CPM-SC-IFDMA--A Power Efficient Transmission Scheme for Uplink LTE

In this thesis we have proposed a power efficient transmission scheme, CPM-SC-IFDMA, for uplink LTE. In uplink LTE, efficiency of the transmitter power amplier is a major concern, as the transmitter is placed in the mobile device which has limited power supply. The proposed scheme, CPM-SC-IFDMA, combines the key advantages of CPM (continuous phase modulation) with SC-IFDMA (single carrier frequency division multiple access with interleaved subcarrier mapping) in order to increase the power amplier efficiency of the transmitter. In this work, we have analyzed the bit error rate (BER) performance of the proposed scheme in LTE specied channels. The BER performance of two CPM-SC-IFDMA scheme are compared with that of a LTE specied transmission scheme, QPSK-LFDMA (QPSK modulated SC-FDMA with localized subcarrier mapping), combined with convolutional coding (CC-QPSK-LFDMA). We first show that CPM-SC-IFDMA has a much higher power efficiency than CC-QPSK-LFDMA by simulating the PAPR (peak-to-average-power-ratio) plots. Then, using the data from the PAPR plots and the conventional BER plots (BER as a function of signal-to-noise-ratio), we show that, when the net BER, obtained by compensating for the power efficiency loss, is considered, CPM-SC-IFDMA has a superior performance relative to CC-QPSK-LFDMA by up to 3.8 dB, in the LTE specified channels

The Utility of AISA Eagle Hyperspectral Data and Random Forest Classifier for Flower Mapping

Peer reviewe

Histopathological evaluation and molecular detection of natural iridovirus infection in cultured grouper fish in Malaysia

Iridovirus is the causative agent of grouper iridovirus infection (GIV), which causes severe epizootics resulting in large-scale mortalities and huge economic losses in cultured and marine fishes worldwide. The current study evaluated the gross and histopathological lesions, and molecular detection of GIV in naturally infected grouper farms in Malaysia. A total of 150 moribund fish showing different clinical signs, presented to the Aquatic unit were used for this study. The fish were necropsied and visceral organs (spleen, kidney, heart, liver, intestine, brain, eyes, gills, and some parts of skin with ulcer) were collected and fixed in 10 % buffered formalin for histopathological processing and evaluation. Molecular detection of the virus was done by polymerase chain reaction (PCR). Grossly, the groupers had ulceration on the operculum and close to the caudal fin with hemorrhages on the margin of the caudal fin. In some fish, there was necrosis of the caudal fin, sloughing of the epidermis, dermal ulceration and popeyes Histological sections showed large basophilic cytoplasmic inclusions and vacuolations in the cytoplasm of hepatocytes. Basophilic or eosinophilic enlarged cells with the presence of mononuclear cellular infiltrations were seen in the kidney, liver, eye and gills, which is the distinctive feature of this disease. PCR detection showed positive amplification from 27 groupers. Based on the gross, histopathological and molecular detection GIV infection was established

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies