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Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatologists in detection, yet the nuances between melanoma and non-melanoma conditions complicate diagnosis. Early identification of melanoma is vital for successful treatment, but manual diagnosis is time-consuming and requires a dermatologist with training. To overcome this issue, this article proposes an Optimized Attention-Induced Multihead Convolutional Neural Network with EfficientNetV2-fostered melanoma classification using dermoscopic images (AIMCNN-ENetV2-MC). The input pictures are extracted from the dermoscopic images dataset. Adaptive Distorted Gaussian Matched Filter (ADGMF) is used to remove the noise and maximize the superiority of skin dermoscopic images. These pre-processed images are fed to AIMCNN. The AIMCNN-ENetV2 classifies acral melanoma and benign nevus. Boosted Chimp Optimization Algorithm (BCOA) optimizes the AIMCNN-ENetV2 classifier for accurate classification. The proposed AIMCNN-ENetV2-MC is implemented using Python. The proposed approach attains an outstanding overall accuracy of 98.75%, less computation time of 98 s compared with the existing models., (© 2024. International Federation for Medical and Biological Engineering.)

The bio-based solid polymer electrolyte serves as a promising choice for the next generation of energy storage devices to meet the requirement of green chemistry. In the current research, a green plasticized magnesium ion-conducting biopolymer electrolyte was developed using simple solution casting method for Electric Double Layer Capacitors (EDLC) applications. The biopolymer Cellulose Acetate (CA) as the host polymer, with varying concentrations of BaTiO 3 as the nanofiller, Mg(CF 3 SO 3 ) 2 as the ionic dopant, and PEG as the plasticizer. A 2 wt% addition of BaTiO 3 to the biopolymer electrolyte exhibits maximum conductivity measuring 2.4 × 10 -3  S/cm. Linear Sweep Voltammetry (LSV) analysis demonstrates maximum stability voltage of 3.51 V. The ionic transference number (t ion ) and (t Mg ) were determined to be 0.99 and 0.41 respectively. The fabricated EDLC device with the same electrolyte showed polarisation curve without any noticeable peaks in the Cyclic Voltammetry (CV) plot, indicating no redox reactions occurring at the electrode-electrolyte interface. Galvanostatic Charge Discharge (GCD) results showed excellent coulombic efficiency, stability and Energy Density and Power Density performance over 2000 cycles. The incorporation of BaTiO 2+ into biopolymer membranes presents a viable approach towards sustainable energy storage solutions by enhancing the energy storage capacity of EDLC devices.3 into biopolymer membranes presents a viable approach towards sustainable energy storage solutions by enhancing the energy storage capacity of EDLC devices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study investigates the spatial and temporal variations of dry-deposited particles on the surface (by turbulence or gravity) in various sites within Gabès city and its surroundings, South-eastern Tunisia. Monthly samples were collected from five distinct locations: suburban-industrial (S2), suburban-residential (S3), and urban sites (S1, S4, and S5). The average monthly particle deposition flows ranged from 7.35 ± 4.24 g/m 2 to 14.41 ± 6.09 g/m 2 , with the suburban-industrial site (S2) exhibiting the highest deposition rates. They are lower than the reference value of 30 g/m 2 in the AFNOR NF-X43-007, but much higher than the Swiss OPair standard (6 g/m 2 ). Compared to the German standard (TALUFT; 10.5 g/m 2 ), only S2 showed significant exceedances. Hierarchical cluster analysis revealed notable statistical affinities among the study sites. Heavy metal analysis indicated fluctuating concentrations across sites, with Zn being the most abundant, followed by Pb, Cu, Ni, and Cd. The enrichment factor (EF) and geoaccumulation index (Igeo) suggested varying degrees of contamination and pollution, highlighting the impact of anthropogenic sources. The findings underscore the need for targeted mitigation strategies to address particle deposition and heavy metal contamination in Gabès and similar regions globally., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Groundwater pollution caused by fluoride is a significant concern for the global population owing to its toxicity, which has negative health consequences. Industrial discharges, agricultural practices, and improper waste disposal are primary concerns in evaluating the degree of fluoride contamination in the selected districts of Eastern India. In a targeted area sampling approach, exactly 196 samples were collected during pre- and post-monsoon, and precise fluoride detection was performed using Ion-Selective Electrodes. Fluoride levels in pre-monsoon water were observed within a range of 0.02 to 2.7 mg/L, with an average abundance of 0.4 ± 0.50. In post-monsoon, the concentration ranged from 0.02 to 4.7 mg/L (mean 0.53 ± 0.60). The study found that 97 % of groundwater samples had acceptable fluoride levels within the 1.5 mg/L limit during pre and post-monsoon. Moreover, approximately 87 % of the samples exhibit fluoride content below the 1 mg/L limit. The hazard quotient was observed to be 0.17 to 0.58 in adults, 0.23 to 0.79 in children and 0.36 to 1.26 in infants during pre-monsoon, whereas 0.05 to 0.55 in adults, 0.12 to 0.74 in children and 0.11to 1.19 in infants during post monsoon. The above data indicates that infants had the highest risk of fluoride exposure, with a significant negative correlation between fluoride and calcium ions. Fluoride had minimal to no link with other ions, a modest positive correlation with sulfate, and a weak negative relationship with overall hardness and alkalinity across both seasons. The present study contributes towards the identification of fluoride levels in various areas, making society aware of water contamination and its health impacts., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Foodomics is an interdisciplinary field that integrates various omics technologies to explore the complex relationship between food and human health in depth. This approach offers valuable insights into the biochemical, molecular, and cellular composition of food by employing advanced omics techniques. Its applications span the food industry and human health, including efforts to combat malnutrition, provide dietary recommendations, and ensure food safety. This paper critically examines the successful applications of foodomics across areas such as food safety, quality, traceability, processing, and bioactivity. It highlights the crucial role of metabolomics, proteomics, and transcriptomics in achieving a comprehensive understanding of food components, their functions, and their interactions with human biology., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier Ltd.)

Artificial Intelligence (AI) is revolutionizing the food industry by optimizing processes, improving food quality and safety, and fostering innovation. This review examines AI's applications in food science, including supply chain management, production, sensory science, and personalized nutrition. It discusses techniques like knowledge-based expert systems, fuzzy logic, artificial neural networks, and machine learning, highlighting their roles in predictive maintenance, quality control, product development, and waste management. The integration of AI with sophisticated sensors enhances real-time monitoring and decision-making in food safety and packaging. However, challenges such as ethical concerns, data security, transparency, and high costs persist. AI is poised to advance sustainability by optimizing resource use, enhance food security through predictive analytics of crop yields, and drive innovation in personalized nutrition and supply chain automation, ensuring tailored products and efficient delivery. This paper underscores AI's transformative potential in the food industry while addressing the obstacles to its widespread adoption., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

