Ultrathin and Self-Supporting MOF/COF-Based Composite Membranes for Hydrogen Separation and Purification from Coke Oven Gas.

Coke oven gas (COG) is considered to be one of the most likely raw materials for large-scale H2 production in the near or medium term, with membrane separation technologies standing out from traditional technologies due to their less energy-intensive structures as well as simple operation and occupation. Based on the "MOF-in/on-COF" pore modification strategy, the COF membrane (named the PBD membrane) and ZIF-67 were used as assembly elements to design advanced molecular sieving membranes for hydrogen separation. The composition and microstructure of membranes before and after ZIF-67 loading as well as ZIF-67-in-PBD membranes under different preparation conditions (metal ion concentration, metal-ligand ratio, and reaction time) were investigated by various characterizations to reveal the synthesis regularity and microstructure regulation. Furthermore, H2/CH4 separation performances and separation mechanisms were also analyzed and compared. Finally, a dense, continuous, ultrathin, and self-supporting ZIF-67-in-PBD membrane with a Co2+ concentration of 0.02 mol/L, a metal-ligand ratio of 1:4, and a reaction time of 6 h exhibited the largest specific surface area, micropore proportion, and the best H2/CH4 separation selectivity (α = 33.48), which was significantly higher than the Robeson upper limit and was in a leading position among reported MOF membranes. The separation mechanism was mainly size screening, and adsorption selectivity also contributed a little.

Determination of organic acids for predicting sourness intensity of tea beverage by liquid chromatography-tandem mass spectrometry and chemometrics methods.

The contents of organic acids (OAs) in tea beverage and their relationship with taste intensity have not been fully understood. In this work, a rapid (10 min for a single run) and sensitive (limits of quantification: 0.0044-0.4486 µg/mL) method was developed and validated for the simultaneous determination of 17 OAs in four types of tea, based on liquid chromatography-tandem mass spectrometry with multiple reaction monitoring mode. The contents of 17 OAs in 96 tea samples were measured at levels between 0.01 and 11.80 g/kg (dried weight). Quinic acid, citric acid, and malic acid were determined as the major OAs in green, black, and raw pu-erh teas, while oxalic acid and tartaric acid exhibited the highest contents in ripe pu-erh tea. Taking the OAs composition as input features, a partial least squares regression model was proposed to predict the sourness intensity of tea beverages. The model achieved a root-mean-square error of 0.58 and a coefficient of determination of 0.84 for the testing set. The proposed model provides a theoretical way to evaluate the sensory quality of tea infusion based on its chemical composition.

Detection of Rehabilitation Training Effect of Upper Limb Movement Disorder Based on MPL-CNN.

Stroke represents a medical emergency and can lead to the development of movement disorders such as abnormal muscle tone, limited range of motion, or abnormalities in coordination and balance. In order to help stroke patients recover as soon as possible, rehabilitation training methods employ various movement modes such as ordinary movements and joint reactions to induce active reactions in the limbs and gradually restore normal functions. Rehabilitation effect evaluation can help physicians understand the rehabilitation needs of different patients, determine effective treatment methods and strategies, and improve treatment efficiency. In order to achieve real-time and accuracy of action detection, this article uses Mediapipe's action detection algorithm and proposes a model based on MPL-CNN. Mediapipe can be used to identify key point features of the patient's upper limbs and simultaneously identify key point features of the hand. In order to detect the effect of rehabilitation training for upper limb movement disorders, LSTM and CNN are combined to form a new LSTM-CNN model, which is used to identify the action features of upper limb rehabilitation training extracted by Medipipe. The MPL-CNN model can effectively identify the accuracy of rehabilitation movements during upper limb rehabilitation training for stroke patients. In order to ensure the scientific validity and unified standards of rehabilitation training movements, this article employs the postures in the Fugl-Meyer Upper Limb Rehabilitation Training Functional Assessment Form (FMA) and establishes an FMA upper limb rehabilitation data set for experimental verification. Experimental results show that in each stage of the Fugl-Meyer upper limb rehabilitation training evaluation effect detection, the MPL-CNN-based method's recognition accuracy of upper limb rehabilitation training actions reached 95%. At the same time, the average accuracy rate of various upper limb rehabilitation training actions reaches 97.54%. This shows that the model is highly robust across different action categories and proves that the MPL-CNN model is an effective and feasible solution. This method based on MPL-CNN can provide a high-precision detection method for the evaluation of rehabilitation effects of upper limb movement disorders after stroke, helping clinicians in evaluating the patient's rehabilitation progress and adjusting the rehabilitation plan based on the evaluation results. This will help improve the personalization and precision of rehabilitation treatment and promote patient recovery.

