Secrecy Throughput Maximization for Full-Duplex Wireless Powered IoT Networks under Fairness Constraints

In this paper, we study the secrecy throughput of a full-duplex wireless powered communication network (WPCN) for internet of things (IoT). The WPCN consists of a full-duplex multi-antenna base station (BS) and a number of sensor nodes. The BS transmits energy all the time, and each node harvests energy prior to its transmission time slot. The nodes sequentially transmit their confidential information to the BS, and the other nodes are considered as potential eavesdroppers. We first formulate the sum secrecy throughput optimization problem of all the nodes. The optimization variables are the duration of the time slots and the BS beamforming vectors in different time slots. The problem is shown to be non-convex. To tackle the problem, we propose a suboptimal two stage approach, referred to as sum secrecy throughput maximization (SSTM). In the first stage, the BS focuses its beamforming to blind the potential eavesdroppers (other nodes) during information transmission time slots. Then, the optimal beamforming vector in the initial non-information transmission time slot and the optimal time slots are derived. We then consider fairness among the nodes and propose max-min fair (MMF) and proportional fair (PLF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of the nodes, while the PLF tries to achieve a good trade-off between the sum secrecy throughput and fairness among the nodes. Through numerical simulations, we first demonstrate the superior performance of the SSTM to uniform time slotting and beamforming in different settings. Then, we show the effectiveness of the proposed fair algorithms

Influence of pollution loading and flow rate on catalytic BTEX removal with a combined Cu2O, Fe0/Zeolite bed

ABSTRACT Environmental impacts and health concerns of BTEX compounds have been pointed in many studies. The agencies responsible for health and environment have delivered standard and guideline for BTEX concentrations. Because of the extensive use in industries and the presence of these compounds in fossil fuels, their emission resources are very divers. Today's, Control of air pollution caused by these compounds is one of the air qualities controlling challenges. "Thermal catalyzed" process is one of the technologies to control this kind of air pollution and consistent with using nanoparticles as a catalyst, this process is further considered now. So, we conducted this study to survey elimination of the BTEX, form polluted air flow, by this process. In this study, removal of the BTEX from polluted air by a thermal catalyzed process in the presence of zero-valent iron and copper oxide nanoparticles was investigated and the effect of changes in pollution load and flow rate was surveyed on removal efficiency and the decomposition of the pollutants. Fe0 and Cu2O nanoparticles were coated on a bed of natural zeolite (Clinoptilolite) with a zeolite grains size of 1-2 mm. The thermal catalyst process was conducted at 350°C and different pollution loading and air flow rate. 96.18% and 78.42% of removal efficiency achieved with the retention times of 14.1s and 7.05s. Increasing the pollution load reduced removal efficiency and pollutants' mineralization. By doubling the pollution load, the removal efficiency declined as much as 14.5 %. According to the results, increasing of the flow rate has a greater effect than the pollution load on the complete decomposition. Also this process showed a good efficiency for BTEX removal under high pollution loading and flow rates

Seven-Year Follow-Up of Peutz-Jeghers Syndrome

One of the clinicopathological criteria for diagnosing Peutz-Jeghers syndrome (PJS) is mucocutaneous pigmentation. We present a 57-year-old Iranian female patient with diffuse pigmentation in buccal and labial mucosa. The first colonoscopy revealed one 0.5 cm rectal polyp. However surveillance colonoscopies over a 7-year polyp showed over 100 colorectal polyps

Settlement prediction of the rock-socketed piles through a new technique based on gene expression programming

The settlement design of bored piles socketed into rock has received considerable attention. Although many design methods of pile settlement are recommended in the literature, proposing new/practical technique(s) with higher performance prediction is of advantage. A new model based on gene expression programming (GEP) is presented in this paper for predicting the settlement of the rock-socketed pile. To do this, 96 piles socketed in different types of rock (mostly granite) as part of the Klang Valley Mass Rapid Transit project, Malaysia, were studied. In order to propose a predictive model with higher performance prediction, a series of GEP analyses were conducted using the most important factors on pile settlement, i.e. ratio of length in soil layer to length in rock layer, ratio of total length to diameter, uniaxial compressive strength, standard penetration test and ultimate bearing capacity. For comparison purpose, using the same dataset, linear multiple regression (LMR) technique was also performed. After developing the equations, their prediction performances were checked through several performance indices. The results demonstrated the feasibility of GEP-based predictive model of settlement. Coefficients of determination (CoD) values of 0.872 and 0.861 for training and testing datasets of GEP equation, respectively, show superiority of this model in predicting pile settlement while these values were obtained as 0.835 and 0.751 for the LMR model. Moreover, root mean square error (RMSE) values of (1.293 and 1.656 for training and testing) and (1.737 and 1.767 for training and testing) were achieved for the developed GEP and LMR models, respectively

