Cache-Enabled in Cooperative Cognitive Radio Networks for Transmission Performance

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user’s effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching

Intra-tumoural lipid composition and lymphovascular invasion in breast cancer via non-invasive magnetic resonance spectroscopy

Acknowledgements The authors would like to thank Dr. Nicholas Senn for conducting data auditing, Dr. Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Dr. Tim Smith for biologist support, Mr. Gordon Buchan for technician support, Ms Bolanle Brikinns for patient recruitment support, Ms Dawn Younie for logistic support and Prof. Andrew M. Blamire for advice on MRS. The authors would also like to thank Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients. Funding: This study has received funding from Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2015 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarshipPeer reviewedPublisher PD

Optimal Phased-Array Signal Combination For Polyunsaturated Fatty Acids Measurement In Breast Cancer Using Multiple Quantum Coherence MR Spectroscopy At 3T

Acknowledgements The author would like to thank Dr Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Ms Bolanle Brikinns, Ms Louisa Pirie, Ms Linda Lett, and Ms Kate Shaw for patient recruitment support, Ms Dawn Younie for logistic support, Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients as well as Mrs Beverly MacLennan, Mrs Nichola Crouch, Mr Mike Hendry, and Ms Laura Reid for radiographer support. This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR). Vasiliki Mallikourti’s PhD study is supported by The Princess Royal Tenovus Scotland Medical Research Scholarship.Peer reviewedPublisher PD

Spatial heterogeneity of peri-tumoural lipid composition in postmenopausal patients with oestrogen receptor positive breast cancer

Funding Information: This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR) (RS2016 004). Sai Man Cheung’s PhD study was jointly supported by Elphinstone scholarship, Roland Sutton Academic Trust and John Mallard scholarship and is currently funded by Cancer Research UK (C68628/A28312). The funding sources were not involved in the study design, in the collection, analysis and interpretation of data, in the writing of the report nor in the decision to submit the article for publication.Peer reviewe

Precise measurement of position and attitude based on convolutional neural network and visual correspondence relationship

Accurate measurement of position and attitude information is particularly important. Traditional measurement methods generally require high-precision measurement equipment for analysis, leading to high costs and limited applicability. Vision-based measurement schemes need to solve complex visual relationships. With the extensive development of neural networks in related fields, it has become possible to apply them to the object position and attitude. In this paper, we propose an object pose measurement scheme based on convolutional neural network and we have successfully implemented end-toend position and attitude detection. Furthermore, to effectively expand the measurement range and reduce the number of training samples, we demonstrated the independence of objects in each dimension and proposed subadded training programs. At the same time, we generated generating image encoder to guarantee the detection performance of the training model in practical applications

Phased-array combination of 2D MRS for lipid composition quantification in patients with breast cancer

Acknowledgements: The author would like to thank Dr Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support, Ms Bolanle Brikinns, Ms Louisa Pirie, Ms Linda Lett, and Ms Kate Shaw, for patient recruitment support, Ms Dawn Younie for logistic support, Mr Roger Bourne and Ms Mairi Fuller for providing access to the patients as well as Mrs Beverly MacLennan, Mrs Nicola Crouch, Mr Mike Hendry, and Ms Laura Reid for radiographer support. Funding: This project was funded by Friends of Aberdeen and North Centre for Haematology, Oncology and Radiotherapy (ANCHOR), Tenovus Scotland, and NHS Grampian Endowment. Vasiliki Mallikourti’s PhD study is supported by The Princess Royal Tenovus Scotland Medical Research Scholarship.Peer reviewedPublisher PD

Peri-Tumoural Lipid Composition and Hypoxia for Early Immune Response to Neoadjuvant Chemotherapy in Breast Cancer

The authors would like to thank Matthew Clemence (Philips Healthcare Clinical Science, UK) for clinical scientist support; Erica Banks and Alison McKay for patient recruitment support; Teresa Morris and Dawn Younie for logistics support; Beverly McLennan, Nichola Crouch, Laura Reid, Mike Hendry for radiographer support; and Gordon Urquhart for providing access to the patients.Peer reviewe

Towards detection of early response in neoadjuvant chemotherapy of breast cancer using Bayesian intravoxel incoherent motion