DV3-IBi_YOLOv5s: A Lightweight Backbone Network and Multiscale Neck Network Vehicle Detection Algorithm.

Vehicle detection is a research direction in the field of target detection and is widely used in intelligent transportation, automatic driving, urban planning, and other fields. To balance the high-speed advantage of lightweight networks and the high-precision advantage of multiscale networks, a vehicle detection algorithm based on a lightweight backbone network and a multiscale neck network is proposed. The mobile NetV3 lightweight network based on deep separable convolution is used as the backbone network to improve the speed of vehicle detection. The icbam attention mechanism module is used to strengthen the processing of the vehicle feature information detected by the backbone network to enrich the input information of the neck network. The bifpn and icbam attention mechanism modules are integrated into the neck network to improve the detection accuracy of vehicles of different sizes and categories. A vehicle detection experiment on the Ua-Detrac dataset verifies that the proposed algorithm can effectively balance vehicle detection accuracy and speed. The detection accuracy is 71.19%, the number of parameters is 3.8 MB, and the detection speed is 120.02 fps, which meets the actual requirements of the parameter quantity, detection speed, and accuracy of the vehicle detection algorithm embedded in the mobile device.

A GM-JMNS-CPHD Filter for Different-Fields-of-View Stochastic Outlier Selection for Nonlinear Motion Tracking.

Most multi-target movements are nonlinear in the process of movement. The common multi-target tracking filtering methods directly act on the multi-target tracking system of nonlinear targets, and the fusion effect is worse under the influence of different perspectives. Aiming to determine the influence of different perspectives on the fusion accuracy of multi-sensor tracking in the process of target tracking, this paper studies the multi-target tracking fusion strategy of a nonlinear system with different perspectives. A GM-JMNS-CPHD fusion technique is introduced for random outlier selection in multi-target tracking, leveraging sensors with limited views. By employing boundary segmentation from distinct perspectives, the posterior intensity function undergoes decomposition into multiple sub-intensities through SOS clustering. The distribution of target numbers within the respective regions is then characterized by the multi-Bernoulli reconstruction cardinal distribution. Simulation outcomes demonstrate the robustness and efficacy of this approach. In comparison to other algorithms, this method exhibits enhanced robustness even amidst a decreased detection probability and heightened clutter rates.

Ionic-Liquid-Assisted One-Step Construction of Mesoporous Metal-Organic Frameworks.

The synthesis of ionic-mesoporous-metal-organic frameworks (ionic-meso-MOFs) has received considerable interest in the fields of macromolecular adsorption, acid-base catalysis, ionic conductivity, etc.; yet, their synthesis still presents significant difficulties. In this study, functionalized mesoporous MIL-101-ILs (Cr) was facilely constructed via an in situ self-assembly method by using aromatic-anion-functionalized ionic liquids (ILs) as competitive ligands. It has been demonstrated that the inclusion of an aromatic moiety into an IL improves the coordination ability and is advantageous for the anchoring of ILs on Cr3+ via amino-metal coordination. Thus, ionic-meso-MOFs with a specific surface area of 441.9-624.9 cm2/g and an average pore diameter of 5.5 to 8.4 nm were successfully synthesized. Because of the presence of open Lewis acidic metal sites on the MOFs and basic active sites on the ILs, the resulting ionic-meso-MOFs demonstrated both an acid-base cooperative effect and a mesoporous structure, indicating a high potential for acid-base catalysis. This in situ synthesis procedure for ionic mesoporous MOFs offers a simple method for developing and fabricating multifunctional mesoporous materials.

