IRS-Aided Uplink Security Enhancement via Energy-Harvesting Jammer

In this paper, we investigate the security enhancement by combining intelligent reflecting surface (IRS) and energy harvesting (EH) jammer for the uplink transmission. Specifically, we propose an IRS-aided secure scheme for the uplink transmission via an EH jammer, to fight against the malicious eavesdropper. The proposed scheme can be divided into an energy transfer (ET) phase and an information transmission (IT) phase. In the first phase, the friendly EH jammer harvests energy from the base station (BS) aided by IRS. We maximize the harvested energy of jammer by obtaining the closed-form solution to the phase-shift matrix of IRS. In the second phase, the user transmits confidential information to the BS while the jamming is generated to confuse the eavesdropper without affecting the legitimate transmission. The phase-shift matrix of IRS and time switching factor are jointly optimized to maximize the secrecy rate. To tackle the non-convex problem, we first decompose it into two sub-problems. The one of IRS can be approximated to convex with fixed time switching factor. Then, the time switching factor can be solved by Lagrange duality. Thus, the solution to the original problem can be obtained by alternately optimizing these two sub-problems. Simulation results show that the proposed Jammer-IRS assisted secure transmission scheme can significantly enhance the uplink security

Extraction of low molecular weight RNA from Citrus trifolita tissues for microRNA Northern blotting and reverse transcriptase polymerase chain reaction (RTPCR)

The study of microRNA (miRNA), a component of low molecular weight RNA (LMW RNA), has received increasing attention in recent years. A critical prerequisite in miRNA studies is acquisition of high quality LMW RNA. LMW RNA is generally obtained from total RNA or from total nucleic acids solutions. Most traditional methods for LMW RNA isolation involve many steps and chemical reagents which upon degradation may negatively affect results. We employed a simple and quick method involving trizol for total RNA extraction from citrus tissues, then generation of LMW RNA using 4M LiCl, which have been successfully utilized in studies in our laboratory. Compared with traditional methods, this method is less expensive and produced high RNA yields while avoiding the use of phenol or other toxic reagents. In addition, the entire procedure can be completed within 4 hours with many samples being processed simultaneously. Therefore, this is a practical and efficient method for LMW RNA extraction from woody fruit crops containing high levels of polysaccharide and polyphenolics. Using the extracted LMW RNA, miRNAs were successfully detected and characterized by reverse transcriptase polymerase chain reaction (RT-PCR) and Northern blotting.Keywords: Citrus, low molecular weight RNA, trizol reagent, 4 M LiCl, microRNA

Secure Beamforming for IRS-Enhanced NOMA Networks

Owing to the increasing demand of higher spectrum efficiency and large-scale connectivity, non-orthogonal multiple access (NOMA) has become a highly competitive candidate for the upcoming sixth-generation (6G) systems. Nevertheless, the instable wireless propagation environment and potential wireless security risk become bottlenecks in applications of NOMA. Fortunately, intelligent reflecting surface (IRS) that can construct the three-dimensional beamforming and reconfigure the channels emerges as a highly efficient technology to break through the limitations of NOMA. Thus, in this article, we first present an overview of NOMA, and particularly illustrate its main shortcomings and security risks. Then, we introduce the IRS technology and provide further enhancement by applying IRS to NOMA networks. In addition, typical security threats in IRSNOMA networks are shown, followed by two countermeasures based on the joint transmit beamforming and IRS reflecting beamforming towards external and internal eavesdropping, respectively. Simulation results are carried out to demonstrate the feasibility and effectiveness of these two schemes. Several challenges and future directions are also discussed

Use of functional MRI to evaluate correlation between acupoints and the somatic sensory cortex activities

published_or_final_versio

A fMRI Study of Correlation Between Acupoints and Brain Cortical Sites Involved in Language Functions

published_or_final_versio

The identification of informative genes from multiple datasets with increasing complexity

