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Breast cancer is the second common cancer in all over the world. Obesity is one of crucial risk factors that have attracted considerable attention of researchers. It is well established that obesity factor increase breast cancer risk in postmenopausal period whereas obesity factor decrease breast cancer risk in pre-menopausal period. However, the association between obesity and breast cancer risk in each menopausal status is also restricted by expression of hormone receptors in tumour. The association between obesity and breast cancer subtypes risk regarding menopausal status is not fully understood in terms of risk factor association and gene expression.Molecular characteristics of different breast cancer subtypes in obese women have been attracted researchers interests. This review will focus on novel data about association and molecular characterisation findings between obesity and breast cancer with regarding to menopausal status and breast cancer subtypes and focuses on area needing further investigations. [ABSTRACT FROM AUTHOR]

A noticeable increase in the number of seawater reverse osmosis (SWRO) desalination plants has been observed during the last decade. This is due to the low energy consumed by reverse osmosis technology and the high freshwater recovery when compared to other desalination technologies. The desalination of seawater is the main source of freshwater in Kuwait. However, SWRO desalination plants generate huge volumes of concentrated brine, which is considered a potential source of mineral content. Some of these minerals are expensive and scarce on earth. The recovery of these minerals from brine can help in increasing the freshwater recovery, reducing the overall cost of desalinated water, offering a new source of raw materials, and decreasing the environmental impact from discharging brine to the sea. This study gives an overview of the different technologies used for the treatment of SWRO brine and explores the benefit to recover and reuse valuable potential minerals in brine. The study is motivated by the strong need to establish a local industry in Kuwait based on the extraction of potential valuable minerals from SWRO brine. Such industries can be combined with desalination plants to form a complex cogeneration of plants that accommodate desalination and power plants. [ABSTRACT FROM PUBLISHER]

Indoor localization is a dynamic and exciting research area. WiFi has exhibited a tremendous capability for internal localization since it is extensively used and easily accessible. Facilitating the use of WiFi for this purpose requires fingerprint formation and the implementation of a learning algorithm with the aim of using the fingerprint to determine locations. The most difficult aspect of techniques based on fingerprints is the effect of dynamic environmental changes on fingerprint authentication. With the aim of dealing with this problem, many experts have adopted transfer-learning methods, even though in WiFi indoor localization the dynamic quality of the change in the fingerprint has some cyclic factors that necessitate the use of previous knowledge in various situations. Thus, this paper presents the maximum feature adaptive online sequential extreme learning machine (MFA-OSELM) technique, which uses previous knowledge to handle the cyclic dynamic factors that are brought about by the issue of mobility, which is present in internal environments. This research extends the earlier study of the feature adaptive online sequential extreme learning machine (FA-OSELM). The results of this research demonstrate that MFA-OSELM is superior to FA-OSELM given its capacity to preserve previous data when a person goes back to locations that he/she had visited earlier. Also, there is always a positive accuracy change when using MFA-OSELM, with the best change achieved being 27% (ranging from eight to 27% and six to 18% for the TampereU and UJIIndoorLoc datasets, respectively), which proves the efficiency of MFA-OSELM in restoring previous knowledge. [ABSTRACT FROM AUTHOR]