This study employs evolutionary optimization and Artificial Intelligence algorithms to determine an individual’s age using a single-faced image as the basis for the identification process. Additionally, we used the WIKI dataset, widely considered the most comprehensive collection of facial images to date, including descriptions of age and gender attributes. However, estimating age from facial images is a recent topic of study, even though much research has been undertaken on establishing chronological age from facial photographs. Retrained artificial neural networks are used for classification after applying reprocessing and optimization techniques to achieve this goal. It is possible that the difficulty of determining age could be reduced by using an algorithm that calculates the predicted value. The utilization of machine learning models that have been trained on massive datasets, the implementation of strategies for correct face alignment, and the utilization of expected value regression formulations have all been significantly incorporated into the suggested approach. The model’s performance is optimized and improved in this study by utilizing several distinct classifiers, increasing the effectiveness of explicit expectations. We aimed to optimize the selection of classifiers to minimize energy consumption while achieving a mean absolute error of 2.08 (average) and a power usage of 2700 W.
Utilizing Energy-Efficient Deep Learning Technique for Age Estimation Through a Hybrid Methodology
Evolutionary optimization
Artificial Intelligence
Feature selection
Age es-timation
Deep Learning
Efficient energy
Publication Date
Tue Mar 01 2022
Journal Name
Iraqi Journal Of Agricultural Sciences
CORRELATION OF TMPRSS2-ERG GENE FUSION STATUS WITH CLINICOPATHOLOGICAL CHARACTERISTICS IN PROSTATE CANCER OF IRAQI PATIENTS
The aim of this study was to establish the existence and interaction of TMPRSS2 – ERG gene fusion status with clinicopathological features of prostate cancer patients. This research consisted of 123 embedded formalin-fixed tissues obtained from the prostate tumor patients. The above gene fusion is detected through the technique of fluorescent in situ hybridization (FISH) by means of a triple color probe. Seven samples have not been scored due to technical difficulties and 46 patients have fusion (39.6%)
while the remaining (70) have not been seen with fusion. Of the 46 fusion-positive
17 (36%) were caused by ERG-translocation
of the other 29 (63%) were caused by the interstitial segment deletion between the two genes due to their sequential position. In order to find a substantial correlation between 116 patients (fusion took place in 46 and non-fusion in 70) with clinicopathological features
the following findings were calculated: Our findings recorded non-significant correlation at age
BMI and tumor size at which (P-value >0.05).While results showed significant association with: pathological T stage (P value = 0.011)
Gleason score (P value = 0.002)
perineural invasion (P value = 0.047) and PSA (P value = 0.033). The clinicopathological features which had a considerable correlation with fusion status are very important as they aid the doctors in prognosis and treatment of such tumor.
Publication Date
Sat Sep 01 2018
Journal Name
Polyhedron
Novel dichloro (bis {2-[1-(4-methylphenyl)-1H-1, 2, 3-triazol-4-yl-κN3] pyridine-κN}) metal (II) coordination compounds of seven transition metals (Mn, Fe, Co, Ni, Cu, Zn and Cd)
The 1
3-dipolar cycloaddition “click” reaction between an azide and an alkyne to give a 1
2
3-triazole was reported by Huisgen in 1961 [1]. In 2002 the Copper(I)-catalyzed Azide-Alkyne Cycloaddition (CuAAC) to prepare a 1
2
3-triazole was reported [2]
[3]. The existence of relatively basic nitrogen atoms in the 1
2
3-triazole rings
and the possibility of introducing additional donor groups in the substituents (Fig. 1)
made the CuAAC “click” reaction an attractive method to prepare differently substituted 1
2
3-triazoles. These compounds have been used as ligands to coordinate to various metal ions that display a range of applications such as in electrochemical and photochemical studies
in supramolecular chemistry
magnetism
metal-ion sensing and catalysis [4]. The reasons for the success of the “click” reaction
is that it is easy to carry out and is widely applicable. It is not affected by a variety of functional groups
and can be carried out with a variety of Cu(I) catalysts and solvents
including aqueous conditions. The Cu(I) catalysts overcome the high activation energy barrier of the non-catalyzed Huisgen reaction by changing the mechanism of the reaction. A large variety of copper catalysts can be used for the CuAAC reaction
on condition that the maximum concentration of Cu(I) species is generated during the reaction. The pre-catalyst can be a Cu(II) salt (usually CuSO4) together with a reducing agent (often sodium ascorbate) or a Cu(I) compound in the presence of a base or amine ligand and a reducing agent to prevent oxidation to Cu(II). Some strong oxidising cupric salts or complexes such as Cu(OAc)2 also work. The solvent is very flexible from organic to aqueous
with the most commonly used combination water + an alcohol (t-BuOH
MeOH or EtOH). The key role of the solvent or solvent mixture is to solubilize the substrates and Cu(I) catalyst in order to ensure rapid reactions. Such aqueous conditions are very useful for biochemical conjugations
as well as for organic syntheses.
We recently reported on the synthesis of a series of differently substituted 1
2
3-triazole chromophores
the substituted 2-(1-phenyl-1H-1
2
3-triazol-4-yl)pyridine ligands [5]
see Fig. 2 middle
with substituents R = H (L1)
CH3 (L2)
OCH3 (L3)
COOH
F
Cl
CN
CF3
O(CH2)3CH3 and N(CH3)2. These versatile ligands were found to coordinate to various first row transition metals
such as manganese
cobalt and nickel [6]. Here we extend the series to include more first row transition metal(II) coordination compounds
iron
copper and zinc
as well as a second row transition metal(II) coordination compound
cadmium
containing the 2-(1-(4-methyl-phenyl)-1H-1
2
3-triazol-1-yl)pyridine chromophore (Fig. 2 right with R = CH3). This series of seven novel coordination compounds is the first series of pyridyl-triazole based transition metal coordination compounds where seven different transition metals are coordinated to the same 1
2
3-triazole chromophore
namely 2-(1-(4-methyl-phenyl)-1H-1
2
3-triazol-1-yl)pyridine.