IntroductionThe early identification of good responders to neoadjuvant chemotherapy (NACT) holds a significant potential in the optimal treatment of breast cancer. A recent Bayesian approach has been postulated to improve the accuracy of the intravoxel incoherent motion (IVIM) model for clinical translation. This study examined the prediction and early sensitivity of Bayesian IVIM to NACT response.Materials and methodsSeventeen female patients with breast cancer were scanned at baseline and 16 patients were scanned after Cycle 1. Tissue diffusion and perfusion from Bayesian IVIM were calculated at baseline with percentage change at Cycle 1 computed with reference to baseline. Cellular proliferative activity marker Ki-67 was obtained semi-quantitatively with percentage change at excision computed with reference to core biopsy.ResultsThe perfusion fraction showed a significant difference (p = 0.042) in percentage change between responder groups at Cycle 1, with a decrease in good responders [−7.98% (−19.47–1.73), n = 7] and an increase in poor responders [10.04% (5.09–28.93), n = 9]. There was a significant correlation between percentage change in perfusion fraction and percentage change in Ki-67 (p = 0.042). Tissue diffusion and pseudodiffusion showed no significant difference in percentage change between groups at Cycle 1, nor was there a significant correlation against percentage change in Ki-67. Perfusion fraction, tissue diffusion, and pseudodiffusion showed no significant difference between groups at baseline, nor was there a significant correlation against Ki-67 from core biopsy.ConclusionThe alteration in tumour perfusion fraction from the Bayesian IVIM model, in association with cellular proliferation, showed early sensitivity to good responders in NACT.Clinical trial registrationhttps://clinicaltrials.gov/ct2/show/NCT03501394, identifier NCT03501394

Transcriptome sequencing of olfactory-related genes in olfactory transduction of large yellow croaker (Larimichthy crocea) in response to bile salts

Fish produce and release bile salts as chemical signalling substances that act as sensitive olfactory stimuli. To investigate how bile salts affect olfactory signal transduction in large yellow croaker (Larimichthy crocea), deep sequencing of olfactory epithelium was conducted to analyse olfactory-related genes in olfactory transduction. Sodium cholates (SAS) have typical bile salt chemical structures, hence we used four different concentrations of SAS to stimulate L. crocea, and the fish displayed a significant behavioural preference for 0.30% SAS. We then sequenced olfactory epithelium tissues, and identified 9938 unigenes that were significantly differentially expressed between SAS-stimulated and control groups, including 9055 up-regulated and 883 down-regulated unigenes. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses found eight categories linked to the olfactory transduction pathway that was highly enriched with some differentially expressed genes (DEGs), including the olfactory receptor (OR), Adenylate cyclase type 3 (ADCY3) and Calmodulin (CALM). Genes in these categories were analysed by RT-qPCR, which revealed aspects of the pathway transformation between odor detection, and recovery and adaptation. The results provide new insight into the effects of bile salt stimulation in olfactory molecular mechanisms in fishes, and expands our knowledge of olfactory transduction, and signal generation and decline

Cache-Enabled in Cooperative Cognitive Radio Networks for Transmission Performance

The proliferation of mobile devices that support the acceleration of data services (especially smartphones) has resulted in a dramatic increase in mobile traffic. Mobile data also increased exponentially, already exceeding the throughput of the backhaul. To improve spectrum utilization and increase mobile network traffic, in combination with content caching, we study the cooperation between primary and secondary networks via content caching. We consider that the secondary base station assists the primary user by pre-caching some popular primary contents. Thus, the secondary base station can obtain more licensed bandwidth to serve its own user. We mainly focus on the time delay from the backhaul link to the secondary base station. First, in terms of the content caching and the transmission strategies, we provide a cooperation scheme to maximize the secondary user’s effective data transmission rates under the constraint of the primary users target rate. Then, we investigate the impact of the caching allocation and prove that the formulated problem is a concave problem with regard to the caching capacity allocation for any given power allocation. Furthermore, we obtain the joint caching and power allocation by an effective bisection search algorithm. Finally, our results show that the content caching cooperation scheme can achieve significant performance gain for the primary and secondary systems over the traditional two-hop relay cooperation without caching