Cloth simulation and animation has been the topic of research since the mid-80's in the field of computer graphics. Enforcing incompressible is very important in real time simulation. Although, there are great achievements in this regard, it still suffers from unnecessary time consumption in certain steps that is common in real time applications.   This research develops a real-time cloth simulator for a virtual human character (VHC) with wearable clothing. This research achieves success in cloth simulation on the VHC through enhancing the position-based dynamics (PBD) framework by computing a series of positional constraints which implement constant densities. Also, the self-collision and collision wit

In the last decades, using mineral admixture in concrete became very necessary to improve concrete properties and reduce CO₂ emissions associated with the cement production process. Subsequently, more sustainable concrete can be obtained.  Ternary blended cement containing two different types of mineral admixture can achieve ambitious steps in this trend. In this research, the synergic effects of mineral admixtures in ternary blended cement and its effects on concrete fresh properties, strength, durability, and efficiency factors of mineral admixture in ternary blended cement, were reviewed. The main conclusion reached after reviewing many literature pieces is that the concrete with ternary blended cement

Fifty-four Sprague-Dawley albino adult male rats were classified into three main groups each of 18 rats treated for a particular duration (1,2, and 4) weeks respectively. Each group was subdivided into three subgroups each of six rats treated as follows; group (1) serve as normal control, group (2, and 3) intra-peritoneal treated with TiO₂NPs (50,200) mg/kg respectively, body *weight of all rats was measured before and after the experiment, then rats were dissected at the end of each experiment and the weights of the thyroid was measured. The result showed a highly significant decrease (p<0.01) in thyroid gland weight, a highly significant increase (p<0.01) in body weights and TSH, while a highly significant decrease (p&

Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences. 

Numerous trace elements, notably metals, are essential for the normal functioning of several biological reactions, especially as enzyme cofactors. Several Trace elements refer to essential micronutrients required in minimal quantities for certain biological functions pertaining to human metabolism, albeit their minimal concentrations in the organism. Nonetheless, our understanding of this topic is considerably restricted, and emerging insights into their metabolic functions necessitate contributions and have implications across various domains, encompassing nutritional chemistry, with a focus on analytical chemistry, biological sciences, medicine, pharmacology, and agricultural sciences. 

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri