We investigated the temporal coherence properties of organic light-emitting devices (OLEDs) by characterizing their coherence lengths. The interferometry based on the Newton’s rings apparatus was ...adopted to characterize the coherence lengths of various OLEDs, including non-doped/doped OLEDs and non-cavity bottom-emitting/cavity top-emitting OLEDs. The types of OLEDs investigated exhibit coherence lengths of 3–10
μm, depending on the device structures/emitters and spectral bandwidths of the OLED emission. OLEDs using emitting molecules with more limited number of allowed vibronic transitions give narrower-band and more coherent emission. Introducing the microcavity into the device structure to induce resonance also narrows the emission spectra and meanwhile increases the coherence length. Such information may be useful for modeling, design, and optimization of optical properties of OLEDs.
New super‐multi‐domain polymer sustained alignment (PSA) liquid crystal displays are developed With this new pixel architecture, premium picture quality with very little oblique gamma distortion and ...color shift (Δ u‘v’ < 0.02) like in‐plane switching (IPS) mode, is obtained. Moreover, it can also realize low‐crosstalk patterned retarder 3D displays without sacrificing the 2D‐mode luminance.
The conventional analog dual‐data type pixel has the same voltage relation for RGB sub‐pixels, which induces yellowish color shift. Therefore, a new approach to create individual RGB sub‐pixel ...voltage relations was proposed. By the optimized individual RGB sub‐pixel design, we improve color‐washout without suffering yellowish color‐shift effect.
New super‐multi‐domain polymer sustained alignment (PSA) liquid crystal displays are developed. Compared to the conventional approach, it has the merits of simpler structure, lower cost, and better ...transmittance. Moreover, premium picture quality with very little oblique gamma distortion and color shift like in‐plane switching (IPS) mode is obtained.
Purpose
Differential counting of blood cells is the basis of diagnostic hematology. In many circumstances, identification of cells in bone marrow smears is the golden standard for diagnosis. ...Presently, methods for automatic differential counting of peripheral blood are readily available commercially. However, morphological assessment and differential counting of bone marrow smears are still performed manually. This procedure is tedious, time-consuming and laden with high inter-operator variation. In recent years, deep neural networks have proven useful in many medical image recognition tasks, such as diagnosis of diabetic retinopathy, and detection of cancer metastasis in lymph nodes. However, there has been no published work on using deep neural networks for complete differential counting of entire bone marrow smear. In this work, we present the results of using deep convolutional neural network for automatic differential counting of bone marrow nucleated cells.
Materials & Methods
The bone marrow smears from patients with either benign or malignant disorders in National Taiwan University Hospital were recruited in this study. The bone marrow smears are stained with Liu's stain, a modified Romanowsky stain. Digital images of the bone marrow smears were taken using 1000x oil immersion lens and 20MP color CCD camera on a single microscope with standard illumination and white-balance settings. The contour of each nucleated cell was artificially defined. These cells were then divided into a training/validation set and a test set. Each cell was then classified into 1 of the 11 categories (blast, promyelocyte, neutrophilic myelocyte, neutrophilic metamyelocyte, neutrophils, eosinophils and precursors, basophil, monocyte and precursors, lymphocyte, erythroid lineage cells, and invalid cell).
In training/validation set, the classification of each cell was annotated once by experienced medical technician or hematologist. The annotated dataset was used to train a Path-Aggregation Network for instance segmentation task. In test set, cell classification was annotated by three medical technicians or hematologists; only over 2/3 consensus was regarded as valid.
After the neural network model was fully trained, the ability of the model to classify and detect bone marrow nucleated cells was evaluated in terms of precision, recall and accuracy.
During the model training, we used group normalization and stochastic gradient descent optimizer for training. Random noise, Gaussian blur, rotation, contrast and color shift were also used as means for data augmentation.
Results
The digital images of 150 bone marrow aspirate smears were taken for this study. They included 61 for acute leukemia, 39 for lymphoma, 2 for myelodysplastic syndrome (MDS), 2 for myeloproliferative neoplasm (MPN), 10 for MDS/MPN, 12 for multiple myeloma, 4 for hemolytic anemia, 9 for aplastic anemia, 8 for infectious etiology and 3 for solid cancers.
The final data contained 5927 images and 187730 nucleated bone marrow cells, which were divided into 2 sets: 5630 images containing 170966 cells as the training/validation set, and 297 images containing 16764 cells as the test set. Among the 16764 cells annotated in test set, 15676 cells (93.6 %) reached over 2/3 consensus. The trained neural network achieved 0.832 recall and 0.736 precision for cell detection task, 0.79 mean intersection over union (IOU) for cell segmentation task, mean average precision of 0.659 and accuracy of 0.801 for cell classification. For individual cell categories, the model performs the best with “erythroid-lineage-cells” (0.971 recall, 0.935 precision) and the worst with “monocyte-and-precursors” (0.825 recall, 0.337 precision).
Conclusions
We have created the largest and the most comprehensive annotated bone marrow smear image dataset for deep neural network training. Compared with previous works, our approach is more practical for clinical application because it is able to take in an entire field of smear and generate differential counts without any other preprocessing steps. Current results are highly encouraging. With continued expansion of dataset, our model would be more precise and clinically useful.
