A new image thresholding method based on Gaussian mixture model

2008-2009 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

Modelling coupled water and heat transport in a soil–mulch–plant–atmosphere continuum (SMPAC) system

Author name used in this publication: K. W. Chau2006-2007 > Academic research: refereed > Publication in refereed journalAccepted ManuscriptPublishe

A hybrid HMM/ANN based approach for online signature verification

2007-2008 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

Statistical models for time sequences data mining

In this paper, we present an adaptive modelling technique for studying past behaviors of objects and predicting the near future events. Our approach is to define a sliding window (of different window sizes) over a time sequence and build autoregression models from subsequences in different windows. The models are representations of past behaviors of the sequence objects. We can use the AR coefficients as features to index subsequences to facilitate the query of subsequences with similar behaviors. We can use a clustering algorithm to group time sequences on their similarity in the feature space. We can also use the AR models for prediction within different windows. Our experiments show that the adaptive model can give better prediction than non-adaptive models.published_or_final_versio

Effect of annealing on the performance of CrO3/ZnO light emitting diodes

Heterojunction CrO3/ZnO light emitting diodes have been fabricated. Their performance was investigated for different annealing temperature for ZnO nanorods. Annealing in oxygen atmosphere had significant influence on carrier concentration in the nanorods, as well as on the emission spectra of the nanorods. Surprisingly, annealing conditions, which yield the lowest band edge-to-defect emission ratio in the photoluminescence spectra, result in the highest band edge-to-defect emission ratio in the electroluminescence spectra. The influence of the native defects on ZnO light emitting diode performance is discussed. © 2009 American Institute of Physics.published_or_final_versio

DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy

Objectives: Treatment and outcomes of acute stroke have been revolutionised by mechanical thrombectomy. Deep learning has shown great promise in diagnostics but applications in video and interventional radiology lag behind. We aimed to develop a model that takes as input digital subtraction angiography (DSA) videos and classifies the video according to (1) the presence of large vessel occlusion (LVO), (2) the location of the occlusion, and (3) the efficacy of reperfusion. / Methods: All patients who underwent DSA for anterior circulation acute ischaemic stroke between 2012 and 2019 were included. Consecutive normal studies were included to balance classes. An external validation (EV) dataset was collected from another institution. The trained model was also used on DSA videos post mechanical thrombectomy to assess thrombectomy efficacy. / Results: In total, 1024 videos comprising 287 patients were included (44 for EV). Occlusion identification was achieved with 100% sensitivity and 91.67% specificity (EV 91.30% and 81.82%). Accuracy of location classification was 71% for ICA, 84% for M1, and 78% for M2 occlusions (EV 73, 25, and 50%). For post-thrombectomy DSA (n = 194), the model identified successful reperfusion with 100%, 88%, and 35% for ICA, M1, and M2 occlusion (EV 89, 88, and 60%). The model could also perform classification of post-intervention videos as mTICI < 3 with an AUC of 0.71. / Conclusions: Our model can successfully identify normal DSA studies from those with LVO and classify thrombectomy outcome and solve a clinical radiology problem with two temporal elements (dynamic video and pre and post intervention). / Key Points: • DEEP MOVEMENT represents a novel application of a model applied to acute stroke imaging to handle two types of temporal complexity, dynamic video and pre and post intervention. • The model takes as an input digital subtraction angiograms of the anterior cerebral circulation and classifies according to (1) the presence or absence of large vessel occlusion, (2) the location of the occlusion, and (3) the efficacy of thrombectomy. • Potential clinical utility lies in providing decision support via rapid interpretation (pre thrombectomy) and automated objective gradation of thrombectomy outcomes (post thrombectomy)

Targeted delivery of C/EBPα -saRNA by pancreatic ductal adenocarcinoma-specific RNA aptamers inhibits tumor growth in vivo

The 5-year survival rate for pancreatic ductal adenocarcinoma (PDAC) remains dismal despite current chemotherapeutic agents and inhibitors of molecular targets. As the incidence of PDAC constantly increases, more effective multidrug approaches must be made. Here, we report a novel method of delivering antitumorigenic therapy in PDAC by upregulating the transcriptional factor CCAAT/enhancer-binding protein-α (C/EBPα), recognized for its antiproliferative effects. Small activating RNA (saRNA) duplexes designed to increase C/EBPα expression were linked onto PDAC-specific 2′-Fluropyrimidine RNA aptamers (2′F-RNA) - P19 and P1 for construction of a cell type–specific delivery vehicle. Both P19- and P1-C/EBPα-saRNA conjugates increased expression of C/EBPα and significantly suppressed cell proliferation. Tail vein injection of the saRNA/aptamer conjugates in PANC-1 and in gemcitabine-resistant AsPC-1 mouse-xenografts led to reduced tumor size with no observed toxicity. To exploit the specificity of the P19/P1 aptamers for PDAC cells, we also assessed if conjugation with Cy3 would allow it to be used as a diagnostic tool on archival human pancreatic duodenectomy tissue sections. Scoring pattern from 72 patients suggested a positive correlation between high fluorescent signal in the high mortality patient groups. We propose a novel aptamer-based strategy for delivery of targeted molecular therapy in advanced PDAC where current modalities fail

Anticancer Gene Transfer for Cancer Gene Therapy

Gene therapy vectors are among the treatments currently used to treat malignant tumors. Gene therapy vectors use a specific therapeutic transgene that causes death in cancer cells. In early attempts at gene therapy, therapeutic transgenes were driven by non-specific vectors which induced toxicity to normal cells in addition to the cancer cells. Recently, novel cancer specific viral vectors have been developed that target cancer cells leaving normal cells unharmed. Here we review such cancer specific gene therapy systems currently used in the treatment of cancer and discuss the major challenges and future directions in this field

Spectroscopic investigation of quantum confinement effects in ion implanted silicon-on-sapphire films

Crystalline Silicon-on-Sapphire (SOS) films were implanted with boron (B$^+$) and phosphorous (P$^+$) ions. Different samples, prepared by varying the ion dose in the range $10^{14}$ to 5 x $10^{15}$ and ion energy in the range 150-350 keV, were investigated by the Raman spectroscopy, photoluminescence (PL) spectroscopy and glancing angle x-ray diffraction (GAXRD). The Raman results from dose dependent B$^+$ implanted samples show red-shifted and asymmetrically broadened Raman line-shape for B$^+$ dose greater than $10^{14}$ ions cm$^{-2}$. The asymmetry and red shift in the Raman line-shape is explained in terms of quantum confinement of phonons in silicon nanostructures formed as a result of ion implantation. PL spectra shows size dependent visible luminescence at $\sim$ 1.9 eV at room temperature, which confirms the presence of silicon nanostructures. Raman studies on P$^+$ implanted samples were also done as a function of ion energy. The Raman results show an amorphous top SOS surface for sample implanted with 150 keV P$^+$ ions of dose 5 x $10^{15}$ ions cm$^{-2}$. The nanostructures are formed when the P$^+$ energy is increased to 350 keV by keeping the ion dose fixed. The GAXRD results show consistency with the Raman results.Comment: 9 Pages, 6 Figures and 1 Table, \LaTex format To appear in SILICON(SPRINGER