Background: Infection with sexually
transmitted diseases is broad and includes
bacterial, viral and protozoa infection.
Large number of infected people goes
untreated because of symptomatic or
unrecognized infections.
Patients and methods: Forty five
patients was complaining from infertility
(primary or secondary), consulting
Kammal El-Sammari Hospital for
infertility from May - 2008 to February -
2009. Control group consisted of twenty
fertile women that consulting private clinic
for checking. Four swabs were taken from
each woman in two groups. Two swabs
were taken from posterior fornix of the
vagina (High vaginal swab) and the last
two were taken from endocervical canal.
First swab (vagina and cervix) was
examined directly under light microscope
(wet mount) and stained by Gram stain.
The other swab was cultured on Blood and
Chocolate agar.
Results: The patients group consisted
from forty-five female patients, their aged
ranged from (22-45 years), (X= 32.9).
Direct examination (wet mount) and Gram
staining of high vaginal swab showed
significant increased in leukocyte (pus
cells) and epithelial cells in infertile group
than normal one. The isolated bacteria
from culture of high vaginal swab were
Streptococcus agalactiae (group B
streptococci) which was significantly
increased than fertile group. This bacteria
was sensitive to Cephaloxtin and
Cephotaxime and resistant to Penicillin
Conclusions: The isolated bacteria from
culture of high vaginal swab were
Streptococcus agalactiae (group B
streptococci). This bacteria was sensitive
to Cephaloxtin and Cephotaxime and
resistant to Penicillin .
Face Recognition Systems (FRS) are increasingly targeted by morphing attacks, where facial features of multiple individuals are blended into a synthetic image to deceive biometric verification. This paper proposes an enhanced Siamese Neural Network (SNN)-based system for robust morph detection. The methodology involves four stages. First, a dataset of real and morphed images is generated using StyleGAN, producing high-quality facial images. Second, facial regions are extracted using Faster Region-based Convolutional Neural Networks (R-CNN) to isolate relevant features and eliminate background noise. Third, a Local Binary Pattern-Convolutional Neural Network (LBP-CNN) is used to build a baseline FRS and assess its susceptibility to d
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Diagnostic characters, a redescription of some of the morphological features, photographs and illustrations are provided for the new record species in this investigation.
Аннотация
в статье рассматриваются проблемы преподавания русской литературы в иракской аудитории.. Использование литературы в преподавании иностранного языка, как правило, имеет две цели. Первая-чисто лингвистическая .. Вторая цель, однако, ассоциируется больше с экстралингвистикой и представляет собой ознакомление студентов с различными аспектами русской жизни, культуры,
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