Modelling and assessment of pneumatic artificial muscle

The pneumatic artificial muscle (PAM) being a new type of actuator is widespread used in engineering field because it possesses the attractive attributes of safe operation, low cost, high output force to volume. It is a prime requirement to establish an effective theoretical model to predict the performance of the PAM as well as other actuators. In this paper a new PAM model is established by employing conservation energy and the Mooney-Rivlin strain energy function for the rubber of PAM. This model is compared with the previous models and the experimental results and it shows that the model truly improves the assessment of forces and contraction that can be achieved by the PAM. However, the significant discrepancy still exists between the theoretical model and the experiment. A number of factors, like friction force, which result in the discrepancy are discusse

Searching for radio pulsation from SGR 1935+2154 with the Parkes Ultra-Wideband Low receiver

Magnetars have been proposed to be the origin of FRBs soon after its initial discovery. The detection of the first Galactic FRB 20200428 from SGR 1935+2154 has made this hypothesis more convincing. In October 2020, this source was supposed to be in an extremely active state again. We then carried out a 1.6-hours follow-up observation of SGR 1935+2154 using the new ultra-wideband low (UWL) receiver of the Parkes 64\,m radio telescope covering a frequency range of 704$-$4032 MHz. However, no convincing signal was detected in either of our single pulse or periodicity searches. We obtained a limit on the flux density of periodic signal of $\rm 3.6\,\mu Jy$ using the full 3.3GHz bandwidth data sets, which is the strictest limit for that of SGR 1935+2154. Our full bandwidth limit on the single pulses fluence is 35mJy ms, which is well below the brightest single pulses detected by the FAST radio telescope just two before our observation. Assuming that SGR 1935+2154 is active during our observation, our results suggest that its radio bursts are either intrinsically narrowband or show a steep spectrum

Machine learning approach for analysing and predicting the modulus response of the structural epoxy adhesive at elevated temperatures

For bonded Fibre Reinforced Polymer (FRP) strengthening systems in civil engineering projects, the adhesive joint performance is a key factor in the effectiveness of the strengthening; however, it is known that the material properties of structural epoxy adhesives change with temperature. This present paper examines the implied relationship between the curing regimes and the storage modulus response of the adhesive using a Machine Learning (ML) approach. A dataset containing 157 experimental data collected from the scientific papers and academic theses was used for training and testing an Artificial Neural Network (ANN) model. The sensitivity analysis reveals that the curing conditions have a significant effect on the glass transition temperatures (Tg) of the adhesive, and consequently on the storage modulus response at elevated temperatures. Curing at an extremely high temperature for a long time does not, however, guarantee a better thermal performance. For the studied adhesive, curing in a warm (≥ 45°C) and dry (near 0 % RH) environment for 21 days is recommended for practical applications. A software with a Graphical User Interface (GUI) was established, which can predict the storage modulus response of the adhesive, plot the corresponding response curve, and estimate the optimum curing condition.</p

Evaluating the effect of curing conditions on the glass transition of the structural adhesive using conditional tabular generative adversarial networks

Owing to its structural advantages, adhesively bonding fibre-reinforced polymers have been a promising solution for strengthening constructions. However, the effectiveness of this technique is significantly influenced by the material properties of the adhesive layer, which are largely determined by its curing condition. A comprehensive analysis of the effect of curing conditions on structural adhesives is hampered by the lack of sufficient experimental data. To mitigate such a limitation, this present study utilises a deep machine learning (ML) tool, the conditional tabular generative adversarial networks (CTGAN), to generate plausible synthetic dataset for developing a robust data-driven model. An artificial neural network (ANN) was trained on synthetic data and tested on real data, following the "Train on Synthetic – Test on Real" philosophy. The ultimately developed CTGAN-ANN model was validated by newly conducted experiments and several published studies (R2 ≥ 0.95), which demonstrated the ability to provide accurate estimates of the glass transition temperature values of the polymer adhesive. A comprehensive evaluation of the effect of each curing condition variable on the adhesive was performed, which revealed the underlying relationships, indicating that curing temperature and curing time have a positive effect, but that curing humidity has a negative effect. The ML model developed could inform the practical use of the structural adhesive in civil engineering

Flux density measurements for 32 pulsars in the 20 cm band

Flux density measurements provide fundamental observational parameters that describe a pulsar. In the current pulsar catalogue, 27% of radio pulsars have no flux density measurement in the 20 cm observing band. Here, we present the first measurements of the flux densities in this band for 32 pulsars observed using the Parkes radio telescope and provide updated pulse profiles for these pulsars. We have used both archival and new observations to make these measurements. Various schemes exist for measuring flux densities. We show how the flux densities measured vary between these methods and how the presence of radio-frequency-interference will bias flux density measurementsComment: Accepted by RA