The requirement for accurate treatments for skin diseases and wounds, generated a rising interest towards multifunctional polymer composites, that are capable of mimicking the natural compositions in human body. Also, electroactive composite films disseminate endogenous electrical stimulations that encourage cell migration and its proliferation at wound site, proposing greater opportunities in upgrading the conventional wound patches. In this work, the composite film made of graphene oxide, Ag 2 O, PVA and chitosan were developed for wound healing applications, by the solution casting method. The even dispersibility of nanofiller in polymeric matrix was validated from the physicochemical analyses. The increment in roughness of the composite film surface was noted from AFM images. The thermal stability and porous nature of the polymer composite were also verified. A conductivity value of 0.16 × 10 -4 Scm -1 was obtained for the film. From MTT assay, it was noted that the films were non-cytotoxic and supported cell adhesion along with cell proliferation of macrophage (RAW 264.7) cells. Moreover, the composite film also demonstrated non-hemolytic activity of <2 %, as well as excellent antibacterial activity towards E. coli and S. aureus. Thus, the obtained results validated that the prepared composite film could be chosen as an innovative candidate for developing state-of-the-art wound dressings., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In the modern era, nanomedicine has developed novel drug-delivery strategies to improve chemotherapy. Nanotechnological-based treatment approaches for cancer through targeted tumour drug delivery and stimulus-responsive tumour microenvironment have gained tremendous success in oncology. The application of building block materials of these nanomedicines plays a vital role in cancer remediation. Despite successful application in various medical treatments, nanocarriers' lack of biodegradability and biocompatibility makes their use in a clinical context difficult. In addition, the preparation of current drug delivery systems is a major constraint. The current cancer treatment methods aim to destroy diseased tissue, frequently with the use of radiation and chemotherapy. These treatment options are accompanied by a significant level of toxicity, which has excellent potential to further medical issues in the afflicted patient. Polyhydroxyalkanoate (PHA) polymers are biodegradable and biocompatible polyesters that can potentially be used as nanoparticular delivery systems for cancer treatment. Previously, PHA has shown tremendous application as a packaging material in the food and pharma industry. PHA-based nanocarriers are an effective drug delivery system because of their non-immunogenicity, regulated drug release, high drug loading capacity, and targeted drug delivery. This review focuses on creating and using PHA-based nanocarriers in cancer treatment. Despite its many benefits, PHA-based nanocarriers have yet to progress to clinical trials for drug delivery applications due to several issues, including the polymers' hydrophobic nature and high production costs. This review examines these challenges along with existing alternatives., Competing Interests: Declaration of competing interest The authors declare no conflict of interests. No funding received., (Copyright © 2024 Elsevier B.V. All rights reserved.)

ADHD is a prevalent childhood behavioral problem. Early ADHD identification is essential towards addressing the disorder and minimizing its negative impact on school, career, relationships, as well as general well-being. The present ADHD diagnosis relies primarily on an emotional assessment which can be readily influenced by clinical expertise and lacks a basis of objective markers. In this paper, an innovative IoT based ADHD detection is proposed using an EEG signal. To the input EEG signal, the min-max normalization technique is processed. Features are extracted as the subsequent step, where improved fuzzy feature, in which the entropy is estimated to increase the effectiveness of recognizing the vector along with, fractal dimension, wavelet transform and non-linear features are extracted. Also, proposes the new hybrid PUDMO algorithm to select the optimal features from the extracted feature set. Subsequently, the selected features are fed to the proposed hybrid detection system that including IDBN and LSTM classifier to detect whether it is ADHD or not. Further, the weights of both classifiers are tuned optimally as per the hybrid PUDMO algorithm to enhance the detection performance. The PUDMO achieved an accuracy of 0.9649 in the best statistical metric, compared to the SLO's 0.8266, SOA's 0.8201, SMA's 0.8060, BRO's 0.8563, DE's 0.8083, POA's 0.8537, and DMOA's 0.8647, respectively. Thus, the assessments and detection help the clinicians to take appropriate decision.

This research is to develop dictated metrics using a multi-proxy approach such as spatial-temporal analysis, statistical evaluation, and hydrogeochemical analysis. We have collected 45 groundwater samples located in the Tamirabarani river basin. To evaluate the aptness of developed metrics for agriculture and domestic needs and eleven years dataset has been analyzed and compared with national and international standards BIS, ICMAR, and WHO Monitoring and all the analysis results revealed that the concentration of calcium (Ca-1679 to 4937 mg/L; and Cl ions 236 to 1126 mg/L) and chloride ions was on the higher side in locations. These higher values may be attributed to the regional point sources as untreated water disposal and off-peak sources as agriculture practices. According to the results of the principal component analysis, the post-monsoon season accounted for an 84.2% variance. The major analyzed cations and anions have been observed in the following order: Na +  > Ca 2+  > Mg 2+  > K + and Cl -  > HCO 3 -  > SO 4 2- , Mg-Ca-Cl, Na-C1, and infused waters have been discovered in the basin region, indicating that anion and cation dominance is not prevalent. This specifies that groundwater quality in this region is significantly degraded and suffers from extensive salinity due to the urban pollutants mixed with unprotected river sites.3 - respectively. Ca-Mg-HCO 3 , Mg-Ca-Cl, Na-C1, and infused waters have been discovered in the basin region, indicating that anion and cation dominance is not prevalent. This specifies that groundwater quality in this region is significantly degraded and suffers from extensive salinity due to the urban pollutants mixed with unprotected river sites., (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Gellan gum (GG) - the microbial exopolysaccharide is increasingly being adopted into drug development, tissue engineering, and food and pharmaceutical products. In spite of the commercial importance and expanding application horizon of GG, little attention has been directed toward the exploration of novel microbial cultures, development of advanced screening protocols, strain engineering, and robust upstream or downstream processes. This comprehensive review not only attempts to summarize the existing knowledge pool on GG bioprocess but also critically assesses their inherent challenges. The process optimization design augmented with advanced machine learning modeling tools, widely adopted in other microbial bioprocesses, should be extended to GG. The unification of mechanistic insight into data-driven modeling would help to formulate optimal feeding and process control strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

A multi-stimuli responsive tetraphenyl substituted tripehnylamine-based aggregation induced emissive (AIE) material coupled with spiropyran was prepared. Owing to the presence of AIE and photochromic moiety, the molecule exhibits emissive aggregates, photochromism, and acidochromism. The multiple stimuli sensitive behavior of the molecule was explored for anti-counterfeiting behavior on TLC plate and commercial banknotes. The fluorogenic and photogenic response under UV and visible light established the potential of the candidate as a new generation encryption material., (© 2024 Wiley-VCH GmbH.)

The dairy industry is becoming one of the biggest sectors within the global food industry, and these industries use almost 34% of the water. The amount of water used is governed by the production process and the technologies employed in the plants. Consequently, the dairy industries generate almost 0.2-10 L of wastewater per liter of processed milk, which must be treated before being discharged into water bodies. The cultivation of microalgae in a mixotrophic regime using dairy wastewater enhances biomass growth, productivity, and the accumulation of value-added product. The generated biomass can be converted into biofuels, thus limiting the dependence on petroleum-based crude oil. To fulfill the algal biorefinery model, it is important to utilize every waste stream in a cascade loop. Additionally, the harvested water generated from algal biomass production can be recycled for further microalgal growth. Economic and sustainable wastewater management, along with proper reclamation of nutrients from dairy wastewater, is a promising approach to mitigate the problem of water scarcity. A bibliometric study revealing limited work on dairy wastewater treatment using microalgae for biofuel production. And, limited work is reported on the pretreatment of dairy wastewater via physicochemical methods before microalgal-based treatment. There are still significant gaps remains in large-scale cultivation processes. It is also crucial to discover robust strains that are highly compatible with the specific concentration of contaminants, as this will lead to increased yields and productivity for the targeted bio-product. Finally, research on reutilization of culture media in photobioreactor is necessary to augument the productivity of the entire process. Therefore, the incorporation of the microalgal biorefinery with the wastewater treatment concept has great potential for promoting ecological sustainability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Singh, Mohanty and Mohanty.)

