Deep Learning Aided Secure Transmission in Wirelessly Powered Untrusted Relaying in the Face of Hardware Impairments

Limited power and computational resources make the employment of complex classical encryption schemes unrealistic in resource-limited networks, e.g., the Internet of Things (IoT). To this end, physical layer security (PLS) has shown great potential in securing such resource-limited networks. To further combat the power scarcity in IoT nodes, radio frequency (RF) based energy harvesting (EH) is an attractive energy source while relaying can enhance the energy efficiency and extend the range of data transmission. Additionally, due to deploying low-cost hardware, imperfections in the RF chain of IoT transceivers are common. Against this background, in this paper, we investigate an untrusted EH relay-aided secure communication with RF impairments. Specifically, the relay simultaneously receives the desired signal from the source and the jamming from the destination in the first phase. Hence the relay is unable to extract the confidential desired signal. The resultant composite signal is then amplified by the relay in the second phase by using the energy harvested from the composite signal followed by its transmission to the destination. Since the destination is the original source of the jamming, its effect can be readily subtracted from the composite signal to recover the original desired signal of the source. Moreover, in the face of hardware impairments (HWIs) in all nodes, maintaining optimal power management both at the source and destination may impose excessive computations on an IoT node. We solve this problem by deep learning (DL) based optimal power management maximizing the secrecy rate based on the instantaneous channel coefficients. We show that our learning-based scheme can reach the accuracy of the exhaustive search method despite its considerably lower computational complexity. Moreover, we developed an optimization framework for judiciously sharing HWIs across the nodes, so that we attain the maximum secrecy rate. To derive an efficient solution, we utilize a majorization-minimization (MM) algorithm, which is a particular instance in the family of successive convex approximation (SCA) methods. The simulation results show that the proposed HWI aware design considerably improves the secrecy rate

Viscoelastic properties of cell walls of single living plant cells determined by dynamic nanoindentation

Plant development results from controlled cell divisions, structural modifications, and reorganizations of the cell wall. Thereby, regulation of cell wall behaviour takes place at multiple length scales involving compositional and architectural aspects in addition to various developmental and/or environmental factors. The physical properties of the primary wall are largely determined by the nature of the complex polymer network, which exhibits time-dependent behaviour representative of viscoelastic materials. Here, a dynamic nanoindentation technique is used to measure the time-dependent response and the viscoelastic behaviour of the cell wall in single living cells at a micron or sub-micron scale. With this approach, significant changes in storage (stiffness) and loss (loss of energy) moduli are captured among the tested cells. The results reveal hitherto unknown differences in the viscoelastic parameters of the walls of same-age similarly positioned cells of the Arabidopsis ecotypes (Col 0 and Ws 2). The technique is also shown to be sensitive enough to detect changes in cell wall properties in cells deficient in the activity of the chromatin modifier ATX1. Extensive computational modelling of the experimental measurements (i.e. modelling the cell as a viscoelastic pressure vessel) is used to analyse the influence of the wall thickness, as well as the turgor pressure, at the positions of our measurements. By combining the nanoDMA technique with finite element simulations quantifiable measurements of the viscoelastic properties of plant cell walls are achieved. Such techniques are expected to find broader applications in quantifying the influence of genetic, biological, and environmental factors on the nanoscale mechanical properties of the cell wall

Interleukin 4 gene polymorphism (−589C/T) and the risk of asthma: a meta-analysis and met-regression based on 55 studies

Background: Numerous investigations have previously evaluated the association of interleukin (IL) 4 gene polymorphisms and the risk of asthma, conferring inconsistent results. To resolve the incongruent outcomes yielded from different single studies, we conducted the most up-to-date meta-analysis of IL4 gene −589C/T (rs2243250) polymorphism and susceptibility to asthma. Methods: A systematic literature search was performed in ISI web of science, Scopus, Medline/PubMed databases prior to September 2020, and the pooled odds ratio (OR) and their corresponding 95% CI were calculated to determine the association strength. Results: Literature search led to retrieving of 49 publications (55 case-control studies) containing 9572 cases and 9881 controls. It was revealed that IL4 gene −589C/T polymorphism increased the risk of asthma across all genetic models, including dominant model (OR = 1.22), recessive model (OR = 1.17), allelic model (OR = 1.21), and TT vs. CC model (OR = 1.34), but not the CT vs. TT model. The subgroup analysis by age indicated that IL4 gene -589C/T polymorphism was significantly associated with asthma risk in both pediatrics and adults. Additionally, the subgroup analysis by ethnicity revealed significant association in Asian, American, and Europeans. Finally, subgroup analysis by East Asian and non-East Asian populations indicated significant associations. Conclusions: The current meta-analysis revealed that IL4 gene -589C/T polymorphism was a susceptibility risk in both pediatrics and adults in the whole and different ethnic groups