Biofeedback Respiratory Rehabilitation Training System Based on Virtual Reality Technology.

Traditional respiratory rehabilitation training fails to achieve visualization and quantification of respiratory data in improving problems such as decreased lung function and dyspnea in people with respiratory disorders, and the respiratory rehabilitation training process is simple and boring. Therefore, this article designs a biofeedback respiratory rehabilitation training system based on virtual reality technology. It collects respiratory data through a respiratory sensor and preprocesses it. At the same time, it combines the biofeedback respiratory rehabilitation training virtual scene to realize the interaction between respiratory data and virtual scenes. This drives changes in the virtual scene, and finally the respiratory data are fed back to the patient in a visual form to evaluate the improvement of the patient's lung function. This paper conducted an experiment with 10 participants to evaluate the system from two aspects: training effectiveness and user experience. The results show that this system has significantly improved the patient's lung function. Compared with traditional training methods, the respiratory data are quantified and visualized, the rehabilitation training effect is better, and the training process is more active and interesting.

Effects of intervention integrating physical literacy into active school recesses on physical fitness and academic achievement in Chinese children.

Background/Objective: The aim of this study was to examine the effects of school-based intervention integrating physical literacy (PL) into active school recesses (ASR) on physical fitness (i.e., body composition, 20-m shuttle run, 50-m run, rope skipping, sit and reach, handgrip) and academic achievement (i.e., academic result of Chinese and Mathematics) in Chinese children. Methods: A total of 357 children (mean age: 7.8 ± 0.7 years; boys: 50.4%) were recruited from two schools and these two schools were randomly assigned as the intervention group (IG) and the control group (CG), respectively. The IG consisted of 155 children (mean age: 7.9 ± 0.7 years, boys: 51.0%), and 202 children (mean age: 7.8 ± 0.7 years; boys: 50%) were allocated to the CG. Children in the IG received a 10-week intervention integrating PL that was conducted during ASR. In the CG, children's regular school activity was remained during the intervention period. Generalized estimating equation was performed to compare the levels of physical fitness and academic achievement between the IG and the CG after intervention. Results: Regarding physical fitness, there was a significant group × time interaction on 20-m shuttle run (ß = -3.89, 95% CI [-5.08; -2.71], p < 0.001) and handgrip (ß = -0.70, 95% CI [-1.20; -0.20], p = 0.006). After intervention, children in the IG had a greater increase than the CG (p < 0.001) in terms of 20-m shuttle run and handgrip. In addition, the post-test analysis indicated that performance of children in the IG was significantly greater than those in the CG (20-m shuttle run: p < 0.001, handgrip: p = 0.002). There was a significant group × time interaction on academic result of Chinese (ß = -1.21, 95% CI [-1.91; -0.56], p = 0.001) and academic result of Mathematics (ß = 16.71, 95% CI [15.14; 18.143], p < 0.001). Statistically significant positive difference in post-test was observed in academic result of Mathematics between the IG and the CG (p = 0.012). Conclusion: The results of this intervention study indicate that intervention integrating PL into ASR could bring a promising effect on physical fitness and academic achievement in children. It is recommended that future studies are necessary to assess the effects of ASR-based PL intervention on physical and cognitive outcomes using a wide range of sample.

Prediction of occult tumor progression via platelet RNAs in a mouse melanoma model: a potential new platform for early detection of cancer.

