Tunable ferroelectric impedance matching networks and their impact on digital modulation system performance

In this paper the bit error rate performance and error vector magnitude of a tunable impedance matching network is analyzed assuming QPSK, 16-QAM and 64-QAM digital modulation schemes. The characterized tunable impedance matching network is based on barium–strontium–titanate ferroelectric thick-film varactors. Inherent dispersive behavior is subsumed into the forward transmission of the passive device. Due to this nonlinear phase response, in general to maximize the overall system performance, an agile tuning of the varactor values is demonstrated, taking into account the phase and group delay of s₂₁ parameter. Detailed signal simulation results based on measured data of a testbed are presented. The influence of varying matched impedances on the tuning behavior with different modulation bandwidths is discussed at a center frequency of 1.9 GHz.     

Graphene Oxide‐Cyclic R10 Peptide Nuclear Translocation Nanoplatforms for the Surmounting of Multiple‐Drug Resistance

Multidrug resistance resulting from a variety of defensive pathways in cancer has become a global concern with a considerable impact on the mortality associated with the failure of traditional chemotherapy. Therefore, further research and new therapies are required to overcome this challenge. In this work, a cyclic R10 peptide (cR₁₀) is conjugated to polyglycerol‐covered nanographene oxide to engineer a nanoplatform for the surmounting of multidrug resistance. The nuclear translocation of the nanoplatform, facilitated by cR₁₀ peptide, and subsequently, a laser‐triggered release of the loaded doxorubicin result in efficient anticancer activity confirmed by both in vitro and in vivo experiments. The synthesized nanoplatform with a combination of different features, including active nucleus‐targeting, high‐loading capacity, controlled release of cargo, and photothermal property, provides a new strategy for circumventing multidrug resistant cancers.     

An Iterative Receiver for Uplink of Coded MIMO DS-CDMA System Employing Layered Space-Time Transmission

We consider a coded multiple-input multiple-output (MIMO) DS-CDMA system using layered space-time transmission in multipath wireless channels, where space-time signals from multiple antennas of multiple users propagate through rich scattering multipath fading. We propose a receiver employing iterative joint detection and decoding with a reduced-complexity detector using linear minimum mean squared error filtering with a priori information and parallel soft-input soft-output (SISO) decoders. Computer simulation results show that the proposed receiver for multi-user MIMO transmission provides high-spectral efficiency and performance approaching to single-user bound. Furthermore, the reduced-complexity receiver outperforms an iterative soft decision-directed maximal ratio combining (DD-MRC) receiver, RAKE receiver as well as a conventional non-iterative receiver.     

Performance improvement for recommender systems using ontology

Recommender systems have emerged in the e-commerce domain and have been developed to actively recommend appropriate items to online users. The use of recently developed hybrid recommendation systems has helped overcome the main drawbacks of Content-Based Filtering (CBF) and Collaborative Filtering (CF). In hybrid recommendation systems that combine CF and CBF, the CF part uses two methods, including memory- and model-based approaches. Both approaches have some advantages and disadvantages for item recommendation. Sparsity has been one of the main difficulties associated with these approaches, whereas recommendation with high accuracy has been one of the important advantages of the memory-based approach. However, this approach is not scalable for current recommendation systems as their databases include huge numbers of items and users. In contrast, the model-based approach generates recommendations with low accuracy but is scalable for large databases in e-commerce recommender systems. Accordingly, to address this problem and take advantage of both approaches, in this work, we propose a new hybrid recommendation method and evaluate it using a real-world dataset. The aim is to improve efficiency and accuracy by designing a heuristic hybrid recommender method that combines memory-based and model-based approaches. Specifically, we use ontology in the CF part and improve ontology structure by eliminating uniformity of edges of the hierarchical relation between concepts (IS-A relation) in item ontology in the CBF part. Ontology structure is considered for improving accuracy; according to this, a new method for measuring semantic similarity that is more accurate than the traditional methods is presented. This new method can enhance the accuracy of CF and CBF in our method. In addition, the number of searches required to find similar clusters and neighbor users of the target user is decreased significantly using ontology, enhanced clustering and the new proposed algorithm. We evaluate the proposed method using a real-world dataset. The experimental results show that our method is more scalable and accurate than the benchmark k-Nearest Neighbor (k-NN) and model-based recommendation methods.     