Purpose: Food forensics is an emerging field and the initial part of this review showcases the toxic effects and the instrumental methods applied for the detection of the most commonly used azo dyes. Electrochemical detection has a lot of advantages and hence the significance of the most important techniques used in the electrochemical detection is discussed. The major part of this review highlights the surface modified electrodes, utilized for the detection of the most important azo dyes to achieve low detection limit (LOD)., Methods: A thorough literature study was conducted using scopus, science direct and other scientific databases using specific keywords such as toxic azo dyes, electrochemical detection, modified electrodes, LOD etc. The recent references in this field have been included., Results: From the published literature, it is observed that with the growing interests in the field of electrochemical techniques, a lot of importance have been given in the area of modifying the working electrodes. The results unambiguously show that the modified electrodes outperform bare electrodes and offer a lower LOD value., Conclusion: According to the literature reports it can be concluded that, compared to other detection methods, electrochemical techniques are much dependable and reproducible. The fabrication of the electrode material with the appropriate modifications is the main factor that influences the sensitivity. Electrochemical sensors can be designed to be more sensitive, more reliable, and less expensive. These sensors can be effectively used by toxicologists to detect trace amounts of harmful dyes in food samples., (© 2024. The Author(s), under exclusive licence to Japanese Association of Forensic Toxicology.)

Yellow mosaic disease (YMD) with typical symptoms of alternating bright yellow to green patches associated with stunting, downward cupping, and wrinkling has been observed in mung bean on agricultural farms in Coimbatore, Tamil Nadu, India. PCR using gene-specific primers indicated the presence of the yellow mosaic virus in symptomatic plants. Rolling circle amplification (RCA) followed by restriction digestion detected ~2.7 kb of DNA-A and DNA-B, allowing the identification of a bipartite genome. The full-length genome sequences were deposited in NCBI GenBank with the accession numbers MK317961 (DNA-A) and MK317962 (DNA-B). Sequence analysis of DNA-A showed the highest sequence identity of 98.39% to the DNA-A of mungbean yellow mosaic virus (MYMV)-Vigna radiata (MW736047), while DNA-B exhibited the highest level of identity (98.21%) to the MYMV-Vigna aconitifolia isolate (DQ865203) reported from Tamil Nadu. Recombinant analysis revealed distinct evidence of recombinant breakpoints of DNA-A within the region encoding the open reading frame (ORF) AC2 (transcription activation protein), with the major parent identified as MYMV-PA1 (KC9111717) and the potential minor parent as MYMV-Namakkal (DQ86520.1). Interestingly, a recombination event in the common region (CR) of DNA-B, which encodes the nuclear shuttle protein and the movement protein, was detected. MYMIV-M120 (FM202447) and MYMV-Vigna (AJ132574) were identified as the event's major and minor parents, respectively. This large variation in DNA-B led us to suspect a recombination in DNA-B. Dimeric MYMV infectious clones were constructed, and the infectivity was confirmed through agroinoculation. In future prospects, unless relying on screening using whiteflies, breeders and plant pathologists can readily use this agroinoculation procedure to identify resistant and susceptible cultivars to YMD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Balasubramaniam, Thangavel, Aiyanathan, Rathnasamy, Rajagopalan, Subbarayalu, Natesan, Kanagarajan, Muthurajan and Manickam.)

Despite considerable advances in interventions and treatment, there is a high mortality rate in patients with myocardial infarction (MI). This is the first study to investigate the protective effects of 3, 4-dihydroxybenzoic acid against isoproterenol induced MI in rats. MI was induced by isoproterenol (100-mg/kg body weight) in rats. Then, rats were treated with 3, 4-dihydroxybenzoic acid (16-mg/kg body weight) for 2 weeks. Serum creatine kinase-MB, cardiac troponin-T, cardiac troponin-I, and heart thiobarbituric acid reactive substances were significantly (p < 0.05) increased and heart superoxide dismutase and catalase activities were significantly (p < 0.05) reduced in isoproterenol-induced myocardial infarcted rats. Isoproterenol induction significantly (p < 0.05) elevated the plasma homocysteine and serum high sensitivity-C-reactive protein levels. Furthermore, an enzyme-linked immunosorbent assay, reverse transcription polymerase chain study, and immunohistochemical (IHC) staining revealed significantly (p < 0.05) elevated levels and expression of serum/myocardial nuclear factor-κB, tumor necrosis factor-alpha, interleukin-1 beta, and Interleukin-6 and significantly (p < 0.05) reduced levels/expression of serum/myocardial interleukin-10 in myocardial infarcted rats. Nevertheless, isoproterenol-induced rats treated with 3, 4-dihydroxybenzoic acid considerably (p < 0.05) attenuated all the biochemical, molecular, and IHC parameters investigated and inhibited oxidative stress and inflammation and protected the heart, through its antioxidant and anti-inflammatory mechanisms., (© 2024 Wiley Periodicals LLC.)

Bioactive polysaccharides and oligosaccharides were successfully extracted from three distinct seaweeds: Sargassum sp., Graciallaria sp., and Ulva sp. utilizing various extraction techniques. The obtained polysaccharides and oligosaccharides were subjected to comprehensive characterization, and their potential antioxidant properties were assessed using a Hep G2 cell model. Analysis via FTIR spectroscopy unveiled the presence of sulfate groups in the polysaccharides and oligosaccharides derived from Sargassum sp. The antioxidant capabilities were assessed through various assays (DPPH, ABTS, Fe-ion chelation, and reducing power), revealing that SAR-OSC exhibited superior antioxidant activity than others. This was attributed to its higher phenolic content (24.6 μg/mg), FRAP value (36 μM Vitamin C/g of extract), and relatively low molecular weight (5.17 kDa). The study also investigated the protective effects of these polysaccharides and oligosaccharides against oxidative stress-induced damage in Hep G2 cells by measuring ROS production and intracellular antioxidant enzyme expressions (SOD, GPx, and CAT). Remarkably, SAR-OSC demonstrated the highest efficacy in protecting Hep G2 cells reducing ROS production and downregulating SOD, GPx, and CAT expressions. Current findings have confirmed that the oligosaccharides extracted by the chemical method show higher antioxidant activity, particularly SAR-OSC, and robust protective abilities in the Hep G2 cells., Competing Interests: Conflict of interestThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript., (© Association of Food Scientists & Technologists (India) 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.)

The prompt and precise identification and delineation of tumor regions within glioma brain images are critical for mitigating the risks associated with this life-threatening ailment. In this study, we employ the UNet convolutional neural network (CNN) architecture for glioma tumor detection. Our proposed methodology comprises a transformation module, a feature extraction module, and a tumor segmentation module. The spatial domain representation of brain magnetic resonance imaging images undergoes decomposition into low- and high-frequency subbands via a non-subsampled shearlet transform. Leveraging the selective and directive characteristics of this transform enhances the classification efficacy of our proposed system. Shearlet features are extracted from both low- and high-frequency subbands and subsequently classified using the UNet-CNN architecture to identify tumor regions within glioma brain images. We validate our proposed glioma tumor detection methodology using publicly available datasets, namely Brain Tumor Segmentation (BRATS) 2019 and The Cancer Genome Atlas (TCGA). The mean classification rates achieved by our system are 99.1% for the BRATS 2019 dataset and 97.8% for the TCGA dataset. Furthermore, our system demonstrates notable performance metrics on the BRATS 2019 dataset, including 98.2% sensitivity, 98.7% specificity, 98.9% accuracy, 98.7% intersection over union, and 98.5% disc similarity coefficient. Similarly, on the TCGA dataset, our system achieves 97.7% sensitivity, 98.2% specificity, 98.7% accuracy, 98.6% intersection over union, and 98.4% disc similarity coefficient. Comparative analysis against state-of-the-art methods underscores the efficacy of our proposed glioma brain tumor detection approach.

