Segmentation of hyphae and yeast in fungi-infected tissue slice images and its application in analyzing antifungal blue light therapy.

Candida albicans is a pathogenic fungus that undergoes morphological transitions between hyphal and yeast forms, adapting to diverse environmental stimuli and exhibiting distinct virulence. Existing research works on antifungal blue light (ABL) therapy have either focused solely on hyphae or neglected to differentiate between morphologies, obscuring potential differential effects. To address this gap, we established a novel dataset of 150 C. albicans-infected mouse skin tissue slice images with meticulously annotated hyphae and yeast. Eleven representative convolutional neural networks were trained and evaluated on this dataset using seven metrics to identify the optimal model for segmenting hyphae and yeast in original high pixel size images. Leveraging the segmentation results, we analyzed the differential impact of blue light on the invasion depth and density of both morphologies within the skin tissue. U-Net-BN outperformed other models in segmentation accuracy, achieving the best overall performance. While both hyphae and yeast exhibited significant reductions in invasion depth and density at the highest ABL dose (180 J/cm2), only yeast was significantly inhibited at the lower dose (135 J/cm2). This novel finding emphasizes the importance of developing more effective treatment strategies for both morphologies.

We studied the effects of blue light therapy on hyphal and yeast forms of Candida albicans. Through image segmentation techniques, we discovered that the changes in invasion depth and density differed between these two forms after exposure to blue light.

The role of DRP1 mediated mitophagy in HT22 cells apoptosis induced by silica nanoparticles.

Silica nanoparticles (SiNPs) are widely used in the biomedical field and can enter the central nervous system through the blood-brain barrier, causing damage to hippocampal neurons. However, the specific mechanism remains unclear. In this experiment, HT22 cells were selected as the experimental model in vitro, and the survival rate of cells under the action of SiNPs was detected by MTT method, reactive oxygen species (ROS), lactate dehydrogenase (LDH), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px) and adenosine triphosphate (ATP) were tested by the kit, the ultrastructure of the cells was observed by transmission electron microscope, membrane potential (MMP), calcium ion (Ca2+) and apoptosis rate were measured by flow cytometry, and the expressions of mitochondrial functional protein, mitochondrial dynein, mitochondrial autophagy protein as well as apoptosis related protein were detected by Western blot. The results showed that cell survival rate, SOD, CAT, GSH-Px, ATP and MMP gradually decreased with the increase of SiNPs concentration, while intracellular ROS, Ca2+, LDH and apoptosis rate increased with the increase of SiNPs concentration. In total cellular proteins,the expressions of mitochondrial functional proteins VDAC and UCP2 gradually increased, the expression of mitochondrial dynamic related protein DRP1 increased while the expressions of OPA1 and Mfn2 decreased. The expressions of mitophagy related proteins PINK1, Parkin and LC3Ⅱ/LC3Ⅰ increased and P62 gradually decreased, as well as the expressions of apoptosis related proteins Apaf-1, Cleaved-Caspase-3, Caspase-3, Caspase-9, Bax and Cyt-C. In mitochondrial proteins, the expressions of mitochondrial dynamic related proteins DRP1 and p-DRP1 were increased, while the expressions of OPA1 and Mfn2 were decreased. Expressions of mitochondrial autophagy associated proteins PINK1, Parkin, LC3II/LC3I increased, P62 decreased gradually, as well as the expressions of apoptosis related proteins Cleaved-Caspase-3, Caspase-3, and Caspase-9 increased, and Cyt-C expressions decreased. To further demonstrate the role of ROS and DRP1 in HT22 cell apoptosis induced by SiNPs, we selected the ROS inhibitor N-Acetylcysteine (NAC) and Dynamin-related protein 1 (DRP1) inhibitor Mdivi-1. The experimental results indicated that the above effects were remarkably improved after the use of inhibitors, further confirming that SiNPs induce the production of ROS in cells, activate DRP1, cause excessive mitochondrial division, induce mitophagy, destroy mitochondrial function and eventually lead to apoptosis.

