Optimizing diesel engine performance and emissions with mahua biodiesel blends using taguchi methodology.

This study investigates how adjusting operational parameters influences the performance and emission characteristics of a diesel engine operating on a blend of traditional diesel fuel and mahua biodiesel. The biodiesel was obtained using the transesterification method, and fuel blends were formulated with diesel proportions ranging from 80% to 100% and biodiesel content from 0% to 20%. Key engine parameters such as engine load (20 -100%), mahua biodiesel blend (0 -20%), and engine speed (1300 -1450 rpm) were varied systematically during the experiments, while the compression ratio was held constant at 18:1.

Genetically determined body mass index is associated with diffuse large B-cell lymphoma in polygenic and Mendelian randomization analyses.

Obesity has been associated with non-Hodgkin lymphoma (NHL), but the evidence is inconclusive. We examined the association between genetically determined adiposity and four common NHL subtypes: diffuse large B-cell lymphoma (DLBCL), follicular lymphoma, chronic lymphocytic leukemia, and marginal zone lymphoma, using eight genome-wide association studies of European ancestry (N = 10,629 cases, 9505 controls) and constructing polygenic scores for body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-hip ratio adjusted for BMI (WHRadjBMI). Higher genetically determined BMI was associated with an increased risk of DLBCL [odds ratio (OR) per standard deviation (SD) = 1.

Protocol for an umbrella review of the state-of-science on public and patient involvement in health and social care research with children, young people and families.

Background: Public and Patient Involvement (PPI) refers to the active collaboration of patients and the public in health and social care research decision-making, enhancing research success, cost-effectiveness, and impact. Children, young people, and their families bring unique lived experiences to PPI in research, relating to others with similar experiences, while factors like age, cognitive maturation, and developmental stage create differences between researchers and patients or the public. Collaboration with children, young people, and their families should be guided by specific project context and a strong evidence base.

Developing multimodal cervical cancer risk assessment and prediction model based on LMIC hospital patient card sheets and histopathological images.

Cervical cancer remains a significant global health burden, particularly in low- and middle-income countries (LMICs) where access to early diagnostic tools is limited. In Ethiopia, cervical cancer diagnosis often relies on manual interpretation of biopsies, which can be time-consuming and subjective. This study aims to develop a multimodal machine learning model that integrates histopathological images and associated patient clinical records to improve cervical cancer risk prediction and biopsy detection.

Age-related hearing loss and dementia risk across the lifespan: mechanisms, equity, and prevention.

Age-related hearing loss (ARHL) has emerged as a significant and potentially modifiable risk factor for neurodegenerative disorders, including Alzheimer's disease. A growing body of evidence links ARHL to structural and functional changes in the brain, with implications for cognitive decline and dementia onset. However, both ARHL and dementia are multifactorial conditions shaped not only by biological mechanisms but also by broader social determinants of health.

Mechanisms of Resistance to PARPi in Pancreatic Ductal Adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly fatal disease with limited treatment options. PARP inhibitors (PARPi) have shown promise in treating PDAC with homologous recombination deficiency (HRD), but rapid acquisition of resistance limits their efficacy. Our objective is to investigate mechanisms of resistance to PARPi in BRCA2-mutant PDAC cells and identify potential therapeutic targets to modulate this resistance.

AI-based research mentors: Plausible scenarios and ethical issues.

Guided by Brey's Anticipatory Technology Ethics, we examined AI-based research mentors (AIRMs) through technology foresight as well as identification and evaluation of ethical issues. Scenario planning was employed to inform foresight, yielding four plausible future scenarios: 1) AIRMs are used solely for guidance, 2) AIRMs are used for guidance and monitoring, 3) AIRMs are banned, and 4) AIRMs are used solely for monitoring. Resnik's twelve principles informed the identification of ethical issues within these scenarios.

Cyber-Creativity: A Decalogue of Research Challenges.

Creativity is the primary driver of our cultural evolution. The astonishing potential of artificial intelligence (AI) and its possible application in the creative process poses an urgent and dramatic challenge for humanity; how can we maximize the benefits of AI while minimizing the associated risks? In this article, we identify all forms of human-AI collaboration in this realm as cyber-creativity. We introduce the following two forward-looking scenarios: a utopian vision for cyber-creativity, in which AI serves to enhance and not replace human creativity, and a dystopian view associated with the pre-emption of all human creative agency caused by the rise of AI.

Health literacy research on the island of Ireland: a systematic review.

