Search

Senescence-accelerated mouse prone 8 (SAMP8) mice exhibit cognitive defects and neuron loss with aging, and are used to study anti-aging effects of Dendrobium nobile alkaloids (DNLA). SAMP8 mice were orally given DNLA from ages 6 to 10 months. At 10 months of age, behavioral tests and neuron damage were evaluated. Protein was extracted and subjected to phosphorylated proteomic analysis. The cognitive deficits and neuron loss in hippocampus and cortex of aged SAMP8 mice were improved by DNLA. Hippocampal proteomic analysis showed differentially expressed protein/genes in SAMP8 compared to age-matched senescence-accelerated resistant mice, including altered tubulin binding, microtubule binding, etc. via Gene Oncology. KEGG revealed endocytosis, mRNA surveillance, tight junction, protein processing in endoplasmic reticulum, aldosterone synthesis and secretion, and glucagon signaling pathway changes. Upregulated protein/genes in the hippocampus of SAMP8 mice, such as Lmtk3, Usp10, Dzip1, Csnk2b, and Rtn1, were attenuated by DNLA; whereas downregulated protein/genes, such as Kctd16, Psd3, Bsn, Atxn2l, and Kif1a, were rescued by DNLA. The aberrant protein/gene expressions of SAMP8 mice were correlated with transcriptome changes of Alzheimer’s disease in the GEO database, and were attenuated by DNLA. Thus, DNLA improved cognitive dysfunction and ameliorated neuronal injury in aged SAMP8 mice, and attenuated aberrant protein/gene expressions.

This paper investigates the kinematics and dynamics of multi-rigid-body systems in screw form. The Newton–Euler dynamics equations are established in screw coordinates. All forces and torques of the multi-rigid-body system can be solved straightforwardly since they are explicit in the form of screw coordinates. The displacement and acceleration are unified in matrix form, which associates the kinematics and dynamics with variable of velocity. A one-step numerical algorithm only is needed to solve the displacements and accelerations. As a result, all absolute displacements, velocities, and accelerations are directly obtained by one kinematic equation. The kinematics and dynamics of Gough–Stewart platform validate this the method. In this paper, the kinematics and dynamics are carried out with the example of a Gough–Stewart platform, which represents the most complex multi-rigid-body system, to verify the computational dynamics method. The proposed algorithm is also fit for the kinematics and dynamics modeling of other multi-rigid-body systems.

Surface wind speed forecast from an operational WRF Ensemble Prediction System (WEPS) was verified, and the system-bias representations of the WEPS were investigated. Results indicated that error characteristics of the ensemble 10-m wind speed forecast were diurnally variated and clustered with the usage of the planetary boundary layer (PBL) scheme. To correct the error characteristics of the ensemble wind speed forecast, three system-bias representations with decaying average algorithms were studied. One of the three system-bias representations is represented by the forecast error of the ensemble mean (BC01), and others are assembled from each PBC group (BC03) as well as an independent member (BC20). System bias was calculated daily and updated within a 5-month duration, and the verification was conducted in the last month, including 316 gauges around Taiwan. Results show that the mean of the calibrated ensemble (BC03) was significantly improved as the calibrated ensemble (BC20), but both demonstrated insufficient ensemble spread. However, the calibrated ensemble, BC01, with the best dispersion relation could be extracted as a more valuable deterministic forecast via the probability matched mean method (PMM).

The antioxidant effect of probiotics has been widely recognized across the world, which is of great significance in food, medicine, and aquaculture. There are abundant marine microbial resources in the ocean, which provide a new space for humans to explore new probiotics. Previously, we reported on the anti-infective effects of Planococcus maritimu ML1206, a potential marine probiotic. The antioxidant activity of ML1206 in C. elegans was studied in this paper. The study showed that ML1206 could improve the ability of nematodes to resist oxidative stress and effectively prolong their lifespan. The results confirmed that ML1206 could significantly increase the activities of CAT and GSH-PX, and reduce the accumulation of reactive oxygen species (ROS) in nematodes under oxidative stress conditions. In addition, ML1206 promoted DAF-16 transfer to the nucleus and upregulated the expression of sod-3, hsp-16.2, and ctl-2, which are downstream antioxidant-related genes of DAF-16. Furthermore, the expression of the SOD-3::GFP and HSP-16.2::GFP was significantly higher in the transgenic strains fed with ML1206 than that in the control group fed with OP50, with or without stress. In summary, these findings suggest that ML1206 is a novel marine probiotic with an antioxidant function that stimulates nematodes to improve their defense abilities against oxidative stress and prolong the lifespan by regulating the translocation of FOXO/DAF-16. Therefore, ML1206 may be explored as a potential dietary supplement in aquaculture and for anti-aging and antioxidant purposes.

Design and fabrication of efficient and stable photocatalysts are critically required for practical applications of solar water splitting. Herein, a series of WSe2/TiO2 nanocomposites were constructed through a facile mechanical grinding method, and all of the nanocomposites exhibited boosted photocatalytic hydrogen evolution. It was discovered that the enhanced photocatalytic performance was attributed to the efficient electron transfer from TiO2 to WSe2 and the abundant active sites provided by WSe2 nanosheets. Moreover, the intimate heterojunction between WSe2 nanosheets and TiO2 favors the interfacial charge separation. As a result, a highest hydrogen evolution rate of 2.28 mmol/g·h, 114 times higher than pristine TiO2, was obtained when the weight ratio of WSe2/(WSe2 + TiO2) was adjusted to be 20%. The designed WSe2/TiO2 heterojunctions can be regarded as a promising photocatalysts for high-throughput hydrogen production.

With the widespread occurrence of aquaculture diseases and the broad application of antibiotics, drug-resistant pathogens have increasingly affected aquatic animals’ health. Marine probiotics, which live under high pressure in a saltwater environment, show high potential as a substitute for antibiotics in the field of aquatic disease control. In this study, twenty strains of non-hemolytic bacteria were isolated from the intestine of wild oysters and perch, and a model of Caenorhabditis elegans infected by Vibrio anguillarum was established. Based on the model, ML1206, which showed a 99% similarity of 16S rRNA sequence to Planococcus maritimus, was selected as a potential marine probiotic, with strong antibacterial capabilities and great acid and bile salt tolerance, to protect Caenorhabditis elegans from being damaged by Vibrio anguillarum. Combined with plate counting and transmission electron microscopy, it was found that strain ML1206 could significantly inhibit Vibrio anguillarum colonization in the intestinal tract of Caenorhabditis elegans. Acute oral toxicity tests in mice showed that ML1206 was safe and non-toxic. The real-time qPCR results showed a higher expression level of genes related to the antibacterial peptide (ilys-3) and detoxification (ugt-22, cyp-35A3, and cyp-14A3) in the group of Caenorhabditis elegans protected by ML1206 compared to the control group. It is speculated that ML1206, as a potential probiotic, may inhibit the infection caused by Vibrio anguillarum through stimulating Caenorhabditis elegans to secrete antibacterial effectors and detoxification proteins. This paper provides a new direction for screening marine probiotics and an experimental basis to support the potential application of ML1206 as a marine probiotic in aquaculture.

Rosa roxburghii Tratt. fruit juice (Cili) is used as a medicinal and edible resource in China due to its antioxidant and hypolipidemic potentials. The efficacy of Cili in protecting alcohol-induced liver injury and its underlying mechanism was investigated. C57BL/6J mice received a Lieber-DeCarli liquid diet containing alcohol to produce liver injury. After the mice were adapted gradually to 5% alcohol, Cili (4 mL and 8 mL/kg/day for 4 weeks) were gavaged for treatment. The serum enzyme activities, triglyceride levels, histopathology and Oil-red O staining were examined. The RNA-Seq and qPCR analyses were performed to determine the protection mechanisms. Cili decreased serum and liver triglyceride levels in mice receiving alcohol. Hepatocyte degeneration and steatosis were improved by Cili. The RNA-Seq analyses showed Cili brought the alcohol-induced aberrant gene pattern towards normal. The qPCR analysis verified that over-activation of CAR and PXR (Cyp2a4, Cyp2b10 and Abcc4) was attenuated by Cili. Cili alleviated overexpression of oxidative stress responsive genes (Hmox1, Gsta1, Gstm3, Nqo1, Gclc, Vldlr, and Cdkn1a), and rescued alcohol-downregulated metabolism genes (Angptl8, Slc10a2, Ces3b, Serpina12, C6, and Selenbp2). Overall, Cili was effective against chronic alcohol liver injury, and the mechanisms were associated with decreased oxidative stress, improved lipid metabolism through modulating nuclear receptor CAR-, PXR-and Nrf2-mediated pathways.

The effectiveness of a model is the key factor of influencing the reliability-based design optimization (RBDO) of multi-failure turbine blades in the power system. A machine learning-based RBDO approach, called fuzzy multi-SVR learning method, was proposed by absorbing the strengths of fuzzy theory, support vector machine of regression (SVR), and multi-response surface method. The model of fuzzy multi-SVR learning method was established by adopting artificial bee colony algorithm to optimize the parameters of SVR models and considering the fuzziness of constraints based on fuzzy theory, in respect of the basic thought of multi-response surface method. The RBDO model and procedure with fuzzy multi-SVR learning method were then resolved and designed by multi-objective genetic algorithm. Lastly, the fuzzy RBDO of a turbine blade with multi-failure modes was performed regarding the design parameters of rotor speed, temperature, and aerodynamic pressure, and the design objectives of blade stress, strain, and deformation, and the fuzzy constraints of reliability degree and boundary conditions, as well. It is revealed (1) the stress and deformation of turbine blade are reduced by 92.38 MPa and 0.09838 mm, respectively. (2) The comprehensive reliability degree of the blade was improved by 3.45% from 95.4% to 98.85%. (3) It is verified that the fuzzy multi-SVR learning method is workable for the fuzzy RBDO of complex structures just like a multi-failure blade with high modeling precision, as well as high optimization, efficiency, and accuracy. The efforts of this study open a new research way, i.e., machine learning-based RBDO, for the RBDO of multi-failure structures, which expands the application of machine learning methods, and enriches the mechanical reliability design method and theory as well.

Tropical cyclones (TCs) are complex sources of atmospheric gravity waves (GWs). In this study, the Weather Research and Forecasting Model was used to model TC Soudelor (2015) and the induced elliptical structures of GWs in the upper troposphere (UT) and lower stratosphere (LS) prior to its landfall over Taiwan. Conventional, spectral and wavelet analyses exhibit dominant GWs with horizontal and vertical wavelengths, and periods of 16&ndash, 700 km, 1.5&ndash, 5 km, and 1&ndash, 20 h, respectively. The wave number one (WN1) wind asymmetry generated mesoscale inertia GWs with dominant horizontal wavelengths of 100&ndash, 300 km, vertical wavelengths of 1.5&ndash, 2.5 km (3.5 km) and westward (eastward) propagation at the rear of the TC in the UT (LS). It was also revealed to be an active source of GWs. The two warm anomalies of the TC core induced two quasi-diurnal GWs and an intermediate GW mode with a 10-h period. The time evolution of dominant periods could be indicative of changes in TC dynamics. The FormoSat-3/COSMIC (Formosa Satellite Mission-3/Constellation Observing System for Meteorology, Ionosphere, and Climate) dataset confirmed the presence of GWs with dominant vertical wavelengths of about 3.5 km in the UT and LS.

Among the different models that have been proposed to explain the origin of avian flightfrom terrestrial predators, the cursorial and arboreal hypotheses remain the most discussed.However, the fossil data at hand show that, taken separately, both theories have significantlimitations in explaining the origin of flight in bird lineage. Here, we describe an aerodynamicsprinciple that fills in the gaps between those apparently contradictory models. The upslope wind inmountain areas and strong wind in plains provided the meteorological conditions allowingfeathered paravians to glide. The results suggest that smaller, feathered paravians could be lifted toglide down to trees on mountain slopes or even to glide up to high trees in plain areas when meetinga strong airflow as they were pursuing a prey or escaping from a predator. The development ofmore aerodynamical limb feathers was a key factor for gliding down the trees because of thedependency of the resultant force on the surface area of a paravian&rsquo, s body. Later in the evolutionprocess, paravians learned to change the orientation of their wings to gain higher lifts. The proposedprinciple and the results obtained in the present research help to better estimate the aerodynamicbehavior of extinct species and will also help to design an efficient and beneficial system for futureflying robots.

Typhoon WRF (TWRF) based on the Advanced Research Weather Research and Forecasting Model (ARW WRF) was operational at the Central Weather Bureau (CWB) for tropical cyclone (TC) predictions since 2010 (named TWRF V1). CWB has committed to improve this regional model, aiming to increase the model predictability toward typhoons over East Asia. In 2016, an upgraded version designed to replace TWRF V1 became operational (named TWRF V2). Compared with V1, which has triple-nested meshes with coarser resolution (45/15/5 km), V2 increased the model resolution to 15/3 km. Since V1 and V2 were maintained in parallel from 2016 to 2018, this study utilized the real-time forecasts to investigate the impact of model resolution on TC prediction. Statistical measures pointed out the superiority of the high-resolution model on TC prediction. The forecast performance was also found competitive with that of two leading global models. The case study further pointed out, with the higher resolution, the model not only advanced the prediction on the TC track and inner core structure but also improved the representativeness of the complex terrain. Overall, the high-resolution model can better handle the so-called terrain phase-lock effect and, therefore, improve the TC quantitative precipitation forecast over the complex Taiwanese terrain.

