Single Frame Image super Resolution using Learned Directionlets

In this paper, a new directionally adaptive, learning based, single image super resolution method using multiple direction wavelet transform, called Directionlets is presented. This method uses directionlets to effectively capture directional features and to extract edge information along different directions of a set of available high resolution images .This information is used as the training set for super resolving a low resolution input image and the Directionlet coefficients at finer scales of its high-resolution image are learned locally from this training set and the inverse Directionlet transform recovers the super-resolved high resolution image. The simulation results showed that the proposed approach outperforms standard interpolation techniques like Cubic spline interpolation as well as standard Wavelet-based learning, both visually and in terms of the mean squared error (mse) values. This method gives good result with aliased images also.Comment: 14 pages,6 figure

Excitonic Transitions and Off-resonant Optical Limiting in CdS Quantum Dots Stabilized in a Synthetic Glue Matrix

Stable films containing CdS quantum dots of mean size 3.4 nm embedded in a solid host matrix are prepared using a room temperature chemical route of synthesis. CdS/synthetic glue nanocomposites are characterized using high resolution transmission electron microscopy, infrared spectroscopy, differential scanning calorimetry and thermogravimetric analysis. Significant blue shift from the bulk absorption edge is observed in optical absorption as well as photoacoustic spectra indicating strong quantum confinement. The exciton transitions are better resolved in photoacoustic spectroscopy compared to optical absorption spectroscopy. We assign the first four bands observed in photoacoustic spectroscopy to 1se–1sh, 1pe–1ph, 1de–1dhand 2pe–2phtransitions using a non interacting particle model. Nonlinear absorption studies are done using z-scan technique with nanosecond pulses in the off resonant regime. The origin of optical limiting is predominantly two photon absorption mechanism

Phase I Evaluation of STA-1474, a Prodrug of the Novel HSP90 Inhibitor Ganetespib, in Dogs with Spontaneous Cancer

The novel water soluble compound STA-1474 is metabolized to ganetespib (formerly STA-9090), a potent HSP90 inhibitor previously shown to kill canine tumor cell lines in vitro and inhibit tumor growth in the setting of murine xenografts. The purpose of the following study was to extend these observations and investigate the safety and efficacy of STA-1474 in dogs with spontaneous tumors.This was a Phase 1 trial in which dogs with spontaneous tumors received STA-1474 under one of three different dosing schemes. Pharmacokinetics, toxicities, biomarker changes, and tumor responses were assessed. Twenty-five dogs with a variety of cancers were enrolled. Toxicities were primarily gastrointestinal in nature consisting of diarrhea, vomiting, inappetence and lethargy. Upregulation of HSP70 protein expression was noted in both tumor specimens and PBMCs within 7 hours following drug administration. Measurable objective responses were observed in dogs with malignant mast cell disease (n = 3), osteosarcoma (n = 1), melanoma (n = 1) and thyroid carcinoma (n = 1), for a response rate of 24% (6/25). Stable disease (>10 weeks) was seen in 3 dogs, for a resultant overall biological activity of 36% (9/25).This study provides evidence that STA-1474 exhibits biologic activity in a relevant large animal model of cancer. Given the similarities of canine and human cancers with respect to tumor biology and HSP90 activation, it is likely that STA-1474 and ganetespib will demonstrate comparable anti-cancer activity in human patients

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994-2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm(-2)) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types.An international team of researchers finds high potential for improving climate projections by a more comprehensive treatment of largely ignored Arctic vegetation types, underscoring the importance of Arctic energy exchange measuring stations.Peer reviewe

Vegetation type is an important predictor of the arctic summer land surface energy budget

Despite the importance of high-latitude surface energy budgets (SEBs) for land-climate interactions in the rapidly changing Arctic, uncertainties in their prediction persist. Here, we harmonize SEB observations across a network of vegetated and glaciated sites at circumpolar scale (1994–2021). Our variance-partitioning analysis identifies vegetation type as an important predictor for SEB-components during Arctic summer (June-August), compared to other SEB-drivers including climate, latitude and permafrost characteristics. Differences among vegetation types can be of similar magnitude as between vegetation and glacier surfaces and are especially high for summer sensible and latent heat fluxes. The timing of SEB-flux summer-regimes (when daily mean values exceed 0 Wm−2) relative to snow-free and -onset dates varies substantially depending on vegetation type, implying vegetation controls on snow-cover and SEB-flux seasonality. Our results indicate complex shifts in surface energy fluxes with land-cover transitions and a lengthening summer season, and highlight the potential for improving future Earth system models via a refined representation of Arctic vegetation types

Development of Directionally Adaptive Techniques for Single Image Super-Resolution

