Enhancing Pixel Charging Efficiency by Optimizing Thin-Film Transistor Dimensions in Gate Driver Circuits for Active-Matrix Liquid Crystal Displays.

Flat panel displays are electronic displays that are thin and lightweight, making them ideal for use in a wide range of applications, from televisions and computer monitors to mobile devices and digital signage. The Thin-Film Transistor (TFT) layer is responsible for controlling the amount of light that passes through each pixel and is located behind the liquid crystal layer, enabling precise image control and high-quality display. As one of the important parameters to evaluate the display performance, the faster response time provides more frames in a second, which benefits many high-end applications, such as applications for playing games and watching movies. To further improve the response time, the single-pixel charging efficiency is investigated in this paper by optimizing the TFT dimensions in gate driver circuits in active-matrix liquid crystal displays. The accurate circuit simulation model is developed to minimize the signal's fall time (Tf) by optimizing the TFT width-to-length ratio. Our results show that using a driving TFT width of 6790 µm and a reset TFT width of 640 µm resulted in a minimum Tf of 2.6572 µs, corresponding to a maximum pixel charging ratio of 90.61275%. These findings demonstrate the effectiveness of our optimization strategy in enhancing pixel charging efficiency and improving display performance.

Application of digital-intelligence technology in the processing of Chinese materia medica.

Processing of Chinese Materia Medica (PCMM) is the concentrated embodiment, which is the core of Chinese unique traditional pharmaceutical technology. The processing includes the preparation steps such as cleansing, cutting and stir-frying, to make certain impacts on the quality and efficacy of Chinese botanical drugs. The rapid development of new computer digital technologies, such as big data analysis, Internet of Things (IoT), blockchain and cloud computing artificial intelligence, has promoted the rapid development of traditional pharmaceutical manufacturing industry with digitalization and intellectualization. In this review, the application of digital intelligence technology in the PCMM was analyzed and discussed, which hopefully promoted the standardization of the process and secured the quality of botanical drugs decoction pieces. Through the intellectualization and the digitization of production, safety and effectiveness of clinical use of traditional Chinese medicine (TCM) decoction pieces were ensured. This review also provided a theoretical basis for further technical upgrading and high-quality development of TCM industry.

Aided diagnosis of thyroid nodules based on an all-optical diffraction neural network.

Background: Thyroid cancer is the most common malignancy in the endocrine system, with its early manifestation being the presence of thyroid nodules. With the advantages of convenience, noninvasiveness, and a lack of radiation, ultrasound is currently the first-line screening tool for the clinical diagnosis of thyroid nodules. The use of artificial intelligence to assist diagnosis is an emerging technology. This paper proposes the use optical neural networks for potential application in the auxiliary diagnosis of thyroid nodules. Methods: Ultrasound images obtained from January 2013 to December 2018 at the Institute and Hospital of Oncology, Tianjin Medical University, were included in a dataset. Patients who consecutively underwent thyroid ultrasound diagnosis and follow-up procedures were included. We developed an all-optical diffraction neural network to assist in the diagnosis of thyroid nodules. The network is composed of 5 diffraction layers and 1 detection plane. The input image is placed 10 mm away from the first diffraction layer. The input of the diffractive neural network is light at a wavelength of 632.8 nm, and the output of this network is determined by the amplitude and light intensity obtained from the detection region. Results: The all-optical neural network was used to assist in the diagnosis of thyroid nodules. In the classification task of benign and malignant thyroid nodules, the accuracy of classification on the test set was 97.79%, with an area under the curve value of 99.8%. In the task of detecting thyroid nodules, we first trained the model to determine whether any nodules were present and achieved an accuracy of 84.92% on the test set. Conclusions: Our study demonstrates the potential of all-optical neural networks in the field of medical image processing. The performance of the models based on optical neural networks is comparable to other widely used network models in the field of image classification.

Extending orbital angular momentum multiplexing to radially high orders for massive mode channels in fiber transmission.