Due to the massive growth in Internet of Things (IoT) devices, it is necessary to properly identify, authorize, and protect against attacks the devices connected to the particular network. In this manuscript, IoT Device Type Identification based on Variational Auto Encoder Wasserstein Generative Adversarial Network optimized with Pelican Optimization Algorithm (IoT-DTI-VAWGAN-POA) is proposed for Prolonging IoT Security. The proposed technique comprises three phases, such as data collection, feature extraction, and IoT device type detection. Initially, real network traffic dataset is gathered by distinct IoT device types, like baby monitor, security camera, etc. For feature extraction phase, the network traffic feature vector comprises packet sizes, Mean, Variance, Kurtosis derived by Adaptive and concise empirical wavelet transforms. Then, the extracting features are supplied to VAWGAN is used to identify the IoT devices as known or unknown. Then Pelican Optimization Algorithm (POA) is considered to optimize the weight factors of VAWGAN for better IoT device type identification. The proposed IoT-DTI-VAWGAN-POA method is implemented in Python and proficiency is examined under the performance metrics, like accuracy, precision, f-measure, sensitivity, Error rate, computational complexity, and RoC. It provides 33.41%, 32.01%, and 31.65% higher accuracy, and 44.78%, 43.24%, and 48.98% lower error rate compared to the existing methods.

Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Facial emotion recognition (FER) is largely utilized to analyze human emotion in order to address the needs of many real-time applications such as computer-human interfaces, emotion detection, forensics, biometrics, and human-robot collaboration. Nonetheless, existing methods are mostly unable to offer correct predictions with a minimum error rate. In this paper, an innovative facial emotion recognition framework, termed extended walrus-based deep learning with Botox feature selection network (EWDL-BFSN), was designed to accurately detect facial emotions. The main goals of the EWDL-BFSN are to identify facial emotions automatically and effectively by choosing the optimal features and adjusting the hyperparameters of the classifier. The gradient wavelet anisotropic filter (GWAF) can be used for image pre-processing in the EWDL-BFSN model. Additionally, SqueezeNet is used to extract significant features. The improved Botox optimization algorithm (IBoA) is then used to choose the best features. Lastly, FER and classification are accomplished through the use of an enhanced optimization-based kernel residual 50 (EK-ResNet50) network. Meanwhile, a nature-inspired metaheuristic, walrus optimization algorithm (WOA) is utilized to pick the hyperparameters of EK-ResNet50 network model. The EWDL-BFSN model was trained and tested with publicly available CK+ and FER-2013 datasets. The Python platform was applied for implementation, and various performance metrics such as accuracy, sensitivity, specificity, and F1-score were analyzed with state-of-the-art methods. The proposed EWDL-BFSN model acquired an overall accuracy of 99.37 and 99.25% for both CK+ and FER-2013 datasets and proved its superiority in predicting facial emotions over state-of-the-art methods.

Efficient treatment of textile dyeing wastewater can be achieved through electrocoagulation (EC) with minimal sludge production; however, the selection of the appropriate electrode is essential in lowering overall costs. Also, the reuse of the treated aqueous azo dye solution from this process has not been explored in detail. With these objectives, this study aims to treat synthetic azo dye solutions and achieve high colour removal efficiency (CRE%) using similar (Ti-Ti) and dissimilar (Ti-Cu) metal electrodes through EC with an attempt to reduce the cost. The aqueous Coralene Rubine GFL azo dye was used to examine the efficiency and cost of the EC process. X-Ray Photoelectron Spectroscopy was used to study the EC mechanism, while High Performance Liquid Chromatography was used to analyse the degradation of the dye and the formation of intermediate compounds. The concentration of metal ions in the treated dye solution was quantified using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES), with Ti-Ti treated solution having 14.20 mg/L concentration of Ti and Ti-Cu treated solution having 0.078 mg/L of Ti and 0.001 mg/L of Cu, respectively. Colour removal efficiency of 99.49% was obtained for both electrode sets, with a lower operating time and voltage for dissimilar metal combination. Ecotoxicity studies showed negligible toxicity of Ti-Cu treated dye samples compared to untreated solutions. Survival rate, protein estimation, and catalase activity was used to validate the treatment method's efficacy. The study found that the dissimilar electrode material exhibited reduced toxicity due to the presence of heavy metals below the permissible limit., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)

The application of quinolones stretches over a large umbrella of medicinal field as well as chemosensor due to the presence of privileged heterocyclic aromatic rig system. Salicyl and Naphthyl Hydrazide motifs are also established fluorophore groups. Therefore in this work, we have designed and synthesized Salicyl hydrazide (3a-c) and naphthyl hydrazide fused nitroquinolones (5a-c) investigated for their fluorescent behaviour. Preliminary UV- absorption studies were carried out and the metal selectivity were examined with various metal ion. Among them, it was found that compound 3a was selective towards Fe 3+ ions (λ ex  = 330 nm, 1:1 DMF:H 2 O at pH = 7.4 in HEPES Buffer medium). 3a shows decrease emission intensity in presence of Fe 3+ ions. Compound 5a shows enhancement in fluorescence intensity upon addition of Pb 2+ ion (λ ex  = 280 nm, 1:1 DMF:H 2 O at pH = 7.4 in HEPES Buffer medium). Further, the concentration dependence, competitive binding and EDTA reversibility were studied for selected compounds towards the respective cations selectivity. Jobs plot analysis indicate that 1:1 binding of 3a with Fe 3+ ion (K a  = 3.17 x10 4 M -1 and Limit Of Detection (LOD) = 5.1 × 10 -7 M) whereas 5a showed 1:2 binding mode with Pb 2+ ions (K a  = 2.14 × 10 6  M -1 and Limit Of Detection (LOD) = 2.613 × 10 -9  M). Density Function Theoretical studies were performed as support for the experimental results., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Steady-state visually evoked potential is one of the active explorations in the brain-computer interface research. Electroencephalogram based brain computer interface studies have been widely applied to perceive solutions for real-world problems in the healthcare domain. The classification of externally bestowed visual stimuli of different frequencies on a human was experimented to identify the need of paralytic people. Although many classifiers are at the fingertip of machine learning technology, recent research has proven that ensemble learning is more efficacious than individual classifiers. Despite its efficiency, ensemble learning technology exhibits certain drawbacks like taking more time on selecting the optimal classifier subset. This research article utilizes the Harris Hawk Optimization algorithm to select the best classifier subset from the given set of classifiers. The objective of the research is to develop an efficient multi-classifier model for electroencephalogram signal classification. The proposed model utilizes the Boruta Feature Selection algorithm to select the prominent features for classification. Thus selected prominent features are fed into the multi-classifier subset which has been generated by the Harris Hawk Optimization algorithm. The results of the multi-classifier ensemble model are aggregated using Stacking, Bagging, Boosting, and Voting. The proposed model is evaluated against the acquired dataset and produces a promising accuracy of 96.1%, 98.7%, 91.91%, and 99.01% with the ensemble techniques respectively. The proposed model is also validated with other performance metrics such as sensitivity, specificity, and F1-Score. The experimental results show that the proposed model proves its supremacy in segregating the multi-class classification problem with high accuracy., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Scientific research targeted at enhancing scaffold qualities has increased significantly during the last few decades. This emphasis frequently centres on adding different functions to scaffolds in order to increase their usefulness as instruments in the field of regenerative medicine. This study aims to investigate the efficacy of a multifunctional sustainable polymer scaffold, specifically Polycaprolactone (PCL) embedded with hydroxyapatite co-doped with vanadium and strontium (HVS), for bone tissue engineering applications. Polycaprolactone was used to fabricate the scaffold, while hydroxyapatite co-doped with vanadium and strontium (HVS) served as the nanofiller. A thorough investigation of the physicochemical and biological characteristics of the HVS nanofiller was carried out using cutting-edge techniques including Dynamic Light Scattering (DLS), and X-ray Photoelectron Spectroscopy (XPS) and in vitro cell studies. A cell viability rate of more than 70 % demonstrated that the synthesised nanofiller was cytotoxic, but in an acceptable range. The mechanical, biological, and physicochemical properties of the scaffold were extensively evaluated after the nanofiller was integrated. The water absorption characteristics of scaffold were enhanced by the addition of HVS nanofillers, leading to increased swelling, porosity, and hydrophilicity. These improvements speed up the flow of nutrients and the infiltration of cells into the scaffold. The scaffold has been shown to have important properties that stimulate bone cell activity, including better biodegradability and improved mechanical strength, which increased from 5.30 ± 0.37 to 10.58 ± 0.42 MPa. Further, its considerable antimicrobial qualities, blood-compatible nature, and capacity to promote biomineralization strengthen its appropriateness for usage in biomedical applications. Mainly, enhanced Alkaline phosphatase (ALP) activity, Alizarin Red Staining (ARS) activity, and excellent cell adhesive properties, indicating the outstanding osteogenic potential observed in rat bone marrow-derived stromal cells (rBMSC). These combined attributes highlight the pivotal role of these nanocomposite scaffolds in the field of bone tissue engineering., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Biofilms play a decisive role in the infectious process and the development of antibiotic resistance. The establishment of bacterial biofilms is regulated by a signal-mediated cell-cell communication process called "quorum sensing" (QS). The identification of quorum sensing inhibitors (QSI) to mitigate the QS process may facilitate the development of novel treatment strategies for biofilm-based infections. In this study, the traditional medicinal plant Ocimum sanctum was screened for QS inhibitory potential. Sub-MICs of the extract significantly affected the secretion of EPS in Gram-negative human pathogens such as Escherichia coli , Pseudomonas aeruginosa PAO1, Proteus mirabilis , and Serratia marcescens , as well as aquaculture pathogens Vibrio harveyi , V. parahaemolyticus , and V. vulnificus , which render the bacteria more sensitive, leading to a loss of bacterial biomass from the substratum. The observed inhibitory activity of the O. sanctum extract might be attributed to the presence of eugenol, as evidenced through ultraviolet (UV)-visible, gas chromatography-mass spectroscopy (GC-MS), Fourier transformer infrared (FTIR) spectroscopy analyses, and computational studies. Additionally, the QSI potential of eugenol was corroborated through in vitro studies using the marker strain Chromobacterium violaceum .