Evaluating the efficacy of anti-fungal blue light therapies via analyzing tissue section images.

Anti-fungal blue light (ABL) therapies have been studied and applied in treating various diseases caused by fungal infection. The existing work has been mainly devoted to study the effect of various light dosages on the fungal viability and on the induced cytotoxic reactive oxygen species (ROS) in the pathogens. While in vivo experimental studies have also been reported, there is still no work targeted on quantifying the effect of light on prohibiting the pathogens from invading into the deeper sites in the skin of their host. This can be attributed to the lack of methods to analyze the tissue section images, which are the main means of examining infected tissues. This work has been devoted to solve such problems, so as to improve dosimetric analyses of ABL therapies on treating fungal infections. Specifically, the invasion depth of the fungi and their ratios to the tissue in four bins at different depths inside the skin were extracted from the tissue section images. The significance of the treatment with different dosages on inhibiting the fungi was also tested by each of these depth-related metrics. The ABL experiments using 415-nm-wavelength LED light were performed on BALB/c mice, whose skin was infected by Candida albicans (C. albicans). The proposed methods were applied to the tissue sections of the experimental animals. The results clearly verified that the fluence up to 180J/cm2 can significantly prohibit the fungal infection into the skin in terms of almost all the newly proposed metrics.

Blue light therapy to treat candida vaginitis with comparisons of three wavelengths: an in vitro study.

Anti-fungal blue light (ABL) therapies have been widely studied to treat various microbial infections in the literature. The blue light with wavelengths ranging from 400 to 470 nm has been reported to be effective to inhibit various kinds of bacteria and fungi. The existing studies usually report the viability rates of the pathogens under the irradiation of the blue light with different dosage parameters. However, to the best of our knowledge, there is still no work especially focusing on studying the effect of ABL therapies on treating candida vaginitis, where it is important to study the viability of both the Candida albicans (C. albicans) and the human vaginal epithelial cells. It is the purpose of this work to conduct ABL experiments on both of these two cells, analyze the effects, and determine the best ABL wavelength out of three candidates, i.e., 405-nm, 415-nm, and 450-nm wavelength. The viability rates of the C. albicans and the human vaginal epithelial cells irradiated by the three blue LED light sources were measured, whose irradiance (power density) were all set to 50 mW/cm2. The dynamic viability models of the C. albicans and the epithelial cells were built based on the experimental data. Moreover, in this work, we also built a functional relationship between the viability of these two types of cells, by which we further compared the effects of the blue light irradiation on both the C. albicans and vaginal epithelial cells. The experimental data showed that when an approximately 80% inhibiting rate of the C. albicans was achieved, the survival rates of the epithelial cells were 0.6700, 0.7748, and 0.6027, respectively for the treatment by the 405-nm, 415-nm, and 450-nm wavelength light. On the other hand, by simulating the functional relationship between the viability of the two types of cells, the survival rates of the epithelial cells became 0.5783, 0.6898, and 0.1918 respectively using the 405-nm, 415-nm and 450-nm wavelength light, when the C. albicans was completely inhibited. Therefore, both the experimental data and the model simulation results have demonstrated that the 415-nm light has a more effective anti-fungal result with less damage to the epithelial cells than the 405-nm and 450-nm light.

Optical Waveguides and Integrated Optical Devices for Medical Diagnosis, Health Monitoring and Light Therapies.

