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There is a demand to ramp up the rate of production of primary aerostructures and as such new processing methods are required. This study investigates a two-stage process for integrating composite structures. In Stage 1, a series of doublers are infused and semi-cured to a target degree of cure ( α ). In Stage 2, these doublers are integrated into a preformed stiffened panel, to increase thickness locally, followed by infusion. The impact of this integration on quality in terms of thickness and void content of the semi-cured doublers is assessed through the processing stages. The results indicate that semi-curing elements to a higher degree of cure ( α  = 0.74) around the gel point ( α  = 0.70) of the epoxy matrix have minimal impact on the relative quality of the final structure. However, at a lower semi-cure ( α  = 0.47), the void (> 100 µm) content increased from 0.8 to 1.92% during the secondary stage. Tracking the thermal profile of the semi-cured elements through the stages combined with a Cure-Temperature-Transition diagram shows that at a lower degree of cure, the resin in the semi-cured doublers will be in a liquid phase during Stage 2 leading to the potential for resin reflow.

Conventional fibre polymer composite materials consist of a single matrix system for a whole part and are selected on the dominant requirements of the part. A multi-matrix composite would provide an expanded design space for a composite part. However, there are few processes available to realise such a composite and these rely on modified forms of resin transfer moulding. These processes require active venting using an expensive vacuum system and the quality is reliant on bag quality. This research is devoted to developing a foundational principle for a processing strategy that uses the localised introduction of resin combined with an out-of-bag consolidation process containing a preheating stage that can form a multi-matrix composite. The resin flow in local deposition and consolidation processes is determined by a complex interplay between the resin and preform. Hence the chosen resin and fabric were characterised extensively. A range of viscosity-tailored consolidation schemes was implemented using a setup to estimate the in-line viscosity using the rheo-kinetics of the fast-curing resin system. By initiating the consolidation pressure at a higher resin viscosity, the voids were found to be suppressed. A simplified model to capture the dominant mechanisms during consolidation was developed. The dominant flow transitioned from a 2D yarn-scale to macro-scale flow on increasing the activation viscosity. The increased resin pressure associated with high resin viscosity during consolidation was found to be a dominating factor in reducing the voids. The model was then used to develop a simple analytical design tool for tailoring the consolidation parameters to minimise the void content. A feasibility study was conducted on combining different matrices to improve the mechanical performance of composites in an open hole tension test. The use of high stiffness carbon nanotube modified resin to locally manipulate the region around the hole increased the strength of the composite. The enhancement of multi-matrix composite was then qualitatively explained using a simple finite element analysis combined with classical laminate theory.

This research presents a novel framework for the design of additively manufactured (AM) composite tooling for the manufacture of carbon fibre-reinforced plastic composites. Through the rigorous design and manufacture of 30 unique AM tools, the viability of a design for AM framework was evaluated through measuring the performance with respect to geometrical accuracy and thermal responsiveness, and simulating the tool specific stiffness. The AM components consisted of a thin layup facesheet, stiffened by a low density lattice geometry. These tools were successfully used to layup and cure small composite components. The tooling was highly thermally responsive, reaching above 93% of the applied oven heating rate and up to 17% faster heating rates compared to similar mass monolithic tools. The results indicate that thermal overshoot has a greater dependence on the lattice density while the heating rate was more sensitive to the facesheet thickness. Lattice densities of as little as 5% were manufactured and the best overall geometry was a graded gyroid lattice with thicker walls near the surface and thinner walls at the base, attached to a 0.7 mm thick facesheet. The outputs from this research can provide a new route to the design and manufacture of mould tools, which could have significant impacts in the composites sector with new, lighter, more energy efficient tooling.

The objective of the present work is to develop an apparatus to measure the thermal conductivity of gas diffusion layer (GDL) as a function of temperature and compression, and also to develop an effective thermal conductivity (ETC) model to predict thermal conductivity of fibrous media as a function of compression. Thermal conductivity of GDL at different operating conditions is essential for accurate thermal modeling in a Proton exchange membrane (PEM) fuel cell stack. Steady state method of guarded hot plate method was used to perform the thermal conductivity measurements and the measurements were carried out on commercially available GDL samples – Toray and SGL (SIGRACET ®). GDL thicknesses at different compressions were also measured to calculate the thermal conductivity of GDL at a given compression. Thermal conductivity of Toray was found to decrease with temperature while that of SGL was constant over temperature. Both Toray and SGL thermal conductivities were observed to increase with compression. Also, contact resistance between GDL-copper surfaces was found to decrease with compression for both Toray and SGL. Furthermore, the effective thermal conductivity model was used to estimate the thermal conductivity of the tested GDL samples at different compressions and was found to match pretty well with the experimentally determined thermal conductivity values.

