The research aims at identifying the level of family violence directed against the kindergarten child, as well as to identify the significance of the difference in family violence directed against the kindergarten child according to the gender variable

(male-female). It aims also to identify the significance of the difference in family violence directed against the kindergarten child according to the Stage variable (kindergarten-pre-primary). The researcher employed the descriptive correlative approach to conduct the study. The research sample was chosen in a simple random way, as the number of the participants was (130) boys and girls, with (70) males and (60) females, distributed according to the stage with (66) participants in

The Leishmania donovani parasite causes visceral leishmaniasis (VL), an acute and fatal form of leishmaniasis. Because traditional therapy alternatives, such as glucantime and other pentavalent medicines, are toxic and have side effects, new treatments with fewer negative effects are needed. Only a handful of drugs are clinically beneficial to treatments of the disease, but considerable limitations threaten their very usage. Novel, safe, and efficient drugs, including those against antimalaria and leishmaniasis co-infections, are so essential. Artemether (ATM) is an Artemisinin derivative that has been demonstrated to be useful in the treatment of malaria and, more recently, leishmaniasis. The current research was carried out to evaluate th

Visceral leishmaniosis is one of the most fatal old-world neglected disease with estimated 90 thousand worldwide cases emerge each year. In Iraq, the cutaneous and visceral form are endemic but available chemotherapies are either toxic with diverse side effects, expensive available drugs or parasite …

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

Fluorescence excitation by Nd:YAG pumped dye laser and single vibrational level fluorescence
spectra of 1,3 benzodioxole in a supersonic jet have been obtained and interpreted. The previous assignment of
the 0 0
0 band was incorrect. In addition, many other bands involving n20 and n19 vibrations of a2 symmetry were
confirmed. As far as a1 totally symmetric vibration is concerned. The n14 was assigned to be located in the fivemembered
ring whereas n13 seem to be located in the benzene ring as a result of the electronic transition in the
benzene ring which affects n13 and not n14 wavenumber.

The state and partial level densities were calculated using the corresponding formulas that are obtained in the frame work of the exciton model with equidistant spacing model (ESM) and non-ESM (NESM). Different corrections have been considered, which are obtained from other nuclear principles or models. These corrections are Pauli Exclusion Principle, surface effect, pairing effect, back shift due to shell effect and bound state effect . They are combined together in a composite formula with the intention to reach the final formula. One-component system at energies less than 100 MeV and mass number range (50-200) is assumed in the present work. It was found that Williams, plus spin formula is the most effective approach to the composite