Super Resolution problem is an inverse problem and refers to the process of producing a High resolution (HR) image, making use of one or more Low Resolution (LR) observations. It includes up sampling the image, thereby, increasing the maximum spatial frequency and removing degradations that arise during the image capture namely aliasing and blurring. The work presented in this thesis is based on learning based single image super-resolution. In learning based super-resolution algorithms, a training set or database of available HR images are used to construct the HR image of an image captured using a LR camera. In the training set, images are stored as patches or coefficients of feature representations like wavelet transform, DCT, etc. Single frame image super-resolution can be used in applications where database of HR images are available. The advantage of this method is that by skilfully creating a database of suitable training images, one can improve the quality of the super-resolved image. A new super resolution method based on wavelet transform is developed and it is better than conventional wavelet transform based methods and standard interpolation methods. Super-resolution techniques based on skewed anisotropic transform called directionlet transform are developed to convert a low resolution image which is of small size into a high resolution image of large size. Super-resolution algorithm not only increases the size, but also reduces the degradations occurred during the process of capturing image. This method outperforms the standard interpolation methods and the wavelet methods, both visually and in terms of SNR values. Artifacts like aliasing and ringing effects are also eliminated in this method. The super-resolution methods are implemented using, both critically sampled and over sampled directionlets. The conventional directionlet transform is computationally complex. Hence lifting scheme is used for implementation of directionlets. The new single image super-resolution method based on lifting scheme reduces computational complexity and thereby reduces computation time. The quality of the super resolved image depends on the type of wavelet basis used. A study is conducted to find the effect of different wavelets on the single image super-resolution method. Finally this new method implemented on grey images is extended to colour images and noisy imagesCochin University of Science and TechnologyDepartment of Electronics Cochin University of Science and Technolog

Stroke Network of Wisconsin (SNOW) Scale Predicts Large Vessel Occlusion Stroke in the Prehospital Setting

Purpose: In previous trials, the Stroke Network of Wisconsin (SNOW) scale accurately predicted large vessel occlusion (LVO) stroke in the hospital setting. This study evaluated SNOW scale performance in the prehospital setting and its ability to predict LVO or distal medium vessel occlusion (DMVO) in patients suspected of having acute ischemic stroke (AIS), a scenario in which transport time to an endovascular treatment-capable facility (ECSC) is critical. Methods: All potential AIS patients with last-known-well time of ≤ 24 hours were assessed by Milwaukee County Emergency Medical Services for LVO using SNOW. Patients with a positive SNOW score were transferred to the nearest ECSC. One such facility, Aurora St. Luke’s Medical Center (ASLMC), was the source of all patient data analyzed in this study. LVO was defined as occlusion of the intracranial carotid artery, middle cerebral artery (M1) segment, or basilar artery. Results: From March 2018 to February 2019, 345 AIS-suspected patients were transported to ASLMC; 19 patients were excluded because no vascular imaging was performed. Of 326 patients, 32 had confirmed LVO and 21 DMVO. For identifying LVO, SNOW scale sensitivity was 0.88, specificity 0.40, positive predictive value (PPV) 0.14, negative predictive value (NPV) 0.97, and area under the curve (AUC) 0.64. Ability to predict DMVO was similar. Overall, the SNOW scale showed sensitivity of 0.83, specificity of 0.39, PPV of 0.10, NPV of 0.97, and AUC of 0.60 in identifying candidates for endovascular thrombectomy. Conclusions: In a prehospital setting, the SNOW scale has high sensitivity in identifying candidates for endovascular thrombectomy and proved highly reliable in ruling out stroke due to LVO

Nonlinear and magneto-optical transmission studies on magnetic nanofluids of non-interacting metallic nickel nanoparticles

Oxide free stable metallic nanofluids have the potential for various applications such as in thermal management and inkjet printing apart from being a candidate system for fundamental studies. A stable suspension of nickel nanoparticles of ∼5 nm size has been realized by a modified two-step synthesis route. Structural characterization by x-ray diffraction and transmission electron microscopy shows that the nanoparticles are metallic and are phase pure. The nanoparticles exhibited superparamagnetic properties. The magneto-optical transmission properties of the nickel nanofluid (Ni-F) were investigated by linear optical dichroism measurements. The magnetic field dependent light transmission studies exhibited a polarization dependent optical absorption, known as optical dichroism, indicating that the nanoparticles suspended in the fluid are non-interacting and superparamagnetic in nature. The nonlinear optical limiting properties of Ni-F under high input optical fluence were then analyzed by an open aperture z-scan technique. The Ni-F exhibits a saturable absorption at moderate laser intensities while effective two-photon absorption is evident at higher intensities. The Ni-F appears to be a unique material for various optical devices such as field modulated gratings and optical switches which can be controlled by an external magnetic fieldCochin University of Science and TechnologyNanotechnology 22 (2011) 375702 (7pp

Writing low-loss waveguides in borosilicate (BK7) glass with a low-repetition-rate femtosecond laser

Borosilicate glass (BK7) is a widely-used material in integrated optics devices and in the optical communications industry. We report on laser-written waveguiding in BK7 glass using a low-repetition-rate (1 kHz) laser producing 40 fs pulses of 800 nm light. A 500 μm slit is used to write structures 100 μ m below the glass surface. These waveguides show strong guidance at 635 nm, with an index contrast of 3 × 10<SUP>-4</SUP> and a propagation loss of ~ 0.5 dB/cm. We measured the change in refractive index for a range of writing conditions as quantified in terms of energy dose; there is an energy dose window (&gt; 0.6 μJ μm<SUP>-3</SUP> and &lt; 1.5 μJ μm<SUP>-3</SUP>) within which the written structures show guidance