Li-ion batteries stand out among energy storage systems due to their higher energy and power density, cycle life, and high-rate performance. Development of advanced, high-capacity anodes is essential for enhancing their performance, safety, and durability, and recently, two-dimensional materials have garnered extensive attention in this regard due to distinct properties, particularly their ability to modulate van der Waals gap through intercalation. Covalently intercalated Graphene oxide interlayer galleries with mono-Boc-ethylenediamine (GO-EnBoc) was synthesized via the ring opening of epoxide, forming an amino alcohol moiety. This creates three coordination sites for Li ion exchange on the graphene oxide nanosheets' surface. Consequently, the interlayer d -spacing expands from 8.47 Å to 13.17 Å, as anticipated. When explored as an anode, Li-GO-EnBoc shows a significant enhancement in the stable and reversible capacity of 270 mA h g -1 at a current density of 25 mA g -1 compared to GO (80 mA h g -1 ), without compromising the mechanical or chemical stability. Through 13 C, 7 Li and 6 Li MAS NMR, XPS, IR, Raman microscopy, and density functional theory (DFT) calculations, we confirm the positioning of Li + ions at multiple sites of the interlayer gallery, which enhances the electrochemical performance. Our findings suggest that these novel systematically modulated van der Waals gap GO-engineered materials hold promise as efficient anodes for Li-ion batteries., Competing Interests: The authors are not involved in conflict of interest., (This journal is © The Royal Society of Chemistry.)

Objective: The Global IDEAL Sub-Framework Study aimed to combine the intended effects of the 2009/2019 IDEAL (Idea, Development, Exploration, Assessment, Long-term study) Framework recommendations on evaluating surgical innovation with the vision outlined by the 2015 Lancet Commission on Global Surgery to provide recommendations for evaluating surgical innovation in low-resource environments., Design: A mixture of methods including an online global survey and semistructured interviews (SSIs). Quantitative data were summarized with descriptive statistics and qualitative data were analyzed using the Framework Method., Participants: Surgeons and surgical researchers from any country., Main Outcome Measures: Findings were used to suggest the nature of adaptations to the IDEAL Framework to address the particular problems of evaluation in low-resource settings., Results: The online survey yielded 66 responses representing experience from 40 countries, and nine individual SSIs were conducted. Most respondents (n=49; 74.2%) had experience evaluating surgical technologies across a range of life cycle stages. Innovation was most frequently adopted based on colleague recommendation or clinical evaluation in other countries. Four themes emerged, centered around: frugal innovation in technological development; evaluating the same technology/innovation in different contexts; additional methodologies important in evaluation of surgical innovation in low/middle-income countries; and support for low-income country researchers along the evaluation pathway., Conclusions: The Global IDEAL Sub-Framework provides suggestions for modified IDEAL recommendations aimed at dealing with the special problems found in this setting. These will require validation in a stakeholder consensus forum, and qualitative assessment in pilot studies. From assisting researchers with identification of the correct evaluation stage, to providing context-specific recommendations relevant to the whole evaluation pathway, this process will aim to develop a comprehensive and applicable set of guidance that will benefit surgical innovation and patients globally., Competing Interests: Competing interests: PM is an editor-in-chief., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)

The present study investigates S. cumini seed extracts which are considered as a promising and valuable source of bioactive compounds were prepared using different solvents such as methanol, ethanol, petroleum ether, acetone, chloroform, and diethyl ether. Among these solvents, methanol exhibited the highest extraction with a yield of 42 %. HPLC analysis revealed the highest concentration of quercetin flavonoids (49.62 mg/gm) in the methanolic S. cumini seed extract. Thus, the current work deals with the MgONPs synthesis through a biological approach using different S. cumini seed extracts. In vitro anti-oxidant properties were evaluated, which showed an IC 50 value of 22.46 μg/mL for MgONPs synthesized from methanolic extract, surpassing the anti-oxidant potency of ascorbic acid by threefold. By leveraging the rich repository of bioactive compounds found within S. cumini seed extract, this study presents a novel approach to MgONPs synthesis. Exploring the symbiotic relationship between S. cumini seed extract and MgONPs, this research elucidates the pivotal role of bioactive compounds in guiding the formation and properties of nanostructures. Further anti-microbial studies on MgONPs from methanolic S. cumini seed extract were conducted against four different bacterial strains ( Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and S. typhimurium ), revealing potent anti-microbial activity with 5.3 mm of inhibition for 100 µl against S. typhimurium . These findings suggest that S. cumini is a source of bioactive compounds responsible for the successful synthesis of MgONPs. Characterization studies of MgONPs were also carried out using UV-vis spectroscopy, FTIR, SEM, XRD, DSC and HPLC., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors. Published by Elsevier B.V.)

