Amidst the rapid development of the fifth generation (5G) networks, Internet of Things (IoT) is considered as one of the most important part of 5G next generation networks as it can support massive object communications. These massive object communications in the context of IoT is expected to consume a huge power. Furthermore, IoT sensors or devices are rather power constrained and are mostly battery operated. Therefore, energy efficiency of such network of IoT devices is a major concern. On the other hand, energy harvesting (EH) is an emerging paradigm that allows the wireless nodes to recharge themselves through radio frequency (RF) signals directed to them from the source node and then relaying or transmitting the information. Although a myriad of works have been carried out in the literature for EH, the vast majority of those works only consider RF EH at the relay node and successfully transmitting the source node data. Those approaches do not consider the data transmission of the relay node that may be an energy deprived IoT node which needs to transmit its own data along with the source node data to their respective destination nodes. Therefore, in this paper, we envisioned a RF EH and information transmission system based on time switching (TS) relaying, power splitting (PS) relaying and non-orthogonal multiple access (NOMA) which is suitable for wireless powered IoT relay systems. A source node information data is relayed through power constrained IoT relay node IoTR that first harvests the energy from source node RF signal using either TS and PS relaying protocol and then transmits the source node information along with its information using NOMA protocol to the respective destination nodes. Considering NOMA as a transmission protocol, we have mathematically derived analytical expressions for TS and PS relaying protocol for our proposed system. We have also formulated an algorithm to find out optimal TS and PS factor that maximizes the sum-throughput for our proposed system. Our proposed system analytical results for TS and PS protocol are validated by the simulation results.
In GPS-denied indoor environments, localization and tracking of people can be achieved with a mobile device such as a smartphone by processing the received signal strength (RSS) of RF signals emitted from known location beacons (anchor nodes), combined with Pedestrian Dead Reckoning (PDR) estimates of the user motion. An enhacement of this localization technique is feasible if the users themselves carry additional RF emitters (mobile nodes), and the cooperative position estimates of a group of persons incorporate the RSS measurements exchanged between users. We propose a centralized cooperative particle filter (PF) formulation over the joint state of all users that permits to process RSS measurements from both anchor and mobile emitters, as well as PDR motion estimates and map information (if available) to increase the overall positioning accuracy, particularly in regions with low density of anchor nodes. Smartphones are used as a convenient mobile platform for sensor measurements acquisition, low-level processing, and data transmission to a central unit, where cooperative localization processing takes place. The cooperative method is experimentally demonstrated with four users moving in an area of 1600 m(2), with 7 anchor nodes comprised of active RFID (radio frequency identification) tags, and additional mobile tags carried by each user. Due to the limited coverage provided by the anchor beacons, RSS-based individual localization is inaccurate (6.1 m median error), but this improves to 4.9 m median error with the cooperative PF. Further gains are produced if the PDR information is added to the filter: median error of 3.1 m (individual) and 2.6 m (cooperative); and if map information is also considered, the results are 1.8 m (individual) and 1.6 m (cooperative). Thus, for each version of the particle filter, cooperative localization outperforms individual localization in terms of positioning accuracy.
There is a rapid increase in the percentage of elderly people in Europe. Consequently, the prevalence of age-related diseases will also significantly increase. Therefore, the main goal of MediHealth, an international research project, is to introduce a novel approach for the discovery of active agents of food plants from the Mediterranean diet and other global sources that promote healthy ageing. To achieve this goal, a series of plants from the Mediterranean diet and food plants from other origins are carefully selected and subjected to in silico, cell-based, in vivo (fly and mouse models), and metabolism analyses. Advanced analytical techniques complement the bio-evaluation process for the efficient isolation and identification of the bioactive plant constituents. Furthermore, pharmacological profiling of bioactive natural products, as well as the identification and synthesis of their metabolites, is carried out. Finally, optimization studies are performed in order to proceed to the development of innovative nutraceuticals, dietary supplements or herbal medicinal products. The project is based on an exchange of researchers between nine universities and four companies from European and non-European countries, exploiting the existing complementary multidisciplinary expertise. Herein, the unique and novel approach of this interdisciplinary project is presented.
Host-defense peptides, also called antimicrobial peptides (AMPs), whose protective action has been used by animals for millions of years, fulfill many requirements of the pharmaceutical industry, such as: (1) broad spectrum of activity; (2) unlike classic antibiotics, they induce very little resistance; (3) they act synergically with conventional antibiotics; (4) they neutralize endotoxins and are active in animal models. However, it is considered that many natural peptides are not suitable for drug development due to stability and biodisponibility problems, or high production costs. This review describes the efforts to overcome these problems and develop new antimicrobial drugs from these peptides or inspired by them. The discovery process of natural AMPs is discussed, as well as the development of synthetic analogs with improved pharmacological properties. The production of these compounds at acceptable costs, using different chemical and biotechnological methods, is also commented. Once these challenges are overcome, a new generation of versatile, potent and long-lasting antimicrobial drugs is expected.
