single acoustic sensor

Abstract We developed a novel workflow that leverages Quantum Kernel feature space expressiveness combined with classical dimensionality reduction techniques. This workflow enables detection and visual identification of multiple simultaneous anomalies using acoustic data from a single non-contact sensor. Our newly developed method provides an intuitive interface for operators to identify specific anomalies. By combining conventional Mel-frequency cepstral coefficients (MFCC) with principal component analysis (PCA), the newly constructed Quantum Kernel achieves near-perfect classification (F1 = 1.0 under specific conditions: j ≥ 9 features, file-level data splits) of complex multi-source anomalies, significantly outperforming the classical RBF kernel (F1 ≈ 0.75–0.76) and 1D-CNN autoencoder baseline (F1 ≈ 0.60–0.85). The Quantum Kernel’s superior representational power enables accurate anomaly detection with minimal training data. Our results demonstrate simulation-based evidence of potential quantum advantage under ideal conditions, where the performance of our method dramatically exceeds that of classical approaches as the number of features increases, pending validation on noisy intermediate-scale quantum (NISQ) hardware. This hybrid quantum-classical machine learning approach demonstrates significant potential for industrial applications, particularly for complex time-series data in data-scarce regimes where classical methods exhibit limited performance.

Signal mining and analysis of adverse events associated with Isotretinoin: A 20-Year real-world pharmacovigilance study based on FAERS and EudraVigilance databases

Objective To systematically characterize the post-marketing safety signals of isotretinoin using real-world data from the U.S. FDA Adverse Event Reporting System (FAERS), with independent external validation in the European EudraVigilance (EV) database. Methods Adverse event (AE) reports in FAERS from 2004Q1 to 2024Q3 were analyzed. Signal detection was conducted using four complementary disproportionality algorithms: reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence propagation neural network (BCPNN), and the multi-item gamma Poisson shrinker (MGPS). Signals concurrently detected by all four methods were defined as robust. Key findings were subsequently examined in EV as an external reference. Results Among 50,519 patients contributing 142,160 isotretinoin-associated AE reports, 469 statistically robust signals were identified, spanning 25 system organ classes (SOCs). Signals were most concentrated in psychiatric disorders (75, 15.99%), gastrointestinal disorders (58, 12.37%), and congenital, familial, and genetic disorders (50, 10.66%). The strongest association was observed for inflammatory bowel disease (IBD; ROR = 579.14); however, temporal clustering and reporter-type profiling suggested substantial stimulated reporting, potentially driven by litigation, warranting cautious interpretation. Several high-ranking signals were not described in current product labeling, including nasal vestibulitis, hypertrophic anal papilla, and SAPHO syndrome. Pregnancy-related signals were prominent, with unintended pregnancy showing a strong signal (ROR = 91.39). External validation in EV demonstrated high concordance, supporting the robustness and reproducibility of the findings. Conclusions Isotretinoin is associated with a broad spectrum of pharmacovigilance signals, with disproportionate representation of psychiatric, gastrointestinal, and pregnancy-related events. While multiple previously unlabelled signals emerged, their clinical relevance remains to be established. These findings underscore the need for strengthened clinical monitoring, rigorous pregnancy prevention strategies, and careful interpretation of spontaneous reporting data.

Enhancing IoT network security with explainable deep learning-based intrusion detection systems

A pilot study on the impact mechanism of internal and external leading variables on consumers’ purchase intention and healthy dietary behavior of plant-rich foods

This study integrates the TPB with Information Processing Theory and Sensory Marketing Theory to investigate the influence mechanisms of Plant-Rich Foods(PRF) attributes and their packaging on consumer purchase intention and healthy eating behaviors. Through the construction of a structural equation model, empirical analysis was conducted on seven core variables and their interrelationships: consumer attitude(CA), socio-cultural environment(SE), consumer individual requirements(CIR), packaging environmental considerations(ECP), perceived experiential value(PEV), food information factors(FIF), and packaging functional attributes(FPP), thereby validating the proposed hypotheses. The results indicate that all seven variables significantly and positively influence purchase intention, albeit with varying strengths. Packaging functional attributes demonstrated the strongest driving force, followed by individual consumer needs and food information factors. Perceived experiential value, consumer attitude, and packaging environmental considerations exhibited moderate influence, while the socio-cultural environment exerted the weakest impact. The overall influence of “externally oriented” product variables on purchase intention surpassed that of “internally oriented” consumer variables. The impact on healthy eating behaviors presented a dual logic of “direct drive and indirect transmission.” consumer individual requirements exhibited a weaker direct influence on healthy eating behaviors compared to their influence on purchase intention, forming a chained transmission pathway from individual needs to purchase intention to healthy behaviors. Theoretically, this research extends the application of the Theory of Planned Behavior, elucidates the transmission mechanisms of variables, and constructs a multidimensional relational framework. Practically, it offers direction for plant-based food enterprises in optimizing packaging and marketing communication strategies, and provides a reference basis for policymakers.

