A. K. M. Azad

Orientation independent compact chipless RFID tag

A design concept of a compact printable orientation independent chipless radio frequency identification tag is presented with near-field and far-field reading techniques. The tag consists of a circular patch loaded with multiple slot ring resonators and it has the advantage to be read from any orientation with the reader due to its symmetric structure. This tag does not have a ground plane and has higher data density and lower cost compared to the most other existing printable chipless tags. Proximity and slot reading techniques are described in details for different applications. This single-sided, compact and orientation independent tag has a great potential to be used in millions both for identification and authentication.

COMPACT PRINTABLE ORIENTATION INDEPENDENT CHIPLESS RFID TAG

A novel design concept of a compact printable orientation independent chipless RFID tag is presented. The tag consists of a circular patch loaded with multiple slot ring resonators. This symmetric frequency domain based tag has the advantage to be read from any orientation with the reader antennas. The tag can be read in close proximity by chipless RFID tag reader with waveguide(s) and also can be read in both near fleld and far-fleld of the RFID tag reader with antennas. This tag does not have a ground plane and has higher data density compared to the existing printable chipless tags. The usability of this single sided tag in close proximity is verifled by waveguide measurements for both proximity applications such as on ID access cards, item level tagging etc. and slot reading application such as on banknotes, credit cards etc.

Dual-band modified complementary split ring resonator (MCSRR) based multi-resonator circuit for chipless RFID tag

As chipless RFID technology has potential to offer ultra-low cost and fully printable tags, recently, there has been considerable interest on implementing a compact chipless RFID tag with adequate data capacity. In this paper, a compact multiresonator circuit for spectral signature based chipless RFID tag is proposed. The multiresonator circuit utilizes a number of modified complementary split ring resonators (MCSRR) placed along the transmission line as data bit encoding element. A novel resonance detuning mechanism proposed here allows the use of an MCSRR to independently encode two data bits instead of one bit. Besides, symmetricity of the MCSRR with respect to the feed line causes the disappearance of the second harmonic and hence the total realizable bandwidth for data bit encoding is also enhanced. The multiresonator circuit is based on coplanar waveguide (CPW) configuration and can be realized on flexible substrate with single sided metallization. Once incorporated with cross polarized UWB tag antennas, the proposed multiresonator circuit can be used for a compact fully printable chipless RFID tag that may replace barcode in the long run.

Prediction of signaling cross-talks contributing to acquired drug resistance in breast cancer cells by Bayesian statistical modeling

BackgroundInitial success of inhibitors targeting oncogenes is often followed by tumor relapse due to acquired resistance. In addition to mutations in targeted oncogenes, signaling cross-talks among pathways play a vital role in such drug inefficacy. These include activation of compensatory pathways and altered activities of key effectors in other cell survival and growth-associated pathways.ResultsWe propose a computational framework using Bayesian modeling to systematically characterize potential cross-talks among breast cancer signaling pathways. We employed a fully Bayesian approach known as the p1-model to infer posterior probabilities of gene-pairs in networks derived from the gene expression datasets of ErbB2-positive breast cancer cell-lines (parental, lapatinib-sensitive cell-line SKBR3 and the lapatinib-resistant cell-line SKBR3-R, derived from SKBR3). Using this computational framework, we searched for cross-talks between EGFR/ErbB and other signaling pathways from Reactome, KEGG and WikiPathway databases that contribute to lapatinib resistance. We identified 104, 188 and 299 gene-pairs as putative drug-resistant cross-talks, respectively, each comprised of a gene in the EGFR/ErbB signaling pathway and a gene from another signaling pathway, that appear to be interacting in resistant cells but not in parental cells. In 168 of these (distinct) gene-pairs, both of the interacting partners are up-regulated in resistant conditions relative to parental conditions. These gene-pairs are prime candidates for novel cross-talks contributing to lapatinib resistance. They associate EGFR/ErbB signaling with six other signaling pathways: Notch, Wnt, GPCR, hedgehog, insulin receptor/IGF1R and TGF- β receptor signaling. We conducted a literature survey to validate these cross-talks, and found evidence supporting a role for many of them in contributing to drug resistance. We also analyzed an independent study of lapatinib resistance in the BT474 breast cancer cell-line and found the same signaling pathways making cross-talks with the EGFR/ErbB signaling pathway as in the primary dataset.ConclusionsOur results indicate that the activation of compensatory pathways can potentially cause up-regulation of EGFR/ErbB pathway genes (counteracting the inhibiting effect of lapatinib) via signaling cross-talk. Thus, the up-regulated members of these compensatory pathways along with the members of the EGFR/ErbB signaling pathway are interesting as potential targets for designing novel anti-cancer therapeutics.

Aperture coupled UWB microstrip patch antenna array for mm-Wave chipless RFID tag reader

A 4×4 aperture coupled UWB microstrip patch antenna array for mm-wave chipless RFID tag reader is presented. The antenna is operating over the 21-27 GHz frequency band with 20 dBi gain. A systematic approach has been followed to design the antenna array, where, firstly a single antenna element is optimized, then a feed network using multistage power divider is designed and finally, the 4×4 antenna array is developed and optimized. Simulation and measurement results of the antenna are described in details with gain, radiation pattern and impedance behavior. Finally, the assembled antenna is used for measuring mm-wave chipless tag to validate its functional accuracy. The antenna can be used in commercial mm-wave chipless RFID tag reader due to its lower profile, cost and higher gain.

Voting-based cancer module identification by combining topological and data-driven properties.

Recently, computational approaches integrating copy number aberrations (CNAs) and gene expression (GE) have been extensively studied to identify cancer-related genes and pathways. In this work, we integrate these two data sets with protein-protein interaction (PPI) information to find cancer-related functional modules. To integrate CNA and GE data, we first built a gene-gene relationship network from a set of seed genes by enumerating all types of pairwise correlations, e.g. GE-GE, CNA-GE, and CNA-CNA, over multiple patients. Next, we propose a voting-based cancer module identification algorithm by combining topological and data-driven properties (VToD algorithm) by using the gene-gene relationship network as a source of data-driven information, and the PPI data as topological information. We applied the VToD algorithm to 266 glioblastoma multiforme (GBM) and 96 ovarian carcinoma (OVC) samples that have both expression and copy number measurements, and identified 22 GBM modules and 23 OVC modules. Among 22 GBM modules, 15, 12, and 20 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Among 23 OVC modules, 19, 18, and 23 modules were significantly enriched with cancer-related KEGG, BioCarta pathways, and GO terms, respectively. Similarly, we also observed that 9 and 2 GBM modules and 15 and 18 OVC modules were enriched with cancer gene census (CGC) and specific cancer driver genes, respectively. Our proposed module-detection algorithm significantly outperformed other existing methods in terms of both functional and cancer gene set enrichments. Most of the cancer-related pathways from both cancer data sets found in our algorithm contained more than two types of gene-gene relationships, showing strong positive correlations between the number of different types of relationship and CGC enrichment -values (0.64 for GBM and 0.49 for OVC). This study suggests that identified modules containing both expression changes and CNAs can explain cancer-related activities with greater insights.

Prediction of plant promoters based on hexamers and random triplet pair analysis

BackgroundWith an increasing number of plant genome sequences, it has become important to develop a robust computational method for detecting plant promoters. Although a wide variety of programs are currently available, prediction accuracy of these still requires further improvement. The limitations of these methods can be addressed by selecting appropriate features for distinguishing promoters and non-promoters.MethodsIn this study, we proposed two feature selection approaches based on hexamer sequences: the Frequency Distribution Analyzed Feature Selection Algorithm (FDAFSA) and the Random Triplet Pair Feature Selecting Genetic Algorithm (RTPFSGA). In FDAFSA, adjacent triplet-pairs (hexamer sequences) were selected based on the difference in the frequency of hexamers between promoters and non-promoters. In RTPFSGA, random triplet-pairs (RTPs) were selected by exploiting a genetic algorithm that distinguishes frequencies of non-adjacent triplet pairs between promoters and non-promoters. Then, a support vector machine (SVM), a nonlinear machine-learning algorithm, was used to classify promoters and non-promoters by combining these two feature selection approaches. We referred to this novel algorithm as PromoBot.ResultsPromoter sequences were collected from the PlantProm database. Non-promoter sequences were collected from plant mRNA, rRNA, and tRNA of PlantGDB and plant miRNA of miRBase. Then, in order to validate the proposed algorithm, we applied a 5-fold cross validation test. Training data sets were used to select features based on FDAFSA and RTPFSGA, and these features were used to train the SVM. We achieved 89% sensitivity and 86% specificity.ConclusionsWe compared our PromoBot algorithm to five other algorithms. It was found that the sensitivity and specificity of PromoBot performed well (or even better) with the algorithms tested. These results show that the two proposed feature selection methods based on hexamer frequencies and random triplet-pair could be successfully incorporated into a supervised machine learning method in promoter classification problem. As such, we expect that PromoBot can be used to help identify new plant promoters. Source codes and analysis results of this work could be provided upon request.