The study assesses the mechanical efficiency, long-lasting characteristics, microstructure, and sustainability of sustainable concrete (SC) samples through several optimization methods, emphasizing the significance of the 3Rs (recycle, reuse, reduce) approach in the construction sector. The study uses advanced techniques like the Taguchi method, grey relational analysis (GRA), analysis of variance (ANOVA), and signal-noise ratio (SNR) to optimize parameters affecting the performance of SC. In this study, the properties of SC are assessed by considering various parameters. These parameters include the use of 10 %, 20 %, and 30 % of ground granulated blast furnace slag (GGBFS) as a replacement for fly ash (FA). Additionally, six different binder contents ranging from 300 kg/m 3 to 600 kg/m 3 are examined. The study also investigates three different molarities of sodium hydroxide (NaOH) (8 M, 12 M, and 16 M), three different ratios of alkaline activators (AA) (1.5, 2.0, and 2.5), three different AA to-binder ratios (0.30, 0.35, and 0.40), and curing temperature (CT) of 30 °C, 60 °C, and 90 °C. The study includes fresh properties such as fresh density (FD) and slump, mechanical properties such as tensile strength (TS), flexural strength (FS), modulus of elasticity (MOE), and compressive strength (CS), and durability studies such as dry density (DD), impact strength, water absorption (WA), and sorptivity. The blended proportions were obtained using the Taguchi method. The study shows that GGBFS accelerates geopolymerization in FA-based concrete, reducing setting time and early-age CS. FA is crucial for setting time, workability, and CS enhancement. GGBFS increases the densities of fresh and hardened concrete, with a highly correlated increase, allowing accurate hardened density prediction with a coefficient of 0.9057. The CS of the cube SC surpassed 40 MPa, irrespective of variables such as the AA ratio, CT, and NaOH molarity. The trail mix with a binder concentration of 600 kg/m 3 , 30 % GGBFS content, 12 M NaOH molarity, 1.5 AA ratio, 0.35 AA to binder ratio, and 90 °C CT exhibited the greatest strength. Mixtures containing 10 % GGBFS can attain a CS above 30 MPa after 28 days, making them suitable for structural purposes. The T 18 mix exhibited a compact Calcium (alumino) silicate hydrate (C-A-S-H) and N-A-S-H gel, whereas the T 3 mix displayed a varied and permeable structure. The study used GRA, ANOVA, and SNR methods to analyze properties varying by six variables, finding GGBFS content as the most influencing parameter. The study found that the SC had a lower sustainability score than the OPC mix, but had better energy efficiency., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)

Around the world, the market for plant-derived beverages is one of the fastest-expanding segments in the functional and specialty beverage areas of newer food product development. Consumers are increasingly likely to choose alternatives to bovine beverages due to factors including lactose intolerance, hypercholesterolemia prevalence, allergies to bovine beverages, and preference for vegan diets that contain functionally active ingredients with health-promoting characteristics. Due to health, ecological, and ethical concerns, many customers are interested in reducing their usage of animal products like bovine milk. A variety of plant-based beverage substitutes are being created by the food sector as a result. To create viable alternatives, it is first necessary to provide an overview of the chemical composition, structure, features, and nutritional attributes of ordinary bovine milk. Sensory acceptability in the case of substitutes for beverages made from legumes is a significant barrier to their widespread acceptance, and thus saliva acts as a sophisticated fluid that serves a variety of purposes in the cavity of the mouth. Designing and producing next-generation plant-based beverages that mimic the physicochemical and functional qualities of conventional bovine-based beverages is gaining popularity, and many of these products can be thought of as colloidal materials that contain the particles or polymers that give them their unique qualities NG-PB foods can have a wide range of rheological qualities, such as fluids with low viscosity (such as plant-based beverages), high-viscosity liquids (like creams), soft liquids (like yogurt), as well as hard solids (such as some cheeses)., (© 2024 Wiley Periodicals LLC.)

This Schiff base chemosensor (SNN) detected dual ions, Al 3+ and Zn 2+ ions selectively. Fluorescence spectrum investigations showed that Al 3+ ions increased fluorescence intensity, notably at 493 nm. Introducing Zn 2+ ions caused a significant blue shift of roughly ∼65 nm at a wavelength of 434 nm, resulting in a notable change in fluorescence intensity. When binding Al 3+ /Zn 2+ ions, the SNN receptor uses three methods. Inhibition of photoinduced electron transfer (PET), excited state intramolecular proton transfer (ESIPT), and restriction of CN isomerization. The jobs plot method found that SNN + Al 3+ and SNN + Zn 2+ complexations had a 1:1 stoichiometry. DFT, LC-HRMS, and 1 H NMR titration confirm this conclusion. The probe SNN's limit of detection (LOD) for Al 3+ /Zn 2+ ions was 3.99 nM and 1.33 nM. Latent fingerprint (LFP), food samples, pharmaceutical products, and E. coli pathogen bio-imaging have all used the SNN probe to identify Al 3+ and Zn 2+ ions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Synthesized monomer and its three oligoesters were characterized by techniques such as 1 H, 13 C{ 1 H}, IR, UV, GPC and applied to chemosensor applications. A series of metal ions was studied with fluorophores to evaluate the sensitivity towards Cu 2+ ion. The fluorophores results exhibit the selective and sensitive "Turn off" fluorescence response with Cu 2+ ion in DMF/H 2 O (1:1, pH: 7.4, fluorophore: 5 µM) solution. Binding stoichiometry and binding constant of fluorophores were calculated using Stern-Volmer equation and Benesi-Hildebrand plots, respectively. Structure of fluorophores were studied using DFT, B3LYP/6-311 +  + G(d,p) level basis set. Quenching mechanisms and electrical properties of fluorophores were explained with theoretical outcomes. Iodine doped and undoped oligoesters electrical conductivity were studied in solid-state and the conductivity was gradually increased with increase the contact time of iodine with oligoesters. At different frequencies and temperatures, the dielectric measurement was calculated using the two-probe method. Among all oligoesters, DMDAP exhibited high electrical conductivity and DMDMP has a higher dielectric constant value than other oligoesters., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The marine red algae Kappaphycus alvarezii (KA), commonly known as cottonii , is a valuable resource with diverse applications. Research has primarily focused on its primary metabolites such as amino acids, proteins, plant hormones etc. Additionally, KA also produces secondary metabolites under stress, some of which exhibit antioxidant and antibacterial properties. This review provides a comprehensive overview of recent in vitro and in vivo research on KA, delving into their therapeutic effects and potential pharmaceutical applications. The study followed a through literature survey in three databases. From the obtained literature, the studies fitting the criteria were reviewed. The study explores the underlying mechanisms behind the algae's diverse characteristics. The results show that KA is a valuable resource for potential therapeutic applications, but a deeper exploration of its various metabolites and rigorous research are necessary for a thorough understanding of its capabilities.

Cerebrovascular accidents (CVAs) often occur suddenly and abruptly, leaving patients with long-lasting disabilities that place a huge emotional and economic burden on everyone involved. CVAs result when emboli or thrombi travel to the brain and impede blood flow; the subsequent lack of oxygen supply leads to ischemia and eventually tissue infarction. The most important factor determining the prognosis of CVA patients is time, specifically the time from the onset of disease to treatment. Artificial intelligence (AI)-assisted neuroimaging alleviates the time constraints of analysis faced using traditional diagnostic imaging modalities, thus shortening the time from diagnosis to treatment. Numerous recent studies support the increased accuracy and processing capabilities of AI-assisted imaging modalities. However, the learning curve is steep, and huge barriers still exist preventing a full-scale implementation of this technology. Thus, the potential for AI to revolutionize medicine and healthcare delivery demands attention. This paper aims to elucidate the progress of AI-powered imaging in CVA diagnosis while considering traditional imaging techniques and suggesting methods to overcome adoption barriers in the hope that AI-assisted neuroimaging will be considered normal practice in the near future. There are multiple modalities for AI neuroimaging, all of which require collecting sufficient data to establish inclusive, accurate, and uniform detection platforms. Future efforts must focus on developing methods for data harmonization and standardization. Furthermore, transparency in the explainability of these technologies needs to be established to facilitate trust between physicians and AI-powered technology. This necessitates considerable resources, both financial and expertise wise which are not available everywhere., Competing Interests: The authors have declared that no competing interests exist., (Copyright © 2024, Hastings et al.)

