A Monte Carlo Comparative Simulation Study for Identification of the Best Performing Panel Cointegration Tests

In this paper the performance of nine panel cointegration tests, having the null hypothesis of no cointegration, with respect to weighted average rank scores under the whole space of alternative using Monte Carlo simulations have been carried out. Our results indicate that PdPtp, PAWS and PdP_V tests are the only three best performing tests among all panel cointegration tests whether time and cross sectional dimensions are small, medium or large. However, PDFTstar, PDFTrhostar and PdGtp panel cointegration tests have also identified as best performer at large cross sectional dimensions

An eco-friendly dyeing of woolen yarn by Terminalia chebula extract with evaluations of kinetic and adsorption characteristics

In the present study Terminalia chebula was used as an eco-friendly natural colorant for sustainable textile coloration of woolen yarn with primary emphasis on thermodynamic and kinetic adsorption aspects of dyeing processes. Polyphenols and ellagitannins are the main coloring components of the dye extract. Assessment of the effect of pH on dye adsorption showed an increase in adsorption capacity with decreasing pH. Effect of temperature on dye adsorption showed 80 °C as optimum temperature for wool dyeing with T. chebula dye extract. Two kinetic equations, namely pseudo first-order and pseudo second-order equations, were employed to investigate the adsorption rates. Pseudo second-order model provided the best fit (R2 = 0.9908) to the experimental data. The equilibrium adsorption data were fitted by Freundlich and Langmuir isotherm models. The adsorption behavior accorded well (R2 = 0.9937) with Langmuir isotherm model. Variety of eco-friendly and sustainable shades were developed in combination with small amount of metallic mordants and assessed in terms of colorimetric (CIEL∗a∗b∗ and K/S) properties measured using spectrophotometer under D65 illuminant (10° standard observer). The fastness properties of dyed woolen yarn against light, washing, dry and wet rubbing were also evaluated

Dyeing studies and fastness properties of brown naphtoquinone colorant extracted from Juglans regia L on natural protein fiber using different metal salt mordants

In this study, wool fibers are dyed with a natural colorant extracted from walnut bark in presence and absence of mordants. The effect of aluminum sulfate, ferrous sulfate, and stannous chloride mordants on colorimetric and fastness properties of wool fibers was investigated. Juglone was identified as the main coloring component in walnut bark extract by UV visible and FTIR spectroscopic techniques. The results showed that pretreatment with metallic mordants substantially improved the colorimetric and fastness properties of wool fibers dyed with walnut bark extract. Ferrous sulfate and stannous chloride mordanted wool fibers shows best results than potassium aluminum sulfate mordanted and unmordanted wool fibers. This is ascribed due to strong chelating power of ferrous sulfate and stannous chloride mordants

Review on green biomass-synthesized metallic nanoparticles and composites and their photocatalytic water purification applications: progress and perspectives

In recent years, the use of biomass for the cost-effective synthesis of nanoparticles has emerged as a promising green technology. Because of their remarkable properties, such as tunable surface plasmon resonance characteristics and high surface areas, bio-synthesised nanomaterials are receiving more scientific and academic attention for their use in various application sectors, especially as catalysts in environmental remediation. Green synthesized nanomaterial's can efficiently contribute to the degradation of a wide range of organic pollutants, including dyes, into harmless by-products. These particles have a cure for recalcitrant organic and inorganic pollutants due to their photocatalytic properties, which largely depend on the production of reactive oxygen species under sunlight or UV illumination. This comprehensive review systematically covers up-to-date knowledge on recent developments in the green synthesis of nanoparticles and composites using plants and microorganisms, unravels underlying mechanisms, and highlights their application areas. It then provides detailed information on their applications in the degradation of potentially toxic organic dyes and the removal of other emerging pollutants, including heavy metals and antibiotics. Finally, the current challenges and perspectives of this technology for future applications are discussed

Synthetically modified bioisosteres of salicyl alcohol and their gastroulcerogenic assessment versus aspirin: biochemical and histological correlates

The present study was conducted to synthesize nitrogen containing derivatives of salicyl alcohol and to investigate in vivo their ulcerogenic potential in comparison with aspirin in rats. The compounds [4-(2-hydroxybenzyl) morpholin-4-iumchloride (I)] and [1,4-bis(2-hydroxybenzyl) piperazine-1,4-diium chloride (II)] were synthesized and their chemical structures were characterized using spectral data. In our previous study (Ali et al., Afr J Pharm Pharmacol 7:585–596, 2013), both compounds showed anti-inflammatory, antinociceptive, and antipyretic properties in standard animal models and a greater binding affinity for cyclooxygenase-2 versus cyclooxygenase-1 in molecular docking and dynamics analysis. For in vivo studies, animals were randomly divided into four groups. The synthetic compounds (both at 100 or 150 mg/kg), aspirin (150 mg/kg), or saline vehicle was administered orally, once daily for 6 days and then tested for ulcerogenic activity. At the end of the procedure, gastric juice and tissues were collected and subjected to biochemical and histological analyses. The results of the study revealed that in the case of the aspirin-treated group, there was a significant increase in gastric juice volume, free acidity, total acidity, and ulcer score and a decrease in gastric pH. Moreover, histological examination of the gastric mucosa of the aspirin-treated group indicated morphological changes while neither of the synthetic compounds showed any significant ulcerogenic or cytotoxic properties. The results of the present study suggest that both compounds are free from ulcerogenic side effects and may represent a better alternative to aspirin

Novel hydroquinone derivatives alleviate algesia, inflammation and pyrexia in the absence of gastric ulcerogenicity

Purpose: To synthesize and characterize novel hydroquinone compounds that exhibit an aspirin-like pharmacological profile devoid of ulcerogenic side effects.Methods: Two novel hydroquinone derivatives, viz, 2,5-bis(piperidinomethyl)hydroquinone and 2,5- bis(pyrrolidinomet hyl)hydroquinone, were synthesized by refluxing hydroquinone, paraformaldehyde and secondary amines (piperidine or pyrrolidine) in ethanol. The structures were authenticated by infrared (IR) spectroscopy, elemental analysis, mass spectrometry (MS) and 1H and 13C nuclear magnetic resonance (NMR) spectroscopic techniques. The synthesized derivatives were evaluated for antinociceptive, anti-inflammatory and antipyretic activities along with gastric-ulcerogenicity using wellknown testing paradigms. Aspirin served as reference standard.Results: The newly synthesized hydroquinone derivatives, significantly attenuated tonic visceral chemically-induced nociception at 10 mg/kg (p < 0.01, p < 0.001), 20 and 40 mg/kg (p < 0.001), inhibited the temporal-inflammatory reaction at 50 mg/kg (2 - 5 h, p < 0.05, p < 0.001), 100 and 150 mg/kg (1 - 5 h, p < 0.05, p < 0.01, p < 0.001) in addition to alleviating the febrile-response at test doses during 0.5 h (p < 0.05, p < 0.01, p < 0.001), 1 and 1.5 h (p < 0.001) of the study period. The synthesized compounds exhibited improved gastric tolerability profile since they were devoid of aspirin-associated biochemical and ulcerative changes. The in silico studies predicted high binding affinity of the hydroquinone derivatives to the active site of the cyclooxygenase 2 (COX-2) enzyme.Conclusion: The synthesized hydroquinone compounds possess analgesic, antipyretic and antiinflammatory properties with low gastric-ulcerogenic potential. This may be credited to preferential inhibition of the COX-2 enzyme and the beneficial basic rather than acidic chemical nature of the compounds. However, further molecular studies are required to substantiate these findings.Keywords: 2,5-Bis(piperidinomethyl)hydroquinone], 2,5- is(pyrrolidinomethyl)hydroquinone, Antiinflammatory, Antinociceptive, Antipyretic, Gastric-ulcerogenicity, Algesi

Mechanical energy harvesting and self-powered electronic applications of textile-based piezoelectric nanogenerators: a systematic review

Environmental pollution resulting from fossil fuel consumption and the limited lifespan of batteries has shifted the focus of energy research towards the adoption of green renewable technologies. On the other hand, there is a growing potential for small, wearable, portable electronic devices. Therefore, considering the pollution caused by fossil fuels, the drawbacks of chemical batteries, and the potential applications of small-scale wearables and portable electronic devices, the development of a more effective lightweight power source is essential. In this context, piezoelectric energy harvesting technology has attracted keen attention. Piezoelectric energy harvesting technology is a process that converts mechanical energy into electrical energy and vice-versa. Piezoelectric energy harvesters can be fabricated in various ways, including through solution casting, electrospinning, melt spinning, and solution spinning techniques. Solution and melt-spun filaments can be used to develop woven, knitted, and braided textile-based piezoelectric energy harvesters. The integration of textile-based piezoelectric energy harvesters with conventional textile clothing will be a key enabling technology in realising the next generation smart wearable electronics. This review focuses on the current achievements on textile based piezoelectric nanogenerators (T-PENGs), basic knowledge about piezoelectric materials and the piezoelectric mechanism. Additionally, the basic understanding of textiles, different fabrication methods of T-PENGs, and the strategies to improve the performance of piezoelectric nanogenerators are discussed in the subsequent sections. Finally, the challenges faced in harvesting energy using textile based piezoelectric nanogenerators (T-PENGs) are identified, and a perspective to inspire researchers working in this area is presented

Wearable nanocomposite textile-based piezoelectric and triboelectric nanogenerators: progress and perspectives

In recent years, the widespread adoption of next-generation wearable electronics has been facilitated by the integration of advanced nanogenerator technology with conventional textiles. This integration has led to the development of textile-based nanogenerators (t-NGs), which hold tremendous potential for harvesting mechanical energy from the surrounding environment and serving as power sources for self-powered electronics. Textile structures are inherently flexible, making them well-suited for wearable applications. However, their electrical performance as nanogenerators is significantly limited when used without any modifications. To address this limitation and enhance the electrical performance of textile-based nanogenerators, nanocomposite textiles have been extensively utilized for fabricating advanced nanogenerators. This critical review focuses on the recent progress in wearable nanocomposite textiles-based piezoelectric and triboelectric nanogenerators. The review covers the fundamentals of piezoelectricity and triboelectricity, the working principles of nanogenerators, and the selection of materials. Furthermore, it provides a detailed discussion of nanocomposite textiles in various forms, such as fibers or yarns, fabrics, and electrospun nanofibrous webs, which are employed in piezoelectric and triboelectric nanogenerators. The review also highlights the challenges associated with their implementation and outlines the prospects of textile-based nanogenerators. It can be concluded that nanocomposite textile based piezoelectric and triboelectric nanogenerators exhibit better electrical output and mechanical strength compared to conventional textile based nanogenerators. Nanocomposite electrospun web based piezoelectric nanogenerators exhibit higher piezoelectric output compared with nanocomposite fibre/yarn or fabric based piezoelectric nanogenerators. This is because an in-situ poling takes place in electrospinning unlike with fibre or fabric based piezoelectric nanogenerators. Nanocomposite electrospun web based triboelectric nanogenerators also show better triboelectric output compared to the fibre or fabric-based equivalents. This is due to the higher contact area developed with electrospun nanocomposite webs compared to the fibre or fabric cases. Overall, it can be concluded that while nanocomposite construction can boost output and durability of textile based nanogenerators, more research is required to bring output, stability and durability up to the levels achievable with non-textile based devices

Enhancement of solubility and dissolution rate of ebastine fast-disintegrating tablets by solid dispersion method

Purpose: To investigate the efficiency of different solubilizing agents in improving solubility as well as dissolution rate of ebastine (a BCS class II drug) by incorporating prepared solid dispersion into fast disintegrating tablets.Method: The solubility of ebastine was determined in distilled water, lipids and solubilizing agents. Subsequently, the binary solid dispersions were prepared by kneading method using varying weight ratios of ebastine and solubilizing agents. The solid dispersions were then incorporated into fast disintegrating tablets (SD-FDT). Central composite rotatable design (CCD) was used to determine the impact of super disintegrating agents on disintegration time and friability of tablets. The solubility and dissolution rate of developed SD-FDT were compared with a marketed brand. The solid dispersion particles were characterized by Fourier-transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), powder x-ray diffraction (P-XRD) and scanning electron microscopy (SEM).Results: The saturated solubility of pure ebastine in water was 0.002 ± 0.041 mg/ml while the aqueous solubility of EBT/poloxamer solid dispersion SET3 (P) was 0.018 ± 2.510 mg/ml; on the other hand, EBT/soluplus solid dispersion SET1(S) has an aqueous solubility of 0.242 ± 1.390 mg/ml. Within 30 min, drug release was 14.00 ± 1.77, 78.00 ± 2.31 and 98.70 ± 2.54 % from pure EBT, SET3 (P) and SET1(S), respectively.Conclusion: The solubility and dissolution rate of ebastine has been successfully enhanced by incorporating its solid dispersion in fast-disintegrating tablets (SD-FDT). Keywords: Ebastine, Solid dispersion, Poloxamer 188, Soluplus, Solubility, Dissolutio

Deep GRU-CNN model for COVID-19 detection from chest X-rays data

In the current era, big data is growing exponentially due to advancements in smart devices. Data scientists apply varied learning-based techniques to identify the underlying patterns in the big medical data to address various health-related issues. In this context, automated disease detection has now become a central concern in medical science due to rapid population growth. It reduces the mortality rate by diagnosing the disease correctly and early enough. The novel virus disease COVID-19 has spread all over the world and is affecting millions of people. Many countries are facing a shortage of test kits, vaccines, and other resources due to substantial growth in COVID-19 cases. In order to accelerate the testing process, scientists around the world have sought to create revolutionary novel alternative methods for the detection of the deadly virus. In this paper, we have proposed a hybrid deep learning model based on a convolutional neural network (CNN) and gated recurrent unit (GRU) for diagnosing the virus from chest X-rays (CXRs). In the proposed model, CNN is used to extract features, and GRU is used as a classifier. The model has been trained on 424 CXRs images with 3 (COIVD-19, Pneumonia, and Normal) classes. The proposed model achieved encouraging results of 0.96, 0.96, and 0.95 in terms of precision, recall, and f1-score, respectively. These findings indicate how deep learning can significantly contribute to the early detection of COVID-19 patients using X-ray scans. Such indications can pave the ways to mitigate the deadly disease. We believe that this model can be an effective tool for medical practitioners for the early diagnosis of coronavirus from CXRs