BACKGROUND: Cancer screening provides the opportunity to detect cancer early, ideally before symptom onset and metastasis, and offers an increased opportunity for a better prognosis. The ideal biomarkers for cancer screening should discriminate individuals who have not developed invasive cancer yet but are destined to do so from healthy subjects. However, most cancers lack effective screening recommendations. Therefore, further studies on novel screening strategies are urgently required. METHODS: We used a simple suboptimal inoculation melanoma mouse model to obtain 'pre-diagnostic samples' of mice with macroscopic melanomas. High-throughput sequencing and bioinformatic analysis were employed to identify differentially expressed RNAs in platelet signatures of mice injected with a suboptimal number of melanoma cells (eDEGs) compared with mice with macroscopic melanomas and negative controls. Moreover, 36 genes selected from the eDEGs via bioinformatics analysis were verified in a mouse validation cohort via quantitative real-time PCR. LASSO regression was utilized to generate the prediction models with gene expression signatures as the best predictors for occult tumor progression in mice. RESULTS: These RNAs identified from eDEGs of mice injected with a suboptimal number of cancer cells were strongly enriched in pathways related to immune response and regulation. The prediction models generated by 36 gene qPCR verification data showed great diagnostic efficacy and predictive value in our murine validation cohort, and could discriminate mice with occult tumors from control group (area under curve (AUC) of 0.935 (training data) and 0.912 (testing data)) (gene signature including Cd19, Cdkn1a, S100a9, Tap1, and Tnfrsf1b) and also from macroscopic tumor group (AUC of 0.920 (training data) and 0.936 (testing data)) (gene signature including Ccr7, Cd4, Kmt2d, and Ly6e). CONCLUSIONS: Our proof-of-concept study provides evidence for potential clinical relevance of blood platelets as a platform for liquid biopsy-based early detection of cancer.

BRD4 inhibition exerts anti-viral activity through DNA damage-dependent innate immune responses.

Chromatin dynamics regulated by epigenetic modification is crucial in genome stability and gene expression. Various epigenetic mechanisms have been identified in the pathogenesis of human diseases. Here, we examined the effects of ten epigenetic agents on pseudorabies virus (PRV) infection by using GFP-reporter assays. Inhibitors of bromodomain protein 4 (BRD4), which receives much more attention in cancer than viral infection, was found to exhibit substantial anti-viral activity against PRV as well as a range of DNA and RNA viruses. We further demonstrated that BRD4 inhibition boosted a robust innate immune response. BRD4 inhibition also de-compacted chromatin structure and induced the DNA damage response, thereby triggering the activation of cGAS-mediated innate immunity and increasing host resistance to viral infection both in vitro and in vivo. Mechanistically, the inhibitory effect of BRD4 inhibition on viral infection was mainly attributed to the attenuation of viral attachment. Our findings reveal a unique mechanism through which BRD4 inhibition restrains viral infection and points to its potent therapeutic value for viral infectious diseases.

LncRNA MALAT1 promotes decidualization of endometrial stromal cells via sponging miR-498-3p and targeting histone deacetylase 4.

Decidualization of human endometrial stromal cells (hESCs) is important for the maintenance of a successful pregnancy. Histone deacetylase 4 (HDAC4) was reported to be involved in the dysfunction of decidua-derived mesenchymal stem cells. However, the role of HDAC4 underlying decidualization of hESCs remains unclear. We intended to explore the function and molecular mechanism of HDAC4 in hESCs. In vitro expansion of hESCs using a serum-free medium was used to confirm the characteristics of hESCs. Gene expression in hESCs was evaluated by reverse transcription-quantitative polymerase chain reaction. CCK-8 assay, TUNEL staining, flow cytometry analysis, and Western blot analysis were performed to test the effects of HDAC4 and metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) on hESCs. RNA pull-down and luciferase reporter assays were performed to validate the relationship between genes. In this study, the characteristics of hESCs were sustained in serum-free medium during a process of propagation. HDAC4 knockdown suppressed hESCs viability and promoted hESCs apoptosis. HDAC4 was targeted by miR-498-3p in hESCs. MALAT1 bound with miR-498-3p in hESCs. HDAC4 expression was positively regulated by MALAT1 and negatively regulated by miR-498-3p in hESCs. HDAC4 upregulation countervailed the effects of MALAT1 silencing on hESCs proliferation, apoptosis, and decidualization of hESCs. Overall, MALAT1 facilitated the decidualization of hESCs via binding with miR-498-3p and upregulating HDAC4, which might provide a new direction for the maintenance of a successful pregnancy.