Optical waveguides and integrated optical devices are promising solutions for many applications, such as medical diagnosis, health monitoring and light therapies. Despite the many existing reviews focusing on the materials that these devices are made from, a systematic review that relates these devices to the various materials, fabrication processes, sensing methods and medical applications is still seldom seen. This work is intended to link these multidisciplinary fields, and to provide a comprehensive review of the recent advances of these devices. Firstly, the optical and mechanical properties of optical waveguides based on glass, polymers and heterogeneous materials and fabricated via various processes are thoroughly discussed, together with their applications for medical purposes. Then, the fabrication processes and medical implementations of integrated passive and active optical devices with sensing modules are introduced, which can be used in many medical fields such as drug delivery and cardiovascular healthcare. Thirdly, wearable optical sensing devices based on light sensing methods such as colorimetry, fluorescence and luminescence are discussed. Additionally, the wearable optical devices for light therapies are introduced. The review concludes with a comprehensive summary of these optical devices, in terms of their forms, materials, light sources and applications.

Consistency of Proximal-to-Distal Tapering of Descending Thoracic Aortic Diameter: Quantification Using a Novel Computer Tomography-based Assessment.

BACKGROUND: Successful endovascular repair of thoracic aorta for type B aortic dissection requires correct stent-graft sizing, particularly of distal landing zone which is mainly based on operator experience. The present study aimed to quantitatively define proximal-to-distal tapering of descending thoracic aortic diameter and its consistency. METHODS: The novel parameter HDP (Hundred times Distance accounts for Percentage)-measured as distance from the distal end of the left subclavian artery to each level along the aortic central line/length from the distal end of the left subclavian artery to the proximal end of the celiac artery along the aortic central line × 100-was calculated per 1% unit of descending thoracic aorta based on 3-mensio software-derived measurements from 281 consecutive individuals who had undergone enhanced chest computer tomography scanning. Association between HDP and maximal diameter of descending thoracic aorta was assessed by using the generalized additive mixed model with smoothing function and threshold saturation effect analyses with generalized estimating equations. Nonadjusted and adjusted models were performed to illuminate its consistency. RESULTS: Three inflection levels (HDPs of 15.01, 36.63, and 77.74) were identified which allowed to divide the descending thoracic aorta into 4 segments. The taper was consistent before and after adjusting for age, sex, height, body mass index, hypertension, smoking habits, hyperlipidemia, and diabetes. Although 1% unit of descending thoracic aorta decreases, the maximal diameter reduces to 0.007 mm (-0.025, 0.010; P = 0.414) in the segment with HDP <15.01, to 0.151 mm (-0.158, -0.145; P < 0.001) in the segment with 15.01 ≤ HDP < 36.63, to 0.038 mm (-0.040, -0.036; P < 0.001) in the segment with 36.63 < HDP ≤ 77.74; and to 0.026 mm (-0.049, -0.002; P = 0.035) in the segment with HDP > 77.74, respectively. CONCLUSIONS: The maximal diameter of descending thoracic aorta decreases gradually and consistently among individuals free of aortic diseases.

Optical design of a compact multispectral LED light source with high irradiance and uniformity.

As light-emitting diodes (LEDs) become dominating solutions in general lighting, their applications are also penetrating into biomedical engineering, especially light therapies. These new applications usually require much higher light power density at a shorter working distance than general lighting. Besides the high power, uniformity in power distribution is another important factor in such applications to illuminate samples with equal irradiance. These factors require designing a compact optical system to transmit light from a highly integrated high-power LED light source. While existing designs mainly focus on providing the desired illuminance in a much larger target space, little work has been devoted to the optical design to achieve a high irradiance that is uniformly distributed onto a target area at a short distance away from the light source. This work proposes a design method to solve such a problem, based on a highly integrated LED module, a mixing rod, and a pair of aspheric lenses. Both numerical simulations and experiments with a prototype are performed, which have verified the effectiveness of the proposed method.

Increasing color saturation by optimizing light spectra constrained on color rendering properties.

