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The manuscript describes an efficient theoretical mechanism to implement the all-optical nibble multiplexer with tri-stated output using the micro-ring resonator (MRR) structure. The proposed article introduces the concept of ultrafast all-optical switching on a nonlinear material (GaAs-AlGaAs)-based MRR structure using the optical pumping method. Further, the switching activity of MRR is used to design the proposed all-optical nibble multiplexer with tri-stated outputs. The design technique involves the additional advantage of all-optical units. The complete layout of the proposed design is mathematically explained, and the desired results are proved using MATLAB simulation software. The article also discusses how to efficiently pick device settings by analyzing performance metrics such as coupling coefficients and radius of MRR structure. The performance affecting parameters of MRR are also analyzed in a detailed manner, which shows the suitability of the proposed unit in the all-optical domain. The design achieves a higher figure of merits, which increases the acceptability of such a device for the future ultrafast all-optical communication system.Graphical abstract

Effective forecasting of the Water Quality Index (WQI) considerably impacts water resource management as well as public health safety. This study proposes a new approach for WQI forecasting using stacked regression ensemble modeling integrated with SHAP (Shapley Additive explanations), a form of Explainable Artificial Intelligence (XAI). The model was developed using a dataset of 1,987 water quality samples from Indian rivers (2005–2014), processed through six optimized machine learning algorithms: XGBoost, CatBoost, Random Forest, Gradient Boosting, Extra Trees, and AdaBoost, combined using Linear Regression as the meta-learner. The model was trained using seven normalized physicochemical parameters as predictors, and the computed WQI (via the weighted arithmetic method) served as the response variable. The stacked ensemble model outperformed all individual models, achieving the highest performance across all evaluation metrics, with R² reaching 0.9952, Adjusted R² at 0.9947, MAE recorded at 0.7637, and RMSE reduced to 1.0704. Among the individual models, CatBoost and Gradient Boosting demonstrated the strongest standalone performance. CatBoost achieved an R² of 0.9894, Adjusted R² at 0.9883 MAE of 0.8399, and RMSE of 1.5905, while Gradient Boosting attained an R² of 0.9907, Adjusted R² at 0.9898 MAE of 1.0759, and RMSE of 1.4898, respectively. SHAP analysis revealed that DO, BOD, conductivity, and pH were the most influential parameters contributing to the prediction of WQI. This integrated framework improves existing approaches by providing high predictive accuracy and model interpretability along with real-time environmental monitoring capabilities. It fosters anticipatory environmental surveillance, automated policy frameworks, and confidence among stakeholders regarding the sustainability of water resources.

This study uses ETABS software’s sophisticated numerical modeling to investigate the seismic performance of multi-story reinforced concrete structures located in seismic zone 5. Three structural configurations, G+4, G+14, and G+24, with ground floor height 3.5 m & remaining floor height 3 m, were examined. Each was planned with four 5m spans in X & Y directions i.e. 20m x 20m square layout. Nonlinear direct integration time history analysis used in this study to assess dynamic structural reactions to seismic excitation. The study examined three different shear wall configurations: (1) Bare frame i.e. building without shear walls, (2) Building with shear walls at corner spans, and (3) Building with shear walls at the middle edges. Near field ground motion records from the Imperial Valley (IV) and Northridge (NR) earthquakes were used to generate seismic input, which included both parallel and normal elements. Important response parameters were measured to evaluate the impact of shear wall placement on seismic resilience, such as inter-story drift, and floor-wise displacement. In order to optimize structural design in high- seismic zones, the results provide important insights into the relative effectiveness of shear wall layouts in reducing seismic demands across structures of different heights.

Concrete is a material that is used universally in construction and it is in transformation to meet two pressing needs which include construction efficiency and environmental sustainability. Among many others, the alternative of replacing fine aggregate with waste rubber, especially crumb rubber that is obtained as an end-of-life tires discard, is a dual-benefit solution: it will decrease the environmental degradation caused by the disposal of rubber, but also decrease the excessive dependence on natural sand. The paper explores the mechanical performance and sustainability of the case whereby fine aggregate is replaced by different sizes and ratios of waste tire rubber in concrete. Based on recent studies and the experimental studies, the paper reviews the impact of rubber inclusion on compressive, split tensile, and flexural strengths, and freeze- thaw resistance, abrasion durability and long-term deformation properties. Experimental evidence shows a tendency of lower compressive strength and modulus of elasticity, which can be explained by lower stiffness of rubber but contrary positive changes in energy absorption, impact resistance, and durability were also noted. Closed porosity is also better incorporated with the use of rubber and therefore resists cracking under cyclic loading conditions. The research also reveals that the ideal particle gradation and replacement percentages (usually 5-15) can provide an achievable balance between retention and sustainability benefits of the strength. Also, SEM and chemical analysis can prove that there is proper bonding between rubber particles and cementitious base by using proper surface treatments. This piece of work highlights the possibilities of using crumb rubber as an aggregate into concrete by replacing fine aggregates. It provides a viable future line of approach in line with the principles of the circular economy, thereby aiding the decrease in solid waste pools and at the same time aiding in the development of eco- friendly infrastructure.

Pearl millet ( Pennisetum glaucum L. R. Br., syn. Cenchrus americanus [L.] Morrone) is a climate-resilient cereal and a vital fodder source in arid and semi-arid regions. Identification and characterization of diverse inbred lines are essential for developing superior forage composites and hybrids with enhanced yield and stress resilience. In this study, 96 fodder pearl millet inbreds along with four checks were evaluated during rainy season 2024 and summer seasons 2025 for 29 morpho-physiological and root architectural traits, complemented by molecular characterization using 46 polymorphic SSR markers. Significant genotypic variation and strong genotype × season interactions were observed for key yield and physiological traits, indicating substantial environmental responsiveness. Correlation analyses identified stem girth, plant height, dry matter yield, and major root traits as major determinants of green fodder yield. Morphological clustering grouped genotypes into five clusters, with maximum divergence between Clusters II and V. SSR analysis detected 203 alleles across 46 loci (average: 5.28 alleles per locus; PIC = 0.62), and population structure analysis resolved six genetic groups highlighting their potential use as heterotic parents. Based on combined phenotypic and molecular diversity, selected inbreds were randomly intermated to develop eight fodder composites. Two composites exhibited 17–20% higher green fodder yield than the best check cultivar. These results demonstrate that integrating morphological and molecular diversity enables effective parental selection and rapid development of superior high-biomass fodder pearl millet composites.

Sesame ( Sesamum indicum L.), an important oilseed crop, requires genetic improvement to ensure food security. Exploitation of a small fraction of genetic diversity is a major limiting factor for this crop. ICAR-NBPGR holds a large sesame base collection (6,000 unique accessions), originating from India and other countries. The study aims at the characterization of a sesame germplasm collection and development of working core set representing the variability of entire germplasm collection in the National Genebank. Characterization was carried out in an Augmented Block Design (ABD) under multi-environmental conditions (six locations representing five agro-ecological zones of India) for two consecutive years based on 33 agro-morphological traits, different levels of biotic stress (phyllody, dry root rot), abiotic stress (water logging, drought), and seed quality parameters (oil, protein, lignan, fatty acids). For core set preparation, the coincidence rate (CR%) for range and the variable rate (VR%) for coefficient of variation were maximum. Levene’s test and Newman-Keuls tests were performed to compare the entire and core collection. Diversity between the two (entire and core collection) was compared using Shannon–Weaver diversity index. We developed a sesame core set of 773 accessions, which consists of 12.88% of the entire collection. Developed core set exhibited a Coincidence rate (CR)% of 99.8% and a variable rate (VR%) of CV 103.59%. A multipurpose core set of sesame germplasm was assembled to benefit the plant breeding community (for trait introgression), farmers, and researchers to develop climate-resilient sesame cultivars.

Waste management is of great concern in today�s world. Every year, an enormous amount of solid waste is generated from different industrial activities. Especially, the waste which produces by iron industries in a particular form of slag. The major issue of emission of carbon-di-oxide from cement industries is a serious problem for the earth's environment and surrounding area. Thus, in this study, the waste iron slag obtained from nearby iron industries was used as a partial substitute for cement. The cement was replaced with iron slag (IS) at the substitution levels of 7.5%, 15%, 22.5%, 30%, and 37.5% by weight of cement. The doses of superplasticizer for every mix were taken based on the essential workability requirements for the reinforced concrete work. Performance of control and blended mixes were evaluated by workability evaluation, compressive strength test, flexural strength test, water permeability test, water absorption evaluation, rapid chloride penetration test (RCPT) and carbonation test. Scanning electron microscope (SEM), X-ray diffraction (XRD) techniques, and Thermogravimetric analysis (TGA) techniques were used to assess the microstructural changes and to evaluate the chemistry of blended mixes. The results obtained from this study were encouraging in terms of compressive and flexural strength. The maximum compressive and flexural strength was recorded at a 22.5% replacement level of slag. Although the results obtained at 30% replacement were also better than the control mix. Resistance of slag made concrete against adverse condition i.e. CO2 penetration, chloride penetration, and water penetration was far better than conventional ones. The results obtained from TGA indicated that the productivity of calcium silicate gel of slag concrete is better than control concrete.

