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Audio long read: How quickly are you ageing? What molecular ‘clocks’ can tell you about your health
Life cycle assessment based method for the environmental and mechanical evaluation of waste tire rubber concretes
Quantifying the dynamics of peak disruption in scientific careers
Abstract We examine the disruption of researchers with long-lived careers in Computer Science and Physics. Despite the epistemological differences between such disciplines, we consistently find that a researcher’s most disruptive publication does not occur at random during their career, as it cannot be explained by a null model. Such publication is accompanied by a peak year in which researchers publish other work that exhibits a higher level of disruption than average. Through a series of linear models, we show that the disruption achieved by a researcher during their peak year is higher when it is preceded by a long period of focus and low productivity. These findings are in stark contrast with the dynamics of academic impact. In these dynamics, researchers are incentivized by the prevalent paradigms of scientific evaluation to pursue high productivity and incremental—less disruptive—work, as evidenced by extensive literature.
Publishers trial paying peer reviewers — what did they find?
Proactive intervention depressurization control for pre-mining roof fall and mining impacts
Analysis of the molecular mechanisms of ulcerative colitis and atherosclerosis by microarray data
Micro-computed tomographic evaluation of root and canal anatomy of maxillary first premolars in Iraqi sub-population
Association between defecation status and the habit of eating vinegar-based dishes in community-dwelling Japanese individuals: a cross-sectional study
Abstract Vinegar intake reportedly has an antihypertensive effect and reduces visceral fat. Nonetheless, studies on the form of vinegar intake and its effect on defecation are scarce. This cross-sectional study aimed to investigate the association between the frequency of vinegar-based dish intake and defecation status using data from the Tarumizu cohort study. The participants (n = 1024, 634 women) responded to a health check survey in 2019 using a brief-type self-administered diet history questionnaire. The association between the frequency of vinegar-based dish intake and defecation status was examined using a multivariate logistic regression analysis. Considering confounding factors influencing the defecation status such as sex, age, dietary fiber intake, and medication history, individuals with a habit of eating vinegar-based dishes, such as “sour main dishes” (odds ratio [OR]: 1.38; p = 0.039), “sunomono” (OR: 1.49; p = 0.035), and “salad with sour dressing” (OR: 1.41; p = 0.049), had a significantly higher defecation frequency. No significant association was observed between the habit of eating vinegar-based dishes and the time required for defecation or straining during defecation. Our study showed that the habit of eating vinegar-based dishes was positively associated with defecation status. Our findings may suggest a novel approach for defecation improvement in people with defecation problems.
The relationship between urinary glyphosate and all-cause and specific-cause mortality: a prospective study
Alternative splicing analysis in a Spanish ASD (Autism Spectrum Disorders) cohort: in silico prediction and characterization
Association between body roundness index and psoriasis: a cross-sectional study
Age at onset and clinical course of RBM20-mediated cardiomyopathy
Effects of the fatty acid synthase inhibitors triclosan and lapatinib on dengue virus and Zika virus infection
C-reactive protein to platelet ratio as an early biomarker in differentiating neonatal late-onset sepsis in neonates with pneumonia
Network analysis of peer attachment and internet addiction among chinese adolescents
Global, regional, and national epidemiology of rheumatoid arthritis among people aged 20–54 years from 1990 to 2021
Effects of storage time and temperature on coagulation factor and natural anticoagulant activities in healthy individuals
Abstract Coagulation test results are influenced by many pre-analytical variables, including clinical sample storage conditions. This study investigated the effects of storage time and temperature on coagulation factor (FII, FV, FVII, FX, FVIII, FIX, FXI, FXII, and FXIII) and natural anticoagulant (antithrombin, protein C, and free protein S) activities. Blood samples were collected from 78 healthy individuals, and 3 samples were used for each coagulation factor and natural anticoagulant. Plasma was tested after centrifugation and storage at room temperature (18 to 25 °C) or refrigerated (2 to 8 °C) for 2, 3, 4, and 5 h, or frozen (− 15 to − 25 °C) for 1, 2, 3, and 4 months. For all storage conditions, the mean percentage change from baseline in evaluated activities was < 15%, except for FV and FVIII. For FV activities after frozen storage at − 15 to − 25 °C and FVIII activities at all storage conditions, the mean percentage change was > 15%. For FV and FVIII activities, the mean percentage change was < 15% after frozen storage at − 75 to − 85 °C for 1, 2, 3, and 4 months. To ensure appropriate clinical testing results, especially for FV and FVIII activity, storage condition and time should be critically controlled.
Non-adherence and non-persistence of Direct Oral Anticoagulants among patients with non-valvular atrial fibrillation: a French retrospective cohort study
Colonial bacterial memetic algorithm and its application on a darts playing robot
Abstract In this paper, we present the Colonial Bacterial Memetic Algorithm (CBMA), an advanced evolutionary optimization approach for robotic applications. CBMA extends the Bacterial Memetic Algorithm by integrating Cultural Algorithms and co-evolutionary dynamics inspired by bacterial group behavior. This combination of natural and artificial evolutionary elements results in a robust algorithm capable of handling complex challenges in robotics, such as constraints, multiple objectives, large search spaces, and complex models, while delivering fast and accurate solutions. CBMA incorporates features like multi-level clustering, dynamic gene selection, hierarchical population clustering, and adaptive co-evolutionary mechanisms, enabling efficient management of task-specific parameters and optimizing solution quality while minimizing resource consumption. The algorithm’s effectiveness is demonstrated through a real-world robotic application, achieving a 100% success rate in a robot arm’s ball-throwing task usually with significantly fewer iterations and evaluations compared to other methods. CBMA was also evaluated using the CEC-2017 benchmark suite, where it consistently outperformed state-of-the-art optimization algorithms, achieving superior outcomes in 71% of high-dimensional cases and demonstrating up to an 80% reduction in required evaluations. These results highlight CBMA’s efficiency, adaptability, and suitability for specialized tasks. Overall, CBMA exhibits exceptional performance in both real-world and benchmark evaluations, effectively balancing exploration and exploitation, and representing a significant advancement in adaptive evolutionary optimization for robotics.