A phase II trial of docetaxel and erlotinib as first-line therapy for elderly patients with androgen-independent prostate cancer

Background: Docetaxel is the standard first-line agent for the treatment of androgen-independent prostate cancer (AIPC). The combination of docetaxel with molecularly targeted therapies may offer the potential to increase the efficacy and decrease the toxicity of cytotoxic chemotherapy for prostate cancer. Previous studies demonstrate activation of the human epidermal growth factor receptor (EGFR) in prostate cancer. Erlotinib is a specific inhibitor of the tyrosine-kinase activity of EGFR. The goal of this study is to determine the anti-cancer activity docetaxel combined with erlotinib for the treatment of elderly subjects with AIPC. Methods: This is a multi-institutional Phase II study in patients with histologically confirmed adenocarcinoma of the prostate and age [greater than or equal to] 65 years. Patients were requred to have progressive disease despite androgen-deprivation therapy as determined by: (1) measurable lesions on cross-sectional imaging; (2) metastatic disease by radionucleotide bone imaging; or (3) elevated prostate specific antigen (PSA). Treatment cycles consisted of docetaxel 60 mg/m2 IV on day 1 and erlotinib 150 mg PO days 1-21. Patients with responding or stable disease after 9 cycles were eligible to continue on erlotinib alone as maintenance therapy. Results: Characteristics of 22 patients enrolled included: median age 73.5 years (range, 65-80); median Karnofsky Performance Status 90 (range 70-100); median hemoglobin 12.1 g/dl (range, 10.0-14.3); median PSA 218.3 ng/ml (range, 9-5754). A median of 6 treatment cycles were delivered per patient (range 1-17). No objective responses were observed in 8 patients with measurable lesions (0%, 95% CI 0-31%). Bone scan improvement and PSA decline was seen in 1 patient (5%, 95% CI 0.1-25%). Five of 22 patients experienced [greater than or equal to] 50% decline in PSA (23%, 95% CI 8-45%). Hematologic toxicity included grade 3 neutropenia in 9 patients and neutropenic fever in 2 patients. Common non-hematologic toxicities ([greater than or equal to] grade 3) included fatigue, anorexia, and diarrhea. Conclusion: Docetaxel/erlotinib can be delivered safely in elderly patients with AIPC. Anti-cancer disease activity appears generally comparable to docetaxel when used as monotherapy. Hematologic and nonhematologic toxicity may be increased over docetaxel monotherapy. Prospective randomized studies would be required to determine if the toxicity of docetaxel and erlotinib justifies its use in this setting.This study was supported by NIH Prostate SPORE P50 CA92131 to DBA. Phase One Foundation to MEG and DBA

Free vibration analysis and design optimization of SMA/Graphite/Epoxy composite shells in thermal environments

Composite shells, which are being widely used in engineering applications, are often under thermal loads. Thermal loads usually bring thermal stresses in the structure which can significantly affect its static and dynamic behaviors. One of the possible solutions for this matter is embedding Shape Memory Alloy (SMA) wires into the structure. In the present study, thermal buckling and free vibration of laminated composite cylindrical shells reinforced by SMA wires are analyzed. Brinson model is implemented to predict the thermo-mechanical behavior of SMA wires. The natural frequencies and buckling temperatures of the structure are obtained by employing Generalized Differential Quadrature (GDQ) method. GDQ is a powerful numerical approach which can solve partial differential equations. A comparative study is carried out to show the accuracy and efficiency of the applied numerical method for both free vibration and buckling analysis of composite shells in thermal environment. A parametric study is also provided to indicate the effects of like SMA volume fraction, dependency of material properties on temperature, lay-up orientation, and pre-strain of SMA wires on the natural frequency and buckling of Shape Memory Alloy Hybrid Composite (SMAHC) cylindrical shells. Results represent the fact that SMAs can play a significant role in thermal vibration of composite shells. The second goal of present work is optimization of SMAHC cylindrical shells in order to maximize the fundamental frequency parameter at a certain temperature. To this end, an eight-layer composite shell with four SMA-reinforced layers is considered for optimization. The primary optimization variables are the values of SMA angles in the four layers. Since the optimization process is complicated and time consuming, Genetic Algorithm (GA) is performed to obtain the orientations of SMA layers to maximize the first natural frequency of structure. The optimization results show that using an optimum stacking sequence for SMAHC shells can increase the fundamental frequency of the structure by a considerable amount