Jwarahara Kwatha Choornam (JKC) is a polyherbal coded Ayurvedic formulation developed by the Central Council for Research in Ayurvedic Sciences (CCRAS), New Delhi, India. Traditionally used for managing chronic fever, cold, and malaria, JKC has gained recognition for its therapeutic benefits, such as enhancing digestion, stimulating appetite, detoxifying blood, modulating the immune response, and offering protection against common bacterial infections. The medicinal plant used in JKC is widely utilized by Ayurvedic practitioners and the general population in the Kerala region, where it holds a longstanding place in traditional health practices. Notably, during the COVID-19 pandemic, both practitioners and users have reported the formulation’s supportive role in treatment, further highlighting its therapeutic relevance. To ensure the quality, safety, and efficacy of this important Ayurvedic preparation, CCRAS has undertaken standardization efforts, including the development of a novel High-Performance Thin-Layer Chromatography (HPTLC) method for the simultaneous estimation of five key bioactive marker compounds. The study establishes a robust High-Performance Thin-Layer Chromatography (HPTLC) method for the simultaneous estimation of five key bioactive markers—Andrographolide (AG), Piperine (PP), Picroside-I (P-I), Picroside-II (P-II), and α-Cyperone (AC) present in the plants Andrographis paniculata, Cyperus rotundus, Piper longum, Piper nigrum, Zingiber officinale, Hedyotis corymbosa, and Picrorhiza kurroa. Used in the Jwarahara Kwatha Choornam (JKC) formulation. Effective separation of these compounds was achieved using a carefully optimized mobile phase comprising Toluene, Ethyl Acetate, Methanol, and Formic Acid in a 4:4:1:1 (v/v/v/v) ratio. The developed HPTLC method, resolved the five targeted bioactive markers— Andrographolide (AG) , Piperine (PP) , Picroside-I (P-I) , Picroside-II (P-II) , and α-Cyperone (AC) —with distinct R f values of 0.563 ± 0.005, 0.706 ± 0.015, 0.280 ± 0.0173, 0.180 ± 0.0115, and 0.803 ± 0.005, respectively, using a mobile phase of Toluene: Ethyl Acetate: Methanol: Formic Acid (4:4:1:1, v/v/v/v ). The method was rigorously validated, demonstrating excellent linearity (r² = 0.97–0.99), precision, accuracy (RSD < 2%), robustness, and ruggedness under optimized analytical conditions. Quantitative analysis of JKC revealed the presence of AG (3.638 ± 0.0234 mg/g), PP (3.360 ± 0.0792 mg/g), P-I (0.1426 ± 0.0031 mg/g), P-II (0.6025 ± 0.0198 mg/g), and AC (0.2102 ± 0.0023 mg/g). This study demonstrates that the developed HPTLC method is a rapid, precise, and reliable analytical tool for simultaneously quantifying five key bioactive markers in individual plant materials and polyherbal formulations. Owing to its robustness and reproducibility, this method offers a practical and efficient approach for routine quality control and standardization of JKC formulations.

Groundnut (Arachis hypogaea L.), also known as peanut, is an allotetraploid legume crop composed of two different progenitor sub-genomes. This crop is an important source for food, feed, and confectioneries. Leveraging translational genomics research has expedited the precision and speed in making selections of progenies in several crops through either marker-assisted selection or genomic selection, including groundnut. The availability of foundational genomic resources such as reference genomes for diploid progenitors and cultivated tetraploids, offered substantial opportunities for genomic interventions, including the development of genotyping assays. Here, a cost-effective and high-throughput genotyping assay has been developed with 5,081 single nucleotide polymorphisms (SNPs) referred to as “mid-density assay.” This multi-purpose assay includes 5,000 highly informative SNPs selected based on higher olymorphism information content (PIC) from our previously developed high-density “Axiom_Arachis” array containing 58,233 SNPs. Additionally 82 SNPs associated with five resilience and quality traits were included for marker-assisted selection. To test the utility of the mid-density genotyping (MDG) assay, 2,573 genotypes from distinct sets of breeding populations were genotyped with the 5,081 SNPs. PIC of the SNPs in the MDG ranged from 0.34 to 0.37 among diverse sets. The first three principal components collectively explained 82.08% of the variance among these genotypes. The mid-density assay demonstrated a proficient ability to distinguish between the genotypes, offering a high level of genome-wide nucleotide diversity. This assay holds promise for possible deployment in the identification of varietal seed mixtures, genetic purity within gene bank germplasms and seed systems, foreground and background selection in backcross breeding programs, genomic selection, and sparse trait mapping studies in groundnut. Plain Language Summary A cost-effective, high-throughput, mid-density genotyping assay was developed and validated for large-scale genomic breeding applications as well as for detecting genetic purity and duplication in genebank and seed system. This newly developed mid-density assay, with 5,081 single nucleotide polymorphisms (SNPs) in groundnut now provides opportunities for deployment in applications mentioned above on a large scale. Being dynamic, AgriSeq genotyping-by-sequencing (T-GBS) assay can be easily modified in future by adding informative SNPs to further increase the utilization of this assay in regular breeding programs of groundnut globally. The deployment of this assay in groundnut will help in enhancing, and achieving high precision and accuracy in gene banks, breeding, pre-breeding, and seed system.

Background The RP-HPLC method has been established to simultaneous estimation of seven markers in polyherbal formulation JKC using the C 18 (25 × 0.46 cm, i.d,5 µm) column. The mobile phase consisted of methanol: water (80:20) at a flow rate of 1.0 mL/min and observed retention time at 2 to 11 min with sharp points. The marker compounds viz. Andrographolide (AG), Piperine (PP), Picroside-I (P-I), Picroside-II (P-II), α-Cyprone (AC), 6-Shogaol (6S), and 6-Gingerol (6G) were quantified in JKC formulations by HPLC method. Detection was performed at the wavelength (λ) of 229 nm for AG, 343 nm for PP, 279 nm for P-I, 264 nm for P-II, 254 nm for AC, and 280 nm for both 6S and 6G by HPLC–PDA detector. Results The marker compounds in JKC formulations were observed in different retention times (R t ) i.e. AG at 3.060 ± 0.01 min, PP at 5.460 ± 0.03 min, P-I at 2.789 ± 0.02 min, P-II at 2.553 ± 0.03 min, AC at 10.951 ± 0.02 min, 6S at 6.302 ± 0.03 min, and 6G at 4.111 ± 0.02 min respectively. The proposed method was validated with acceptable linearity (r 2 0.9995–0.9999), precision, robustness, ruggedness, and accuracy (RSD < 2%) under optimum conditions. The limit of detection and quantification of bioactive markers were as: AG (1.386; 4.200 ppm), PP (2.033; 6.161 ppm), P-I (2.822; 8.553 ppm), P-II (2.538; 7.691 ppm), AC (0.269; 0.815 ppm), 6G (0.158; 0.480 ppm), 6S (0.188; 0.569 ppm). The amount (mg/g) of bioactive markers detected and estimated in plants and formulation were as: AG (41.282 ± 0.48; 10.06 ± 0.18), PP (53.81 ± 0.25, 13.82 ± 0.37 in PN, PL; 4.27 ± 0.07), P-I (15.97 ± 0.01; 0.48 ± 0.003), P-II (63.24 ± 0.35; 2.31 ± 0.006), AC (0.42 ± 0.01; 0.36 ± 0.006), 6G (0.71 ± 0.03; 0.16 ± 0.001), and 6S (2.64 ± 0.09; 0.12 ± 0.004) respectively. Method was found to be rugged and robust. The results found for all the validation parameters were within the limits according to ICH guidelines. Conclusion The proposed method is fast, precise, economic, and specific and used for the simultaneously quantifiable analysis of seven major bioactive markers in the ingredients (herbs) and the JKC formulations.

We estimated the effectiveness of two doses of the ChAdOx1 nCoV-19 (Covishield) vaccine against any COVID-19 infection among individuals ≥45 years in Chennai, Tamil Nadu, India. A community-based cohort study was conducted from May to September 2021 in a selected geographic area in Chennai. The estimated sample size was 10,232. We enrolled 69,435 individuals, of which 21,793 were above 45 years. Two-dose coverage of Covishield in the 18+ and 45+ age group was 18% and 31%, respectively. Genomic analysis of 74 out of the 90 aliquots collected from the 303 COVID-19-positive individuals in the 45+ age group showed delta variants and their sub-lineages. The vaccine’s effectiveness against COVID-19 disease in the ≥45 age group was 61.3% (95% CI: 43.6–73.4) at least 2 weeks after receiving the second dose of Covishield. We demonstrated the effectiveness of two doses of the ChAdOx1 vaccine against the delta variant in the general population of Chennai. We recommend similar future studies considering emerging variants and newer vaccines. Two-dose vaccine coverage could be ensured to protect against COVID-19 infection.

We study chaos in non-Lorentzian field theories, specifically Galilean and Carrollian conformal field theories in two dimensions. In a large central charge limit, we find that the Lyapunov exponent saturates the bound on chaos, conjectured originally for relativistic field theories. We recover the same Lyapunov exponent holographically by a shock-wave calculation in three-dimensional flat space cosmologies, providing further evidence for flat space holography.