Search Results (15)

The task of image captioning in low-resource languages like Tamil is fraught with challenges due to limited linguistic resources and complex semantic structures. This paper addresses the problem of generating contextually and linguistically coherent captions in Tamil. We introduce the Dynamic Context-Aware Transformer (DCAT), a novel approach that synergizes the Vision Transformer (ViT) with the Generative Pre-trained Transformer (GPT-3), reinforced by a unique Context Embedding Layer. The DCAT model, tailored for Tamil, innovatively employs dynamic attention mechanisms during its Initialization, Training, and Inference phases to focus on pertinent visual and textual elements. Our method distinctively leverages the nuances of Tamil syntax and semantics, a novelty in the realm of low-resource language image captioning. Comparative evaluations against established models on datasets like Flickr8k, Flickr30k, and MSCOCO reveal DCAT’s superiority, with a notable 12% increase in BLEU score (0.7425) and a 15% enhancement in METEOR score (0.4391) over leading models. Despite its computational demands, DCAT sets a new benchmark for image captioning in Tamil, demonstrating potential applicability to other similar languages. Full article

The deployment of hydrogen fuel cell electric vehicles (FCEVs) is critical to achieve zero emissions. A key parameter influencing FCEV performance and durability is hydrogen fuel quality. The real impact of contaminants on FCEV performance is not well understood and requires reliable measurements from real-life events (e.g., hydrogen fuel in poor-performing FCEVs) and controlled studies on the impact of synthetic hydrogen fuel on FCEV performance. This paper presents a novel methodology to flow traceable hydrogen synthetic fuel directly into the FCEV tank. Four different synthetic fuels containing N₂ (90–200 µmol/mol), CO (0.14–5 µmol/mol), and H₂S (4–11 nmol/mol) were supplied to an FCEV and subsequently sampled and analyzed. The synthetic fuels containing known contaminants powered the FCEV and provided real-life performance testing of the fuel cell system. The results showed, for the first time, that synthetic hydrogen fuel can be used in FCEVs without the requirement of a large infrastructure. In addition, this study carried out a traceable H₂ contamination impact study with an FCEV. The impact of CO and H₂S at ISO 14687:2019 threshold levels on FCEV performance showed that small exceedances of the threshold levels had a significant impact, even for short exposures. The methodology proposed can be deployed to evaluate the composition of any hydrogen fuel. Full article

Formic acid is an intermediate of the steam methane reforming process for hydrogen production. According to International Standard ISO 14687, the amount fraction level of formic acid present in the hydrogen supplied to fuel cell electric vehicles must not exceed 200 nmol·mol⁻¹. The development of formic acid standards in hydrogen is crucial to validate the analytical results and ensure measurement reliability for the fuel cell electric vehicles industry. NPL demonstrated that these standards can be gravimetrically prepared and validated at 4 to 100 µmol·mol⁻¹, with a shelf-life of 1 year (stability uncertainty < 7%; k = 2). Stability was not affected over 1 year or by low temperature or pressure. At sub-µmol·mol⁻¹ level, formic acid amount fraction was found to decrease due to adsorption on the gas cylinder surface; however, it is possible to certify the formic acid amount fraction after a period of 20 days and ensure the certified value validity for 1 year with an uncertainty below 7% (k = 1) confirmed by thermodynamic investigation. This study demonstrated that formic acid in hydrogen gas reference materials can be prepared with reasonable uncertainty (>7%, k = 1) and shelf life (>1 year). Potential applications include the calibration of analysers and for studying the impact of formic acid on future application with relevant traceability and accuracy. Full article

Among the most perilous factors affecting tomato plant functioning and yield is salinity. The efficacy of halotolerant marine macroalgal extract of Chaetomorpha antennina (Seaweed Extract—SWE) in mitigating the toxic effects of salt stress (150 mM) in tomato plants to promote and enhance both plant functionality and yield was tested. It was evident that salt stress undesirably affected germination and plant growth in terms of quality and quantity. Treatment with SWE improved the functionality of salt-strained tomato plants by enhancing their germination indexes, growth and morphological traits, and photosynthetic pigments, as well as protein and phenol concentrations. SWE also exerted a positive influence on protecting the plant against salt stress by increasing the synthesis and accumulation of antioxidant enzymes, superoxide dismutase and lipoxygenase enzymes, along with the contents of lycopene and vitamin C. SWE also increased the nutraceutical quality, flavour and organolepty of emerged tomato fruits. GCMS analysis of fruit pericarp showed increased siloxane, phenol, antioxidant and indole acetic acid compounds, along with aromatic benzene compounds. These results indicate the potentiality of SWE in protecting plants against salt stress induced toxicities by prompting the synthesis of protective compounds such as siloxane and antioxidant enzymes. It was also noted that SWE plays a crucial role in promoting plant growth and survivability by improving plant functionality, yield and nutrition, by promoting cultivation in saline soils in an eco-friendly and sustainable manner. Full article