Enhancing the color saturation of objects via illumination with specially designed light spectra is promising in many commercial and scientific applications. Existing literature has focused on studying the colors that can be rendered by white light with various correlated color temperatures, and by the mixed light from various monochromatic light-emitting diodes. However, very little literature has been devoted to methods that can actively configure the light spectrum to enhance the color saturation of an arbitrary object. This paper proposes an optimization-based method to extend the gamut that can be achieved by a given polychromatic lamp toward a chosen direction, i.e., to increase the saturation of a specific color. Moreover, to trade-off the increased saturation of a color sample with the reduced colorfulness of other samples, constraints with tunable thresholds are imposed to the optimization problem to bound the variation of a contrast color sample. In addition, the effect of uncontrollable ambient light can be taken into account by mild modifications of the optimization problem. Simulation results show that the optimized light spectrum can effectively enhance the saturation of any specific color, while maintaining the other rendered colors as intact as possible. Visual experiments have also been conducted with 22 human subjects, whose responses agree with the simulation results.

Optimization of LED light spectrum to enhance colorfulness of illuminated objects with white light constraints.

Enhancing the colorfulness of illuminated objects is a promising application of LED lighting for commercial, exhibiting, and scientific purposes. This paper proposes a method to enhance the color of illuminated objects for a given polychromatic lamp. Meanwhile, the light color is restricted to white. We further relax the white light constraints by introducing soft margins. Based on the spectral and electrical characteristics of LEDs and object surface properties, we determine the optimal mixing of the LED light spectrum by solving a numerical optimization problem, which is a quadratic fractional programming problem by formulation. Simulation studies show that the trade-off between the white light constraint and the level of the color enhancement can be adjusted by tuning an upper limit value of the soft margin. Furthermore, visual evaluation experiments are performed to evaluate human perception of the color enhancement. The experiments have verified the effectiveness of the proposed method.

MAEF-Net: MLP Attention for Feature Enhancement in U-Net based Medical Image Segmentation Networks.

Medical image segmentation plays an important role in diagnosis. Since the introduction of U-Net, numerous advancements have been implemented to enhance its performance and expand its applicability. The advent of Transformers in computer vision has led to the integration of self-attention mechanisms into U-Net, resulting in significant breakthroughs. However, the inherent complexity of Transformers renders these networks computationally demanding and parameter-heavy. Recent studies have demonstrated that multilayer perceptrons (MLPs), with their simpler architecture, can achieve comparable performance to Transformers in natural language processing and computer vision tasks. Building upon these findings, we have enhanced the previously proposed "Enhanced-Feature-Four-Fold-Net" (EF 3-Net) by introducing an MLP-attention block to learn long-range dependencies and expand the receptive field. This enhanced network is termed "MLP-Attention Enhanced-Feature-four-fold-Net", abbreviated as "MAEF-Net". To further enhance accuracy while reducing computational complexity, the proposed network incorporates additional efficient design elements. MAEF-Net was evaluated against several general and specialized medical image segmentation networks using four challenging medical image datasets. The results demonstrate that the proposed network exhibits high computational efficiency and comparable or superior performance to EF 3-Net and several state-of-the-art methods, particularly in segmenting blurry objects.

SAHIS-Net: a spectral attention and feature enhancement network for microscopic hyperspectral cholangiocarcinoma image segmentation.

Cholangiocarcinoma (CCA) poses a significant clinical challenge due to its aggressive nature and poor prognosis. While traditional diagnosis relies on color-based histopathology, hyperspectral imaging (HSI) offers rich, high-dimensional data holding potential for more accurate diagnosis. However, extracting meaningful insights from this data remains challenging. This work investigates the application of deep learning for CCA segmentation in microscopic HSI images, and introduces two novel neural networks: (1) Histogram Matching U-Net (HM-UNet) for efficient image pre-processing, and (2) Spectral Attention based Hyperspectral Image Segmentation Net (SAHIS-Net) for CCA segmentation. SAHIS-Net integrates a novel Spectral Attention (SA) module for adaptively weighing spectral information, an improved attention-aware feature enhancement (AFE) mechanism for better providing the model with more discriminative features, and a multi-loss training strategy for effective early stage feature extraction. We compare SAHIS-Net against several general and CCA-specific models, demonstrating its superior performance in segmenting CCA regions. These results highlight the potential of our approach for segmenting medical HSI images.

Robust Data-Driven Iterative Learning Control for Linear-Time-Invariant and Hammerstein-Wiener Systems.

Iterative learning control (ILC) relies on a finite-time interval output predictor to determine the output trajectory in each trial. Robust ILCs intend to model the uncertainties in the predictor and to guarantee the convergence of the learning process subject to such model errors. Despite the vast literature in ILCs, parameterizing the uncertainties with the stochastic errors in the predictor parameters identified from system I/O data and thus robustifying the ILC have not yet been targeted. This work is devoted to solving such problems in a data-driven fashion. The main contributions are two-fold. First, a data-driven ILC method is developed for LTI systems. The relationship is established between the errors in the predictor matrix and the stochastic disturbances to the system. Its robust monotonic convergence (RMC) is then linked with the closed-loop learning gain matrix that contains the predictor uncertainties and is analyzed based on a closed-form expectation of this gain matrix multiplied with its own transpose, that is, in a mean-square sense (MS-RMC). Second, the data-driven ILC and MS-RMC analysis are extended to nonlinear Hammerstein-Wiener (H-W) systems. The advantages of the proposed methods are finally verified via extensive simulations in terms of their convergence and uncorrelated tracking performance with the stochastic parametric uncertainties.

Suppressing epithelial-mesenchymal-transition blue light therapy for reducing macrophage-mediated cancerous pulmonary fibrosis: An in-vitro study.

Lung cancer is the leading killer among all types of cancer globally. As a key factor, epithelial-mesenchymal transition (EMT) plays a crucial role in pathological fibrosis and lung cancer metastasis. This study endeavors to investigate the effect of blue light at specific wavelengths of 405 nm and 415 nm (54 J/cm2 ) on EMT induced by TGF-ß1 in A549 cells. The results revealed that the blue light irradiation reduced the morphological characteristics of EMT in the A549 cells, and cell-to-cell connections were weakened significantly. Molecular analysis showed upregulation of epithelial marker E-cadherin and downregulation of EMT marker vimentin. Additionally, exposure to blue light irradiation at 405 nm and 415 nm significantly decelerated the ability of invasion and migration. Moreover, cell viability was also investigated. Based on these findings, blue light can serve as a useful therapeutic option for inhibiting EMT in cases of lung cancer and fibrotic lung disease.

Efficient distributed control of light-emitting diode array lighting systems.

We consider illumination rendering with distributed control of a lighting system with an array of light-emitting diodes (LEDs). As low-cost microprocessors become standard components in LED drivers, distributing the computation of the control signals to individual LED drivers becomes attractive. Common distributed control algorithms require each individual controller to exchange information with all the others and process it. This incurs too large a communication and processing overhead for a low-cost local controller. In this Letter, we propose a distributed control algorithm for achieving global illumination rendering, wherein a controller only needs to communicate within a selected neighborhood. We present design criteria for defining the communication neighborhood and study its impact on rendering performance.

Effect of inactivating RNA viruses by coupled UVC and UVA LEDs evaluated by a viral surrogate commonly used as a genetic vector.