Turbine blisk low cycle fatigue (LCF) is affected by various factors such as heat load, structural load, operation parameters and material parameters, it seriously influences the reliability and performance of the blisk and aeroengine. To study the influence of thermal-structural coupling on the reliability of blisk LCF life, the generalized regression extreme neural network (GRENN) method was proposed by integrating the basic thoughts of generalized regression neural network (GRNN) and the extreme response surface method (ERSM). The mathematical model of the developed GRENN method was first established in respect of the LCF life model and the ERSM model. The method and procedure for reliability and sensitivity analysis based on the GRENN model were discussed. Next, the reliability and sensitivity analyses of blisk LCF life were performed utilizing the GRENN method under a thermal-structural interaction by regarding the randomness of gas temperature, rotation speed, material parameters, LCF performance parameters and the minimum fatigue life point of the objective of study. The analytical results reveal that the reliability degree was 0.99848 and the fatigue life is 9419 cycles for blisk LCF life when the allowable value is 6000 cycles so that the blisk has some life margin relative to 4500 cycles in the deterministic analysis. In comparison with ERSM, the computing time and precision of the proposed GRENN under 10,000 simulations is 1.311 s and 99.95%. This is improved by 15.18% in computational efficiency and 1.39% in accuracy, respectively. Moreover, high efficiency and high precision of the developed GRENN become more obvious with the increasing number of simulations. In light of the sensitivity analysis, the fatigue ductility index and temperature are the key factors of determining blisk LCF life because their effect probabilities reach 41% and 26%, respectively. Material density, rotor speed, the fatigue ductility coefficient, the fatigue strength coefficient and the fatigue ductility index are also significant parameters for LCF life. Poisson&rsquo, s ratio and elastic modulus of materials have little effect. The efforts of this paper validate the feasibility and validity of GRENN in the reliability analysis of blisk LCF life and give the influence degrees of various random parameters on blisk LCF life, which are promising to provide useful insights for the probabilistic optimization of turbine blisk LCF life.

Polyaniline (PANI), an attractive conductive polymer, has been successfully applied in fabricating various types of enzyme-based biosensors. In this study, we have employed mesoporous silica SBA-15 to stably entrap horseradish peroxidase (HRP), and then deposited the loaded SBA-15 on the PANI modified platinum electrode to construct a GA/SBA-15(HRP)/PANI/Pt biosensor. The mesoporous structures and morphologies of SBA-15 with or without HRP were characterized. Enzymatic protein assays were employed to evaluate HRP immobilization efficiency. Our results demonstrated that the constructed biosensor displayed a fine linear correlation between cathodic response and H(2)O(2) concentration in the range of 0.02 to 18.5 mM, with enhanced sensitivity. In particular, the current approach provided the PANI modified biosensor with improved stability for multiple measurements.

Typhoon rainfall is one of the most important water resources in Taiwan. However, heavy rainfall during typhoons often leads to serious disasters. Therefore, accurate typhoon rainfall forecasts are always desired for water resources managers and disaster warning systems. In this study, the quantitative rainfall forecasts from an ensemble numerical weather prediction system in Taiwan are used. Furthermore, a novel strategy, which is based on the use of a self-organizing map (SOM) based cluster analysis technique, is proposed to integrate these ensemble forecasts. By means of the SOM-based cluster analysis technique, ensemble forecasts that have similar features are clustered. That is helpful for users to effectively combine these ensemble forecasts for providing better typhoon rainfall forecasts. To clearly demonstrate the advantage of the proposed strategy, actual application is conducted during five typhoon events. The results indicate that the ensemble rainfall forecasts from numerical weather prediction models are well categorized by the SOM-based cluster analysis technique. Moreover, the integrated typhoon rainfall forecasts resulting from the proposed strategy are more accurate when compared to those from the conventional method (i.e., the ensemble mean of all forecasts). In conclusion, the proposed strategy provides improved forecasts of typhoon rainfall. The improved quantitative rainfall forecasts are expected to be useful to support disaster warning systems as well as water resources management systems during typhoons.