Satellite-Based Monitoring of Growing Agricultural Water Consumption in Hyper-Arid Regions

Land-use change has a key role in hydrologic processes and biodiversity. Although many satellite-based studies have been conducted to reveal the interaction between land-use changes in hydrological processes worldwide, the land-use change impact on agricultural water consumption in hyper-arid regions is poorly understood. Here, we investigate increased agricultural water consumption in the Qom province, a hyper-arid region in Iran, using derived imageries from Landsat 5 Tm and Landsat 8 OLI during the last three decades. We used maximum likelihood classification (MLC) and decision tree classification (DTC) to analyze the satellite images. The MLC method showed that croplands have increased from 30,547 ha in 1989 to 39,255 ha in 2019 (i.e., a 29% increase). In this period, the total orchard area increased from 3904 ha to 6307 ha, revealing a growth of 61%. In the DTC method, the increases in the cropland and orchard areas were, respectively, 34% and 60%. Although both MLC and DTC satisfied the accuracy criteria, the former was more consistent than the latter concerning ground data and documented statistics. Satellite-based and MLC results showed an increase in agricultural water consumption from 152 million cubic meters (MCM) in 1989 to 209 MCM in 2019, showing a 38% increase (i.e., 1.27% annually). Our findings send an alarming message for policymakers to reduce the water demand through sustainable agricultural practices in the Qom province, where the agricultural sector uses approximately 90% of annual water demand

The stereological, immunohistological, and gene expression studies in an infected ischemic wound in diabetic rats treated by human adipose-derived stem cells and photobiomodulation

We investigated the impacts of photobiomodulation (PBM) and human allogeneic adipose-derived stem cells (ha-ADS) together and or alone applications on the stereological parameters, immunohistochemical characterizing of M1 and M2 macrophages, and mRNA levels of hypoxia-inducible factor (HIF-1α), basic fibroblast growth factor (bFGF), vascular endothelial growth factor-A (VEGF-A) and stromal cell-derived factor-1α (SDF-1α) on inflammation (day 4) and proliferation phases (day 8) of repairing tissues in an infected delayed healing and ischemic wound model (IDHIWM) in type 1 diabetic (DM1) rats. DM1 was created in 48 rats and an IDHIWM was made in all of them, and they were distributed into 4 groups. Group1 = control rats with no treatment. Group2 = rats received (10 × 100000 ha-ADS). Group3 = rats exposed to PBM (890 nm, 80 Hz, 3.46 J/cm2). Group4 = rats received both PBM and ha-ADS. On day 8, there were significantly higher neutrophils in the control group than in other groups (p < 0.01). There were substantially higher macrophages in the PBM + ha-ADS group than in other groups on days 4 and 8 (p < 0.001). Granulation tissue volume, on both days 4 and 8, was meaningfully greater in all treatment groups than in the control group (all, p = 0.000). Results of M1 and M2 macrophage counts of repairing tissue in the entire treatment groups were considered preferable to those in the control group (p < 0.05). Regarding stereological and macrophage phenotyping, the results of the PBM + ha-ADS group were better than the ha-ADS and PBM groups. Results of the tested gene expression of repairing tissue on inflammation and proliferation steps in PBM and PBM + ha-ADS groups were meaningfully better than the control and ha-ADS groups (p < 0.05). We showed that PBM, ha-ADS, and PBM plus ha-ADS, hastened the proliferation step of healing in an IDHIWM in rats with DM1 by regulation of the inflammatory reaction, macrophage phenotyping, and augmented granulation tissue formation. In addition PBM and PBM plus ha-ADS protocols hastened and increased mRNA levels of HIF-1α, bFGF, SDF-1α, and VEGF-A. Totally, in terms of stereological and immuno-histological tests, and also gene expression HIF-1α and VEGF-A, the results of PBM + ha-ADS were superior (additive) to PBM, and ha-ADS alone treatments.This study was financially supported in part by Dr. Anwarul Hasan, and also by NIH grants no R44DK133065, and no R44DK105692.Scopu