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Yeh:aether AI: Other: CEO and co-founder. Yang:aether AI: Employment. Tien:Novartis: Honoraria; Daiichi Sankyo: Honoraria; Celgene: Research Funding; Roche: Honoraria; Johnson &Johnson: Honoraria; Alexion: Honoraria; BMS: Honoraria; Roche: Research Funding; Celgene: Honoraria; Pfizer: Honoraria; Abbvie: Honoraria. Hsu:aether AI: Employment.
A new PAM impulse driving method was introduced for active
matrix micro LED on Glass, which is getting a great attention as a
next‐generation display with various excellent characteristics in
optical ...performance, reliability, and high‐resolution possibility.
New 13.55" panel was prepared, and the result was analyzed by the
difference in driving concept from the conventional PWM driving
panel. In addition, the panel performance, image quality and color
characteristics were compared and analyzed accordingly.
In this paper, we report that by inserting a nanoparticle diffuser film by spincoating between the OLED and the glass substrate as the scattering structure. The external quantum efficiency and the ...cd/A efficiency of conventional bottom emitting OLEDs can be significantly improved 1.96×for quantum efficiency and 2.04× for cd/A efficiency. The fabrication of nanoparticle diffuser film is simple and attractive for OLED application and mass production.
Electrochemical deposition of Al-doped ZnO (AZO) on the ITO glass was investigated in baths containing various concentrations of aluminum nitrate. The electrochemical and chemical reactions can be ...deduced by means of investigating cathodic polarization curves and time/electroplating-current curves for further characterizing structures of ZnO and AZO, and establishing growth mechanism. High-quality AZO nanorods, depositing on ITO substrate that coated with ZnO seed-layer, were utilized the electrochemical method at-1.0 V (against a reference electrode of Ag/AgCl in 3.0M KCl) in the bath of 90 °C. After annealing at 350 °C, ZnO and AZO nanorods were analyzed by field-emission scanning electron microscope (FESEM) to explore the morphology of nanostructure. The SEM image displayed that the lower Al3+ concentrations (20 ~ 60 μM) in the bath, the average diameter of nanorods decreased; while the Al3+ concentrations excessed over 60 μM, the morphology of the AZO nanorods turned into partial-area nanosheets instead of the nanorods spread. The crystal structure of the AZO nanorods were identified by using grazing-incident X-ray diffraction (GIXRD). The patterns of the Al3+ ions in the range of 20 ~ 60 μM in the bath showed that the preferred orientations were along with the 002 direction which confirmed the result of AZO nanorods well aligned in c-axis orientation, and the characterized peak (002) slightly shifted to the right suggested that Al atoms had doped into the ZnO lattice. We also adopted the X-ray photoelectron spectroscopy to characterize the elemental and chemical compositions of the AZO nanorods. XPS spectrums confirmed that the Al atoms successfully doped. Finally, for identifying the optimal boundary condition of Al content in ZnO, the nanorods with various Al concentrations were utilized via dye-sensitized solar cells (DSSC) experiment with the standard solar Simulators (AM1.5G) and J-V Measurement. We found that the AZO nanorods as the photoanode contained 2.84 at.% Al (60 μM aluminum nitrate in the bath) which performed the highest fill-factor (0.53) and the maximum efficiency (0.41%).
By thinning the metal electrode, the SPP modes of OLEDs can be coupled to the outside surface of the device, where they can be recycled for external emission by simply capping the device with an ...appropriate absorbing/re‐emission medium. A modest efficiency enhancement has been observed. In addition, such an approach provides double‐emitting OLEDs with a wide‐range color tuning capability, which may be of use for some applications.
Minocycline is a second-generation tetracycline with multiple biological effects, including inhibition of microglial activation. Recently, microglial activation has been implicated in the development ...of nerve injury-induced neuropathic pain. In this study, the authors examined the effects of continuous intrathecal minocycline on the development of neuropathic pain and microglial activation induced by L5/6 spinal-nerve ligation in rats.
Under isoflurane anesthesia, male Sprague-Dawley rats (200-250 g) received right L5/6 spinal-nerve ligation and intrathecal catheters connected to an infusion pump. Intrathecal saline or minocycline (2 and 6 microg/h) was given continuously after surgery for 7 days (n = 8 per group). The rat right hind paw withdrawal threshold to von Frey filament stimuli and withdrawal latency to radiant heat were determined before surgery and on days 1 to 7 after surgery. Spinal microglial activation was evaluated with OX-42 immunoreactivity on day 7 after surgery.
Spinal-nerve ligation induced mechanical allodynia and thermal hyperalgesia on the affected hind paw of saline-treated rats. Intrathecal minocycline (2 and 6 microg/h) prevented the development of mechanical allodynia and thermal hyperalgesia induced by nerve ligation. It also inhibited nerve ligation-induced microglial activation, as evidenced by decreased OX-42 staining. No obvious histopathologic change was noted after intrathecal minocycline (6 microg/h) infusion.
In this study, the authors demonstrate the preventive effect of continuous intrathecal minocycline on the development of nociceptive behaviors induced by L5/6 spinal-nerve ligation in rats. Further studies are required to examine if continuous intrathecal minocycline could be used safely in the clinical setting.
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