RNA viruses are ubiquitous in nature, many of which can cause severe infectious syndromes to humanity, e.g., the SARS-CoV-2 virus. Ultraviolet (UV) radiation has been widely studied for inactivating various species of microorganisms, including viruses. The most applicable UV light for viruses ranges from 200nm to 280nm in wavelength, i.e., UVC. More recently, the synergy of UVA light with UVC has been studied in disinfecting bacteria in polluted water. However, little attention has been paid to studying viral inactivation by coupled UVC and UVA LEDs. The necessity of such research is to find an effective and economical solution for the LEDs of these two bands. Along this track, we attempt to tackle two major challenges. The first is to find a suitable viral surrogate that can safely be used in ordinary labs. In this aspect, lentivirus is commonly used as a genetic vector and has been selected to surrogate RNA viruses. Another is to determine the effective dosage of the coupled UVC and UVA light. To this end, the surrogate lentivirus was irradiated by 280nm (UVC) LEDs, 365nm (UVA) LEDs, and their combination at various doses. Survival rates were detected to compare the efficacy of various options. Moreover, the viral RNA damage was detected by RT-qPCR to disclose the mechanism of viral death. The results have shown that for the same duration of irradiation, the effect of the full-power 280nm LEDs is equivalent to that of the half-power 280nm LEDs combined with a suitable radiant power of the 365nm LEDs. The observations have been further confirmed by the effect of damaging the viral RNA by either the 280nm or 365nm light. In conclusion, the experimental results provide clear evidence of alleviating the requirement of UVC LEDs in viral inactivation by substituting them partially with UVA LEDs.

Analysis and Data-Based Modeling of the Photochemical Reaction Dynamics of the Induced Singlet Oxygen in Light Therapies.

OBJECTIVE: The macroscopic singlet oxygen (MSO) model for quantifying the light-induced singlet oxygen ( 1O2) always contain a set of nonlinear dynamic equations and therefore are generally difficult to be applied. This work was devoted to analyze and simplify this dynamic model. METHODS: Firstly, the nonlinearity of the MSO model was analyzed with control theory. The conditions, under which it can be simplified to a linear one, were derived. Secondly, in the case of ample triplet oxygen concentration, a closed-form exact solution of the 1O2 model was further derived, in a nonlinear algebraic form with only four parameters that can be easily fitted to experimental data. Finally, in vitro experiments of anti-fungal light therapies were conducted, where the fungi, Candida albicans, were irradiated respectively by the 385, 405, 415, and 450 nm wavelength light. The singlet oxygen concentration levels in the fungi were measured, and then used to fit the developed models. RESULTS: The parameters of the closed-form exact solution were estimated from both the simulated and the measured experimental data. Based on this model, a functional relationship between the photon energy, fluence rate and singlet oxygen concentration was also established. The fitting accuracy of this model to the data was satisfactory, which therefore demonstrates the effectiveness of the proposed modeling techniques. CONCLUSION: The results from simulating the closed-form model indicate that the photon energy within the range of either 2.7  âˆ¼  2.8 eV or 3.0  âˆ¼  3. 2 eV (388  âˆ¼  413 nm or 443  âˆ¼  459 nm in wavelength) is more effective in generating singlet oxygen in the fungi studied in this work. SIGNIFICANCE: It is the first attempt of applying control theory to analyze the photochemical reaction dynamics of light therapies in terms of their nonlinearity. The proposed modeling techniques also offer opportunities for determining the light dosages in treating fungal infection diseases, especially those on the surface tissues of human body.

Analyzing Efficacy and Safety of Anti-Fungal Blue Light Therapy via Kernel-Based Modeling the Reactive Oxygen Species Induced by Light.

OBJECTIVE: The goal of this study is to investigate the efficacy, safety, and mechanism of ABL for inactivating Candida albicans (C. albicans), and to determine the best wavelength for treating candida infected disease, by experimental measurements and dynamic modeling. METHODS: The changes in reactive oxygen species (ROS) in C. albicans and human host cells under the irradiation of 385, 405, and 415 nm wavelengths light with irradiance of 50 mW/cm2 were measured. Moreover, a kernel-based nonlinear dynamic model, i.e., nonlinear autoregressive with exogenous inputs (NARX), was developed and applied to predict the concentration of light-induced ROS, whose kernels were selected by a newly developed algorithm based on particle swarm optimization (PSO). RESULTS: The ROS concentration was increased respectively about 10-12 times in C. albicans and about 3-6 times in human epithelial cells by the ABL treatment with the same fluence of 90 J/cm2. The NARX models were respectively fitted to the data from the experiments on both types of cells. Besides, four different kernel functions, including Gaussian, Laplace, linear and polynomial kernels, were compared in their fitting accuracies. The errors with the Laplace kernel turned out to be only 0.2704 and 0.0593, as respectively fitted to the experimental data of the C. albicans and human host cells. CONCLUSION: The results demonstrated the effectiveness of the NARX modeling approach, and revealed that the 415 nm light was more effective as an anti-fungal treatment with less damage to the host cells than the 405 or 385 nm light. SIGNIFICANCE: The kernel-based NARX model identification algorithm offers opportunities for determining the effective and safe light dosages in treating various fungal infection diseases.