Orbital angular momentum (OAM) beams with different angular indices l have the potential to greatly increase communication capacity. However, the finite aperture of optical systems limits the value of the angular index. In order to fully use the orthogonal mode channels supported in the fiber for high-capacity communications, we propose extending the radial indices p of OAM modes as an additional multiplexing dimension. In this paper, we introduce spatially discrete multiple phase planes to multiplex the angular and radial OAM modes simultaneously. Due to the orthogonal property of the central symmetric OAM modes, a two-dimensional (2D) input Gaussian beams array can be converted to coaxial OAM modes through Cartesian to log-polar coordinate transformation by inverse design. For a proof-of-concept demonstration, a 10-mode multiplexer for high-order radial OAM modes was designed using five phase planes. The fabricated multiplexer generated high-quality multiplexed OAM modes with a loss of less than 5.4 dB. The multiplexed OAM modes were coupled into a specially designed ring-core fiber by mode-field matching, achieving stable mode transmission in 2 km fiber. The approach provides a scalable technology to increase the number of transmission channels and could lead to the practical applications of OAM multiplexing in communication.

Pulmonary Nodule Detection and Classification Using All-Optical Deep Diffractive Neural Network.

A deep diffractive neural network (D2NN) is a fast optical computing structure that has been widely used in image classification, logical operations, and other fields. Computed tomography (CT) imaging is a reliable method for detecting and analyzing pulmonary nodules. In this paper, we propose using an all-optical D2NN for pulmonary nodule detection and classification based on CT imaging for lung cancer. The network was trained based on the LIDC-IDRI dataset, and the performance was evaluated on a test set. For pulmonary nodule detection, the existence of nodules scanned from CT images were estimated with two-class classification based on the network, achieving a recall rate of 91.08% from the test set. For pulmonary nodule classification, benign and malignant nodules were also classified with two-class classification with an accuracy of 76.77% and an area under the curve (AUC) value of 0.8292. Our numerical simulations show the possibility of using optical neural networks for fast medical image processing and aided diagnosis.

Deep-learning based image reconstruction for MRI-guided near-infrared spectral tomography.

Non-invasive near-infrared spectral tomography (NIRST) can incorporate the structural information provided by simultaneous magnetic resonance imaging (MRI), and this has significantly improved the images obtained of tissue function. However, the process of MRI guidance in NIRST has been time consuming because of the needs for tissue-type segmentation and forward diffuse modeling of light propagation. To overcome these problems, a reconstruction algorithm for MRI-guided NIRST based on deep learning is proposed and validated by simulation and real patient imaging data for breast cancer characterization. In this approach, diffused optical signals and MRI images were both used as the input to the neural network, and simultaneously recovered the concentrations of oxy-hemoglobin, deoxy-hemoglobin, and water via end-to-end training by using 20,000 sets of computer-generated simulation phantoms. The simulation phantom studies showed that the quality of the reconstructed images was improved, compared to that obtained by other existing reconstruction methods. Reconstructed patient images show that the well-trained neural network with only simulation data sets can be directly used for differentiating malignant from benign breast tumors.

Early administration of tirofiban after urokinase-mediated intravenous thrombolysis reduces early neurological deterioration in patients with branch atheromatous disease.

OBJECTIVES: To investigate the effects of early administration of tirofiban after intravenous thrombolysis on early neurological deterioration in patients with branch atheromatous disease. METHODS: We analyzed clinical data from patients with branch atheromatous disease. We enrolled seven cases into the urokinase-only (UO) control group and 10 cases into the urokinase + tirofiban (UT) treatment group. National Institutes of Health Stroke Scale (NIHSS) scores were obtained at admission and on days 3 and 5 after admission. Modified Rankin Scale (mRS) scores were obtained 3 months after admission. RESULTS: Significant differences between the UO and UT groups were evident on days 3 and 5 after admission. In the UT group, there was a significant difference between NIHSS scores at admission and on day 5, while there were no significant differences in scores in the UO group. The early neurological deterioration rates were not significantly different between the two groups. However, there were significant differences in these rates at 72 and 120 hours. Both the mRS scores and the prognoses at 3 months differed between the two groups. CONCLUSION: Early administration of tirofiban after urokinase-mediated intravenous thrombolysis reduces early neurological deterioration and improves the long-term prognosis of patients with branch atheromatous disease.

Main Traits of Breast Fibroadenoma Among Adolescent Girls.

Objective: To investigate the clinicopathological features of breast fibroadenoma among female teenagers and provide some bases for its diagnosis and treatment, the authors conducted this study. Methods: Retrospective analysis on 80 female teenagers with fibroadenoma was carried out. The histological sections of H&E were reviewed, and immunohistochemical staining with ki67, CD34, and SMA were performed. The patients were followed up. Results: The age of included patients ranged from 12 to 18 years old, with a mean age of 17. Bilateral lesions occurred in 10% of the patients, and mean tumor diameter was 2.8 cm. Histologically, tumors in most cases showed clear boundary with no capsule. Also, 90% of the cases were confirmed to be pericanalicular mixed types, while about 20% had atypical foliation structure. The mean density of mesenchymal cells was 30%. The upper limit of mitotic figure was 2/10HPF in 80% of the cases, and the positive index of ki-67 was no more than 5% in 80% of cases. Sixteen percent of the cases also simultaneously suffered epithelial micropapillary hyperplasia. Six cases (6/39, 15%) faced relapse after tumor resection, with an average recurrence interval of 4.9 years after surgery. Tumor size, mitotic activity, ki67 positive index, and the density of mesenchymal cells were not associated with relapse. Conclusions: Adolescent fibroadenoma is a group of biphasic breast tumors with unique clinical and pathological features. Although fibroadenoma shows a local recurrence rate to a certain degree, its recurrent lesions grow slowly.

Luminescent Down-Conversion Semiconductor Quantum Dots and Aligned Quantum Rods for Liquid Crystal Displays.

Herein, emerging applications of luminescent semiconductor nanocrystals are addressed, such as quantum dots and quantum rods as down-conversion materials used in liquid crystal displays (LCD). Their precisely tunable emission wavelengths and narrow emission bandwidths offer high color purity resulting in a wide color gamut with vivid colors for LCDs. Anisotropic materials, such as quantum rods, have the additional advantage of polarized emission, which can bring a significant improvement to the efficiency of LCD displays. The basic optical properties of these nanomaterials are considered, with a focus on quantum rods, and the challenges and progress in their assembly are discussed. Different techniques for quantum rod alignment are introduced such as shear-oriented, electric field and magnetic field assisted assembly, mechanical rubbing, stretching, and electrospinning. The photoalignment approach allows for an easy arrangement of quantum rods in-plane, and the implications of this method to patterning are considered. Different configurations of LCDs utilizing semiconductor quantum dots and quantum rods as down-conversion layers are also presented, and the potential applications that are enabled by the wide range of emerging materials are highlighted.

Inkjet-printed aligned quantum rod enhancement films for their application in liquid crystal displays.

Semiconductor quantum rods (QRs) show a polarized emission, which opens up the possibility of the enhancement of both brightness and color for liquid crystal displays (LCD) in the form of quantum rod enhancement films (QREFs) for LCD backlights. However, the QR alignment over a large area, suitable for displays, is a challenge. Inkjet printing of QREFs, introduced here, allows fabrication of well-aligned, uniform QREFs on photoaligned substrates using optimized QR inks. We observed that the ink composition and printing conditions affect the QR alignment quality significantly. A relative humidity of 50% with an exposure energy of 1 J cm-2 for the photoalignment process provided optimal conditions for QREFs. We have successfully shown a good QR alignment for 2.5-inch films and were able to align QRs in multiple layers. Thus, fabricated QREFs show a polarization ratio of 7.2 : 1 for the emitted light. These QREFs were combined with a blue LED and deployed as a backlight unit for an LCD which shows a brightness of ∼250 nits with an optical efficiency of ∼8%, reaching an NTSC of 109% in a CIE1976 color space. Thus, these printed QREFs, over a large area, provide an unprecedented increase of 77% in the optical efficiency of the LCDs and simultaneously offer better color performance.