Background In microarray data analysis, factors such as data quality, biological variation, and the increasingly multi-layered nature of more complex biological systems complicates the modelling of regulatory networks that can represent and capture the interactions among genes. We believe that the use of multiple datasets derived from related biological systems leads to more robust models. Therefore, we developed a novel framework for modelling regulatory networks that involves training and evaluation on independent datasets. Our approach includes the following steps: (1) ordering the datasets based on their level of noise and informativeness; (2) selection of a Bayesian classifier with an appropriate level of complexity by evaluation of predictive performance on independent data sets; (3) comparing the different gene selections and the influence of increasing the model complexity; (4) functional analysis of the informative genes. Results In this paper, we identify the most appropriate model complexity using cross-validation and independent test set validation for predicting gene expression in three published datasets related to myogenesis and muscle differentiation. Furthermore, we demonstrate that models trained on simpler datasets can be used to identify interactions among genes and select the most informative. We also show that these models can explain the myogenesis-related genes (genes of interest) significantly better than others (P < 0.004) since the improvement in their rankings is much more pronounced. Finally, after further evaluating our results on synthetic datasets, we show that our approach outperforms a concordance method by Lai et al. in identifying informative genes from multiple datasets with increasing complexity whilst additionally modelling the interaction between genes. Conclusions We show that Bayesian networks derived from simpler controlled systems have better performance than those trained on datasets from more complex biological systems. Further, we present that highly predictive and consistent genes, from the pool of differentially expressed genes, across independent datasets are more likely to be fundamentally involved in the biological process under study. We conclude that networks trained on simpler controlled systems, such as in vitro experiments, can be used to model and capture interactions among genes in more complex datasets, such as in vivo experiments, where these interactions would otherwise be concealed by a multitude of other ongoing events

Extraction of SSVEPs-Based Inherent Fuzzy Entropy Using a Wearable Headband EEG in Migraine Patients

© 1993-2012 IEEE. Inherent fuzzy entropy is an objective measurement of electroencephalography (EEG) complexity reflecting the robustness of brain systems. In this study, we present a novel application of multiscale relative inherent fuzzy entropy using repetitive steady-state visual evoked potentials (SSVEPs) to investigate EEG complexity change between two migraine phases, i.e., interictal (baseline) and preictal (before migraine attacks) phases. We used a wearable headband EEG device with O1, Oz, O2, and Fpz electrodes to collect EEG signals from 80 participants [40 migraine patients and 40 healthy controls (HCs)] under the following two conditions: During resting state and SSVEPs with five 15-Hz photic stimuli. We found a significant enhancement in occipital EEG entropy with increasing stimulus times in both HCs and patients in the interictal phase, but a reverse trend in patients in the preictal phase. In the 1st SSVEP, occipital EEG entropy of the HCs was significantly lower than that of patents in the preictal phase (FDR-adjusted p < 0.05). Regarding the transitional variance of EEG entropy between the 1st and 5th SSVEPs, patients in the preictal phase exhibited significantly lower values than patients in the interictal phase (FDR-adjusted p < 0.05). Furthermore, in the classification model, the AdaBoost ensemble learning showed an accuracy of 81 pm 6%and area under the curve of 0.87 for classifying interictal and preictal phases. In contrast, there were no differences in EEG entropy among groups or sessions by using other competing entropy models, including approximate entropy, sample entropy, and fuzzy entropy on the same dataset. In conclusion, inherent fuzzy entropy offers novel applications in visual stimulus environments and may have the potential to provide a preictal alert to migraine patients

No effect of 14 day consumption of whole grain diet compared to refined grain diet on antioxidant measures in healthy, young subjects: a pilot study

<p>Abstract</p> <p>Background</p> <p>Epidemiological evidence supports that a diet high in whole grains is associated with lowered risk of chronic diseases included coronary heart disease, obesity, type 2 diabetes, and some types of cancer. One potential mechanism for the protective properties of whole grains is their antioxidant content. The aim of this study was to compare differences in antioxidant measures when subjects consumed either refined or whole grain diets.</p> <p>Methods</p> <p>Twenty healthy subjects took part in a randomized, crossover dietary intervention study. Subjects consumed either a refined grain or whole grain diet for 14 days and then the other diet for the next 14 days. Male subjects consumed 8 servings of grains per day and female subjects consumed 6 servings of grains per day. Blood and urine samples were collected at the end of each diet. Antioxidant measures included oxygen radical absorbance capacity (ORAC) in blood, and isoprostanes and thiobarbituric acid reactive substances (TBARS) in urine.</p> <p>Results</p> <p>The whole grain diet was significantly higher in dietary fiber, vitamin B6, folate, selenium, copper, zinc, iron, magnesium and cystine compared to the refined grain diet. Despite high intakes of whole grains, no significant differences were seen in any of the antioxidant measures between the refined and whole grain diets.</p> <p>Conclusions</p> <p>No differences in antioxidant measures were found when subjects consumed whole grain diets compared to refined grain diets.</p

Molecular beam epitaxy growth of high quality p-doped SnS van der Waals epitaxy on a graphene buffer layer

Author name used in this publication: W. K. FongAuthor name used in this publication: C. Surya2011-2012 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Characterization and source apportionment of atmospheric organic and elemental carbon during fall and winter of 2003 in Xi'an, China

Author name used in this publication: Lee, S. C.2005-2006 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe