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Venom proteome of Bungarus sindanus (Sind krait) from Pakistan and in vivo cross-neutralization of toxicity using an Indian polyvalent antivenom
No full textThe proteome of the Pakistani B. sindanus venom was investigated with reverse-phase HPLC and nano-ESI-LCMS/MS analysis. At least 36 distinct proteins belonging to 8 toxin protein families were identified. Three-finger toxin (3FTx), phospholipase A2 (including β-bungarotoxin A-chains) and Kunitz-type serine protease inhibitor (KSPI) were the most abundant, constituting ~95% of total venom proteins. The other toxin proteins of low abundance are snake venom metalloproteinase (SVMP), L-amino acid oxidase (LAAO), acetylcholinesterase (AChE), vespryn and cysteine-rich secretory protein (CRiSP). The venom was highly lethal to mice with LD50 values of 0.04 μg/g (intravenous) and 0.15 μg/g (subcutaneous). The 3FTx proteins are diverse, comprising kappa-neurotoxins, neurotoxin-like protein, non-conventional toxins and muscarinic toxin-like proteins. Kappa-neurotoxins and β-bungarotoxins represent the major toxins that mediate neurotoxicity in B. sindanus envenoming. Alpha-bungarotoxin, commonly present in the Southeast Asian krait venoms, was undetected. The Indian VINS Polyvalent Antivenom (VPAV) was immunoreactive toward the venom, and it moderately cross-neutralized the venom lethality (potency = 0.25 mg/ml). VPAV was able to reverse the neurotoxicity and prevent death in experimentally envenomed mice, but the recovery time was long. The unique toxin composition of B. sindanus venom may be considered in the formulation of a more effective pan-regional, polyspecific antivenom. Biological significance: Bungarus sindanus, an endemic krait species distributed mainly in the Sindh Province of Pakistan is a cause of snake envenomation. Its specific antivenom is, however, lacking. The proteomic study of its venom revealed a substantial presence of κ-bungarotoxins and β-bungarotoxins. The toxin profile corroborates the potent neurotoxicity and lethality of the venom tested in vivo. The heterologous Indian VINS polyvalent antivenom (VPAV) cross-reacted with B. sindanus venom and cross-neutralized the venom neurotoxicity and lethality in mice, albeit the efficacy was moderate. The findings imply that B. sindanus and the phylogenetically related B. caeruleus of India share certain venom epitopes. Research should be advanced to improve the efficacy spectrum of a pan-regional polyspecific antivenom
A machine learning approach of predicting high potential archers by means of physical fitness indicators
No full textk-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. The present study classified and predicted high and low potential archers from a set of physical fitness variables trained on a variation of k-NN algorithms and logistic regression. 50 youth archers with the mean age and standard deviation of (17.0 ± 0.56) years drawn from various archery programmes completed a one end archery shooting score test. Standard fitness measurements of the handgrip, vertical jump, standing broad jump, static balance, upper muscle strength and the core muscle strength were conducted. Multiple linear regression was utilised to ascertain the significant variables that affect the shooting score. It was demonstrated from the analysis that core muscle strength and vertical jump were statistically significant. Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the significant variables identified. k-NN model variations, i.e., fine, medium, coarse, cosine, cubic and weighted functions as well as logistic regression, were trained based on the significant performance variables. The HACA clustered the archers into high potential archers (HPA) and low potential archers (LPA). The weighted k-NN outperformed all the tested models at itdemonstrated reasonably good classification on the evaluated indicators with an accuracy of 82.5 ± 4.75% for the prediction of the HPA and the LPA. Moreover, the performance of the classifiers was further investigated against fresh data, which also indicates the efficacy of the weighted k-NN model. These findings could be valuable to coaches and sports managers to recognise high potential archers from a combination of the selected few physical fitness performance indicators identified which would subsequently save cost, time and energy for a talent identification programme
Meta-cognitive Recurrent Recursive Kernel OS-ELM for concept drift handling
