Jagannath University

Gallbladder cancer (GBC) is the most common biliary tract neoplasm. Identifying biomarkers for GBC initiation and progression remains a challenge. This study aimed to identify GBC biomarkers using machine learning and bioinformatics. Differentially expressed genes (DEGs) were identified from two microarray datasets (GSE100363, GSE139682) from the GEO database. Gene Ontology and pathway analyses were performed using DAVID. A protein–protein interaction network was constructed using STRING, and hub genes were identified via three ranking algorithms (degree, MNC and closeness centrality). Feature selection methods (Pearson correlation, recursive feature elimination) were applied to extract key gene subsets. Machine learning models (SVM, NB and RF) were trained on GSE100363 and validated on GSE139682 to assess predictive performance. Biomarkers were further validated using the GEPIA database. A total of 146 DEGs were identified, including 39 upregulated and 107 downregulated genes. Eleven hub genes were identified, with SLIT3, COL7A1 and CLDN4 strongly correlated with GBC. Machine learning results confirmed their diagnostic potential. The study highlights NTRK2, COL14A1, SCN4B, ATP1A2, SLC17A7, SLIT3, COL7A1, CLDN4, CLEC3B, ADCYAP1R1 and MFAP4 as crucial genes associated with GBC. SLIT3, COL7A1 and CLDN4 serve as highly predictive biomarkers, and findings can improve early diagnosis and prognosis, aiding clinical decision‐making.

A series of novel thiazole‐Schiff base analogs ( 2a‐2i ) were synthesized through a multicomponent reaction involving thiosemicarbazide, 4‐phenoxybenzaldehyde, and α‐haloketone/phenacyl bromide derivatives. IR, ¹ H NMR, and HRMS spectroscopic techniques characterized the newly synthesized derivatives. These compounds were subsequently employed for their antimicrobial and antioxidant activities using agar disc diffusion and DPPH free radical scavenging methods. The multi‐faceted activity of compound 2c was revealed in both In Vitro experiments. It exhibited the highest potency against Bacillus subtilis (26.0 ± 1.0 mm) and Aspergillus niger (22.3 ± 0.6 mm) which exceeded the inhibitory value of standard ceftriaxone (20.7 ± 0.6 mm) and amphotericin B (8.7 ± 0.6 mm), respectively. Additionally, 2c demonstrated a remarkable sevenfold increase in antioxidant capability (IC 50 = 7.17 ± 2.61 µg/mL) compared to the standard ascorbic acid (IC 50 = 49.69 ± 19.18 µg/mL). The in silico ADMET prediction demonstrated that most synthesized compounds adhered to Lipinski's rule of five and Veber's rule, with 2i being the exception with one violation. Molecular docking studies and dynamics simulation were conducted to explore potential binding sites, interactions, and stability of the ligand‐protein complexes, providing insights aligned with the In Vitro results.

The invasion of Rohingya refugees has greatly influenced the landscape of the Cox’s Bazar district, especially in designated resettlement areas like the Kutupalong camp, one of Bangladesh’s largest refugee camps located in Ukhia Upazila (or Sub-District). To address sustainable groundwater management in this area, this research utilizes Geographic Information System (GIS) and Analytic Hierarchy Process (AHP) methods to assess groundwater possibility in Ukhia Upazila (or Sub-District), Cox’s Bazar, with a focus on the post-settlement scenario, following the future groundwater hazard potential due to the Rohingyas’ invasion. By examining 11 crucial factors that impact groundwater potential—such as elevation, geology, rainfall, slope, aspect, drainage density, proximity to rivers, soil type, land use/land cover, NDVI (Normalized Difference Vegetation Index), and lineament density—the study assigns weights to these factors using Saaty’s 9-point scale. Through AHP’s eigenvector technique, elevation is identified as the most influential factor (24%), followed by proximity to rivers (20%), rainfall (16%), and drainage density (12%), with other factors showing less impact. The study classifies groundwater potential zones into four classes: low, moderate, high, and very high—covering 35.19 km2, 156.16 km2, 68.99 km2, and 1.55 km2, respectively. Validation using the Area Under the Curve (AUC) and the Receiver Operating Characteristic (ROC) methods yields an AUC score of 0.827, indicating strong model performance in predicting groundwater potential. The results provide a valuable spatial overview of groundwater potential and backup-informed policymaking for water resource planning and administration in Ukhia Upazila, in view of the future hazard potential.

The rapid spread of infectious diseases, such as COVID-19, has highlighted the critical need for reliable and efficient face mask detection systems. This study proposes a novel parallel hybrid convolutional neural network (CNN) architecture that integrates VGG16 and MobileNetV2 to enhance feature extraction and classification accuracy. By leveraging advanced parallel architectures, the proposed model optimizes feature learning and parameter efficiency, outperforming conventional deep learning (DL) frameworks. To evaluate its effectiveness, we compare our hybrid model with established transfer learning (TL) architectures, including VGG16, MobileNetV2, and ResNet50. A comprehensive class-wise performance analysis was conducted to assess the model’s robustness in detecting both masked and unmasked faces. Experimental results demonstrate that our hybrid architecture achieves superior performance, with an accuracy of 99.49%, precision of 98.95%, recall of 100%, and an F1-score of 99.48%. These results indicate a significant improvement over traditional TL models. The high accuracy and reliability of our model suggest its practical viability for real-time face mask detection in public health monitoring and disease prevention efforts. The proposed approach offers a powerful and effective solution for enforcing mask compliance, thereby contributing to global efforts in mitigating infectious disease transmission.

