Preparation, Characterization and Spectroscopic Study of New Tridentate Schiff Base and its Cu(II), Ni(II) and Zn(II) Metal Complexes

A new tridentate ligand has been synthesized derived from phenyl(pyridin-3-yl)methanone. Three coordinated metal complexes were prepared by complexation of the new ligand with Cu(II), Ni(II) and Zn(II) metal salts. The new Schiff base “benzyl -2-[phenyl(pyridin-3-yl)methylidene]hydrazinecarbodithioate” and the new metal complexes were characterized using various physico-chemical and spectroscopic techniques. From the analysis results, the expected structure to the metal complexes are octahedral in geometry for Cu(II) complex, square planner for Ni(II) and tetrahedral for Zn(II) complex. The new compounds are expected to show strong bioactivity against bacteria and cancer cells

Synthesis and Characterization of Novel Methyl 2-(1,7,7-Tri methylbicyclo[2.2.1]hept-2-yieldene)hydrazinecarbodithioate Schiff Bases Derived From Methylhydrazine carbodithioate And Their Bi(III) And Ag(II) Complexes

Novel bidentate Schiff bases having nitrogen-sulphur donor sequence was synthesized from condensation of racemate camphor, (R)-camphor and (S)-camphor with Methyl hydrazinecarbodithioate (SMDTC). Its metal complexes were also prepared through the reaction of these ligands with silver and bismuth salts. All complexes were characterized by elemental analyses and various physico-chemical techniques. These Schiff bases behaved as uninegatively charged bidentate ligands and coordinated to the metal ions via ?-nitrogen and thiolate sulphur atoms. The NS Schiff bases formed complexes of general formula, [M(NS)2] or [M(NS)2.H2O] where M is BiIII or AgI, the expected geometry is octahedral for Bi(III) complexes while Ag(I) is expected to oxidized to Ag(II) forming square planner complexes

Effects Of Mind Maps Teaching Approaches And Gender On Jordanian 7Th Graders’ Rational Number Achievement And Creative Thinking

The purpose of this study was to determine the effect of mind maps and gender on rational number achievement and creative thinking among Jordanian seventh-grade students. The researcher used a quasi-factorial design (3x2) approach that was supported by qualitative data. To achieve the study’s objectives, four instruments were used, including the Rational Number Achievement Test (RNAT), the Torrance Test for Creative Thinking (TTCT), a questionnaire to assess students’ attitudes toward teaching methods, and an interview protocol for teachers. The researcher used the tools on a purposive sample of seventh-grade students in Irbid Governorate, which included (120) students divided into three groups: 60 female students and 60 male students. The control group is taught conventionally, while the first experimental group is taught with paper mind maps method and the second experimental group with digital mind maps methods. Two-way analysis of variance (ANOVA) and two-way analysis of covariance (ANCOVA) were used to analyze the data. The results of the two-way ANOVA analysis indicated that the teaching method (CM, PMM, or DMM) had a significant main effect on achievement in rational number among 7th-grade students. Students who were taught using the DMM improved more in Post Achievement in Rational Number than students who were taught using the PMM and CM

Prevalence and clinical characteristics of depression among elderly patients attending primary health care centers in Diyala Governorate

Background: In the elderly, depression is the most frequent mood condition. It has been linked to major consequences such as disability, functional decline, decreased quality of life, higher mortality, it is the most costly health problem among elderly, a little study is written about depression among elderly patients in Iraq. Objectives: To determine the prevalence of depression in elderly aged 60 years and more who visited primary health care centers in Diyala. Methodology: It is a descriptive, cross-sectional study that was conducted on 218 patients from PHCs of 2 sectors: Al-Kales and 1st Baquba, Diyala governorate-Iraq. A direct interview was conducted by the researcher. The survey was conducted over seven months from 1st of September 2020 till 1st of April 2021. The diagnosis of depression in geriatric measure by use short form of Geriatric Depression Scale (GDS) the Arabic version and the socio-demographical factors was also inquired in this study. Results: The prevalence of depression among the study participants was found to be 63.3% .There was a statistically significant association between depression and gender(in female more than male 69.2%), marital status(in widowed 84.8%), current residence(93.3% who residence alone), and source of monthly income(78.1% financial assistance), medical illnesses(70.2%), and previous depression(71.3%). Conclusions: Depressive symptoms are prevalent among elderly attending primary health centers in Diyala Governorate and primary care settings present opportunities for the detection and management of depression in the elderly patients