Automatic diagnosis and control of distributed solid state lighting systems.

This paper describes a new design concept of automatically diagnosing and compensating LED degradations in distributed solid state lighting (SSL) systems. A failed LED may significantly reduce the overall illumination level, and destroy the uniform illumination distribution achieved by a nominal system. To our knowledge, an automatic scheme to compensate LED degradations has not yet been seen in the literature, which requires a diagnostic step followed by control reconfigurations. The main challenge in diagnosing LED degradations lies in the usually unsatisfactory observability in a distributed SSL system, because the LED light output is usually not individually measured. In this work, we tackle this difficulty by using pulse width modulated (PWM) drive currents with a unique fundamental frequency assigned to each LED. Signal processing methods are applied in estimating the individual illumination flux of each LED. Statistical tests are developed to diagnose the degradation of LEDs. Duty cycle of the drive current signal to each LED is re-optimized once a fault is detected, in order to compensate the destruction of the uniform illumination pattern by the failed LED.

Active and Adequate Exposure of the Facial Nerve and Chorda Tympani Nerve to Improve the Safety of Cochlear Implantation.

BACKGROUND: The posterior tympanum approach of cochlear implantation is easy to damage the facial nerve and cord tympanic nerve. Therefore, we need to improve the safety of cochlear implantation. OBJECTIVES: To discuss the safety and feasibility of active and adequate transparent exposure of the facial nerve and chorda tympani nerve during the surgery. METHODS: A retrospective analysis was performed on all 945 patients who underwent cochlear implantation from January 2011 to September 2017. All patients have been followed up for 14 months to 5 years postoperatively and postoperative complications have been observed. RESULTS: All 945 patients received artificial cochlear implantation. The facial nerves of 76 cases were above the horizontal semicircular canal plane, while narrow facial recess was observed in 44 cases. Serious chorda tympani nerve variation was found in 1 case. No facial paralysis and facial nerve irritation and abnormal taste occurred after operation. CONCLUSIONS: Cochlear implantation with initiative and adequate exposure of facial nerve and the chorda tympani nerve can improve the safety of the cochlear implant surgery. Our study provide a safe and effective method for clinical cochlear implantation to reduce facial nerve and tympanic cord nerve injury.

Effect of the Inclination Angle on Premixed Flame Dynamics in Half-Open Ducts.

The propagation of premix methane/air flames in long half-open ducts with different inclination angles θ between the sidewall and the horizon was numerically investigated using the laminar model. The numerical result was compared with the experimental and theoretical ones to validate the numerical model. The results show that the numerical results are in good agreement with them. The investigation provides the basic understanding of the effects on changing the shape of the ducts to promote the premixed flame combustion. For methane/air, the position where the flame front begins to concave is pushed back with the increase in angle θ. The so-called "tulip" flame even disappeared, if the angle θ is bigger than one certain value. Moreover, the flame propagation speed and pressure are enhanced as the angle θ increases. In addition, the numerical simulation indicates that the burning gas creates an eddy near the tip of the flame, altering the flow field and causing the tulip flame to appear. However, with the angle θ increased, the flame propagation is restrained by the change in sidewalls, resulting in the different flow patterns to suppress the formation of tulip flames and promote flame combustion.