Back ground: The innervations of the pineal
gland from the superior cervical ganglion have
shown some form of a chromatolysis reaction.
Objective:
1-Tracing the innervations of the pineal gland by
removing the target tissue (the pineal gland in
this study) i.e. (pinealoctomy) and removal of the
superior cervical ganglion i.e. (ganglionectomy).
2- The localization and total number of the
neurons which project into the rat pineal gland
3-The effect of pinealoctomy on the SCG after a
different time interval.
Methods: Twenty five albino rats were used in
this study, Pinealoctomy was done, then after a
different time interval ganglionectomy was done,
in order to study the Chromatolysis in their cell
body.
Result: The present study has demonstrated
that the chromatolysis reaction in the neurons
following Pinealoctomy confirms the
innervations of the pineal gland from the SCG.
The present study has demonstrated that the most
obvious the Chromatolysis reaction occurred one
day after pinealoctomy.
Conclusion: This study confirms the
innervations of the pineal gland from the SCG,
the study shows that the distribution of the
Chromatolysis neurons; of all age group occurred
in all parts of the ganglion; although it was more
abundant in the rostal 2/3.
طريقة سهلة وبسيطة ودقيقة لتقدير السبروفلوكساسين في وجود السيفاليكسين او العكس بالعكس في خليط منهما. طبقت الطريقة المقترحة بطريقة الاضافة القياسية لنقطة بنجاح في تقدير السبروفلوكساسين بوجود السيفاليكسين كمتداخل عند الاطوال الموجية 240-272.3 نانوميتر وبتراكيز مختلفة من السبروفلوكساسين 4-18 مايكروغرام . مل-1 وكذلك تقدير السيفاليكسين بوجود السبروفلوكساسين الذي يتداخل باطوال موجية 262-285.7 نانوميتر وبتراكيز مخ
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s
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