Cancer remains a leading cause of mortality and morbidity worldwide. Advances in cancer therapies—including immunotherapies (e.g., checkpoint inhibitors, gene-targeted therapies), antibody-based cancer toxins, chemotherapy, radiotherapy, and surgery—have significantly improved survival rates 1,2. However, this progress has led to a surge in the prevalence of cardiovascular disease (CVD) among cancer survivors, now recognised as a leading cause of mortality in this population 3,4. These intersecting burdens highlight the growing need to prevent, detect, and manage cardiovascular complications in cancer care pathways and call for important initiatives in establishing cardio-oncology services globally.

Translation is a vital process that needs much more understanding and mutual background knowledge on the part of ESL or EFL learners in terms of grammar , meaning and context of both the SL and TL . Thus , the main aim of the current research paper is to identify and figure out the techniques used by ESL or EFL learners when translating English barnyard verbs into Arabic . The main problem of this study is attributed to the fact that ESL or EFL learners may not be able to identify and understand the connotative meaning of barnyard verbs since these verbs are onomatopoeic (i.e,) a word that phonetically imitates, or suggests the source of sound that it describes. Therefore they may be unable to translate these verbs appropriately and accura

Background: Joint hypermobility  was first mentioned by Hippocrates as an isolated feature, when he described the Celts' Incapacity to Pull a Bowstring or Throw a Dart, Due to The Slackness of Their Limbs

Objective: to determine the prevalence of mitral valve prolapse(MVP)in patients with benign hypermobility syndrome (BJHS).

Type of the study: Cross –sectional study.

Methods: Ninety patients with BJHS were included in this study. Full cardiological assessment was done for all of them,  which  include clinical examination, electrocardiography and echocardiography. Cardiac assessment was done for another sixty age and sex matched (

The nature of the dark sector of the Universe remains one of the outstanding problems in modern cosmology, with the search for new observational probes guiding the development of the next generation of observational facilities. Clues come from tension between the predictions from Λ cold dark matter (ΛCDM) and observations of gravitationally lensed galaxies. Previous studies showed that galaxy clusters in the ΛCDM are not strong enough to reproduce the observed number of lensed arcs. This work aims to constrain the warm dark matter (WDM) cosmologies by means of the lensing efficiency of galaxy clusters drawn from these alternative models. The lensing characteristics of two samples of simulated clusters in the Λ warm dark matter and ΛCDM

Despite recent attempts to improve safety in the construction sector, this sector is considered dangerous and unsafe. Iraq is one of the emerging nations that suffers from a lack of construction safety management. In 2018, the construction sector in Iraq was responsible for 38% of all industrial accidents. Creating a safety program minimizes this problem by making safety an intrinsic part of construction projects. As a result, this article aims to identify the crucial safety factors that affect the safety performance in Iraqi construction projects. After conducting a critical literature review of the related literature, a list of 35 sub-factors classified into nine categories of main factors was chosen to rank each facto

Cardiovascular disease (CVD) remains the leading cause of mortality in women. Estimating cardiovascular risk using prediction models is essential for guiding preventive strategies. Despite progress, conventional risk models still omit critical women-specific factors, limiting their accuracy. Precision medicine, supported by artificial intelligence, provides a framework to integrate these overlooked determinants. This approach may help close existing gaps in cardiovascular risk prediction. Sex-specific biomarkers that contribute to overall cardiovascular risk can be incorporated into risk assessment tools to improve prevention strategies, early detection, and personalized intervention. The integration of imaging-derived variables enh

This study proposes a new version of the Autoregressive Integrated Moving Average (ARIMA) model using Artificial Neural Networks (ANNs) denoted by ARIMA-NN. The new model incorporates a multi-layer perceptron with matrix multiplication within a feed-forward network. The logistic, hyperbolic tangent (tanh), and sigmoid activation functions are used for weight updates in ARIMA-NN. A new forecasting algorithm is proposed, and one-step and multiple-steps forecasting procedures are rigorously analyzed. The proposed model was evaluated against existing forecasting model using performance metrics such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (