Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus. The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patients into two groups(severe cases and non-severe cases groups). Ferritin, lactate dehydrogenase LDH, D-dimer and CRP were markedly increased in COVID-19 patients in the first group (severe cases). Our findings imply that early measured levels of (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) are linked to a decreased probability of COVID-19 severity. Elevated levels of this biomarker may predict COVID severity development.
This study expands the state of the art in studies that assess torsional retrofit of reinforced concrete (RC) multi-cell box girders with carbon fiber reinforced polymer (CFRP) strips. The torsional behavior of non-damaged and pre-damaged RC multi-cell box girder specimens externally retrofitted by CFRP strips was investigated through a series of laboratory experiments. It was found that retrofitting the pre-damaged specimens with CFRP strips increased the ultimate torsional capacity by more than 50% as compared to the un-damaged specimens subjected to equivalent retrofitting. This indicated that the retrofit has been less effective for the girder specimen that did not develop distortion beforehand as a result of pre-loading. From
... Show MoreAbstract:
Saudi Arabia and United States long relation could present an important
subject to understand alliance kind in international relations types. We trying
in this study to diagnose and analyze the Saudi Arabia and United States
model to find balance and unbalance statues and its influence on the
directions of Saudi Arabia foreign policy positions.
We divided the study in two parts, each part have many sections. The
first part deal with the historian emergence of Saudi Arabia state and its
development in three stages including its foreign relations with regions and
international powers. While the second part was dedicated in analyzing and
understanding the mechanism and active facts that drawing the Sa
Nowadays, internet security is a critical concern; the One of the most difficult study issues in network security is "intrusion detection". Fight against external threats. Intrusion detection is a novel method of securing computers and data networks that are already in use. To boost the efficacy of intrusion detection systems, machine learning and deep learning are widely deployed. While work on intrusion detection systems is already underway, based on data mining and machine learning is effective, it requires to detect intrusions by training static batch classifiers regardless considering the time-varying features of a regular data stream. Real-world problems, on the other hand, rarely fit into models that have such constraints. Furthermor
... Show MoreBackground: It has been well known that the success of mandibular implant- retained overdenture heavily depends on initial stability, retention and long term osseointegration this is might be due to optimal stresses distribution in surrounding bones. Types of mandibular implant- retained overdenture anchorage system and number of dental implants play an important role in stresses distribution at the implant-bone interface. It is necessary to keep the stresses below the physiologic tolerance level of the bone .since. And it is difficult to measure these stresses around bone in vivo. In the present study, finite element analysis used to study the stresses distribution around dental implant supporting Mandible implant retained overdenture Mate
... Show MoreThis study explores the barriers to adopting green environmental criteria in Supplier Selection (SS) within the Iraqi food industry. It aims to enhance the understanding of sustainable supply chain management in developing nations, with a particular focus on the Iraqi context. A case study approach was utilized to identify eleven key green environmental criteria and 54 sub-criteria, alongside seven major barriers to their adoption. The Best–Worst Method (BWM) was employed to rank the criteria, and Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA) was used to prioritize the barriers. The analysis revealed that Environmental Management Systems are the most critical criterion for SS. On the other hand, legislation and policies emerged
... Show MoreNew series of metal ions complexes have been prepared from the new ligand 1,5- Dimethyl-4- (5-oxohexan-2- ylideneamino) -2-phenyl- 1H-pyrazol-3 (2H)-one derived from 2,5-hexandione and 4-aminophenazone. Then, its V(IV), Ni(II), Cu(II), Pd(II), Re(V) and Pt(IV) complexes prepared. The compounds have been characterized by FT-IR, UV-Vis, mass and 1H and 13C-NMR spectra, TGA curve, magnetic moment, elemental microanalyses (C.H.N.O.), chloride containing, Atomic absorption and molar conductance. Hyper Chem-8 program has been used to predict structural geometries of compounds in gas phase, the heat of formation, (binding, total and electronic energy) and dipole moment at 298 K.
Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d