Consistently, low health literacy has been found to lead to poorer health outcomes, both internationally, and in Ireland. Given this knowledge, there is a need to understand key thematic trends, methodological approaches and evidence gaps in policy and practice. Seven electronic databases (Science Direct, MEDLINE, CINAHL Complete, Web of Science, Scopus, PsychoINFO, and SPORTDiscus) were searched between October and December 2023 focusing on studies published in English between 2013 and 2023.

Scalable Lignin Monomer Production Via Machine Learning-Guided Reductive Catalytic Fractionation of Lignocellulose.

Efficient valorization of lignocellulosic biomass into high-value lignin monomers is a cornerstone of sustainable biorefineries, yet the complexity of optimizing reductive catalytic fractionation limits industrial scalability. This study presents a machine learning (ML)-driven framework that harnesses 3,451 experimental data points from 54 peer-reviewed studies to model and optimize lignin monomer production. Among four advanced ML models developed, eXtreme Gradient Boosting Regression is found to achieve the highest predictive accuracy (R = 0.

Nature-based interventions: a systematic review of reviews.

Background: Nature-based interventions are emerging as an alternative to therapeutic approaches aimed to reduce and prevent mental and physical ailments. However, little is known of the types of interventions available to use by healthcare professionals. This systematic review of reviews aimed to classify and categorise different types of Nature-Based Interventions (NBIs) which currently exist under different names and approaches.

Five prerequisites to achieving excellence in supportive cancer care by 2030: oncology nursing in the driver's seat.

The Multinational Association for Supportive Care (MASCC) recently published its Supportive Care 2030 Movement with the aims of developing consensus about shared, equitable and translatable ambitions to drive excellence in and outline the desired state of supportive cancer care by 2030. In response to the publication of the ambition statements, the major oncology nursing organizations launched a collaboration in June 2024 with the aim of achieving global nursing excellence and leadership within the wider interdisciplinary model of supportive cancer care. This editorial presents our collective response to the ambitions set by the Supportive Care 2030 Movement.

Sequence-Dependent Shape and Stiffness of DNA and RNA Double Helices: Hexanucleotide Scale and Beyond.

The structure and deformability of double-stranded DNA and RNA depend on the sequence of bases, affecting biological processes and nanostructure design, but this dependence is incompletely understood. Here we present mechanical properties of DNA and RNA duplexes inferred from atomic-resolution, explicit-solvent molecular dynamics (MD) simulations of 107 DNA and 107 RNA oligomers containing all hexanucleotide sequences. In addition to the level of rigid bases, minor and major grooves, we probe the length and sequence dependence of global material constants such as persistence lengths, stretching and twisting rigidities.

Label Accuracy in Electronic Health Records and Its Impact on Machine Learning Models for Early Prediction of Gestational Diabetes: 3-Step Retrospective Validation Study.

Background: Several studies have used electronic health records (EHRs) to build machine learning models predicting the likelihood of developing gestational diabetes mellitus (GDM) later in pregnancy, but none have described validation of the GDM "label" within the EHRs.

Objective: This study examines the accuracy of GDM diagnoses in EHRs compared with a clinical team database (CTD) and their impact on machine learning models.

Methods: EHRs from 2018 to 2022 were validated against CTD data to identify true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN).

From student to nurse: exploring transition shock through stress, locus of control, and coping strategies in newly graduated nurses.

Background: Newly graduated nurses often face a difficult transition from academic training to clinical practice, commonly experiencing "transition shock." This period is characterized by heightened occupational stress, reduced coping capacity, and uncertainty about role identity.

Aim: This study aimed to investigate the effects of occupational stress, coping strategies, and work locus of control on transition shock among newly graduated nurses.

Dual-stream hybrid architecture with adaptive multi-scale boundary-aware mechanisms for robust urban change detection in smart cities.

Urban environments undergo continuous changes due to natural processes and human activities, which necessitates robust methods for monitoring changes in land cover and infrastructure for sustainable developments. Change detection in remote sensing plays a pivotal role in analyzing these temporal variations and supports various applications, including environmental monitoring. Many deep learning-based methods have been widely investigated for change detection in the literature.

Validating adverse events in administrative healthcare data in ireland: a retrospective chart review study.

Background: Pneumonia, urinary tract infections, pressure ulcers and delirium are adverse events that affect older inpatients. Accurate administrative data are key to improving patient safety and healthcare quality. The aim of the study was to validate Hospital In-Patient Enquiry (HIPE) data on the occurrence of pneumonia, urinary tract infections, pressure ulcers and delirium in older patients discharged from an acute hospital in Ireland through retrospective chart review.

