Targeted delivery of DNA encoding cytotoxic proteins through high-affinity fibroblast growth factor receptors

Nonviral DNA delivery strategies for gene therapy have generally been limited by a lack of specificity and efficacy. However, ligand-mediated endocytosis can specifically deliver DNA in vitro to cells bearing the appropriate cognate receptors. Similarly, in order to circumvent problems related to efficacy, DNA must encode proteins with high intrinsic activities. We show here that the ligand basic fibroblast growth factor (FGF2) can target FGF receptor-bearing cells with DNA encoding therapeutic proteins. Delivery of genes encoding saporin, a highly potent ribosomal inactivating protein, or the conditionally cytotoxic herpes simplex virus thymidine kinase, a protein that can kill cells by activating the prodrug ganciclovir, is demonstrated. The saporin gene was codon optimized for mammalian expression and demonstrated to express functional protein in a cell-free assay. FGF2-mediated delivery of saporin DNA or thymidine kinase DNA followed by ganciclovir treatment resulted in a 60 and 75% decrease in cell number, respectively. Specificity of gene delivery was demonstrated in competition assays with free FGF2 or with recombinant soluble FGF receptor. Alternatively, when histone H1, a ligand that binds to cell surface heparan sulfate proteoglycans ("low-affinity" FGF receptors), was used to deliver DNA encoding thymidine kinase, no ganciclovir sensitivity was observed. These findings establish the feasibility of using ligands such as FGF2 to specifically deliver genes encoding molecular chemotherapeutic agents to cells.     

Performance evaluation of an adaptive self-organizing frequency reuse approach for OFDMA downlink

Orthogonal frequency division multiple access (OFDMA) is extensively utilized for the downlink of cellular systems such as long term evolution (LTE) and LTE advanced. In OFDMA cellular networks, orthogonal resource blocks can be used within each cell. However, the available resources are rare and so those resources have to be reused by adjacent cells in order to achieve high spectral efficiency. This leads to inter-cell interference (ICI). Thus, ICI coordination among neighboring cells is very important for the performance improvement of cellular systems. Fractional frequency reuse (FFR) has been widely adopted as an effective solution that improves the throughput performance of cell edge users. However, FFR does not account for the varying nature of the channel. Moreover, it exaggerates in caring about the cell edge users at the price of cell inner users. Therefore, effective frequency reuse approaches that consider the weak points of FFR should be considered. In this paper, we present an adaptive self-organizing frequency reuse approach that is based on dividing every cell into two regions, namely, cell-inner and cell-outer regions; and minimizing the total interference encountered by all users in every region. Unlike the traditional FFR schemes, the proposed approach adjusts itself to the varying nature of the wireless channel. Furthermore, we derive the optimal value of the inner radius at which the total throughput of the inner users of the home cell is as close as possible to the total throughput of its outer users. Simulation results show that the proposed adaptive approach has better total throughput of both home cell and all 19 cells than the counterparts of strict FFR, even when all cells are fully loaded, where other algorithms in the literature failed to outperform strict FFR. The improved throughput means that higher spectral efficiency can be achieved; i.e., the spectrum, which is the most precious resource in wireless communication, can be utilized efficiently. In addition, the proposed algorithm can provide significant power saving, that can reach 50% compared to strict FFR, while not penalizing the throughput performance.

     

Cotton Leaf Diseases Recognition Using Deep Learning and Genetic Algorithm

Globally, Pakistan ranks 4 in cotton production, 6 as an importer of raw cotton, and 3 in cotton consumption. Nearly 10% of GDP and 55% of the country's foreign exchange earnings depend on cotton products. Approximately 1.5 million people in Pakistan are engaged in the cotton value chain. However, several diseases such as Mildew, Leaf Spot, and Soreshine affect cotton production. Manual diagnosis is not a good solution due to several factors such as high cost and unavailability of an expert. Therefore, it is essential to develop an automated technique that can accurately detect and recognize these diseases at their early stages. In this study, a new technique is proposed using deep learning architecture with serially fused features and the best feature selection. The proposed architecture consists of the following steps: (a) a self-collected dataset of cotton diseases is prepared and labeled by an expert; (b) data augmentation is performed on the collected dataset to increase the number of images for better training at the earlier step; (c) a pre-trained deep learning model named ResNet101 is employed and trained through a transfer learning approach; (d) features are computed from the third and fourth last layers and serially combined into one matrix; (e) a genetic algorithm is applied to the combined matrix to select the best points for further recognition. For final recognition, a Cubic SVM approach was utilized and validated on a prepared dataset. On the newly prepared dataset, the highest achieved accuracy was 98.8% using Cubic SVM, which shows the perfection of the proposed framework..     

Sensor location optimization for fault diagnosis with a comparison to linear programming approaches

The critical importance of sustaining fault diagnosis, as a major system tool, is unquestionable if the high performance and reliability of increasingly complex engineering systems is to be sustained over time and across a wide operating range. However, it is quite difficult to retain the joint ability of fault detection and isolation as it requires a strong system architecture. That is why, before designing an industrial supervision system, the determination of a system’s monitoring ability based on technical specifications is important as finding the source of the failure is not trivial in systems with a large number of components and complex component relationships. This paper presents an efficient and cost-effective fault detection and isolation (FDI) scheme that evolved from an earlier work [1]. FDI specifications are translated into constraints of the optimization problem considering that the whole set of analytical redundancy relations has been generated, under the assumption that all candidate sensors are installed and later on tested by an optimization algorithm using binary and relaxed versions of linear and nonlinear programming. By doing so, critical information about the presence or absence of a fault is gained in the shortest possible time, with not only confirmation of the findings but also an accurate unfolding in time of the finer details of the fault, thus completing the overall diagnostic picture of the system under test. The proposed scheme is evaluated extensively on a two-tank process used in industry, exemplified by a benchmarked laboratory-scale coupled-tank system.     

Design and Experimental Evaluation of a Database-Assisted V2V Communications System Over TV White Space

In the past years, many works have demonstrated the applicability of Coarse-Grained Reconfigurable Array (CGRA) accelerators to optimize loops by using software pipelining approaches. They are proven to be effective in reducing the total execution time of multimedia and signal processing applications. However, the run-time reconfigurability of CGRAs is hampered overheads introduced by the needed translation and mapping steps. In this work, we present a novel run-time translation technique for the modulo scheduling approach that can convert binary code on-the-fly to run on a CGRA. We propose a greedy approach, since the modulo scheduling for CGRA is an NP-complete problem. In addition to read-after-write dependencies, the dynamic modulo scheduling faces new challenges, such as register insertion to solve recurrence dependences and to balance the pipelining paths. Our results demonstrate that the greedy run-time algorithm can reach a near-optimal ILP rate, better than an off-line compiler approach for a 16-issue VLIW processor. The proposed mechanism ensures software compatibility as it supports different source ISAs. As proof of concept of scaling, a change in the memory bandwidth has been evaluated. In this analysis it is demonstrated that when changing from one memory access per cycle to two memory accesses per cycle, the modulo scheduling algorithm is able to exploit this increase in memory bandwidth and enhance performance accordingly. Additionally, to measure area and performance, the proposed CGRA was prototyped on an FPGA. The area comparisons show that a crossbar CGRA (with 16 processing elements and including an 4-issue VLIW host processor) is only 1.11 × bigger than a standalone 8-issue VLIW softcore processor.     