Advancements in research concerning the occurrence of microplastics (MPs) in human blood, sputum, urine, and breast milk samples have piqued the interest of the scientific community, prompting further investigation. MPs present in the placenta, amniotic fluid, and meconium raise concerns about interference with embryonic development, leading to preeclampsia, stillbirth, preterm birth, and spontaneous abortion. The challenges posed by MPs extend beyond pregnancy, affecting the digestive, reproductive, circulatory, immune, and central nervous systems. This has spurred scientists to examine the origins of MPs in distinct environmental layers, including air, water, and soil. These risks continue after birth, as neonates are continuously exposed to MPs through everyday items such as breast milk, cow milk and infant milk powder, as well as plastic-based products like feeding bottles and breast milk storage bags. It is the need of the hour to strike a balance amidst lifestyle changes, alternative choices to traditional plastic products, raising awareness about plastic-related health risks, and fostering collaboration between the scientific community and policymakers. This review aims to provide fresh insights into potential sources of MP pollution, with a specific focus on pregnancy and neonates. It is the first compilation of its kind so far that includes critical studies on recently reported discoveries., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

This study delves into the intricate dynamics of air pollution in the rapidly expanding northern regions of India, examining the intertwined influences of agricultural burning, industrialization, and meteorological conditions. Through comprehensive analysis of key pollutants (PM 2.5 , PM 10 , NO 2 , SO 2 , CO, O 3 ) across ten monitoring stations in Uttar Pradesh, Haryana, Delhi, and Punjab, a consistent pattern of high pollution levels emerges, particularly notable in Delhi. Varanasi leads in SO 2 and O 3 concentrations, while Moradabad stands out for CO levels, and Jalandhar for SO 2 concentrations. The study further elucidates the regional distribution of pollutants, with Punjab receiving significant contributions from SW, SE, and NE directions, while Haryana and Delhi predominantly face air masses from SE and NE directions. Uttar Pradesh's pollution sources are primarily local, with additional inputs from various directions. Moreover, significant negative correlations (p < 0.05) between PM 10 , NO 2 , SO 2 , O 3 , and relative humidity (RH) underscore the pivotal role of meteorological factors in shaping pollutant levels. Strong positive correlations between PM 2.5 and NO 2 (0.71 to 0.93) suggest shared emission sources or similar atmospheric conditions in several cities. This comprehensive understanding highlights the urgent need for targeted mitigation strategies to address the multifaceted drivers of air pollution, ensuring the protection of public health and environmental sustainability across the region., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Kodo millet (Paspalum scrobiculatum L.) is an underutilized crop that encompasses nutritional benefits and climate resilience, making it a viable option for future crop development with nutraceutical properties. The cultivation of this crop has ancient roots, where it was revered for its ability to thrive in times of famine and was a vital companion crop to rice. Dishes made with Kodo millet are highly palatable and can be easily integrated into mainstream rice-based dishes. Among all cereals, Kodo millet is distinguished by its gluten-free composition, high phosphorus content, and significant antioxidant potential, which contributes to a diet that may reduce cardiovascular disease risk. Often grown in rainfed zones by marginal farmers, Kodo millet is valued for its grain and fodder. This less demanding crop can tolerate both biotic and abiotic stress, allowing it to thrive in soils with low organic matter and with minimal inputs, making it an ideal dual-purpose crop for rainfed areas. Despite its nutritional and agricultural benefits, Kodo millet's popularity is hindered by challenges such as low yield, market demand, lodging at harvest, and poor dehulling recovery, which necessitate the development of high-yielding varieties through the latest breeding advancements. Systematic investment and concerted breeding efforts are essential to harness the full potential of this nutrient-dense crop. The absence of whole genome sequence for Kodo millet poses a barrier to uncovering novel genetic traits. Consequently, there is an imperative to establish a millet-based value chain that elevates these underutilized crops, shaping smart cropping patterns and enhancing nutritional profiles for sustainable diets. Accordingly, this review highlights the significance of Kodo millet and the impact of breeding to establish it as a smart food choice for the future., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Mathematical modelling of microbial polyhydroxyalkanoates (PHAs) production is essential to develop optimal bioprocess design. Though the use of mathematical models in PHA production has increased over the years, the selection of kinetics and model identification strategies from experimental data remains largely heuristic. In this study, PHA production from Cupriavidus necator utilizing sucrose and urea was modelled using a parametric discretization approach. Product formation kinetics and relevant parameters were established from urea-free experimental sets, followed by the selection of growth models from a batch containing both sucrose and urea. Logistic growth and Luedeking-Piret model for PHA production was selected based on regression coefficient (R 2 : 0.941), adjusted R 2 (0.930) and AICc values (-42.764). Model fitness was further assessed through cross-validation, confidence interval and sensitivity analysis of the parameters. Model-based optimal batch startup policy, incorporating multi-objective desirability, suggests an accumulation of 2.030 g l -1 of PHA at the end of 120 h. The modelling framework applied in this study can be used not only to avoid over-parameterization and identifiability issues but can also be adopted to design optimal batch startup policies., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Organic fluorescence sensor for selectively detecting and quantifying toxic heavy metal ions has received significant interest due to their environmental hazards. Herein, we have designed and synthesized a simple tripodal Schiff base ligand (1) based on hydroxy-naphthaldehyde and tris(2-aminoethyl)amine (TREN) and demonstrated highly selective turn-on fluorescence sensing of Cd 2+ ions. The free ligand did not show any fluorescence in DMF. In contrast, Cd 2+ (10 - 4  M) addition exhibited a strong enhancement of fluorescence at 450 nm. Interestingly, other metal ions including Zn 2+ , which exhibit similar chemistry, did not show any turn-on fluorescence. The concentration-dependent studies of 1 with Cd 2+ showed the detection limit of 6.78 × 10 - 8  M. NMR spectra of 1 with Cd 2+ and computational studies were performed to understand the mechanism of sense., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Silica nanoparticles, also known as SiO 2 nanoparticles, have wider applications in biomedical, building, water treatment, agriculture, and food industries. It is used as an anticaking agent in the food industry, used to remove heavy metals from water, and used in cement-based materials. SiO 2 nanoparticles synthesized by physical and chemical methods require high energy and use of toxic chemicals which is quite expensive, have a greater impact causing health-related issues, and have environmental side effects. Hence, there is a need to synthesize nanoparticles in an eco-friendly way. The biological or green synthesis method uses microbes, such as bacteria, fungi, algae, and plants for synthesizing nanoparticles. Algae contain natural biochemicals that act as reducing agents. These biomolecules are non-toxic as they are naturally occurring compounds and can be used to fabricate nanoparticles by avoiding the use of toxic chemicals in an eco-friendly method. In this study, silica nanoparticles were synthesized by green synthesis methods using microalgae extract. Further, the green synthesized silica nanoparticles were characterized using ultra violet-visible (UV-VIS) spectroscopy, Fourier transform-infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and energy-dispersive X-ray analysis (EDAX). The antimicrobial activity of the silica nanoparticles against E. coli was studied. This study revealed that the nanoparticles can be synthesized using green synthesis methods with low cost, less toxic chemicals, eco-friendly, and have antimicrobial activity against E. coli., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The rapid deployment of 5G networks necessitates innovative solutions for efficient and dynamic resource allocation. Current strategies, although effective to some extent, lack real-time adaptability and scalability in complex, dynamically-changing environments. This paper introduces the Dynamic Resource Allocator using RL-CNN (DRARLCNN), a novel machine learning model addressing these shortcomings. By merging Convolutional Neural Networks (CNN) for feature extraction and Reinforcement Learning (RL) for decision-making, DRARLCNN optimizes resource allocation, minimizing latency and maximizing Quality of Service (QoS). Utilizing a state-of-the-art "5G Resource Allocation Dataset", the research employs Python, TensorFlow, and OpenAI Gym to implement and test the model in a simulated 5 G environment. Results demonstrate the effectiveness of DRARLCNN, showcasing an impressive R score of 0.517, MSE of 0.035, and RMSE of 0.188, surpassing existing methods in allocation efficiency and latency. The DRARLCNN model not only outperforms existing methods in allocation efficiency and latency but also sets a new benchmark for future research in dynamic 5G resource allocation. Through its innovative approach and promising results, DRARLCNN opens avenues for further advancements in optimizing resource allocation within dynamic 5G networks.2 score of 0.517, MSE of 0.035, and RMSE of 0.188, surpassing existing methods in allocation efficiency and latency. The DRARLCNN model not only outperforms existing methods in allocation efficiency and latency but also sets a new benchmark for future research in dynamic 5G resource allocation. Through its innovative approach and promising results, DRARLCNN opens avenues for further advancements in optimizing resource allocation within dynamic 5G networks.