Automatic Segmentation of Standing Trees from Forest Images Based on Deep Learning.

Semantic segmentation of standing trees is important to obtain factors of standing trees from images automatically and effectively. Aiming at the accurate segmentation of multiple standing trees in complex backgrounds, some traditional methods have shortcomings such as low segmentation accuracy and manual intervention. To achieve accurate segmentation of standing tree images effectively, SEMD, a lightweight network segmentation model based on deep learning, is proposed in this article. DeepLabV3+ is chosen as the base framework to perform multi-scale fusion of the convolutional features of the standing trees in images, so as to reduce the loss of image edge details during the standing tree segmentation and reduce the loss of feature information. MobileNet, a lightweight network, is integrated into the backbone network to reduce the computational complexity. Furthermore, SENet, an attention mechanism, is added to obtain the feature information efficiently and suppress the generation of useless feature information. The extensive experimental results show that using the SEMD model the MIoU of the semantic segmentation of standing tree images of different varieties and categories under simple and complex backgrounds reaches 91.78% and 86.90%, respectively. The lightweight network segmentation model SEMD based on deep learning proposed in this paper can solve the problem of multiple standing trees segmentation with high accuracy.

Multimodal Feature Fusion Method for Unbalanced Sample Data in Social Network Public Opinion.

With the wide application of social media, public opinion analysis in social networks has been unable to be met through text alone because the existing public opinion information includes data information of various modalities, such as voice, text, and facial expressions. Therefore multi-modal emotion analysis is the current focus of public opinion analysis. In addition, multi-modal emotion recognition of speech is an important factor restricting the multi-modal emotion analysis. In this paper, the emotion feature retrieval method for speech is firstly explored and the processing method of sample disequilibrium data is then analyzed. By comparing and studying the different feature fusion methods of text and speech, respectively, the multi-modal feature fusion method for sample disequilibrium data is proposed to realize multi-modal emotion recognition. Experiments are performed using two publicly available datasets (IEMOCAP and MELD), which shows that processing multi-modality data through this method can obtain good fine-grained emotion recognition results, laying a foundation for subsequent social public opinion analysis.

Controllable Construction of Amino-Functionalized Dynamic Covalent Porous Polymers for High-Efficiency CO2 Capture from Flue Gas.

The design of high-efficiency CO2 adsorbents with low cost, high capacity, and easy desorption is of high significance for reducing carbon emissions, which yet remains a great challenge. This work proposes a facile construction strategy of amino-functional dynamic covalent materials for effective CO2 capture from flue gas. Upon the dynamic imine assembly of N-site rich motif and aldehyde-based spacers, nanospheres and hollow nanotubes with spongy pores were constructed spontaneously at room temperature. A commercial amino-functional molecule tetraethylenepentamine could be facilely introduced into the dynamic covalent materials by virtue of the dynamic nature of imine assembly, thus inducing a high CO2 capacity (1.27 mmol·g-1) from simulated flue gas at 75 °C. This dynamic imine assembly strategy endowed the dynamic covalent materials with facile preparation, low cost, excellent CO2 capacity, and outstanding cyclic stability, providing a mild and controllable approach for the development of competitive CO2 adsorbents.

Autism spectrum disorder and severe social impairment associated with elevated plasma interleukin-8.

BACKGROUND: Autism spectrum disorder (ASD) is a neurodevelopmental disorder with an unclear etiology and pathophysiology. Previous studies have indicated that the dysregulation of cytokines may be involved in the pathogenesis of ASD and that the levels of cytokines may serve as potential biomarkers of this disorder. METHODS: The current study employed a family triad-based case-control design to study the levels of plasma cytokines in families with ASD (n = 45 triads) and controls (n = 38 triads) with a Human Cytokine Twenty-Five-Plex Kit. The Social Responsiveness Scale (SRS) was used to measure social impairment of ASD children. RESULTS: After controlling for the levels of parental cytokines, we identified that interferon-α (IFN-α), interleukin-7 (IL-7), IL-8, IFN-γ-inducible protein-10, and macrophage inflammatory protein-1ß were associated with ASD, and IL-8 was the only cytokine also associated with the levels of both parental cytokines in the offspring-parents regression analysis and three subdomains of SRS (social awareness, cognition, and motivations) in the children with ASD. The receiver operating characteristic curve showed that the log-transformed IL-8 level discriminated children with autism from controls with an area under the curve of 0.858 (95% confidence interval: 0.777-0.939). CONCLUSIONS: Our study suggests that IL-8 is a potential biomarker for ASD and may be involved in the pathogenesis of ASD. IMPACT: The study suggests that IL-8 is a promising biomarker for ASD and may be involved in the pathogenesis of ASD. Only a very few studies have reported the parental cytokine levels. The significant strength of this article is that we applied the family triad-based approach to explore cytokine levels in families with autism and controls. There are no objective biomarkers, making the accurate diagnosis, prognostic prediction and effective treatment difficult, and our study provides promising results.

Efficacy of 5-Aminolevulinic Acid (ALA)-Photodynamic Therapy (PDT) in Refractory Vulvar Lichen Sclerosus: Preliminary Results.

BACKGROUND As a chronic inflammatory skin disease of unknown etiology, vulvar lichen sclerosus (VLS) mainly affects postmenopausal and perimenopausal women. The main clinical manifestations of VLS include itching, burning pain, and sexual dysfunction, which can lead to a decline in quality of life. The existing treatment options include topical corticosteroid ointment, estrogen, and traditional Chinese medicine; however, their therapeutic effects on VLS remain unsatisfactory. MATERIAL AND METHODS Thirty patients with VLS and routine treatment failure were treated with 5-aminolevulinic acid (ALA)-photodynamic therapy (PDT). A 20% ALA water-in-oil emulsion was applied to the vulvar lesions and sealed with plastic film for 3 h. Patients were irradiated at a power density of 60 to 90 mW/cm² with a red light at a wavelength of 635±15 nm for 20 min, delivering a total dose of 100 to 150 J/cm² per session. The treatment was repeated 3 times every 2 weeks. The objective parameters, female sexual function index (FSFI) and quality of life (QoL) scores, were used before and after treatment to evaluate the clinical curative effect. RESULTS All patients completed 3 treatment cycles of ALA-PDT and follow-up visits. The clinical symptoms of pruritus completely disappeared in 27 cases, and itching improved from severe to mild in 3 cases. The pathological changes of all patients were objectively improved. FSFI score decreased significantly after treatment (P<0.001). The main adverse effects of ALA-PDT were pain, erythema, and swelling. These adverse effects were temporary and tolerable. The QoL score was significantly improved after treatment (P<0.001). CONCLUSIONS ALA-PDT is an effective and safe approach for the treatment of VLS.

Predictive factors of surgical site infection after hysterectomy for endometrial carcinoma: a retrospective analysis.

