Nobiletin Inhibits Expression of Inflammatory Mediators and Regulates JNK/ERK/p38 MAPK and PI3K/Akt Pathways in Human Osteoarthritic Chondrocytes

Purpose: To investigate the anti-inflammatory effects of nobiletin on human osteoarthritic chondrocytes and also to explore possible related molecular events.Methods: Isolated human osteoarthritic chondrocytes were stimulated with IL-1β. The effect of nobiletin (75, 150 or 300 μg) on chondrocyte viability was assessed. Furthermore, the effect on NO production was determined using Griess reagent while the levels of IL-6 and PGE2 were assessed by enzyme linked immunosorbent assay (ELISA). The influence of nobiletin on the expression of COX-2, iNOS and proteins of PI3/Akt, NF-κB and MAPK cascades were also assessed.Results: Nobiletin (75, 150 and 300 μg) significantly (p < 0.05) improved the viability of chondrocytes, and remarkably reduced the levels of NO, IL-6 and PGE2. The expression levels of COX-2 and iNOS both at mRNA and protein levels were strikingly reduced by nobiletin, in a dose-dependent way. In addition, nobiletin caused marked (p < 0.05) down-regulation of the NF-κB signalling pathway. IL-1β- induced activation of PI3/Akt, and JNK, ERK and p38 MAPK cascades were significantly (p < 0.05) inhibited by nobiletin with 300 μg dose exhibiting maximum effects.Conclusion: Inflammatory cytokines are critically involved in the pathogenesis of OA. Significant suppression of cytokines and modulation of PI3/Akt and MAPK signalling cascades by nobiletin suggests its potent anti-inflammatory and anti-osteoarthritic effects.Keywords: Chondrocytes, Inflammation, Mitogen-activated protein kinases, NF-κB, Nobiletin, Osteoarthriti

A high performance surface acoustic wave visible light sensor using novel materials: Bi2S3 nanobelts

Low dimensional Bi2S3 materials are excellent for use in photodetectors with excellent stability and fast response time. In this work, we developed a visible light sensor with good performance based on surface acoustic wave (SAW) devices using Bi2S3 nanobelts as the sensing materials. The SAW delay-line sensor was fabricated on ST-cut quartz with a designed wavelength of 15.8 microns using conventional photolithography techniques. The measured center frequency was 200.02 MHz. The Bi2S3 nanobelts prepared by a facile hydrothermal process were deposited onto SAW sensors by spin-coating. Under irradiation of 625 nm visible light with a power intensity of 170 μW cm−2, the sensor showed a fast and large response with a frequency upshift of 7 kHz within 1 s. The upshift of the frequency of the SAW device is mainly attributed to the mass loading effect caused by the desorption of oxygen from the Bi2S3 nanobelts under visible light radiation

A high performance surface acoustic wave visible light sensor using novel materials: Bi2S3 nanobelts

Low dimensional Bi2S3 materials are excellent for use in photodetectors with excellent stability and fast response time. In this work, we developed a visible light sensor with good performance based on surface acoustic wave (SAW) devices using Bi2S3 nanobelts as the sensing materials. The SAW delay-line sensor was fabricated on ST-cut quartz with a designed wavelength of 15.8 microns using conventional photolithography techniques. The measured center frequency was 200.02 MHz. The Bi2S3 nanobelts prepared by a facile hydrothermal process were deposited onto SAW sensors by spin-coating. Under irradiation of 625 nm visible light with a power intensity of 170 μW cm−2, the sensor showed a fast and large response with a frequency upshift of 7 kHz within 1 s. The upshift of the frequency of the SAW device is mainly attributed to the mass loading effect caused by the desorption of oxygen from the Bi2S3 nanobelts under visible light radiation

Marine propulsion shaft system fault diagnosis method based on partly ensemble empirical mode decomposition and SVM

This paper investigates the application of the Partly Ensemble Empirical Mode Decomposition (PEEMD), Principal Component Analysis (PCA) and Support Vector Machine (SVM) on signal processing, attribute reduction and pattern recognition. On this basis, a novel method for mechanical faulty diagnosis based on PEEMD, PCA and SVM is presented, which utilizes the PEEMD to extract faulty feature parameters from the statistical characteristics of intrinsic mode functions to constitute feature vectors, and then makes the attribute reduction by PCA method to obtain the key features, lastly these key features are input into GA-optimized SVM to accomplish faulty pattern recognition. The experimental results of the proposed method to fault diagnosis of the rolling bearing and stern bearing on marine propulsion shaft system show that this method can extract the faulty features, which have better classification ability and at the same time reduce the computation complexity significantly, accordingly improve the classifier efficiency and achieve a better classification performance

Simulating cold regions hydrological processes using a modular model in the west of China

