Objective: This review will focus on the late neurological complications from cranial irradiation and relevant mitigation strategies.Background: Radiotherapy (RT) remains an important pillar in the management of brain metastases.Patients being treated in the modern era do experience longer survival, because of superior intra-and extracranial disease control. As a result, they can be more prone to developing and manifesting late complications post-brain radiotherapy.Methods: A search and narrative review of prospective clinical trials relating to neurological toxicity outcomes was conducted.Conclusions: Neurological toxicities can be challenging to diagnose and manage and should be considered during consideration of radiotherapy in brain metastasis, hence more emphasis should be placed on prevention and upfront mitigation of these complications, with novel strategies showing promising results in prospective trials being adopted into clinical practice.

Green computing is the process of reducing the power consumed by a computer and thereby reducing carbon emissions. The total power consumed by the computer excluding the monitor at its fully computative load is equal to the sum of the power consumed by the GPU in its idle state and the CPU at its full state. Recently, there have been tremendous interests in the acceleration of general computing applications using a Graphics Processing Unit (GPU). Now the GPU provides the computing powers not only for fast processing of graphics applications, but also for general computationally complex data intensive applications. On the other hand, power and energy consumptions are also becoming important design criteria. Consequently, software designs have to consider the power/energy consumptions together with performance when they are developing software.The GPU therefore does the 100% of the CPU work in its idle state .Hence the power consumed by the GPU will be low. Also when the GPU is doing all the work the CPU will remain at a load less than its idle load. Hence the power consumed will be equal to the power consumed by the CPU at a load less than its idle load plus the power consumed by a GPU. Â

Content-based image retrieval (CBIR) is widely adopted method for finding images from vast collection of images in the database. As the collections of images are growing at a rapid rate, demand for efficient and effective tools for retrieval of query images from database is increased significantly. Among them, content-based image retrieval systems (CBIR) have become very popular for browsing, searching and retrieving images from a large database of digital images as it requires relatively less human intervention. The requirement for development of CBIR is enhanced due to tremendous growth in volume of images as well as the widespread application in multiple fields. Texture, color, shaped, contours etc are the important entities to represent and search the images. These features of images are extracted and implemented for a similarity check among images. In this paper, we have conducted a survey on the CBIR techniques and its approaches and their usage in various domains.

e24014 Background: There is evidence from RCTs demonstrating that our current models of CGA guided care can reduce treatment related toxicity effectively. However, it is unclear if CGA guided care can improve OS and HRQL. We aimed to determine the effect of CGA guided care compared with usual care on OS and HRQL. Methods: We searched MEDLINE, EMBASE, CENTRAL and CINAHL from date of inception to October 2022 for RCTs comparing CGA guided care with usual care for patients with cancer who were 60 years old and greater on OS and HRQL. We assessed the risk of bias using Cochrane ROB 2 tool. We performed the meta-analysis using random-effects models. The I2 statistic was adopted to assess heterogeneity between studies. We adopted the Synthesis without meta-analysis approach for data not amenable for meta-analysis. The certainty of evidence was rated using the GRADE approach. This study is registered with Cochrane Database of Systematic Reviews (DOI: 10.1002/14651858.CD014875). Results: We found 15 eligible RCTs including 3507 participants. There are variations in types of CGA used with 4 trials using CGA to recommend oncology treatment regimen and 10 trials making no recommendation on oncology treatment. The implementation of CGA recommendations were carried out by a geriatrician in 14 trials, but by the primary oncologist in 1 trial. Six, five and four RCTs were judged to have low, unclear and high risk of bias respectively. Eleven and six RCTs reported OS and HRQL outcomes respectively. There was no significant difference between CGA guided and usual care for OS (Hazard Ratio 1.02, 95% CI (0.90 to 1.15), I2 = 0%; moderate certainty). There was significant variation in the measurement of HRQL in terms of instruments, summary measures and time points. EORTC QLQ C30 and ELD 14 were used in 3 RCTs. The effects of CGA guided care on HRQL were inconsistent. Two trials using FACT-G or Elderly Functional Index (ELFI) reported significant improvement in HRQL at 3 and 6 months post randomization. Meta-analysis of the mean difference in the change of the EORTC QLQ C30 and E14 HRQL scores relative to baseline at 6 months post randomization demonstrated no significant difference between CGA guided and usual care for HRQL across various domains (moderate certainty evidence). Conclusions: The current models of CGA guided care did not improve OS and had variable effects on HRQL when compared to usual care in older patients with cancer. The inconsistent effects of CGA guided care on HRQL suggest that CGA guided care may have more significant effects on the social and functional outcomes domains, aspects of HRQL that is predominantly measured in FACT-G and ELFI score respectively. There is also heterogeneity in how CGAs are performed and implemented. Future research should focus on developing new models of CGA guided care to improve OS and HRQL.