Understanding interindividual variability in response to dietary polyphenols remains essential to elucidate their effects on cardiometabolic disease development. A meta-analysis of 128 randomized clinical trials was conducted to investigate the effects of berries and red grapes/wine as sources of anthocyanins and of nuts and pomegranate as sources of ellagitannins on a range of cardiometabolic risk biomarkers. The potential influence of various demographic and lifestyle factors on the variability in the response to these products were explored. Both anthocyanin-and ellagitannin-containing products reduced total-cholesterol with nuts and berries yielding more significant effects than pomegranate and grapes. Blood pressure was significantly reduced by the two main sources of anthocyanins, berries and red grapes/wine, whereas waist circumference, LDL-cholesterol, triglycerides, and glucose weremost significantly lowered by the ellagitannin-products, particularly nuts. Additionally, we found an indication of a small increase in HDL-cholesterol most significant with nuts and, in flow-mediated dilation by nuts and berries. Most of these effects were detected in obese/overweight people but we found limited or non-evidence in normoweight individuals or of the influence of sex or smoking status. The effects of other factors, i.e., habitual diet, health status or country where the study was conducted, were inconsistent and require further investigation.
We report self-assembly and phase transition behavior of lower diamondoid molecules and their primary derivatives using molecular dynamics (MD) simulation and density functional theory (DFT) calculations. Two lower diamondoids (adamantane and diamantane), three adamantane derivatives (amantadine, memantine and rimantadine) and two artificial molecules (ADM*Na and DIM*Na) are studied separately in 125-molecule simulation systems. We performed DFT calculations to optimize their molecular geometries and obtained atomic electronic charges for the corresponding MD simulation, by which we predicted self-assembly structures and simulation trajectories for the seven different diamondoids and derivatives. Our radial distribution function and structure factor studies showed clear phase transitions and self-assemblies for the seven diamondoids and derivatives.
Sensing advances in plant phenotyping are of vital importance in basic and applied plant research. Plant phenotyping enables the modeling of complex shapes, which is useful, for example, in decision-making for agronomic management. In this sense, 3D processing algorithms for plant modeling is expanding rapidly with the emergence of new sensors and techniques designed to morphologically characterize. However, there are still some technical aspects to be improved, such as an accurate reconstruction of end-details. This study adapted low-cost techniques, Structure from Motion (SfM) and MultiView Stereo (MVS), to create 3D models for reconstructing plants of three weed species with contrasting shape and plant structures. Plant reconstruction was developed by applying SfM algorithms to an input set of digital images acquired sequentially following a track that was concentric and equidistant with respect to the plant axis and using three different angles, from a perpendicular to top view, which guaranteed the necessary overlap between images to obtain high precision 3D models. With this information, a dense point cloud was created using MVS, from which a 3D polygon mesh representing every plants' shape and geometry was generated. These 3D models were validated with ground truth values (e.g., plant height, leaf area (LA) and plant dry biomass) using regression methods. The results showed, in general, a good consistency in the correlation equations between the estimated values in the models and the actual values measured in the weed plants. Indeed, 3D modeling using SfM algorithms proved to be a valuable methodology for weed phenotyping, since it accurately estimated the actual values of plant height and LA. Additionally, image processing using the SfM method was relatively fast. Consequently, our results indicate the potential of this budget system for plant reconstruction at high detail, which may be usable in several scenarios, including outdoor conditions. Future research should address other issues, such as the time-cost relationship and the need for detail in the different approaches.
Functional foods containing peptides offer the possibility to modulate the absorption of sugars and insulin levels to prevent diabetes. This study investigates the potential of germinated soybean peptides to modulate postprandial glycaemic response through inhibition of dipeptidyl peptidase IV (DPP-IV), salivary -amylase, and intestinal -glucosidases. A protein isolate from soybean sprouts was digested by pepsin and pancreatin. Protein digest and peptide fractions obtained by ultrafiltration (10 kDa) and subsequent semipreparative reverse phase liquid chromatography (F1, F2, F3, and F4) were screened for in vitro inhibition of DPP-IV, -amylase, maltase, and sucrase activities. Protein digest inhibited DPP-IV (IC50 = 1.49 mg/mL), -amylase (IC50 = 1.70 mg/mL), maltase, and sucrase activities of -glucosidases (IC50 = 3.73 and 2.90 mg/mL, respectively). Peptides of 5-10 and >10 kDa were more effective at inhibiting DPP-IV (IC50 = 0.91 and 1.18 mg/mL, respectively), while peptides of 5-10 and <5 kDa showed a higher potency to inhibit -amylase and -glucosidases. Peptides in F1, F2, and F3 were mainly fragments from -conglycinin, glycinin, and P34 thiol protease. The analysis of structural features of peptides in F1-F3 allowed the tentative identification of potential antidiabetic peptides. Germinated soybean protein showed a promising potential to be used as a nutraceutical or functional ingredient for diabetes prevention.
A series of sp²-iminosugar glycomimetics differing in the reducing or nonreducing character, the configurational pattern (d- or l- ), the architecture of the glycone skeleton, and the nature of the nonglycone substituent has been synthesized and assayed for their inhibition properties towards commercial glycosidases. On the basis of their affinity and selectivity towards GH1 β-glucosidases, reducing and nonreducing bicyclic derivatives having a hydroxylation profile of structural complementarity with d-glucose and incorporating an -octyl-isourea or -isothiourea segment were selected for further evaluation of their inhibitory/chaperoning potential against human glucocerebrosidase (GCase). The 1-deoxynojirimycin (DNJ)-related nonreducing conjugates behaved as stronger GCase inhibitors than the reducing counterparts and exhibited potent chaperoning capabilities in Gaucher fibroblasts hosting the neuronopathic G188S/G183W mutation, the isothiourea derivative being indeed one of the most efficient chaperone candidates reported up to date (70% activity enhancement at 20 pM). At their optimal concentration, the four selected compounds promoted mutant GCase activity enhancements over 3-fold; yet, the inhibitor/chaperoning balance became unfavorable at much lower concentration for nonreducing as compared to reducing derivatives.