Query Processing over Distributed Heterogeneous Sensor Networks in Future Internet: Scalable Architecture and Challenges

The wireless networked sensors embedded with everyday objects will become an integral part of Futrure Internet, where the interaction among people, computer and those objects will shift the current Internet to a new paradigm, namely the Internet of Things. The terabyte torrent of data generated by billions of sensors belonging to a large number of distributed heterogeneous sensor networks in Future Internet will only be valuable if they can be effectively used on purpose, which leads to the necessity of an Internet scale query processing framework. In this paper, firstly, we focus on the distinct challenges present in Internet scale query processing over distributed sensor networks. Then, we propose a flexible and scalable system architecture capable of handling the complex scenario that might arise from the integration of a large number of such networks in Future Internet. Finally, we discuss the overall query processing methodology over such system and present some directions on the possible solutions to a number of identified research challenges. The outcome of this paper would foster the sensor network research in Future Internet domain.

Bayesian model of signal rewiring reveals mechanisms of gene dysregulation in acquired drug resistance in breast cancer

Small molecule inhibitors, such as lapatinib, are effective against breast cancer in clinical trials, but tumor cells ultimately acquire resistance to the drug. Maintaining sensitization to drug action is essential for durable growth inhibition. Recently, adaptive reprogramming of signaling circuitry has been identified as a major cause of acquired resistance. We developed a computational framework using a Bayesian statistical approach to model signal rewiring in acquired resistance. We used the p1-model to infer potential aberrant gene-pairs with differential posterior probabilities of appearing in resistant-vs-parental networks. Results were obtained using matched gene expression profiles under resistant and parental conditions. Using two lapatinib-treated ErbB2-positive breast cancer cell-lines: SKBR3 and BT474, our method identified similar dysregulated signaling pathways including EGFR-related pathways as well as other receptor-related pathways, many of which were reported previously as compensatory pathways of EGFR-inhibition via signaling cross-talk. A manual literature survey provided strong evidence that aberrant signaling activities in dysregulated pathways are closely related to acquired resistance in EGFR tyrosine kinase inhibitors. Our approach predicted literature-supported dysregulated pathways complementary to both node-centric (SPIA, DAVID, and GATHER) and edge-centric (ESEA and PAGI) methods. Moreover, by proposing a novel pattern of aberrant signaling called V-structures, we observed that genes were dysregulated in resistant-vs-sensitive conditions when they were involved in the switch of dependencies from targeted to bypass signaling events. A literature survey of some important V-structures suggested they play a role in breast cancer metastasis and/or acquired resistance to EGFR-TKIs, where the mRNA changes of TGFBR2, LEF1 and TP53 in resistant-vs-sensitive conditions were related to the dependency switch from targeted to bypass signaling links. Our results suggest many signaling pathway structures are compromised in acquired resistance, and V-structures of aberrant signaling within/among those pathways may provide further insights into the bypass mechanism of targeted inhibition.

A novel reader architecture for chipless RFID tags

The design architecture of a reader for detecting dual polarized chipless RFID tags is presented. The proposed reader is based on ultra-wideband chirp signal interrogation for multi-resonator based chipless RFID tags. Here, linear chirp signal is generated to read the tag data in amplitude signatures for both polarizations. The advantage of this very low cost design using single voltage-controlled oscillator (VCO) is that, it does not require any calibration tag to decode the tag data, and can read the dual polarized tags and other tags which required measurement in both polarizations. Moreover, the former linearly polarized version of the chipless tags can also be measured using this reader.