Validation of within-person associations with coverage and momentary EMA self-reports using an objective standard (physical activity)

Editorial Note: Multi-objective optimization using improved NSGA-II for integrated process planning and scheduling problems in a machining job shop for large-size valve

Dissociation in the temporal dissipation of motor and perceptual aftereffects following trampoline jumping

People use fast and flat simulation to reason about new games

Abstract Games have long been a microcosm for studying planning and reasoning in both natural and artificial intelligence, often focusing on expert-level or even super-human play 1–6 . But real life also pushes human intelligence along a different frontier, requiring people to flexibly navigate decision-making problems that they have never thought about before. Here we use novice gameplay to study how people reason about new problem settings. Through a series of large-scale behavioural studies with over 1,000 participants and 121 two-player strategic board games (almost all novel to our participants), we show that people are systematic and adaptively rational in how they play a game for the first time or evaluate a game (for example, how fair or how fun it is likely to be) before they have played it even once. We explain these capacities via a computational cognitive model that we call the ‘Intuitive Gamer’: a model based on mechanisms of fast and flat (depth-limited) goal-directed probabilistic simulation. Our work offers insights into how people rapidly evaluate, act and make suggestions when encountering novel problems, and could inform the design of more flexible and human-like artificial intelligence systems that can determine not just how to solve new tasks but also whether a task is worth thinking about at all.

Developing comprehensive perinatal quality of care instruments in Mexico: An inclusive, multidisciplinary, and culturally sensitive approach

Ensuring high-quality care during pregnancy, childbirth, postpartum, and the newborn period is essential for reducing maternal and neonatal morbidity and mortality. In Mexico, a significant gap exists in comprehensive, culturally relevant instruments to assess quality of care (QoC) across these critical stages. This study aimed to develop robust, context-specific instruments to evaluate key dimensions of maternal and neonatal care, including patient experience, clinical processes, and hospital infrastructure. Using a modified Delphi method, we conducted two national workshops with 78 unique national experts, including academic researchers, healthcare decision-makers, and maternal health advocates. In Workshop 1, 45 experts identified 1,162 QoC indicators, which our research team subsequently reduced to 521 through a systematization process. Workshop 2 engaged 62 experts–approximately 20% of whom had also participated in Workshop 1–who discussed and rated the 521 indicators. Based on these expert ratings, our research team conducted a subsequent systematization, which further reduced the list to 489 QoC indicators. The final 489 indicators were categorized into five core QoC domains (i.e., Woman, Care Processes, Health Personnel, Infrastructure, and Supplies and Medications ) and used to develop three instruments (1) a Semi-Structured Interview Guide to explore women’s care experiences; (2) a Childbirth Observation Instrument to assess QoC during labor and immediate postpartum care, including sociodemographic details, facility characteristics, clinical processes, and adherence to best practices, and (3) a Hospital Information Instrument to gather data on infrastructure, personnel, supplies, medications, and service utilization. These instruments offer a rigorous, context-specific framework for evaluating maternal and neonatal QoC in Mexico, helping identify gaps, guide improvements, and promote health equity. They address a critical need by providing tailored tools with strong potential to inform practice and improve outcomes.

