A new macrocyclic multidentate Schiff-base ligand Na4L consisting of two submacrocyclic units (10,21-bis-iminomethyl-3,6,14,17- tricyclo[17.3.1.18,12]tetracosa-1(23),2,6,8,10,12(24),13,17,19,21,-decaene-23,24-disodium) and its tetranuclear metal complexes with Mn(II), Co(II), Ni(II), Cu(II), and Zn(II) are reported. Na4L was prepared via a template approach, which is based on the condensation reaction of sodium 2,4,6-triformyl phenolate with ethylenediamine in mole ratios of 2 : 3. The tetranuclear macrocyclic-based complexes were prepared from the reaction of the corresponding metal chloride with the ligand. The mode of bonding and overall geometry of the compounds were determined through physicochemical and spectroscopic methods. These studies revealed tetrahedral geometries about Mn, Co, and Zn atoms. However, square planar geometries have been suggested for NiII and CuII complexes. Biological activity of the ligand and its metal complexes against Gram positive bacterial strain Staphylococcus aureus and Gram negative bacteria Escherichia coli revealed that the metal complexes become more potentially resistive to the microbial activities as compared to the free ligand. However, these metal complexes do not exhibit any effects on the activity of Pseudomonas aeruginosa bacteria. There is therefore no inhibition zone.
Voice Activity Detection (VAD) is considered as an important pre-processing step in speech processing systems such as speech enhancement, speech recognition, gender and age identification. VAD helps in reducing the time required to process speech data and to improve final system accuracy by focusing the work on the voiced part of the speech. An automatic technique for VAD using Fuzzy-Neuro technique (FN-AVAD) is presented in this paper. The aim of this work is to alleviate the problem of choosing the best threshold value in traditional VAD methods and achieves automaticity by combining fuzzy clustering and machine learning techniques. Four features are extracted from each speech segment, which are short term energy, zero-crossing rate, auto
... Show MoreActivity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif
... Show MoreThe determination of captopril (CAP) using a new continuous flow injection analysis (CFIA) method was given in this work CAP in its pure state and some of its pharmaceutical preparations. The technique can be described as simple, fast, sensitive, easy to operate, and low-cost. The CAP reacted with ammonium ceric(IV) sulfate (ACS)2(NH4 )2SO4Ce(SO4)2. 3 H2O in an acidic medium and the reaction led to the formation of a white, slightly yellowish precipitate. The formed precipitate was studied using Ayah 6S×1-ST-2D Solar cell-CFI Analyzer, a through the reflection of accident light on the surfaces of the precipitate particles at (0-1800), expressed as the response
... Show MoreTwelve N-(6-sustirured benzothanol-2-y1) succinamic acids and 3-(6-substitted benzonathol-2-y1)-carbamoyl propionyl chloride were synthesized in good yields from reaction of benzonathol2-yl)
The current study was designed to remove Lead, Copper and Zinc from industrial wastewater using Lettuce leaves (Lactuca sativa) within three forms (fresh, dried and powdered) under some environmental factors such as pH, temperature and contact time. Current data show that Lettuce leaves are capable of removing Lead, Copper and Zinc ions at significant capacity. Furthermore, the powder of Lettuce leaves had highest capability in removing all metal ions. The highest capacity was for Lead then Copper and finally Zinc. However, some examined factors were found to have significant impacts upon bioremoval capacity of studied ions, where best biosorption capacity was found at pH 4, at temperature 50º C and contact time of 1 hour.
Our research aimed to find a new material that can be an efficient heavy metal free flame retardant for plasticized poly(vinyl chloride) comparable to the conventional flame retardants. One of these extraordinary materials is Oxydtron using as an admixture for concrete. Oxydtron showed unexpected efficiency as a flame retardant agent and an excellent heat stabilizer as well. Limiting oxygen index (LOI), static heat stability, Congo-red, and differential scanning calorimetry (DSC) were carried out. The thermal tests proved that Oxydtron is suitable to improve plasticized poly(vinyl chloride) performance at high temperatures applications in terms of flame retarding and thermal stability
Pomegranate peels were used to remove zinc, chromium and nickel from industrial wastewater. Three forms of these peels (fresh, dried small pieces and powder) were tested under some environmental factors such as pH, temperature and contact time.
The obtained results showed that these peels are capable of removing zinc, chromium and nickel ions at significant capacities. The powder of the peels had the highest capability in bioremoving all zinc, chromium and nickel ions while dried peels had the lowest capacity again for all metals under test. However, the highest capacities were found in a sequence of chromium, nickel and zinc. Furthermore, all these data were significantly (LSD peel forms = 2.761 mg/l, LSD metal ions = 1.756 mg/l) var