Spectrum and Energy Efficiency Tradeoff in IRS-Assisted CRNs with NOMA: A Multi-Objective Optimization Framework

Non-orthogonal multiple access (NOMA) is a promising candidate for the sixth generation wireless communication networks due to its high spectrum efficiency (SE), energy efficiency (EE), and better connectivity. It can be applied in cognitive radio networks (CRNs) to further improve SE and user connectivity. However, the interference caused by spectrum sharing and the utilization of non-orthogonal resources can downgrade the achievable performance. In order to tackle this issue, intelligent reflecting surface (IRS) is exploited in a downlink multiple-input-single-output (MISO) CRN with NO-MA. To realize a desirable tradeoff between SE and EE, a multi-objective optimization (MOO) framework is formulated. An iterative block coordinate descent (BCD)-based algorithm is exploited to optimize the beamforming design and IRS reflection coefficients iteratively. Simulation results demonstrate that the proposed scheme can achieve a better balance between SE and EE than baseline schemes

Multi-Objective Optimization for Spectrum and Energy Efficiency Tradeoff in IRS-Assisted CRNs with NOMA

Non-orthogonal multiple access (NOMA) is a promising candidate for the sixth generation wireless communication networks due to its high spectrum efficiency (SE), energy efficiency (EE), and better connectivity. It can be applied in cognitive radio networks (CRNs) to further improve SE and user connectivity. However, the interference caused by spectrum sharing and the utilization of non-orthogonal resources can downgrade the achievable performance. In order to tackle this issue, intelligent reflecting surface (IRS) is exploited in a downlink multiple-input-single-output (MISO) CRN with NOMA. To realize a desirable tradeoff between SE and EE, a multi-objective optimization (MOO) framework is formulated under both the perfect and imperfect channel state information (CSI). An iterative block coordinate descent (BCD)-based algorithm is exploited to optimize the beamforming design and IRS reflection coefficients iteratively under the perfect CSI case. A safe approximation and the S-procedure are used to address the non-convex infinite inequality constraints of the problem under the imperfect CSI case. Simulation results demonstrate that the proposed scheme can achieve a better balance between SE and EE than baseline schemes. Moreover, it is shown that both SE and EE of the proposed algorithm under the imperfect CSI can be significantly improved by exploiting IRS

Design of three-dimensional fitted garment pieces in a virtual environment

2004-2005 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

D-Ribose Induces Cellular Protein Glycation and Impairs Mouse Spatial Cognition

BACKGROUND: D-ribose, an important reducing monosaccharide, is highly active in the glycation of proteins, and results in the rapid production of advanced glycation end products (AGEs) in vitro. However, whether D-ribose participates in glycation and leads to production of AGEs in vivo still requires investigation. METHODOLOGY/PRINCIPAL FINDINGS: Here we treated cultured cells and mice with D-ribose and D-glucose to compare ribosylation and glucosylation for production of AGEs. Treatment with D-ribose decreased cell viability and induced more AGE accumulation in cells. C57BL/6J mice intraperitoneally injected with D-ribose for 30 days showed high blood levels of glycated proteins and AGEs. Administration of high doses D-ribose also accelerated AGE formation in the mouse brain and induced impairment of spatial learning and memory ability according to the performance in Morris water maze test. CONCLUSIONS/SIGNIFICANCE: These data demonstrate that D-ribose but not D-glucose reacts rapidly with proteins and produces significant amounts of AGEs in both cultured cells and the mouse brain, leading to accumulation of AGEs which may impair mouse spatial cognition

A meta-analysis of long-term effects of conservation agriculture on maize grain yield under rain-fed conditions

Conservation agriculture involves reduced tillage, permanent soil cover and crop rotations to enhance soil fertility and to supply food from a dwindling land resource. Recently, conservation agriculture has been promoted in Southern Africa, mainly for maize-based farming systems. However, maize yields under rain-fed conditions are often variable. There is therefore a need to identify factors that influence crop yield under conservation agriculture and rain-fed conditions. Here, we studied maize grain yield data from experiments lasting 5 years and more under rain-fed conditions. We assessed the effect of long-term tillage and residue retention on maize grain yield under contrasting soil textures, nitrogen input and climate. Yield variability was measured by stability analysis. Our results show an increase in maize yield over time with conservation agriculture practices that include rotation and high input use in low rainfall areas. But we observed no difference in system stability under those conditions. We observed a strong relationship between maize grain yield and annual rainfall. Our meta-analysis gave the following findings: (1) 92% of the data show that mulch cover in high rainfall areas leads to lower yields due to waterlogging; (2) 85% of data show that soil texture is important in the temporal development of conservation agriculture effects, improved yields are likely on well-drained soils; (3) 73% of the data show that conservation agriculture practices require high inputs especially N for improved yield; (4) 63% of data show that increased yields are obtained with rotation but calculations often do not include the variations in rainfall within and between seasons; (5) 56% of the data show that reduced tillage with no mulch cover leads to lower yields in semi-arid areas; and (6) when adequate fertiliser is available, rainfall is the most important determinant of yield in southern Africa. It is clear from our results that conservation agriculture needs to be targeted and adapted to specific biophysical conditions for improved impact

Clear Genetic Distinctiveness between Human- and Pig-Derived Trichuris Based on Analyses of Mitochondrial Datasets

The whipworm, Trichuris trichiura, causes trichuriasis in ∼600 million people worldwide, mainly in developing countries. Whipworms also infect other animal hosts, including pigs (T. suis), dogs (T. vulpis) and non-human primates, and cause disease in these hosts, which is similar to trichuriasis of humans. Although Trichuris species are considered to be host specific, there has been considerable controversy, over the years, as to whether T. trichiura and T. suis are the same or distinct species. Here, we characterised the entire mitochondrial genomes of human-derived Trichuris and pig-derived Trichuris, compared them and then tested the hypothesis that the parasites from these two host species are genetically distinct in a phylogenetic analysis of the sequence data. Taken together, the findings support the proposal that T. trichiura and T. suis are separate species, consistent with previous data for nuclear ribosomal DNA. Using molecular analytical tools, employing genetic markers defined herein, future work should conduct large-scale studies to establish whether T. trichiura is found in pigs and T. suis in humans in endemic regions

Multiplexed Quantum Dot Labeling of Activated c-Met Signaling in Castration-Resistant Human Prostate Cancer

The potential application of multiplexed quantum dot labeling (MQDL) for cancer detection and prognosis and monitoring therapeutic responses has attracted the interests of bioengineers, pathologists and cancer biologists. Many published studies claim that MQDL is effective for cancer biomarker detection and useful in cancer diagnosis and prognosis, these studies have not been standardized against quantitative biochemical and molecular determinations. In the present study, we used a molecularly characterized human prostate cancer cell model exhibiting activated c-Met signaling with epithelial to mesenchymal transition (EMT) and lethal metastatic progression to bone and soft tissues as the gold standard, and compared the c-Met cell signaling network in this model, in clinical human prostate cancer tissue specimens and in a castration-resistant human prostate cancer xenograft model. We observed c-Met signaling network activation, manifested by increased phosphorylated c-Met in all three. The downstream survival signaling network was mediated by NF-κB and Mcl-1 and EMT was driven by receptor activator of NF-κB ligand (RANKL), at the single cell level in clinical prostate cancer specimens and the xenograft model. Results were confirmed by real-time RT-PCR and western blots in a human prostate cancer cell model. MQDL is a powerful tool for assessing biomarker expression and it offers molecular insights into cancer progression at both the cell and tissue level with high degree of sensitivity