Adjunctive vitamin D supplementation in women receiving dienogest therapy for endometriosis: a randomized controlled trial

Why there needs to be a global debate on inequality

Exploring the relationship between supervisory support, self-efficacy, and satisfaction among nursing students in Saudi Arabia

Background Supervisory support during clinical placements is central to nursing students’ professional development. Professional self-efficacy, students’ confidence in performing clinical tasks, is increasingly recognised as a key outcome associated with transition to practice and workforce retention. In Saudi Arabia, Vision 2030 healthcare reforms have intensified demand for qualified nurses, making the quality of clinical supervision a strategic priority. This study examined the relationships among supervisory support, professional self-efficacy, and nursing student satisfaction at King Saud University-affiliated hospitals. Methods This descriptive cross-sectional study was conducted among 145 nursing students (second-, third-, and fourth-year bachelor’s degree students) at three King Saud University-affiliated teaching hospitals in Riyadh, Saudi Arabia. Participants were selected using stratified random sampling based on year of study. Data were collected using four validated instruments: a sociodemographic questionnaire, the Supervisory Support Scale (9 items; Cronbach’s α = 0.90), the Nursing Student Satisfaction Scale (6 items; α = 0.88), and an adapted Professional Self-Efficacy Scale (12 items; α = 0.90). Descriptive statistics summarised the three key study variables (supervisory support, professional self-efficacy, and student satisfaction) alongside sociodemographic characteristics. Pearson correlation coefficients assessed the strength and direction of linear associations among continuous study variables. Formal mediation analysis was conducted using the PROCESS macro (Model 4) with 5,000 bias-corrected bootstrap resampling iterations. Results Of 175 students approached and meeting eligibility criteria, 145 returned valid questionnaires (response rate = 82.9%). The sample was predominantly female (60.7%) and in the age range of 20–22 years (66.9%). Students reported high levels of supervisory support (mean = 4.10 ± 0.53 out of 5), satisfaction with clinical placements (mean = 4.11 ± 0.52), and professional self-efficacy (mean = 4.06 ± 0.56). Supervisory support was strongly correlated with satisfaction (r = 0.68, p < 0.001) and professional self-efficacy (r = 0.57, p < 0.001); professional self-efficacy was positively correlated with satisfaction (r = 0.49, p < 0.001Statistical mediation analysis revealed that professional self-efficacy partially mediated the supervisory support–satisfaction relationship: the indirect association (ab = 0.13, 95% CI [0.07, 0.19]) was statistically significant and accounted for approximately 19% of the total association. In regression analysis, supervisory support remained significantly associated with satisfaction (β = 0.43, p < 0.001) even after accounting for professional self-efficacy, consistent with partial statistical mediation. Conclusions Supervisory support was significantly and positively associated with nursing students’ satisfaction and professional self-efficacy. These findings, grounded in social cognitive theory, suggest that high-quality supervision may enhance clinical learning outcomes both directly and through strengthening students’ professional confidence. Standardising supervisory practices, investing in supervisor training, and creating structured feedback mechanisms are priorities for improving nursing education in Saudi Arabia and advancing national nursing workforce goals under Vision 2030.

The effect of compaction pressure and sintering temperature on phase evolution and technological properties of alumina mullite zirconia ceramics

Abstract Alumina–mullite–zirconia ceramic composites were fabricated using a solid-state reaction involving nano silica, alumina, and zirconia powder mixes at varying sintering temperatures (1450–1600 °C) and compaction pressures (80–160 MPa). Magnesia was added in a consistent proportion to stabilize the tetragonal phase of zirconia at room temperature and as sintering aid. The densification parameters of sintered ceramic composites, namely bulk density, apparent porosity, and linear change, were measured. The phase composition and microstructure of sintered ceramics were determined using XRD and SEM. The results show that a specific quantity of nano silica (5 wt%) plays an important role in improving the sintering and densification parameters of sintered samples. Compaction pressures of up to 120 MPa enhanced the densification parameters in sintered samples due to increases in powder compact and sold state sintering processes. Stress-induced phase transformation from tetragonal to monoclinic in zirconia, which is accompanied by a 3–5% volume expansion, may improve the mechanical properties of sintered samples. This volume expansion forms a compressive stress zone around a crack tip, thereby preventing it from propagating.