Fuel cell electric vehicles (FCEV) are developing quickly from passenger vehicles to trucks or fork-lifts. Policymakers are supporting an ambitious strategy to deploy fuel cell electrical vehicles with infrastructure as hydrogen refueling stations (HRS) as the European Green deal for Europe. The hydrogen fuel quality according to international standard as ISO 14687 is critical to ensure the FCEV performance and that poor hydrogen quality may not cause FCEV loss of performance. However, the sampling system is only available for nozzle sampling at HRS. If a FCEV may show a lack of performance, there is currently no methodology to sample hydrogen fuel from a FCEV itself. It would support the investigation to determine if hydrogen fuel may have caused any performance loss. This article presents the first FCEV sampling system and its comparison with the hydrogen fuel sampling from the HRS nozzle (as requested by international standard ISO 14687). The results showed good agreement with the hydrogen fuel sample. The results demonstrate that the prototype developed provides representative samples from the FCEV and can be an alternative to determine hydrogen fuel quality. The prototype will require improvements and a larger sampling campaign. Full article

Fuel cell electric vehicles are expanding quickly from light-duty to heavy-duty applications such as buses or trucks. Hydrogen fuel quality needs to comply with ISO14687:2019 to avoid any improper performance of the vehicles. Total sulphur is one of the most impactful contaminants to a fuel cell system and has a threshold of 4 nmol/mol. Most analytical methods provide a limit of detection (LOD) of 1 nmol/mol for total sulphur in hydrogen. Total sulphur is often not quantified and reported as below LOD due to lack of sensitivity. A new analytical method using cryo-focussing gas chromatography with sulphur chemiluminescence detector (cryo-GC-SCD) was developed for picomol/mol analysis of total sulphur. The method achieved linearity between 150–16,000 picomol/mol, validated against NPL reference materials, and relative expanded uncertainty of 21% (k = 2). Samples from 11 hydrogen refuelling stations (HRS) were analysed using this method. The total sulphur amount fraction for all the HRSs was more than 10 times lower than the actual ISO14687:2019 threshold with highest value around 290 picomol/mol. The study demonstrated that the cryo-GC-SCD method can measure total sulphur at picomol/mol in hydrogen fuel. Additionally, it provided the first results on sulphur compound stability in an aluminium gas cylinder for which further study is needed. Full article

The new variant of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), Omicron, has been quickly spreading in many countries worldwide. Compared to the original virus, Omicron is characterized by several mutations in its genomic region, including the spike protein’s receptor-binding domain (RBD). We have computationally investigated the interaction between the RBD of both the wild type and Omicron variant of SARS-CoV-2 with the human angiotensin-converting enzyme 2 (hACE2) receptor using molecular dynamics and molecular mechanics-generalized Born surface area (MM-GBSA)-based binding free energy calculations. The mode of the interaction between Omicron’s RBD with the hACE2 receptor is similar to the original SARS-CoV-2 RBD except for a few key differences. The binding free energy difference shows that the spike protein of Omicron has an increased affinity for the hACE2 receptor. The mutated residues in the RBD showed strong interactions with a few amino acid residues of hACE2. More specifically, strong electrostatic interactions (salt bridges) and hydrogen bonding were observed between R493 and R498 residues of the Omicron RBD with D30/E35 and D38 residues of the hACE2, respectively. Other mutated amino acids in the Omicron RBD, e.g., S496 and H505, also exhibited hydrogen bonding with the hACE2 receptor. A pi-stacking interaction was also observed between tyrosine residues (RBD-Tyr501: hACE2-Tyr41) in the complex, which contributes majorly to the binding free energies and suggests that this is one of the key interactions stabilizing the formation of the complex. The resulting structural insights into the RBD:hACE2 complex, the binding mode information within it, and residue-wise contributions to the free energy provide insight into the increased transmissibility of Omicron and pave the way to design and optimize novel antiviral agents. Full article

Drug discovery is the most expensive, time-demanding, and challenging project in biopharmaceutical companies which aims at the identification and optimization of lead compounds from large-sized chemical libraries. The lead compounds should have high-affinity binding and specificity for a target associated with a disease, and, in addition, they should have favorable pharmacodynamic and pharmacokinetic properties (grouped as ADMET properties). Overall, drug discovery is a multivariable optimization and can be carried out in supercomputers using a reliable scoring function which is a measure of binding affinity or inhibition potential of the drug-like compound. The major problem is that the number of compounds in the chemical spaces is huge, making the computational drug discovery very demanding. However, it is cheaper and less time-consuming when compared to experimental high-throughput screening. As the problem is to find the most stable (global) minima for numerous protein–ligand complexes (on the order of 10${}^6$ to 10${}^{12}$), the parallel implementation of in silico virtual screening can be exploited to ensure drug discovery in affordable time. In this review, we discuss such implementations of parallelization algorithms in virtual screening programs. The nature of different scoring functions and search algorithms are discussed, together with a performance analysis of several docking softwares ported on high-performance computing architectures. Full article

Quercetin is a bioflavonoid which has a broad spectrum of biological activity. Due to its lower chemical stability, it is usually encapsulated, or a metal–quercetin complex is formed to enhance its biological activity at a lower concentration. Here, our novel approach was to form a quercetin complex to magnesium-doped calcium silicate (CMS) ceramics through a coprecipitation technique so as to take advantage of quercetin’s antibacterial activity within the antibacterial and osteogenic potential of the silicate. Due to quercetin’s inherent metal-chelating ability, (Ca+Mg)/Si increased with quercetin concentration. Quercetin in magnesium-doped calcium silicate ceramic showed concentration-dependent pro-oxidant and antioxidant activity in SaOS-2 with respect to quercetin concentration. By optimizing the relative concentration, we were able to achieve 3-fold higher proliferation and 1.6-fold higher total collagen at day 14, and a 1.7-fold higher alkaline phosphatase production at day 7 with respect to polycaprolactone/polyvinylpyrrolidone (PCL/PVP) scaffold. Quercetin is effective against Gram-positive bacteria such as S. aureus. Quercetin is coupled with CMS provided similar effect with lower quercetin concentration than quercetin alone. Quercetin reduced bacterial adhesion, proliferation and biofilm formation. Therefore, quercetin-coupled magnesium-doped calcium silicate not only enhanced osteogenic potential, but also reduced bacterial adhesion and proliferation. Full article

Maritime transport is investigating several options to reduce its greenhouse gases and air pollutant emissions. An experimental ship, Energy Observer, is using excess renewable energy to generate onboard hydrogen by electrolysis of purified seawater. As a promising option for storing energy, it can provide on-demand energy to the ship through a hydrogen fuel cell (FC). As hydrogen FCs lifetime and performance are correlated to hydrogen quality, the hydrogen produced onboard needs to be monitored. This study assesses the probability of contaminants presence for this electrolyser, using purified seawater and supports the results with a hydrogen fuel quality analysis from the Energy Observer ship. It demonstrates that an electrolyser using onboard purified seawater can generate hydrogen of a quality compliant with ISO 14687:2019. Additional contaminants (i.e., ions, heavy metal) were also measured. The study highlights the potential contaminants to be monitored and future research on new contaminants from seawater to further develop hydrogen fuel for maritime applications. Full article

The widescale distribution of hydrogen through gas networks is promoted as a viable and cost-efficient option for optimising its application in heat, industry, and transport. It is a key step towards achieving decarbonisation targets in the UK. A key consideration before the injection of hydrogen into the UK gas networks is an assessment of the difference in hydrogen contaminants presence from different production methods. This information is essential for gas regulation and for further purification requirements. This study investigates the level of ISO 14687 Grade D contaminants in hydrogen from steam methane reforming, proton exchange membrane water electrolysis, and alkaline electrolysis. Sampling and analysis of hydrogen were carried out by the National Physical Laboratory following ISO 21087 guidance. The results of analysis indicated the presence of nitrogen in hydrogen from electrolysis, and water, carbon dioxide, and particles in all samples analysed. The contaminants were at levels below or at the threshold limits set by ISO 14687 Grade D. This indicates that the investigated production methods are not a source of contaminants for the eventual utilisation of hydrogen in different applications including fuel cell electric vehicles (FCEV’s). The gas network infrastructure will require a similar analysis to determine the likelihood of contamination to hydrogen gas. Full article

A wide variety of neurodegenerative diseases are characterized by the accumulation of protein aggregates in intraneuronal or extraneuronal brain regions. In Alzheimer’s disease (AD), the extracellular aggregates originate from amyloid-β proteins, while the intracellular aggregates are formed from microtubule-binding tau proteins. The amyloid forming peptide sequences in the amyloid-β peptides and tau proteins are responsible for aggregate formation. Experimental studies have until the date reported many of such amyloid forming peptide sequences in different proteins, however, there is still limited molecular level understanding about their tendency to form aggregates. In this study, we employed umbrella sampling simulations and subsequent electronic structure theory calculations in order to estimate the energy profiles for interconversion of the helix to β-sheet like secondary structures of sequences from amyloid-β protein (KLVFFA) and tau protein (QVEVKSEKLD and VQIVYKPVD). The study also included a poly-alanine sequence as a reference system. The calculated force-field based free energy profiles predicted a flat minimum for monomers of sequences from amyloid and tau proteins corresponding to an α-helix like secondary structure. For the parallel and anti-parallel dimer of KLVFFA, double well potentials were obtained with the minima corresponding to α-helix and β-sheet like secondary structures. A similar double well-like potential has been found for dimeric forms for the sequences from tau fibril. Complementary semi-empirical and density functional theory calculations displayed similar trends, validating the force-field based free energy profiles obtained for these systems. Full article

Impurities in carbon dioxide can affect several aspects of the carbon capture and storage process, including storage capacity, rock erosion, accuracy of flow meters, and toxicity of potential leaks. There is an industry need for guidance on performing purity analysis before carbon dioxide is transported and stored. This paper reviews selected reports that specifically provide threshold amount fraction limits for impurities in carbon dioxide for the purpose of transport and storage, with rationales for these limits. A carbon dioxide purity specification is provided (including threshold amount fractions of impurities) on the basis of the findings, as well as recommendations on further work required to develop a suitable gas metrology infrastructure to support these measurements including primary reference materials, sampling methods, and instruments for performing purity analysis. These recommendations provide important guidance to operators and gas analysis laboratories for performing quality assurance. Full article

Monoamine oxidase B (MAOB) is expressed in the mitochondrial membrane and has a key role in degrading various neurologically active amines such as benzylamine, phenethylamine and dopamine with the help of Flavin adenine dinucleotide (FAD) cofactor. The Parkinson’s disease associated symptoms can be treated using inhibitors of MAO-B as the dopamine degradation can be reduced. Currently, many inhibitors are available having micromolar to nanomolar binding affinities. However, still there is demand for compounds with superior binding affinity and binding specificity with favorable pharmacokinetic properties for treating Parkinson’s disease and computational screening methods can be majorly recruited for this. However, the accuracy of currently available force-field methods for ranking the inhibitors or lead drug-like compounds should be improved and novel methods for screening compounds need to be developed. We studied the performance of various force-field-based methods and data driven approaches in ranking about 3753 compounds having activity against the MAO-B target. The binding affinities computed using autodock and autodock-vina are shown to be non-reliable. The force-field-based MM-GBSA also under-performs. However, certain machine learning approaches, in particular KNN, are found to be superior, and we propose KNN as the most reliable approach for ranking the complexes to reasonable accuracy. Furthermore, all the employed machine learning approaches are also computationally less demanding. Full article

We have examined several approaches relying on the Polarizable Embedding (PE) scheme to predict optical band shapes for two chalcone molecules in methanol solution. The PE-TDDFT and PERI-CC2 methods were combined with molecular dynamics simulations, where the solute geometry was kept either as rigid, flexible or partly-flexible (restrained) body. The first approach, termed RBMD-PE-TDDFT, was employed to estimate the inhomogeneous broadening for subsequent convolution with the vibrationally-resolved spectra of the molecule in solution determined quantum-mechanically (QM). As demonstrated, the RBMD-PE-TDDFT/QM-PCM approach delivers accurate band widths, also reproducing their correct asymmetric shapes. Further refinement can be obtained by the estimation of the inhomogeneous broadening using the RBMD-PERI-CC2 method. On the other hand, the remaining two approaches (FBMD-PE-TDDFT and ResBMD-PE-TDDFT), which lack quantum-mechanical treatment of molecular vibrations, lead to underestimated band widths. In this study, we also proposed a simple strategy regarding the rapid selection of the exchange-correlation functional for the simulations of vibrationally-resolved one- and two-photon absorption spectra based on two easy-to-compute metrics. Full article