Radio-over-free space optical space division multiplexing system using 3-core photonic crystal fiber mode group multiplexers

Wireless Networks - Radio over free space optics (Ro-FSO) systems have previously relied on the signal intensity, wavelength and polarization for multiplexing data streams in...     

Dynamic TDD Fixed Cellular Systems Using Smart and Sectored Antennas

There are many benefits in using time division duplex (TDD) instead of frequency division duplex (FDD) schemes in fixed wireless cellular systems. For example, channel reciprocity for a single carrier frequency used on both uplinks and downlinks will allow easy access to channel state information, reduced complexity of RF design, much higher flexibility in handling dynamic traffic, simpler frequency plan, etc. However, there exists a serious limiting factor in using dynamic TDD (D-TDD) in cellular systems. This is due to a steady interference on an uplink in any cell caused by downlink transmissions in other cells. Simulation results show in D-TDD cellular systems, performance is unacceptable, when an omnidirectional antenna is used at base stations. Simulation results also suggest great potential for smart antennas in achieving substantial performance improvement in fixed D-TDD bandwidth-on-demand wireless systems.     

Biodegradable Polymeric Nanoparticles Containing an Immune Checkpoint Inhibitor (aPDL1) to Locally Induce Immune Responses in the Central Nervous System

Immunotherapy is an efficient approach to clinical oncology. However, the immune privilege of the central nervous system (CNS) limits the application of immunotherapeutic strategies for brain cancers, especially glioblastoma (GBM). Tumor resistance to immune checkpoint inhibitors is a further challenge in immunotherapies. To overcome the immunological tolerance of brain tumors, a novel multifunctional nanoparticle (NP) for highly efficient synergetic immunotherapy is reported. The NP contains an anti-PDL1 antibody (aPDL1), upconverting NPs, and the photosensitizer 5-ALA; the surface of the NP is conjugated with the B1R kinin ligand to facilitate transport across the blood-tumor-barrier. Upon irradiation with a 980 nm laser, 5-ALA is transformed into protoporphyrin IX, generating reactive oxygen species. Photodynamic therapy (PDT) further promotes intratumoral infiltration of cytotoxic T lymphocytes and sensitizes tumors to PDL1 blockade therapy. It is demonstrated that combining PDT and aPDL1 can effectively suppress GBM growth in mouse models. The proposed NPs provide a novel and effective strategy for boosting anti-GBM photoimmunotherapy.     

Composite Living Fibers for Creating Tissue Constructs Using Textile Techniques

The fabrication of cell‐laden structures with anisotropic mechanical properties while having a precise control over the distribution of different cell types within the constructs is important for many tissue engineering applications. Automated textile technologies for making fabrics allow simultaneous control over the color pattern and directional mechanical properties. The use of textile techniques in tissue engineering, however, demands the presence of cell‐laden fibers that can withstand the mechanical stresses during the assembly process. Here, the concept of composite living fibers (CLFs) in which a core of load bearing synthetic polymer is coated by a hydrogel layer containing cells or microparticles is introduced. The core thread is drawn sequentially through reservoirs containing a cell‐laden prepolymer and a crosslinking reagent. The thickness of the hydrogel layer increases linearly with to the drawing speed and the prepolymer viscosity. CLFs are fabricated and assembled using regular textile processes including weaving, knitting, braiding, winding, and embroidering, to form cell‐laden structures. Cellular viability and metabolic activity are preserved during CLF fabrication and assembly, demonstrating the feasibility of using these processes for engineering functional 3D tissue constructs.