BACKGROUND: Surgical site infection (SSI) is a common postoperative complication. We aimed to analyze the potential risk factors of SSI in patients with endometrial carcinoma. METHODS: Patients with endometrial carcinoma who underwent surgery treatment in our hospital from Sept 1, 2018 to August 31, 2020 were included. We retrospectively compared the characteristics of SSI and no SSI patients, and logistic regression analyses were performed to identify the risk factors of SSI in patients with endometrial carcinoma. RESULTS: A total of 318 postoperative patients with endometrial carcinoma were included. The incidence of SSI in patients with endometrial carcinoma was 14.47 %. There were significant differences on the FIGO stage, type of surgery, durations of drainage, postoperative serum albumin and postoperative blood sugar (all p < 0.05), and no significant differences on the age, BMI, hypertension, diabetes, hyperlipidemia, estimated blood loss, length of hospital stay were found (all p > 0.05). FIGO stage IV (HR3.405, 95 %CI 2.132-5.625), open surgery (HR2.692, 95 %CI 1.178-3.454), durations of drainage ≥ 7 d (HR2.414,95 %CI 1.125-2.392), postoperative serum albumin < 30 g/L (HR1.912,95 %CI 1.263-2.903), postoperative blood sugar ≥ 10 mmol/L (HR1.774,95 %CI 1.102-2.534) were the independent risk factors of SSI in patients with endometrial carcinoma (all p < 0.05). CONCLUSIONS: Measures including reasonable control of serum albumin and blood glucose levels, minimally invasive surgery as much as possible, timely assessment of drainage and early removal of the tube may be beneficial to reduce the postoperative SSI in in patients with endometrial carcinoma.

High-Magnetic-Field Tunneling Spectra of ABC-Stacked Trilayer Graphene on Graphite.

ABC-stacked trilayer graphene (TLG) was predicted to exhibit novel many-body phenomena due to the existence of almost dispersionless flat bands near the charge neutrality point. Here, using high-magnetic-field scanning tunneling microscopy, we present Landau Level (LL) spectroscopy measurements of high-quality ABC-stacked TLG on graphite. We observe an approximately linear magnetic-field scaling of valley splitting and spin splitting in the ABC-stacked TLG. Our experiment indicates that the spin splitting decreases dramatically with increasing the LL index. When the lowest LL is partially filled, we find an obvious enhancement of the spin splitting, attributing to strong many-body effects. Moreover, we observe linear energy scaling of the inverse lifetime of quasiparticles, providing an additional evidence for the strong electron-electron interactions in the ABC-stacked TLG. These results imply that interesting broken-symmetry states and novel electron correlated effects could emerge in the ABC-stacked TLG in the presence of high magnetic fields.

Combinatorial optical complex wavelet-fractional Fourier transform.

By using the technique of integration within ordered product of operators, we put forward the combinatorial optical complex wavelet-fractional Fourier transform in the context of quantum optics. The unitary operator for this new transform is found and its normally ordered form is deduced. We apply this new transform to the two-mode vacuum state and the two-mode number state and explain that it can be used to analyze and identify various quantum optical states.

Noise-Induced Cochlear Synaptopathy and Ribbon Synapse Regeneration: Repair Process and Therapeutic Target.

The synapse between the inner hair cells (IHCs) and the spiral ganglion neurons (SGNs) in mammalian cochleae is characterized as having presynaptic ribbons and therefore is called ribbon synapse. The special molecular organization is reviewed in this chapter in association with the functional feature of this synapse in signal processing. This is followed by the review on noise-induced damage to this synapse with a focus on recent reports in animal models in which the effect of brief noise exposures is observed without causing significant permanent threshold shift (PTS). In this regard, the potential mechanism of the synaptic damage by noise and the impact of this damage on hearing are summarized to clarify the concept of noise-induced hidden hearing loss, which is defined as the functional deficits in hearing without threshold elevation. A controversial issue is addressed in this review as whether the disrupted synapses can be regenerated. Moreover, the review summarizes the work of therapeutic research to protect the synapses or to promote the regeneration of the synapse after initial disruption. Lastly, several unresolved issues are raised for investigation in the future.