Anaerobic digestion (AD) is widely recognised as a sustainable technology for managing organic waste and generating renewable energy. Despite its potential, slow kinetics, instability under varying operational conditions, and inhibition from toxic intermediates often hinder AD processes. Nanobiotechnology has emerged as a mechanistically promising approach to enhance process stability and methane production by strengthening microbial performance, accelerating hydrolysis kinetics, and reinforcing syntrophic electron transfer pathways. The addition of zero-valent iron, carbon nanotubes, and metal oxides enhances hydrolysis rates, stimulates methanogenic pathways, and facilitates direct interspecies electron transfer (DIET). These mechanisms collectively improve methane yield while maintaining redox balance, buffering capacity, and long-term operational stability. Evidence from laboratory- and pilot-scale studies indicates that nanomaterial amendments can enhance methane production, typically by 10%–60% under optimised dosing conditions in most systems, with higher enhancements reported for selected conductive transition metal carbides under controlled experimental regimes. Reductions in lag phase duration of 15%–40% and improved tolerance to ammonia concentrations exceeding 1.5–3.0 g L −1 NH 4 + –N have also been documented, depending on reactor configuration and substrate type. These enhancement ranges are derived from condition-resolved extraction of experimental studies meeting predefined inclusion criteria and were normalised against non-amended controls under identical operational settings rather than selectively cited maximum values. Additionally, integrating nanomaterials with pretreatment techniques, bioaugmentation, and bio-electrochemical systems offers synergistic pathways for optimising biogas production. However, the application of nanomaterials also raises important environmental and biosafety concerns, including their transformation during digestion, partitioning into digestates, potential impacts on soil and aquatic systems following land application, and challenges related to dose optimisation, recovery, and lifecycle risk assessment. This review applies a condition-resolved quantitative synthesis by extracting methane yield and production rate and stability indicators (e.g., lag phase, VFA, alkalinity, TAN/FAN tolerance) and normalising enhancements against non-amended controls within operational clusters (temperature regime, reactor configuration, ISR/SIR, substrate class, and nanomaterial dose).

The COVID-19 pandemic spurred mRNA vaccine innovation, but new SARS-CoV-2 variants highlight the need for vaccines with improved potency and durability. This report presents a novel mRNA vaccine platform encoding virus-like particle antigens (mRNA-VLPs) that mimic native virus structures, aiming to boost antibody responses via enhanced B cell activation. In animal studies, mRNA-VLP vaccines generated stronger neutralizing antibody responses across multiple variants compared to conventional mRNA vaccines expressing native spike proteins. In non-human primates, these elevated antibodies lasted at least six months. An mRNA-VLP vaccine encoding the Omicron spike outperformed traditional mRNA vaccines in mice as both a monovalent and bivalent (with ancestral spike) formulation. In hamsters, even low doses of mRNA-VLP vaccine provided complete protection, similar to high doses of native spike mRNA vaccines. These results suggest the mRNA-VLP platform could significantly strengthen vaccine efficacy and breadth against evolving SARS-CoV-2 variants.

Fiber Bragg Grating (FBG) is an up-and-coming technology for all-optical switching and sensing applications. The proposed manuscript deals with the all-optical sensing and switching mechanism of the non-linear Fiber Bragg Grating structure. Initially, the manuscript describes a detailed mathematical analysis of coupled-mode theory for the Fiber Bragg Grating structure and its utility as sensors and all-optical switches. The manuscript introduces the concept of all-optical switching based on the cross-phase modulation effect in a phase-shifted FBG. The optical pump signals are used to control the switching of a weak continuous wave optical signal. The switching characteristics of the FBG device are investigated to show the transferring process of the information from the pump signal to the weak continuous wave signal. Finally, cascaded structures of phase-shifted FBGs with various combinations of pump signals and phase shifts are used to design all-optical half-adder and subtractor circuits. The analysis of the results shows the suitability of the proposed FBG designs as sensors and switching units in the form of all-optical half-adder and half-subtractor circuits.