Abstract:

Germplasm (Oocyte and embryo) and ovarian tissue cryopreservation have become routine procedure in human in vitro fertilization and embryo transfer. Human oocyte and embryo cryopreservation field has been much progress during its fourth decade history. Two basic strategies have ruled the mammalian germplasm cryopreservation field: the traditional slow freezing technique also referred as conventional slow freezing or controlled slow freezing which started in the 1970s, and followed by vitrification technique developed in the late 1980s, In the slow freezing protocol, the embryo is placed in a hypertonic solution and slowly cooled using a programmable freezer to sub-zero temperatures, and then plunged into liquid nitrogen, whereas vitrification technique can be performed by using high cooling rates and high concentration of cryoprotectants. In recent years vitrification technique is a common method for cryopreservation of oocytes and embryos in comparable to slow freezing method. Vitrification appears to be associated with a significantly higher post-thawing survival rate, higher implantation rate and more pregnancies than slow freezing. Vitrification protocol simplifies the cryopreservation process without physical damage to embryos and oocytes and decreases the chilling injuries of germplasm as it passes through a very low temperature very rapidly. Although germplasm cryopreservation has decreased the number of fresh embryo transfers and maximized the effectiveness of the in vitro fertilization cycle, further prospective trials are necessary to confirm that vitrification is a superior technique to slow freezing method. The purpose of the present mini-review is to highlight oocyte and embryo cryopreservation technique in general, with comparing the different laboratory methods in particular slow freezing (vs) vitrification and successful implantation after transfer. 

Abstract

Walking considered as one of the safest modes of

travel available, sustainable to human society as well as

environmentally beneficial. In this context, the aim of this

research is to investigate pedestrians’ traffic gap acceptance

and crossing decision for Mid-block Street crossing in urban

areas in Malaysia. Pedestrian crossing behaviour at

Rughaya Street has been examined in terms of the decision

to cross or not the street and size of traffic gaps accepted by

pedestrian, as well as the related contributing factors. A

field study was conducted to collect the data of pedestrians’

decisions under real mix traffic Condition using video

camera on a typical unsignalized urban street section. JPEG

files were obtained from video recording by using Snapshot

Wizard software. The data extracted included traffic

characteristics such as traffic size, traffic speed, etc.

pedestrian individual characteristics such as gender, in

addition to individual behavior such as waiting, frequency

of attempt, etc.). Furthermore, The extracted data were

used to develop and examine a pedestrian gap acceptance

model based on A lognormal regression model and binary

logistic model by SPSS (22) in order to validate the impact

of various parameters on the size of traffic gaps accepted by

pedestrians as well as the effect on the decision of

pedestrians to cross the street or not. So that the effect of

the gap accepted available and of other factors on the

decision of pedestrians to cross the street or not is examined.

These results indicate that the data set for this particular

location has a majority of male pedestrians which were

insignificant variables in both models moreover a lognormal

regression results shows that accepted gaps size depend on

traffic size, crossing distance, speed of approaching vehicle

and time spent by pedestrian at the curb waiting for a

suitable gap size to start crossing. The BL model performs

well for the reason that it captures the pedestrian decision

making process with traffic taking the relevant attributes

into consideration. According to the coefficients of BL

regression analysis equation we noticed that the illegal

parking, traffic size, traffic waiting time and gap size are the

vital attributes for the Pedestrian gap acceptance model..

Index Terms: Pedestrian crossing, gap acceptance, crossing

decision, multiple linear regression, binary logistic

regression.