This study describes the preparation of new series of tetra-dentate N₂O₂ dinuclear complexes (Cr³⁺, Co²⁺, Cu²⁺) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and ¹H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all

This study describes the preparation of new series of tetra-dentate N2O2 dinuclear complexes (Cr3+, Co2+, Cu2+) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and 1H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all complexes of the (Cr3+, Co2+, Cu2+). conductivity measurement shows t

This study aims at recognizing Pesticides and how the process of pesticides biodegradation by microbiology took place, and the effect of environmental condition on this process. And how the research uncovered the efficiency of microbiology in the biodegradation process of pesticides, as the perfect temperature for the biodegradation process is 40 °C and humidity effect on pesticides efficiency, when high humidity reduces pesticide efficiency and the perfect acidity to increase bacteria efficiency is 7, for the incubation period, it was found during the previous studies that the best incubation period is 5-7 days, in this period the bacteria imprint on pesticides and increase biodegradation of it.

ABSTRACT : This research involves the synthesis of five to seven heterocyclic compounds starting with Schiff’s bases which derived from oxime as a starting material. 1.3-oxazepine derivatives were prepared from adding different anhydrides to the Schiff bases, tetrazole and thiazolidinone derivatives synthesized from add sodium azide and thioglycolic acid to the same Schiff’s bases as a five members ring. Pyrimidine derivatives were prepared after the reaction of the azomethine group with acetyl chloride and then urea and thiourea to synthesis on derivatives contain the six members ring. Another step included identified and confirmed these compounds by FT- IR, 1HNMR, TLC and 13CNMR finally, step included the assay of biological activity

The ligand 4-(2-aminmo-5-nitro-phenylazo)-1,5-dimethyl-2-phenyl-1,2-dihydro-pyrazol-3-one derived from 4-aminoantipyrine and 4-nitroaniline was synthesized. The synthesized ligand was characterized by 1HNMR, FT-IR, UV-Vis spectra and (C.H.N) analysis. Complexes of (YIII and LaIII ) with the ligand were prepared in aqueous ethanol with a 1:2 M:L ratio and at optimum pH. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis spectra,(C.H.N) analysis and conductivity measurement. The stoichiometry of complexes was studied by the mole ratio and job methods. A concentration range (1×10-4 - 3×10-4 M) obeyed Beer's law, the complex solutions show high values of molar absorption. On the basis of physicochemical

The ligand 4-(2-aminmo-5-nitro-phenylazo)-1,5-dimethyl-2-phenyl-1,2-dihydro-pyrazol-3-one derived from 4-aminoantipyrine and 4-nitroaniline was synthesized. The synthesized ligand was characterized by 1HNMR, FT-IR, UV-Vis spectra and (C.H.N) analysis. Complexes of (YIII and LaIII ) with the ligand were prepared in aqueous ethanol with a 1:2 M:L ratio and at optimum pH. The prepared complexes were characterized by using flame atomic absorption, FT-IR, UV-Vis spectra,(C.H.N) analysis and conductivity measurement. The stoichiometry of complexes was studied by the mole ratio and job methods. A concentration range (1×10-4 - 3×10-4 M) obeyed Beer's law, the complex solutions show high values of molar absorption. On the basis of physicochemical

The study aimed to increase the biological value of white bean. The effect of different concentrations 0.01 ,0.02,0.03,and 0.04 M of sodium sulfite solutions for 1hr at 70 ºC on the trypsin inhibitors activity, protein isolate and protein solubility of complete and dehulling white bean flour were studied.Trypsin inhibitors activity were reduced by 42.97, 58.69, 68.59 and 69.58% in complete white bean flour at 0.01 ,0.02, 0.03, 0.04 M respectively, while the corresponding values were 50.43, 61.00, 75.61 and 85.66% respectively in dehulling white bean flour .Protein isolate value was 13.41% and protein solubility was 2.2% in control sample, Furthermore, the using of chemical treatment showed that protein isolate was reduced gradually and

In Indonesia, cattle feces (CF) and water hyacinth (WH) plants are abundant but have not been widely revealed. The use of microorganisms as decomposers in the fermentation process has not been widely applied, so researchers are interested in studying further. This study was to evaluate the effect of the combination of CF with WH on composting by applying white-rot fungal (WRF) (Ganoderma sp) microorganism as a decomposer. A number of six types of treatment compared to R₁(ratio of CF:WH)(25%:75%)+WRF; R₂(ratio of CF:WH)(50%:50%)+WRF; R₃(ratio of CF:WH)(75%:25%)+WRF; R₄(ratio of CF:WH)(25%:75%) without WRF; R₅(ratio of CF:WH)(50%:50%) without WRF; R₆(ratio of CF:WH)

Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca