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Abstract Domain membrane protein (DMP) gene is one of the key genes regulating in vivo haploid production in maize. Here, full-length sequence (931 bp) of DMP gene was sequenced in five mutant and five wild-type maize inbreds to study allelic variation. Two SNPs viz., T to C (SNP1) and G to A (SNP2) that distinguished wild-type and mutant- allele of DMP gene, converted methionine to threonine and alanine to threonine at positions 44 and 87, respectively. Two breeder-friendly PCR-based markers (DMP_SNP_TC and DMP_SNP_GA) specific to SNP1 and SNP2 were developed. These markers identified four haplotypes, viz., Hap-DMP-TG, Hap-DMP-CG, Hap-DMP-TA, and Hap-DMP-CA among a set of 48 diverse maize inbreds. Both SNP1 and SNP2 were present in DUF679_motif-2 and DUF679_motif-1, respectively and were conserved among maize and its paralogues, hence resulting in altered protein. Analysis with 11 paralogues of maize showed high similarity with DMP gene. Comparison with 11 paralogues revealed that maize DUF679 protein of DMP gene was more similar to dmp_Zm_Zm00001eb110420 paralogue. Gene structure analysis showed that most of the DMP genes have single exon. The breeder-friendly markers developed in the present study can be utilized in marker-assisted introgression of DMP gene to develop new haploid inducer lines in maize. This is the first report on identification of novel SNP differentiating the wild-type and mutant allele of DMP gene, besides comprehensive molecular characterization of the DMP gene in maize and its paralogues.

Abstract This study presents a thermodynamic analysis of a mixed-mode solar dryer incorporating both sensible and latent heat energy storage materials. Black pebbles were utilized for sensible heat storage, while Lauric acid was selected for latent heat storage. The integration of these energy storage materials significantly enhanced the thermodynamic performance of the dryer, achieving a peak energy efficiency of 14.2% and a 53% increase in average energy efficiency. Additionally, the inclusion of latent heat storage in the collector resulted in the highest recorded collector energy efficiency of 84.6%. Exergy analysis indicated a maximum exergy efficiency of 51.3%, with an average exergy efficiency of 34.3% for the dryer. The implementation of combined thermal energy storage led to a 50% reduction in drying time. Sustainability assessments demonstrated that integrating both sensible and latent heat storage improved energy utilization while minimizing losses, thereby enhancing the overall sustainability and productivity of the solar dryer.The environmental analysis estimated a CO₂ mitigation potential of 83.97 tonnes per year, with a corresponding carbon credit value of $419.85. The system exhibited a remarkably low energy payback period of 1.82 years when operated with both thermal energy storage materials. This research underscores the potential benefits of combining latent and sensible heat storage in solar drying applications, highlighting its contribution to sustainability and the environmental advantages of solar thermal systems.

Abstract We examine the effectiveness of green innovation on CO2 emissions in the top twelve polluting nations—China, the US, India, Russia, Japan, South Korea, Canada, Mexico, Turkey, Italy, Poland, and the UK—from 1996 to 2020. Using panel data fixed and random effect model and decision tree analysis, we found that industrialization, urbanization, and economic growth increase CO2 emissions, whereas green energy consumption and governance decrease CO2 emissions. In the panel data tree-based model, governance is in the second and third positions in the decision tree fixed, and random effect model. Green innovation is not statistically significant despite the expected negative sign. The findings suggest that policymakers should encourage investment in green energy production and governance to combat environmental degradation. Investment in green energy should be escalated to ensure energy efficiency in the long term.

Abstract Many analyses are performed by the LHC experiments to search for heavy gauge bosons, which appear in several new physics models. The invariant mass reconstruction of heavy gauge bosons is difficult when they decay to $$\tau $$ τ leptons due to missing neutrinos in the final state. Machine learning techniques are widely utilized in experimental high-energy physics, in particular in analyzing the large amount of data produced at the LHC. In this paper, we study various machine learning techniques to reconstruct the invariant mass of $$Z^{\prime }~\rightarrow ~\tau \tau $$ Z ′ → τ τ and $$W^{\prime }~\rightarrow ~\tau \nu $$ W ′ → τ ν decays, which can improve the sensitivity of these searches.

Objective To determine the clinical manifestations, risk factors, treatment modalities and maternal outcomes in pregnant women with lab-confirmed COVID-19 and compare it with COVID-19 negative pregnant women in same age group. Design Multicentric case-control study. Data sources Ambispective primary data collection through paper-based forms from 20 tertiary care centres across India between April and November 2020. Study population All pregnant women reporting to the centres with a lab-confirmed COVID-19 positive result matched with controls. Data quality Dedicated research officers extracted hospital records, using modified WHO Case Record Forms (CRF) and verified for completeness and accuracy. Statistical analysis Data converted to excel files and statistical analyses done using STATA 16 (StataCorp, TX, USA). Odds ratios (ORs) with 95% confidence intervals (CI) estimated using unconditional logistic regression. Results A total of 76,264 women delivered across 20 centres during the study period. Data of 3723 COVID positive pregnant women and 3744 age-matched controls was analyzed. Of the positive cases 56·9% were asymptomatic. Antenatal complications like preeclampsia and abruptio placentae were seen more among the cases. Induction and caesarean delivery rates were also higher among Covid positive women. Pre-existing maternal co-morbidities increased need for supportive care. There were 34 maternal deaths out of the 3723(0.9%) positive mothers, while covid negative deaths reported from all the centres were 449 of 72,541 (0·6%). Conclusion Covid-19 infection predisposed to adverse maternal outcomes in a large cohort of Covid positive pregnant women as compared to the negative controls.

At the LHC, the gluon-initiated processes are considered to be the primary source of di-Higgs production. However, in the presence of a new resonance, the light-quark initiated processes can also contribute significantly. In this letter, we look at the di-Higgs production mediated by a new singlet scalar. The singlet is produced in both quark-antiquark and gluon fusion processes through loops involving a scalar leptoquark and right-handed neutrinos. With benchmark parameters inspired from the recent resonant di-Higgs searches by the ATLAS collaboration, we examine the prospects of such a resonance in the TeV-range at the High-Luminosity LHC (HL-LHC) in the bb¯τ+τ− mode with a multivariate analysis. We obtain the 5σ and 2σ contours and find that a significant part of the parameter space is within the reach of the HL-LHC.

PCR amplification and detection of GC rich sequences in DNA is a challenge due to formation of secondary structures which resist denaturation, thereby stalling Taq DNA polymerases as well as affecting primer annealing. Presently, high fidelity Taq DNA polymerase is used for amplifying long and GC-rich fragments, while dimethyl sulfoxide (DMSO) has also been suggested as an additive in Polymerase Chain Reaction (PCR) mix to avoid formation of secondary structures in templates containing high GC content. In the present study, the amplification efficiency of normal Taq DNA polymerase with 5% DMSO as compared to high fidelity Taq DNA polymerase has been applied for better amplification of fragments with high GC content of sd1 gene in rice. Normal Taq DNA polymerase with 5% DMSO displayed better and reproducible results as compared to platinum DNA polymerase for the amplification of gene sd1, thereby successfully detecting the dominant wild type allele governing tall plant height from the recessive semi-dwarf allele. There were no adverse effects of 5% DMSO in PCR amplification and the amplified fragments improved significantly indicating the improvement in amplification efficiency. The modified PCR protocol including DMSO provides a cost effective and cheaper alternative for reliable assessment of the genomic differences in GCrich regions of the gene. This will help in eliminating the need for costly high fidelity Taq DNA polymerase, thereby helping in economizing marker assisted selection.

Basmati rice is known for its extra-long slender grains, exceptional kernel dimensions after cooking, high volume expansion, and strong aroma. Developing high yielding Basmati rice varieties with good cooking quality is a gigantic task. Therefore, identifying the genomic regions governing the grain and cooked kernel dimension traits is of utmost importance for its use in marker-assisted breeding. Although several QTLs governing grain dimension traits have been reported, limited attempts have been made to map QTLs for grain and cooked kernel dimension traits of Basmati rice. In the current study, a population of recombinant inbred lines (RIL) was generated from a cross of Sonasal and Pusa Basmati 1121 (PB1121). In the RIL population, there was a significant positive correlation among the length (RRL: rough rice length, MRL: milled rice length, CKL: cooked kernel length) and breadth (RRB: rough rice breadth, MRB: milled rice breadth and CKB: cooked kernel breadth) of the related traits, while there was significant negative correlation between them. QTL mapping has led to the identification of four major genomic regions governing MRL and CKL. Two QTLs co-localize with the earlier reported major gene GS3 and a QTL qGRL7.1, while the remaining two QTLs viz., qCKL3.2 (qMRL3.2) and qCKL4.1 (qMRL4.1) were novel. The QTL qCKL3.2 has been bracketed to a genomic region of 0.78 Mb between the markers RM15247 and RM15281. Annotation of this region identified 18 gene models, of which the genes predicted to encode pentatricopeptides and brassinosteroid insensitive 1-associated receptor kinase 1 precursor may be the putative candidate genes. Furthermore, we identified a novel QTL qKER2.1 governing kernel elongation ratio (KER) in Basmati rice.

Abstract The search for new physics at high energy accelerators has been at the crossroads with very little hint of signals suggesting otherwise. The challenges at a hadronic machine such as the LHC is compounded by the fact that final states are swamped with jets which one needs to understand and unravel. A positive step in this direction would be to separate the jets in terms of their gluonic and quark identities, much in a similar spirit of distinguishing heavy quark jets from light quark jets that has helped in improving searches for both neutral and charged Higgs bosons at the LHC. In this work, we utilise this information using the jet substructure techniques to comment on possible improvements in sensitivity as well as discrimination of new resonances in the all hadronic mode that would be crucial in pinning down new physics signals at HL-LHC, HE-LHC and any future 100 TeV hadron collider.

Abstract Vector boson fusion proposed initially as an alternative channel for finding heavy Higgs has now established itself as a crucial search scheme to probe different properties of the Higgs boson or for new physics. We explore the merit of deep-learning entirely from the low-level calorimeter data in the search for invisibly decaying Higgs. Such an effort supersedes decades-old faith in the remarkable event kinematics and radiation pattern as a signature to the absence of any color exchange between incoming partons in the vector boson fusion mechanism. We investigate among different neural network architectures, considering both low-level and high-level input variables as a detailed comparative analysis. To have a consistent comparison with existing techniques, we closely follow a recent experimental study of CMS search on invisible Higgs with 36 fb $$^{-1}$$ - 1 data. We find that sophisticated deep-learning techniques have the impressive capability to improve the bound on invisible branching ratio by a factor of three, utilizing the same amount of data. Without relying on any exclusive event reconstruction, this novel technique can provide the most stringent bounds on the invisible branching ratio of the SM-like Higgs boson. Such an outcome has the ability to constraint many different BSM models severely.

Abstract Background Direct-seeded rice (DSR) is a potential technology for sustainable rice farming as it saves water and labor. However, higher incidence of weed under DSR limits productivity. Therefore, there is a need to develop herbicide tolerant (HT) rice varieties. Results We used marker assisted backcross breeding (MABB) to transfer a mutant allele of Acetohydroxy acid synthase (AHAS) gene, which confers tolerance to imidazolinone group of herbicides from the donor parent (DP) “Robin” into the genetic background of an elite popular Basmati rice variety, Pusa Basmati 1121 (PB 1121). Foreground selection was done using the AHAS gene linked Simple Sequence Repeat (SSR) marker RM6844 and background selection was performed using 112 genome-wide SSR markers polymorphic between PB 1121 and Robin. Phenotypic selection for agronomic, Basmati grain and cooking quality traits in each generation was carried out to improve the recovery of recurrent parent phenome (RPP). Finally, a set of 12 BC4F4 near isogenic lines (NILs), with recurrent parent genome (RPG) recovery ranging from 98.66 to 99.55% were developed and evaluated. PB 1121-HT NILs namely 1979-14-7-33-99-10, 1979-14-7-33-99-15 and 1979-14-7-33-99-66 were found superior to PB 1121 in yield with comparable grain and cooking quality traits and herbicide tolerance similar to Robin. Conclusion Overall, the present study reports successful development of HT NILs in the genetic background of popular Basmati rice variety, PB 1121 by introgression of mutated AHAS allele. This is the first report on the development of HT Basmati rice. Superior NILs are being evaluated in the national Basmati trials, the release of which is likely to provide a viable option for the adoption of DSR technology in Basmati rice cultivation.

Ammonia is a cytotoxic metabolite with pleiotropic molecular and metabolic effects, including senescence induction. During dysregulated ammonia metabolism, which occurs in chronic diseases, skeletal muscle becomes a major organ for nonhepatocyte ammonia uptake. Muscle ammonia disposal occurs in mitochondria via cataplerosis of critical intermediary metabolite α-ketoglutarate, a senescence-ameliorating molecule. Untargeted and mitochondrially targeted data were analyzed by multiomics approaches. These analyses were validated experimentally to dissect the specific mitochondrial oxidative defects and functional consequences, including senescence. Responses to ammonia lowering in myotubes and in hyperammonemic portacaval anastomosis rat muscle were studied. Whole-cell transcriptomics integrated with whole-cell, mitochondrial, and tissue proteomics showed distinct temporal clusters of responses with enrichment of oxidative dysfunction and senescence-related pathways/proteins during hyperammonemia and after ammonia withdrawal. Functional and metabolic studies showed defects in electron transport chain complexes I, III, and IV; loss of supercomplex assembly; decreased ATP synthesis; increased free radical generation with oxidative modification of proteins/lipids; and senescence-associated molecular phenotype–increased β-galactosidase activity and expression of p16INK, p21, and p53. These perturbations were partially reversed by ammonia lowering. Dysregulated ammonia metabolism caused reversible mitochondrial dysfunction by transcriptional and translational perturbations in multiple pathways with a distinct skeletal muscle senescence-associated molecular phenotype.

South Asian countries have seen remarkable economic growth and development in the past few decades. This has been driven by financial sector reforms, industrialization, and expansion of foreign trade. The present study is designed to identify the long- and short-run relationships among environmental degradation, economic growth, energy consumption, and trade openness in the South Asian region. Our research contributes to the literature by employing a new approach (the NARDL method). We examine annual data for four South Asian countries between 1971 and 2014. We found that there was a long-run equilibrium relationship between environmental degradation, economic growth, energy consumption, and trade openness. The results confirmed the inverted U-shaped EKC hypothesis only for India and Pakistan. However, the long-term coefficients related to energy consumption were statistically significant only in Pakistan. The most interesting finding was that only in Sri Lanka did the long-run coefficients associated with trade openness shocks significantly impact carbon dioxide emissions. These impacts were based on the scale effect. Our study has some policy implications. Foremost, the governments of South Asian countries should promote and subsidize green energy use by increasing R&D spending on renewable energy.

Pearl millet is a climate-resilient, nutritious crop with low input requirements that could provide economic returns in marginal agro-ecologies. In this study, we report quantitative trait loci (QTLs) for iron (Fe) and zinc (Zn) content from three distinct production environments. We generated a genetic linkage map using 210 F6 recombinant inbred line (RIL) population derived from the (PPMI 683 × PPMI 627) cross using genome-wide simple sequence repeats (SSRs). The molecular linkage map (seven linkage groups) of 151 loci was 3,273.1 cM length (Kosambi). The content of grain Fe in the RIL population ranged between 36 and 114 mg/Kg, and that of Zn from 20 to 106 mg/Kg across the 3 years (2014–2016) at over the three locations (Delhi, Dharwad, and Jodhpur). QTL analysis revealed a total of 22 QTLs for grain Fe and Zn, of which 14 were for Fe and eight were for Zn on three consecutive years at all locations. The observed phenotypic variance (R2) explained by different QTLs for grain Fe and Zn content ranged from 2.85 (QGFe.E3.2014–2016_Q3) to 19.66% (QGFe.E1.2014–2016_Q3) and from 2.93 (QGZn.E3.2014–2016_Q3) to 25. 95% (QGZn.E1.2014–2016_Q1), respectively. Two constitutive expressing QTLs for both Fe and Zn co-mapped in this population, one on LG 2 and second one on LG 3. Inside the QTLs candidate genes such as Ferritin gene, Al3+ Transporter, K+ Transporters, Zn2+ transporters and Mg2+ transporters were identified using bioinformatics approaches. The identified QTLs and candidate genes could be useful in pearl millet population improvement programs, seed, restorer parents, and marker-assisted selection programs.

Nucleate pool steaming is an effective mode of transfer of heat that helps to reduce the use of fossil fuels and thus reduce pollution. Transfer of heat in nucleate pool steaming is examined to occur through the combination of natural convection, enhanced latent heat and convection transport. At the intermediate heat flux range, all three components play a principal character. In the elevated flux of heat area as the heat flux increases the enhanced convection contribution decreases while latent heat transport contribution has been found to increase considerably. In this study, we attempt to develop a heat transfer relationship for the coefficient of transfer of heat and suggested based on the relative benefactions of three components to the boiling flux of heat. The current work stressed the absolute motion of warmth guaranteeing from the summation of each of the three segments of regular convection, upgraded convection and idle warmth transport for water and methanol with round mathematical formed. The hypotheses of air pocket development in nucleate pool bubbling hypothesize for a significant bit of warmth move to the air pocket happens by conduction through a fluid microlayer framed on the warmed surface has been thought of. The maximum deviation of error between the present analytical and experimental one for water, methanol, ethanol and benzene is 6.89%, 5.24%, 5.64% and 6.21% respectively. The highest divergence in the middle of the forecasted data and different (analytical and investigational) outcomes is found to be ±2.54. Results from many other investigators have also been compared for the better visualization of heat transfer correlations to the present one. The highest divergence in the middle of the forecasted data and investigational one for Nusselt number is observed to be ±3.27 along with the present analytical ones.

We develop empirical models using difference-in-difference method to find out how COVID-19 testing and infection rates impact the BRICS economy. Our results show that strict government measures, areas of poor people and people with heart diseases have resulted in high COVID-19 testing due to the increasing infections, However, economic development and population density are not found to be rather insignificant towards the COVID-19 testing rates. Hence, both from policy and pandemic perspectives, it is inferred that these developing economies need to divert more resources and infuse more investment in the healthcare sector in the coming days. • Governments must give due stress to the health sector along with development irrespective of nature of the economy. • Our results show that strict government measures, areas of poor people and people with heart diseases have resulted in high COVID-19 testing due to the increasing infections. • Both from policy and pandemic perspectives, it is inferred that these BRICS economies need to divert more resources and infuse more investment in the healthcare sector.

Plant oils serve as a major resource of food, feed, as well as raw materials for various industrial applications. Castor bean (Ricinus communis L.) is a plant of Euphorbiaceae family which have high level of ricinoleic acid (over 85%) in its seed. Ricinoleic acid is a hydroxy fatty acid (HFA) which is accumulated in seeds as Triacylglycerols (TAGs). Castor oil has a very high demand all over the world and India is the country who majorly fulfils world’s demand. Due to its wide industrial usages and associated undesirable characters such as low genetic variability, presence of toxin ricin and allergens, various approaches such as conventional and transgenic approaches are being undertaken for production of ricinoleic acid. For later, understanding of genes involved in the metabolic pathways for the synthesis and accumulation of such fatty acids are crucial, so that they can be engineered to alternate oilseed crops. Present research work deals with the cloning of fatty acid hydroxylase gene from high oil yielding varieties of castor. This study majorly discussed the accumulation of major fatty acids in developing seeds of castor variety (48-1) which describes storage reserve accumulation. Ricinoleic acid accumulation started between 20-30 days after flowering (DAF) and continued to increase till 40 DAF with a slight decrease during maturation stage. This study can be further utilized for biotechnological interventions for production of ricinoleic acid.

This paper presents a modified intuitionistic fuzzy clustering (IFCM) algorithm for medical image segmentation. IFCM is a variant of the conventional fuzzy C-means (FCM) based on intuitionistic fuzzy set (IFS) theory. Unlike FCM, IFCM considers both membership and nonmembership values. The existing IFCM method uses Sugeno’s and Yager’s IFS generators to compute nonmembership value. But for certain parameters, IFS constructed using above complement generators does not satisfy the elementary condition of intuitionism. To overcome this problem, this paper adopts a new IFS generator. Further, Hausdorff distance is used as distance metric to calculate the distance between cluster center and pixel. Extensive experimentations are carried out on standard datasets like brain, lungs, liver and breast images. This paper compares the proposed method with other IFS based methods. The proposed algorithm satisfies the elementary condition of intuitionism. Further, this algorithm outperforms other methods with the use of various cluster validity functions.

A class of phenolphthalein anilide (PA)-based poly(ether sulfone) multiblock copolymers containing pendant quaternary ammonium (QA) and imidazolium (IM) groups were synthesized and evaluated as anion exchange membrane (AEM) materials. The AEMs were flexible and mechanically strong with good thermal stability. The ionomeric multiblock copolymer AEMs exhibited well-defined hydrophobic/hydrophilic phase-separated morphology in small-angle X-ray scattering and atomic force microscopy. The distinct nanophase separated membrane morphology in the AEMs resulted in higher conductivity (IECw = 1.3–1.5 mequiv./g, σ(OH−) = 30–38 mS/cm at 20 °C), lower water uptake and swelling. Finally, the membranes were compared in terms of microbial fuel cell performances with the commercial cation and anion exchange membranes. The membranes showed a maximum power density of ~310 mW/m2 (at 0.82 A/m2); 1.7 and 2.8 times higher than the Nafion 117 and FAB-PK-130 membranes, respectively. These results demonstrated that the synthesized AEMs were superior to Nafion 117 and FAB-PK-130 membranes.

Rice germplasm is a rich resource for discovering genes associated with salt tolerance. In the current study, a set of 96 accessions were evaluated for seedling stage salinity tolerance and its component traits. Significant phenotypic variation was observed among the genotypes for all the measured traits and eleven accessions with high level of salt tolerance at seedling stage were identified. The germplasm set comprised of three sub-populations and genome-wide association study (GWAS) identified a total of 23 marker–trait associations (MTAs) for traits studied. These MTAs were located on rice chromosomes 1, 2, 5, 6, 7, 9, and 12 and explained the trait phenotypic variances ranging from 13.98 to 29.88 %. Twenty-one MTAs identified in this study were located either in or near the previously reported quantitative trait loci (QTLs), while two MTAs namely, qSDW2.1 and qSNC5 were novel. A total of 18 and 13 putative annotated candidate genes were identified in a genomic region spanning ~200 kb around the MTAs qSDW2.1 and qSNC5, respectively. Some of the important genes underlying the novel MTAs were OsFBA1,OsFBL7, and mTERF which are known to be associated with salinity tolerance in crops. These MTAs pave way for combining salinity tolerance with high yield in rice genotypes through molecular breeding.

Drought stress at the reproductive stage in rice is one of the most important cause for yield reduction, affecting both productivity and quality. All Basmati rice varieties, including the popular cultivar “Pusa Basmati 1 (PB1)” is highly sensitive to reproductive stage drought stress (RSDS). We report for the first time, improvement of a Basmati cultivar for RSDS tolerance, with the introgression of a major quantitative trait locus (QTL), “qDTY1.1” into PB1. The QTL was sourced from an aus variety, Nagina 22 (N22). A microsatellite (simple sequence repeat (SSR)) marker “RM 431” located at telomeric end (38.89 mb) of chromosome 1, and located within a 1.04 mb QTL region was employed for foreground selection for qDTY1.1 in the marker assisted backcross breeding process. A set of 113 SSR markers polymorphic between N22 and PB1 were utilized for background selection to ensure higher recurrent parent genome recovery. After three backcrosses followed by five generations of selfing, eighteen near isogenic lines (NILs) were developed, through combinatory selection for agro-morphological, grain and cooking quality traits. The NILs were evaluated for three consecutive Kharif seasons, 2017, 2018 and 2019 under well-watered and drought stress conditions. RSDS tolerance and yield stability indicated that P1882-12-111-3, P1882-12-111-5, P1882-12-111-6, P1882-12-111-7, P1882-12-111-12, P1882-12-111-15 and P1882-12-111-17 were best in terms of overall agronomic and grain quality under RSDS. Additionally, NILs exhibited high yield potential under normal condition as well. The RSDS tolerant Basmati NILs with high resilience to water stress, is a valuable resource for sustaining Basmati rice production under water limiting production environments.

A class of phenolphthalein anilide (PA)-based poly(ether sulfone) multiblock copolymers containing pendant quaternary ammonium (QA) and imidazolium (IM) groups were synthesized and evaluated as anion exchange membrane (AEM) materials. The AEMs were flexible and mechanically strong with good thermal stability. The ionomeric multiblock copolymer AEMs exhibited well-defined hydrophobic/hydrophilic phase-separated morphology in small-angle X-ray scattering and atomic force microscopy. The distinct nanophase separated membrane morphology in the AEMs resulted in higher conductivity (IECw = 1.3-1.5 mequiv./g, σ(OH-) = 30-38 mS/cm at 20 °C), lower water uptake and swelling. Finally, the membranes were compared in terms of microbial fuel cell performances with the commercial cation and anion exchange membranes. The membranes showed a maximum power density of ~310 mW/m2 (at 0.82 A/m2); 1.7 and 2.8 times higher than the Nafion 117 and FAB-PK-130 membranes, respectively. These results demonstrated that the synthesized AEMs were superior to Nafion 117 and FAB-PK-130 membranes.