SummaryThe Cold Regions Hydrological Model platform (CRHM), a flexible object-oriented modeling system, was devised to simulate cold regions hydrological processes and predict streamflow by its capability to compile cold regions process modules into purpose-built models. In this study, the cold regions hydrological processes of two basins in western China were evaluated using CRHM models: Binggou basin, a high alpine basin where runoff is mainly caused by snowmelt, and Zuomaokong basin, a steppe basin where the runoff is strongly affected by soil freezing/thawing. The flexibility and modular structure of CRHM permitted model structural intercomparison and process falsification within the same model framework to evaluate the importance of snow energy balance, blowing snow and frozen soil infiltration processes to successful modeling in the cold regions of western China. Snow accumulation and ablation processes were evaluated at Binggou basin by testing and comparing similar models that contained different levels of complexity of snow redistribution and ablation modules. The comparison of simulated snow water equivalent with observations shows that the snow accumulation/ablation processes were simulated much better using an uncalibrated, physically based energy balance snowmelt model rather than with a calibrated temperature index snowmelt model. Simulated seasonal snow sublimation loss was 138mm water equivalent in the alpine region of Binggou basin, which accounts for 47 % of 291mm water equivalent of snowfall, and half of this sublimation loss is attributed to 70mm water equivalent of sublimation from blowing snow particles. Further comparison of simulated results through falsification of different snow processes reveals that estimating blowing snow transport processes and sublimation loss is vital for accurate snowmelt runoff calculations in this region. The model structure with the energy balance snowmelt and blowing snow components performed well in reproducing the measured streamflow using minimal calibration, with R2 of 0.83 and NSE of 0.76. The influence of frozen soil and its thaw on runoff generation was investigated at Zuomaokong basin by comparing streamflow simulated by similar CRHM models with and without an infiltration to frozen soil algorithm. The comparison of simulated streamflow with observation shows that the model which included an algorithm describing frozen soil infiltration simulated the main runoff events for the spring thawing period better than that which used an unfrozen infiltration routine, with R2 of 0.87 and NSE of 0.79. Overall, the test results for the two basins show that hydrological models that use appropriate cold regions algorithms and a flexible spatial structure can predict cold regions hydrological processes and streamflow with minimal calibration and can even perform better than more heavily calibrated models in this region. Given that CRHM and most of its algorithms were developed in western Canada, this is encouraging for predicting hydrology in ungauged cold region basins around the world

Embedded Character Recognition System using Random Forest Algorithm for IC Inspection System

Character recognition system based on human inspection is unpractical due to lack of accuracy and high cost. Therefore, investigating on automated character inspection system by computer is needed to improve the accuracy, reduce the cost and inspection time. In this project, a Beagle Bone Black (BBB) was used as a processing device and Logitech webcam was used for as an image acquisition device. Total of 1080 training samples will undergo the image pre-processing, character segmentation, feature extraction and training using random forest classifier. The optimal parameter values of random forest classifier are determined by computing crossvalidation misclassification rate. The maximum number of splits, number of trees, and learning rate that yields the zeromisclassification rate is 1, 39 and 0.10 respectively. The process of testing random forest classifier was done using SN74LS27N chip under five different illuminations: no LED, one LED, two LED, three LED and four LED. From the experiments, it shows that the proposed system able to achieve 90.00% of accuracy within 1second to recognize characters on the SN74LS27N chip compared to 65.56% accuracy of human inspection

Demonstration of Adiabatic Variational Quantum Computing with a Superconducting Quantum Coprocessor

Adiabatic quantum computing enables the preparation of many-body ground states. This is key for applications in chemistry, materials science, and beyond. Realisation poses major experimental challenges: Direct analog implementation requires complex Hamiltonian engineering, while the digitised version needs deep quantum gate circuits. To bypass these obstacles, we suggest an adiabatic variational hybrid algorithm, which employs short quantum circuits and provides a systematic quantum adiabatic optimisation of the circuit parameters. The quantum adiabatic theorem promises not only the ground state but also that the excited eigenstates can be found. We report the first experimental demonstration that many-body eigenstates can be efficiently prepared by an adiabatic variational algorithm assisted with a multi-qubit superconducting coprocessor. We track the real-time evolution of the ground and exited states of transverse-field Ising spins with a fidelity up that can reach about 99%.Comment: 12 pages, 4 figure

Pengaruh Implementasi Kebijakan Tambahan Penghasilan Terhadap Motivasi Kerja Pegawai Dinas Kesehatan Provinsi Sulawesi Tengah

This study was conducted to determine how much influence the implementation of additional policies on work motivation income civil servants in Central Sulawesi province. This study uses the theory of Van Meter and Van Horn with standard dimensions and policy objectives, resources, communication between the implementing agency, the implementing body characteristics, social, economic and political, disposition / attitude implementers. The method used in the study is survay analytic using cross sectional design of a study to study the dynamics of the correlation between risk factors by means of observation or data collection approach as well. The results showed that the magnitude of the effect of the implementation of additional policies on work motivation of employees earning the provincial health bureau in Central Sulawesi was the degree of correlation moderate to very low-level relations with the interval of the correlation coefficient between 0.172 up to 0.457