On Detecting Spectrum Opportunities for Cognitive Vehicular Networks in the TV White Space

We overview the challenges related to spectrum awareness in the vehicular environment, with emphasis on awareness in the TV licensed band. In the vehicular environment the cognitive radio can help to: 1) satisfy capacity demand for Intelligent Transportation Systems (ITS) applications; and 2) offload time insensitive applications from the ITS dedicated spectrum. However, using simple propagation models we show that neither sensing, nor geolocation database lookup alone can provide sufficient incumbent protection. Collaboration among the sensors to take advantage of spatial diversity is difficult due to the rapidly changing network topology. Nevertheless, mobility provides the opportunity to use time diversity at each sensor. We also discuss the influence of sensing subsystem design on the vehicular cognitive network medium access (MAC) sublayer. Whenever appropriate, we evaluate applicability of the requirements imposed by the Federal Communications Commission (FCC) and the IEEE 802.22 standard to the cognitive vehicular networks.     

Influence of pre-electrophoresis on protein separations in polyacrylamide gels

Polyacrylamide gel electrophoresis (PAGE) is a widely used technique in protein separations. In this study, the effects of pre-electrophoresis (i.e., exposing polyacrylamide gels to an electrical field prior to loading samples) on the separation of a mixture of 10 standard proteins was investigated. Three different gel concentrations (based on amounts of acrylamide and bis-acrylamide, always at a 37.5:1 ratio) relative to the volume of the gel solution were tested: 6%, 9%, and 12%. For each concentration, multiple slab gels were subjected to pre-electrophoresis prior to separation of proteins, while multiple other (i.e., companion) slab gels were used but without applying the pre-electrophoresis technique. Separation results were investigated, showing that the application of the pre-electrophoresis technique had a significant effect on separations particularly for 6% and 9% gels.     

Exploring differential trends in severe and fatal child pedestrian injury in New South Wales, Australia (1997–2006)

The study explores trends in severe and fatal child pedestrian injuries in New South Wales (NSW), over the 10-year period 1997–2006, in comparison to adults and for various subgroups. Data on pedestrian injury (reported as fatalities or hospitalisations) were obtained from the Traffic Accident Database System (TADS; Roads and Traffic Authority of New South Wales) which captures road traffic events reported to police, and from the NSW Admitted Patients Data Collection (APDC) which captures all hospital inpatient separations. Annual percentage changes in injury counts and rates were compared using Poisson regression. A substantial drop in the pedestrian injury rate was observed; however, the rate of decline was steeper for children (aged less than 15 years) than for adults. The drop in child pedestrian injury was manifest in both the police report data and the hospital admission data. The annual percentage decrease was significantly greater for boys than for girls, and the three major urban centres compared with elsewhere in the state. No differences were detected in the annual rate decrease between school days and non-school days (a proxy for safe school zones), or between different road types (a proxy for restricted speed limits). Past research suggests that injury rate reductions are not solely due to decreased exposure. There remains, however, limited data on the extent of pedestrian mobility. Differences in relative reduction in pedestrian injury rates suggest a differential benefit arising from road safety initiatives.     

Minimum thickness of elliptical masonry arches

In this paper, we compute the minimum thickness and the location of the imminent intrados hinge of symmetric elliptical masonry arches when subjected to their weight. While this problem (Couplet’s problem) was solved rigorously for semicircular arches more than a century ago, no results have been available for elliptical arches. Motivated from the recent growing interest in identifying the limit equilibrium states of historic structures, this paper first computes two neighboring physically admissible thrust-lines which can just be located in elliptical arches by adopting either a polar or a cartesian coordinate system. These two distinguishable, physically admissible thrust-lines are neighboring thrust-lines to Hooke’s catenary which is not a physically admissible thrust-line as has been shown recently. Accordingly, the paper shows that the answer for the minimum thickness of symmetric elliptical masonry arches is not unique and that it depends on the coordinate system adopted and the associated stereotomy exercised. This result is confirmed by developing a variational formulation after selecting the appropriate directions of the rupture that initiates at the intrados hinge. The paper concludes that Hooke’s limiting catenary, although not a physically admissible thrust-line, offers a conservative value for the minimum thickness in most practical configurations.