Serum Levels of Lactate Dehydrogenase and Alkaline Phosphatase Enzymes in Colorectal Cancer

Colorectal cancer (CRC) remains one of the main public health problems throughout the world. It has recently been observed that both of lactate dehydrogenase (LDH) and alkaline phosphatase (ALP) enzymes play critical role in cancer expansion. Current study was enrolled for investigating serum levels of LDH and ALP before and after surgery, as well as to assess if whether association of these enzymes with the histological grades of CRC. By using colorimetric method the activity LDH and ALP were determined in serum of 50 CRC patients before surgery, and in 30 patients after surgical compared with 30 healthy controls. The levels of LDH and ALP were increase in patients group before surgical treatment (p<0.001) than that in control group. Further, significant differences were found in the mean of serum enzymes after surgery in 30 patients, also mean serum levels of these enzymes increased in patients with advanced stages of tumor. These finding suggest that serum levels of LDH and ALP appears to be of some prognostic value in CRC

Awareness requirement and performance management for adaptive systems : a survey

Self-adaptive software can assess and modify its behavior when the assessment indicates that the program is not performing as intended or when improved functionality or performance is available. Since the mid-1960s, system adaptivity has been extensively researched, and during the last decade, many application areas and technologies involving self-adaptation have gained prominence. All of these efforts have in common the introduction of self-adaptability through software. Thus, it is essential to investigate systematic software engineering methods to create self-adaptive systems that may be used across different domains. The primary objective of this research is to summarize current advances in awareness requirements for adaptive strategies and their performance management based on an examination of state-of-the-art methods described in the literature. This paper reviews self-adaptive systems in the context of requirement awareness and summarizes the most common methodologies applied. At first glance, it examines the previous surveys and works about self-adaptive systems. Afterward, it classifies the current self-adaptive systems based on six criteria. Then, it presents performance management in the current adaptive systems and then evaluates the most common self-adaptive approaches. Lastly, the self-adaptive models are evaluated based on four concepts (requirements description, monitoring, relationship, dependency/impact, and tools)

Manipulation of Plant Growth Regulators on Phytochemical Constituents and DNA Protection Potential of the Medicinal Plant Arnebia benthamii

Arnebia benthamii of the family Boraginaceae is a critically endangered nonendemic plant of the Kashmir Himalayas and is used to treat a number of human diseases. The current study was based on developing an in vitro micropropagation protocol vis-à-vis induction of various secondary metabolites under in vitro conditions for the possible biological activity. A tissue culture protocol was developed for A. benthamii for the first time in the Himalayan region using varied combinations and proper media formulations, including various adjuvants: Murashige and Skoog (MS) media, growth hormones, sugars, agar, and so forth. The influence of different media combinations was estimated, and the MS + thidiazuron (TDZ) + indole 3-acetic acid (IAA) combination favors a higher regeneration potential. The higher amounts of chemical constituents were also recorded on the same treatment. The in vitro plant samples also showed a noteworthy effect of scavenging of hydroxyl radicals vis-à-vis protection from oxidative DNA damage. The in vitro raised plants are good candidates for the development of antioxidant molecules

Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction

Accurate and reliable prediction of Perfobond Rib Shear Strength Connector (PRSC) is considered as a major issue in the structural engineering sector. Besides, selecting the most significant variables that have a major influence on PRSC in every important step for attaining economic and more accurate predictive models, this study investigates the capacity of deep learning neural network (DLNN) for shear strength prediction of PRSC. The proposed DLNN model is validated against support vector regression (SVR), artificial neural network (ANN), and M5 tree model. In the second scenario, a comparable AI model hybridized with genetic algorithm (GA) as a robust bioinspired optimization approach for optimizing the related predictors for the PRSC is proposed. Hybridizing AI models with GA as a selector tool is an attempt to acquire the best accuracy of predictions with the fewest possible related parameters. In accordance with quantitative analysis, it can be observed that the GA-DLNN models required only 7 input parameters and yielded the best prediction accuracy with highest correlation coefficient (R = 0.96) and lowest value root mean square error (RMSE = 0.03936 KN). However, the other comparable models such as GA-M5Tree, GA-ANN, and GA-SVR required 10 input parameters to obtain a relatively acceptable level of accuracy. Employing GA as a feature parameter selection technique improves the precision of almost all hybrid models by optimally removing redundant variables which decrease the efficiency of the model