Bone-conducted ultrasonic auditory brainstem response thresholds in a mouse model of cisplatin-induced hearing loss

Cisplatin is widely used in cancer treatment but can cause hearing loss, predominantly at high frequencies. Auditory responses to bone-conducted ultrasonic stimulation have been proposed as a potential indicator of cochlear function, but it remains unclear how such responses are affected by cochlear damage. In this study, we measured auditory brainstem response (ABR) thresholds within and beyond the conventional hearing range in a mouse model of cisplatin-induced hearing loss. Of 32 mice initially examined, 9 were excluded at baseline because of pre-existing high-frequency hearing impairment. The remaining animals received either saline or cisplatin, and post-treatment analysis in the cisplatin group was based on 16 surviving mice. Cisplatin administration increased ABR thresholds within the conventional hearing range. In contrast, threshold shifts evoked by bone-conducted ultrasonic stimulation were often smaller. Paired comparison of mean threshold shifts showed that changes evoked by bone-conducted ultrasonic stimulation were significantly smaller than those within the conventional hearing range. These findings show that ABR threshold shifts evoked by bone-conducted ultrasonic stimulation do not necessarily parallel those within the conventional hearing range in cisplatin-treated mice.

Interplay of ELF5, GATA-3 and FLI-1 regulate malignant transformation of keratinocytes

Abstract Cutaneous squamous cell carcinoma (cSCC) arises from epidermal keratinocytes and is the second most common epithelial malignancy. E74-like factor 5 (ELF5) is a member of the epithelium specific ETS subfamily of transcription factors and is essential for epithelial development, homeostasis and prevention of epithelial tumourigenesis. Transformation of keratinocytes involves the disruption of the progenitor differentiation program causing keratinocytes to fail to complete the process. This can lead to dysplastic epithelium and precancerous cells in skin. However, the precise mechanisms that causes the failure of keratinocytes to differentiate completely is not well understood. In our study, we discovered that ELF5 is abundantly expressed in healthy human skin (both basal and suprabasal layers), while its expression is lost in cSCC tissue biopsies. Using CRISPR-Cas9 knockout technology, functional studies along with transcript and protein analysis, loss of ELF5 in immortalised healthy keratinocytes leads to decreased ability of cells to differentiation and increased migration and tumourigenicity, in vitro. Overexpression of ELF5 leads to inhibition of cell migration and proliferation in keratinocytes and in cancer cell lines (A431 and SCC-9), in vitro. Further analysis using RNA transcriptomics has uncovered that GATA-3 and FLI-1 are potentially key molecular targets of ELF5 in keratinocytes. ELF5 regulation of both GATA-3 and FLI-1 is required to maintain the balance between healthy keratinocytes (proliferation/differentiation) and to inhibit precancerous cell formation (tumourigenicity). Our data indicates that ELF5 plays an important role in potentially preventing transformation of keratinocytes and could suppresses skin tumourigenesis. However, additional studies are required to determine this, which could lead the targeting of ELF5 for future drug treatments in cSCC. Better understanding of the underlying mechanisms by which ELF5 regulates gene expression and consequently cell activity will provide new knowledge that can be translated into long-term benefits for patients with precancerous lesions to cSCC.

Rising dust pollution across Europe in a changing climate

Abstract Mineral desert dust is a major contributor to total atmospheric particulate matter 1 . Desert dust outbreaks degrade air quality and can pose adverse health effects 2 , including asthma exacerbation 3 and increased mortality 4 . At some European locations, there has been a rise in the intensity and frequency of transported dust outbreaks from deserts in recent decades 5–9 . However, it remains unclear whether this increase is consistent across Europe and whether desertification and aridity or shifts in atmospheric circulation are the main drivers behind this rise. Here we compile a database of daily dust metal concentrations from European sites, establishing robust elemental ratios for transported dust. Using this database, we develop a machine learning model to estimate daily PM 10 (particulate matter smaller than 10 μm) dust concentrations from 2012 to 2021, ranging from 2.09 ± 1.05 μg m −3 across northern and central Europe to 5.28 ± 2.65 μg m −3 across the south. In southern Europe, residents are exposed to transported dust events averaging 9.68 ± 4.85 μg m −3 , linked to a 0.67 ± 0.02% rise in daily mortality. Intensified dust intrusions over the past decade are linked to shifts in atmospheric circulation. Data from an Alpine ice core record shows a 110% increase in dust concentrations since pre-industrial times, mostly associated with North African desertification. As climate change accelerates land degradation and affects weather patterns, worsening dust pollution may pose increasing risks to public health and air quality goals.