In recent years, researchers have been actively investigating metal oxide-based materials with narrow bandgaps due to their potential applications toward wastewater treatment and oxygen evolution reactions (OER). In this study, we successfully synthesized g-C 3 N 4 (GCN), Fe 2 O 3, and Fe 2 O 3 /g-C 3 N 4 (FGCN) using thermal polymerization and hydrothermal methods. We characterized the physicochemical and structural properties of these materials through various analytical techniques including XRD, FT-IR, UV-DRS, XPS, FE-SEM, and HR-TEM analyses, confirming the effective construction of the FGCN composite catalyst. We evaluated the photocatalytic activity of Fe 2 O 3 , GCN, and FGCN composite catalysts by assessing their ability to degrade rhodamine B (RhB) and crystal violet (CV) by exposing them to sunlight for 150 min. Among these catalysts, the FGCN composite demonstrated excellent photocatalytic performance, achieving 93 % and 95 % degradation of RhB and CV, respectively, under 150 min of sunlight exposure. The developed Fe 2 O 3 /g-C 3 N 4 @Nickel foam (FGCN@NF) composite catalyst exhibits remarkable OER performance, with a reduced Tafel slope of 64 mV/dec and a low overpotential of 290 mV at a current density of 10 mA/cm 2 and shows excellent durable performance over a long time (15 h). Total Organic Carbon (TOC) analysis confirmed the mineralization of both dyes. The photocatalytic performance remained largely unchanged after five consecutive experiments, demonstrating excellent reusability and photostability. Trapping experiments revealed that O 2 is the main species responsible for the photocatalytic decomposition of various dyes by the FGCN composite catalyst. Therefore, the development of a versatile photo/electrocatalytic system that can efficiently promote energy conversion in environmental applications has attracted great attention.●- is the main species responsible for the photocatalytic decomposition of various dyes by the FGCN composite catalyst. Therefore, the development of a versatile photo/electrocatalytic system that can efficiently promote energy conversion in environmental applications has attracted great attention., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Widespread adoption of lithium-ion batteries in electronic products, electric cars, and renewable energy systems has raised severe worries about the environmental consequences of spent lithium batteries. Because of its mobility and possible toxicity to aquatic and terrestrial ecosystems, lithium, as a vital component of battery technology, has inherent environmental problems. Leaching of lithium from discharged batteries, as well as its subsequent migration through soil and water, represents serious environmental hazards, since it accumulates in the food chain, impacting ecosystems and human health. This study thoroughly analyses the effects of lithium on plants, including its absorption, transportation, and toxicity. An attempt has been made to examine how lithium moves throughout plants through symplastic and apoplastic pathways and the factors that affect lithium accumulation in plant tissues, such as soil pH and calcium. This review focuses on the possible toxicity of lithium and its impact on ecosystems and human health. Aside from examining the environmental impacts, this review also emphasizes the significance of proper disposal and recycling measures in order to offset the negative effects of used lithium batteries. The paper also highlights the need for ongoing research to develop innovative and sustainable techniques for lithium recovery and remediation., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Key Message: The CcGRXS12 gene protects plants from cellular oxidative damage that are caused by both biotic and abiotic stresses. The protein possesses GSH-disulphide oxidoreductase property but lacks Fe-S cluster assembly mechanism. Glutaredoxins (Grxs) are small, ubiquitous and multi-functional proteins. They are present in different compartments of plant cells. A chloroplast targeted Class I GRX (CcGRXS12) gene was isolated from Capsicum chinense during the pepper mild mottle virus (PMMoV) infection. Functional characterization of the gene was performed in Nicotiana benthamiana transgenic plants transformed with native C. chinense GRX (Nb:GRX), GRX-fused with GFP (Nb:GRX-GFP) and GRX-truncated for chloroplast sequences fused with GFP (Nb:Δ2MGRX-GFP). Overexpression of CcGRXS12 inhibited the PMMoV-I accumulation at the later stage of infection, accompanied with the activation of salicylic acid (SA) pathway pathogenesis-related (PR) transcripts and suppression of JA/ET pathway transcripts. Further, the reduced accumulation of auxin-induced Glutathione-S-Transferase (pCNT103) in CcGRXS12 overexpressing lines indicated that the protein could protect the plants from the oxidative stress caused by the virus. PMMoV-I infection increased the accumulation of pyridine nucleotides (PNs) mainly due to the reduced form of PNs (NAD(P)H), and it was high in Nb:GRX-GFP lines compared to other transgenic lines. Apart from biotic stress, CcGRXS12 protects the plants from abiotic stress conditions caused by H 2 O 2 and herbicide paraquat. CcGRXS12 exhibited GSH-disulphide oxidoreductase activity in vitro; however, it was devoid of complementary Fe-S cluster assembly mechanism found in yeast. Overall, this study proves that CcGRXS12 plays a crucial role during biotic and abiotic stress in plants., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

In this study, the objective is to explore the practicability of incorporating synthetic fibre reinforced polymer (SFRP) stirrups into reinforced concrete beams. This investigation revolves around evaluating their effectiveness from two key perspectives: their structural performance and environmental impact. To accomplish this, four set of specimens were prepared, each integrating SFRP stirrups, and testing them under a rigorous three-point bending load test. The structural performance analysis entails a comprehensive examination on the critical design factors such as: the load-deflection relationship and the contribution these SFRP stirrups to improve the ductility performance, flexural stiffness, deformability factor, flexural toughness and energy absorption capacity. The findings of this study indicate that the SFRP stirrups exhibit commendable shear capacity, meeting the necessary requirements, and simultaneously demonstrate satisfactory ductility. It is determined, that the optimal design for these SFRP stirrups involves utilizing narrow and thin stirrups placed at relatively larger intervals. Furthermore, this research delves into assessing the environmental impact of incorporating SFRP stirrups. This assessment enables us to comprehensively evaluate the environmental implications of the entire life cycle of these stirrups in structural beam. Moreover, the analysis reveals that, SFRP stirrups yields lower environmental impacts compared to their steel counterparts, they still provide valuable insights into the overall sustainability considerations within the context of reinforced concrete structures., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)