No full textIn this paper, a Meta-cognitive Recurrent Recursive Kernel Online Sequential Extreme Learning Machine with Drift Detector Mechanism (meta-RRKOS-ELM-DDM) is proposed. It combines the strengths of Recurrent Kernel Online Sequential Extreme Learning Machine with a new modified Drift Detector Mechanism (DDM) and Approximate Linear Dependency Kernel Filter (ALD) in solving concept drift problems and reducing complex computations in the learning. The recursive kernel method successfully replaces the normal kernel method in Recurrent Kernel Online Sequential Extreme Learning Machine with DDM (RKOS-ELM-DDM) and generates a fixed reservoir with optimized information in enhancing the forecasting performance. Meta-cognitive learning strategy decides when the incoming data needs to be updated, retrained, or discarded during learning and automatically finding ALD threshold that reduces the learning time of prediction model. In the experiment, six synthetic and three real-world time series datasets are used to evaluate the ability of recursive kernel method, the performance of concept drift detectors, and meta-cognitive learning strategy in time series prediction. Experimental results indicate the meta-RRKOS-ELM with DDM has superior prediction ability in the different predicting horizons as compared with other algorithms
Understanding consumers’ behavior intentions towards dealing with the plastic waste: Perspective of a developing country
No full textPlastic consumption has been increasing globally, creating large amount of litter and posing threat to the environment. The recycling of the plastic waste can help in reducing it and its environmental threat. The purpose of this paper is to identify the factors that influence the consumer's return/recycling intention regarding plastic waste. Moreover, recycling behavior of consumer was explored in detail. The theory of planned behavior was adapted and extended to measure the determinants of recycling behavior. Survey research design was employed whereas data includes valid 243 households, collected through survey questionnaire, by employing purposive sampling. PLS-SEM was applied on the collected data for hypotheses testing. The finding of this study indicates that subjective norms, awareness consequences and convenience are major predictors of return/recycling intention. Whereas, hypothesis for the attitude, perceived behavioral control and moral norms were rejected and they all have insignificant impact on return/recycling intention. Moreover, return intention have positive significant impact on resell, reuse, dispose and donate. Reuse was the most predicted by the return intention. This study enriches the literature of reverse logistics helping to understand the consumers’ perspective. Provides the insights that will help government and organizations to understand consumers’ return/recycling intention and formulate such strategies that will increase the involvement of consumers in recycling activities
CFD modelling of weld pool formation and solidification in a laser micro-welding process
No full textThe application of developed thermal models has demonstrated that parameters, such as power, scanning velocity and spot diameter of laser beams have considerable effects on the formation of weld pools. The properties of the weld metal are heavily dependent on the solidification microstructure, and an accurate prediction of the weld pool solidification requires consideration in both the thermodynamics and kinetics of solidification. The computations we presented for a transient three-dimensional model show the aspects of weld pool formation and solidification in a quantitative manner. Our focus was the examination of heat transfer and fluid flow analysis in laser micro-welding of thin stainless-steel sheet (SUS304) using the computational fluid dynamics (CFD) approach. In this research work, a useful linkage between the laser micro-welding parameters and the geometry of the micro-weld can be derived from the results, and informative guidance was achieved as to how the width, depth and length of the weld pool differ during laser micro-welding as a function of spot diameter, scanning velocity and laser power. The simulation results have been compared with two sets of experimental data to predict the weld bead geometry and solidification pattern made on thin stainless steel sheet using a continuous wave (CW) fibre laser. The reasonable agreement between the simulated and experimental results, demonstrates the reliability of the computed model, and the results can be used to determine the laser micro-welding conditions necessary to achieve an appropriate target microstructure. However, the results allow estimation of acceptable ranges of welding variables, to attain the required micro-weld geometry
Polarizing effect of MoSe2-coated optical waveguides
No full textIn this paper, an optical waveguide polarizer based on molybdenum diselenide (MoSe2) coating is proposed and demonstrated. By applying drop-casting method, MoSe2 is coated onto an optical polymer waveguide. The extinction ratio is recorded at wavelength of 980 nm, 1310 nm, 1480 nm and 1550 nm. The highest extinction ratio obtained through this experiment is 14.0 dB, in the 1480 nm wavelength region, with MoSe2 coating thickness and coating length of 24 µm and 1.2 mm, respectively. This work demonstrates a polarizing effect of MoSe2 coated SU-8 polymer optical waveguide
Microring resonator made by ion-exchange technique for detecting the CO2, H2O, and NaCl as cladding layer
No full textA system of Microring Resonator (MRR) based the comb-like sensor devices has been simulated. We present a Silicon-On-Insulator (SOI) ring resonator based on refractive index sensor. The novelty of the architecture lies in the capability to sense the shifts of multiple peaks simultaneously with an MRR waveguide. The behavior of optical MRRs, especially when functioning as refractive index sensors, is studied. Resonant wavelength, i.e. the wavelength at which the transmission spectrum exhibits a dip (peak) depends on the geometrical characteristics of the circular waveguide and the effective refractive index of the propagating mode. The previous studies have shown that the depth and vertical symmetry of buried waveguides are noticeably affected by the field perturbation. One of cost effective and low loss methods can be the technology known as ion-exchange which uses the glass substrates and the AgNO3/NaNO3 salt-melt at different temperatures and duration can be deposited on the glass substrates. Afterward, an MRR was designed on the glass substrates, where the effect of the carbon dioxide (CO2), Dihydrogen oxide (H2O), and sodium chloride (NaCl) as the cladding on the ion-exchange waveguide studied. Within the compare of the resonance in drop port and throughput port, it can understand that they roughly have the same distance of wavelength in the resonance. H2O is one of the materials showing higher Qfactor and FSR while it was in drop port also in throughput CO2 was the highest in these parameters
An efficient wideband hafnia-bismuth erbium co-doped fiber amplifier with flat-gain over 80 nm wavelength span
No full textA new wideband erbium doped fiber amplifier (EDFA) is proposed and demonstrated, utilizing a newly fabricated hafnia-bismuth erbium co-doped fiber (HB-EDF) as a gain medium. The proposed amplifier is tested in both double-pass series and parallel configurations, using 22 cm and 150 cm long HB-EDFs to realize amplification in C and L-band wavelength region, respectively. Both series and parallel configurations obtained a wideband operation at wavelength region from 1520 to 1610 nm. At input signal power of −10 dBm, the parallel HB-EDFA achieved a flat gain of 12.1 dB with a gain ripple of less than 2 dB, along the wavelength region of 80 nm from 1525 to 1605 nm. Within the flat gain region, the noise figure was less than 11.8 dB. Overall, the parallel HB-EDFA has a better performance than the series HB-EDFA
Ternary MoWSe2 alloy saturable absorber for passively Q-switched Yb-, Er- and Tm-doped fiber laser
No full textA ternary molybdenum tungsten selenide (MoWSe2) alloy is proposed and demonstrated as a saturable absorber (SA) to induce Q-switching in the 1. 0μm, 1. 5μm and 2.0μm regions. The MoWSe2 based SA is fabricated by mechanical exfoliation and sandwiched between two fiber ferrules to complete the fiberized SA assembly. The MoWSe2-SA is integrated into ytterbium, erbium and thulium-doped fiber laser cavities, and stable self-starting Q-switched pulses are observed at 1038 nm, 1554 nm and 1964 nm respectively. Maximum repetition rates at 120.2 kHz, 48 kHz and 61.5 kHz are observed at these wavelengths, along with corresponding pulse widths as narrow as 0.96 μs, 1.9 μs and 2.4 μs respectively. These results validate the performance of MoWSe2 as a broadband SA for Q-switching operation, offering new opportunities of ternary transition metal dichalcogenide alloys in future photonics devices
Compact L-band switchable dual wavelength SOA based on linear cavity fiber laser
No full textA semiconductor optical amplifier (SOA) based linear cavity L-band dual wavelength fiber laser (DWFL) with a switchable output is proposed and its operation demonstrated. The DWFL is configured as a linear cavity, with a 1 × 24 arrayed waveguide grating together with two optical switches providing channel spacing tunability. An L-band SOA, with a central operating wavelength of 1580 nm and an operation bandwidth of 1500–1640 nm serves as the gain medium of the proposed laser cavity. The DWFL is able to generate a dual-wavelength output, with the widest spacing obtained being 18.7 nm and the narrowest spacing being 0.8 nm. The generated output is highly stable, with only minor power fluctuations of less than 2 dB as well as having a signal-to-noise ratio of 42 dB. The proposed setup would have numerous uses, particularly for sensor applications