One-pot synthesis of 2-alkyl cycloketones on bifunctional Pd/ZrO₂ catalyst

2-Alkyl cycloketones are essential chemicals and intermediates for synthetic perfumes and pesticides, which are conventionally produced by multistep process including aldol condensation, separation and hydrogenation. In present work, a batch one-pot cascade approach using aldehydes and cycloketones as the raw materials, and a bifunctional Pd/ZrO2 catalyst was developed for the synthesis of 2-alkyl cycloketones, e.g., cyclohexanone and cycloheptanone. Very high aldehydes (except for paraldehyde with large steric hindrance) conversion and high yields for 2-alkyl cycloketones (e.g., 99 % of conversion for n-butanal and 76 wt.% of yield for 2-butyl cyclohexanone) were obtained at mild temperature of 140 °C. After 10 cycles of reuse, Pd/ZrO2 catalyst showed slight deactivation (ca. 5 % conversion and 10 % yield losses), due to the coke on the catalyst. However, the performance of the catalyst was completely recovered after an oxidative regeneration

SOAPsplice: Genome-Wide ab initio Detection of Splice Junctions from RNA-Seq Data

RNA-Seq, a method using next generation sequencing technologies to sequence the transcriptome, facilitates genome-wide analysis of splice junction sites. In this paper, we introduce SOAPsplice, a robust tool to detect splice junctions using RNA-Seq data without using any information of known splice junctions. SOAPsplice uses a novel two-step approach consisting of first identifying as many reasonable splice junction candidates as possible, and then, filtering the false positives with two effective filtering strategies. In both simulated and real datasets, SOAPsplice is able to detect many reliable splice junctions with low false positive rate. The improvement gained by SOAPsplice, when compared to other existing tools, becomes more obvious when the depth of sequencing is low. SOAPsplice is freely available at http://soap.genomics.org.cn/soapsplice.html

Probing the Emission States of PSR J1107−5907

The emission from PSR J1107−5907 is erratic. Sometimes the radio pulse is undetectable, at other times the pulsed emission is weak, and for short durations the emission can be very bright. In order to improve our understanding of these state changes, we have identified archival data sets from the Parkes radio telescope in which the bright emission is present, and find that the emission never switches from the bright state to the weak state, but instead always transitions to the "off" state. Previous work had suggested the identification of the "off" state as an extreme manifestation of the weak state. However, the connection between the "off" and bright emission reported here suggests that the emission can be interpreted as undergoing only two emission states: a "bursting" state consisting of both bright pulses and nulls, and the weak emission state

ZnO nanorod arrays assembled on activated carbon fibers for photocatalytic degradation:Characteristics and synergistic effects

Well-aligned ZnO nanorod arrays were assembled on activated carbon fibers by a stepwise sequence of sol-gel and hydrothermal synthesis methods. These ZnO nanorod arrays on activated carbon fibers having different characteristics such as surface area, rod concentration, aspect ratio and defect level, were applied as catalysts for the photodegradation of an aqueous methylene blue solution. They showed very promising methylene blue adsorbility in the dark (ca. 0.025–0.031 mg methylene blue m−2 catalyst, vs. 0.072 mg methylene blue m−2 activated carbon fibers). Significantly, the defect level of ZnO nanorod arrays has a major effect on the turnover frequency compared to other characteristics. A synergistic effect between activated carbon fibers and ZnO nanocrystals on enhancing turnover frequency was more significant for the well-assembled ZnO nanorod arrays on activated carbon fibers catalysts compared to the mechanically mixed ZnO powder with activated carbon fibers catalyst. Further, turnover frequency for the ZnO nanorod arrays on activated carbon fibers (0.00312 molmethylene blue molZnO−1 h−1) was twice higher than that for the corresponding bare ZnO nanorod arrays, and 3 times higher than that for a commercial ZnO powder. In addition, ZnO nanorod arrays on activated carbon fibers show high degradation (77.5%) and mineralization (55.0%) levels for methylene blue, and also good reusability (or stability) as demonstrated by a sequential 5-time recycle routine. These outstanding features indicate that activated carbon fibers supported ZnO nanorod arrays have significant potential to be used as catalysts for photodegradation

On the Circular Polarisation of Repeating Fast Radio Bursts

Fast spinning (e.g., sub-second) neutron star with ultra-strong magnetic fields (or so-called magnetar) is one of the promising origins of repeating fast radio bursts (FRBs). Here we discuss circularly polarised emissions produced by propagation effects in the magnetosphere of fast spinning magnetars. We argue that the polarisation-limiting region is well beyond the light cylinder, suggesting that wave mode coupling effects are unlikely to produce strong circular polarisation for fast spinning magnetars. Cyclotron absorption could be significant if the secondary plasma density is high. However, high degrees of circular polarisation can only be produced with large asymmetries in electrons and positrons. We draw attention to the non-detection of circular polarisation in current observations of known repeating FRBs. We suggest that the circular polarisation of FRBs could provide key information on their origins and help distinguish different radiation mechanisms.Comment: ApJ accepte