Preparation of Graphene-Perfluoroalkoxy Composite and Thermal and Mechanical Properties.

Perfluoroalkoxy (PFA) material exhibits perfect corrosion resistance under both acid or alkaline circumstances; thus, steel heat exchangers are being substituted by those made of PFA in high corrosion atmospheres. However, the low thermal conductivity of PFA degrades its heat transfer efficiency. Based on the extremely high heat conductivity of graphene, a novel grapheme-PFA composite was proposed to simultaneously meet the demands of heat transfer and corrosion resistance. Ultrasonic dispersion technology was used to disperse the aggregated graphene in the composite. Graphene⁻PFA composites with different graphene contents and using different dispersing solvents were prepared with a hot pressing method, and thermal conductivity, abrasion resistance, crystallization and pyrolysis properties were investigated. The thermal conductivity of PFA composites with graphene content of 20 wt % reached 5.017 W (m·k)-1, which is 21.88 times that of pure PFA. The relationship between the abrasion loss and the friction coefficient of the composites with different graphene contents was obtained. A thermogravimetric analyzer was used to investigate the crystallization and pyrolysis behavior of the composites; correspondingly, the temperature range that composites work in was determined. The heat conduction mechanism was analyzed through the thermal conductivity model of composite materials. The composite material is expected to play an important role in the development of high-performance thermal equipment.

Photoaligned Nanorod Enhancement Films with Polarized Emission for Liquid-Crystal-Display Applications.

Semiconductor nanorods (NR) emit polarized light, which is expected to bring manifold benefits, in terms of brightness and color enhancement, for modern liquid-crystal displays (LCD). In this regard, photoaligned nanorod enhancement films (NREF) for color and polarization conversion for LCD backlights are introduced here. The photoinduced anchoring forces, by the photoalignment layer, stimulate well-ordered self-assembly of NR in the thin polymer films. Green and red emitting NR with a quantum yield of ≈80% are aligned unidirectionally and in-plane, showing a polarization ratio of >7:1 and a degree of polarization of >0.81. The photoalignment technique facilitates the fabrication of mixed and multiple stacked NREF for LCDs, which improves the color gamut and polarization efficiency, and is thus expected to increase the optical efficiency of conventional LCDs by ≈60%.

Photoinduced Micropattern Alignment of Semiconductor Nanorods with Polarized Emission in a Liquid Crystal Polymer Matrix.

Photoalignment technology provides high alignment quality with an exceptional control over the local director of liquid crystals. Because of the reorientation ability of sulfonic azo dye molecules, they offer high azimuthal and polar anchoring energy with a low pretilt angle for the orientation of liquid crystals and liquid crystal composites. In this work, we make use of this approach to align thin film composites of light-emitting semiconductor nanorods dispersed in a liquid crystal polymer into both one-dimensional and two-dimensional microscale patterns. After unidirectional alignment, the patterns are fabricated by a second irradiation with different polarization azimuth and the employment of a photomask. Fluorescence micrographs reveal the nanorod pattern alignment in domain sizes down to 2 µm. Apart from demonstrating the possibility of controlling the orientation of anisotropic nanocrystals with strongly polarized emission on microscopic scale, our results are promising for the fabrication of complex nanostructures for photonic applications.

Integrated and reconfigurable optical paths based on stacking optical functional films.

A strategy for integrated and reconfigurable optical paths based on stacking optical functional films is proposed. It is demonstrated by stacking two liquid crystal polymer q-plates and one quarter-wave plate for vector vortex beams generation. The topological charge and polarization order of generated vector vortex beams can be controlled independently by stacking and reordering different optical films with repeated adhesive ability. It supplies a low-cost, light-weight and versatile technique for reducing the volume of free-space optical system and has a great potential in optical researches and applications.