Evaluation of the Agreement Between Research-Grade Actigraphy Sleep, Consumer-Grade Smartwatches and Self-Reported Sleep Diaries in Masters Endurance Athletes.

Sleep monitoring is a tool widely used to support recovery and performance in endurance athletes. This study aimed to assess agreement between research-grade actigraphy (ActiGraph GT9X), consumer-grade smartwatches (Garmin), and self-reported sleep diaries in masters endurance athletes. Seventy athletes (43 males, 46.

Unheard voices: The critical role of nurses and midwives in climate resilience and disaster preparedness in Small Island Developing States.

Island nations such as Barbados, Jamaica, and Tonga face rising threats from climate change, including hurricanes, flooding, and sea-level rise. Nurses and midwives are crucial frontline responders, leading disaster preparedness, emergency care, and community recovery. This paper highlights their leadership, resilience, and innovation in addressing the health impacts of climate-related disasters.

Ionic photofragmentation cross sections of the HS, HS and HCl molecular ions near the 2p threshold.

The absolute cross sections for the production of X and X ions following absorption of monochromatised SOLEIL synchrotron radiation by the HX hydride molecular ions (X = S, Cl) are presented as a function of photon energy in the region of the X ionisation thresholds (∼180 eV and ∼220 eV for sulphur and chlorine, respectively). The experimental results are interpreted with the help of extensive density functional theory (DFT) and post-Hartree-Fock configuration interaction calculations including spin-orbit coupling to compute the absorption oscillator strengths of the X 2p core excitations to valence and Rydberg states. In order to account for all the experimental features, the calculations must include vibrational dynamics and spin-orbit coupling.

Burst agitation rate promotes sustained semicontinuous cultivation of filamentous fungi in stirred tank reactors.

Edible filamentous fungi L. edodes (shiitake mushrooms) were cultivated in submerged fermentation in stirred tank bioreactors (STR) both in batch and semicontinuous cultivation in a corn steep liquor (CSL) medium. The adjustment of a combination of constant impeller agitation speed, a short duration of a high-speed agitation (burst), and the frequency of bursts improved biomass (cell dry weight (CDW) titre from 1.

Assessing the reliability of an online measure of the temporal binding window of audiovisual integration.

A growing body of evidence suggests that imprecise multisensory temporal processing is associated with a range of adverse clinical outcomes. Specifically, this research has shown that the temporal binding window of audiovisual integration widens with advancing age, whereas individuals with various neurodevelopmental disorders exhibit distinctive profiles of multisensory processing when compared to their neurotypical counterparts. While this line of research has made significant inroads in emphasising the importance of multisensory processing in both typical and atypical cognition, the field would greatly benefit from the validation of web-based tools for assessing multisensory temporal processing, enabling larger sample sizes and the recruitment of typically hard-to-reach populations.

Diagnostic test accuracy of screening tools for the detection of neurocognitive disorders in older adults post-trauma in acute care settings: a systematic review.

Purpose: Neurocognitive disorders (NCDs), including delirium, cognitive impairment, or dementia, are prevalent in older patients with physical trauma in acute care settings. Identifying NCDs in these patients can enhance care decisions to improve outcomes. This study aimed to identify the diagnostic accuracy of screening tools for NCDs in older patients with trauma in acute care settings.

Barriers and Facilitators of Help-Seeking for LGBTQ+ Survivors of Sexual Violence: A Systematic Review.

People who identify as LGBTQ+ (Lesbian, Gay, Bisexual, Transgender, Queer, plus) are known to experience similar or higher levels of sexual violence compared to their heterosexual cisgender counterparts. However, sexual violence research has largely focused on heterosexual female survivors of male perpetrated crime. Thus, the unique support needs and help-seeking patterns of LGBTQ+ survivors are poorly understood.

New Imaging Method of Mobile Phone-Based Colorimetric Sensor for Iron Quantification.

Blood iron levels are related to many health conditions, affecting hundreds of millions of individuals worldwide. To aid in the prevention and treatment of iron-related disorders, previous research has developed a low-cost, accurate, point-of-care method for measuring iron from a single finger-prick blood sample. This study builds upon that work by introducing an improved imaging method that accurately reads sensor images irrespective of variations in environmental illumination and camera quality.