The COVID-19 epidemic altered the interactions, structure, and psychology of global society. Economic recovery was not possible either, struck with lockdowns, isolation, and constant fear of COVID-19 on people’s minds. Widespread anxiety, depression, and psychoses became a new social order indeed! But evolution prevails, people society and norms around the globe had to shift and learn how to navigate this new environment. The pandemic changed people’s everyday life including how they educated themselves, in countries like India, the pandemic pushed the use of digital educational technologies with or without a valid need because of the shutdown of schools and universities. When millions of students benefited from online education, it revealed the existing inequalities in technology, usage, and connection to the online space. The most affected after the transition were not the students but the regions which are already disadvantaged making it even more difficult for the students to access education by sitting at a computer. Furthermore, the rapid shift to virtual education posed psychological challenges for both students and educators, as they navigated the new pressures of remote learning. Psychological stability is crucial for managing stress and adapting to change. In education, especially with the move to online learning, it supports concentration, motivation, and a positive learning environment. Maintaining psychological well-being enhances individual quality of life and strengthens social connections, productivity, and overall societal functioning. This paper tends to explore the socio-psychological impact of the Coronavirus, pandemic, and the transformation. In the context of change, education with a particular focus on India’s shift to online learning turns the highlights to the urgent need for addressing digital shift and providing psychological support to ensure a more inclusive and sustainable education system in the post-pandemic era.

Background Inequality in maternal healthcare service (MHS) utilization is a significant global health challenge in low- and middle-income countries (LMICs). Recently, the literature on MHS inequality in LMICs has expanded. We conducted a scoping review to synthesize existing evidence and identify knowledge gaps. Methods Following PRISMA-ScR guidelines, we systematically searched PubMed, Scopus, and CINAHL Ultimate in June 2023 for literature published since January 1, 2015. We included empirical studies using nationally representative data to measure inequality in at least one of five MHS indicators: antenatal care (ANC), skilled birth attendance (SBA), facility-based delivery (FBD), caesarean-section (C-section) delivery, and postnatal care (PNC). Our review encompassed 132 peer-reviewed articles on MHS inequality in LMICs. Results ANC, FBD, and SBA were more frequently analyzed indicators for inequality measurement compared to PNC and C-section delivery. None of the 132 studies assessed all five MHS indicators together. The concentration index was the most frequently used inequality measure across all MHS indicators. Included studies were predominantly focused on economic (wealth) and geographic (residence, region) inequalities, while sociocultural factors (e.g., religion, ethnicity) remain underexplored. Inequality was most pronounced in low-income (LICs) and lower-middle-income countries (LwMICs). The extant literature mainly concentrates on India and Ethiopia as research settings. Conclusion Our review highlights significant gaps in health inequality research, particularly in LICs and upper-middle-income countries (UMICs), with a heavy reliance on cross-sectional data, limited assessment of PNC and C-section delivery and lack of comprehensive analysis across all five common MHS indicators. Future research in LMICs should address the gaps identified in this review.

Traditionally regarded as a vestigial organ, the appendix is now being reevaluated for its significant function in health and nutrition of humans. Serving as a “safe house” for beneficial, desired gut bacteria, the appendix is protected by resilient biofilms that create a secure environment. This makes the appendix a”basin” for gut microbiota (GM), replenishing the microbial population following disruptions from infections, antibiotic use, or inflammatory bowel disease (IBD). Beyond simply hosting bacteria, the appendix has an active role in functions of the immune system. Disruption of the Appendix Microbiome (AM), such as through appendectomy, was found to result in lowered diversity of gut microorganisms and an increased risk of various diseases. The potential therapeutic applications of the AM are a particularly promising area of research. The appendix’s unique microbial environment and its impact on immunity open new avenues for treatments. These include modulating GM to improve cancer treatment outcomes, mitigating IBD, regulating metabolic pathways in obesity and diabetes, influencing neurotransmitter production in neurological disorders, and addressing cardiovascular and autoimmune diseases. This review highlights the appendix’s transformation from a misunderstood organ to a critical component of gut health and immunity. It explores the function of the human appendix as a resilient reservoir for desired microorganisms, and its role in disease progression. Furthermore, it examines the potential therapeutic applications of AM, presenting exciting opportunities for future research and treatment innovations.

Marine biomass presents a promising and sustainable pathway for advancing electrochemical energy storage (EES) technologies. This review provides a comprehensive, state-of-the-art examination of marine biomass-derived carbon as a high-performance electrode material for EES devices. The global abundance and distribution of marine biomass are discussed, followed by a detailed investigation into the chemical composition of various aquatic organisms. Key conventional synthesis methods for converting marine biomass into carbon are critically analyzed, emphasizing strategies to enhance electrochemical performance. Diverse applications of marine biomass-derived carbon in EES are explored, offering an in-depth evaluation of its electrochemical activity and mechanical properties in relation to structural variations. A dedicated section addresses the “Technology to Market” transition, presenting a strategic overview of the commercial potential of this material. Lastly, the review identifies current challenges and future opportunities, emphasizing the need for continued research into both structural innovations and scalable solutions to advance sustainable energy storage systems, addressing critical environmental and economic issues.

Alzheimer’s disease (AD) is a progressive neurodegenerative condition that causes a substantial decline in cognitive functions and affects memory, thinking abilities, and daily behavior. The most prominent hallmark of AD pathogenesis is the formation of amyloid-β plaques, among other associated pathways such as neurofibrillary tangles, mitochondrial dysfunction, neuroinflammation, and oxidative stress. Butyrylcholinesterase (BuChE), an acetylcholine-degrading enzyme, plays a critical role in the progression of Alzheimer’s disease, particularly through its involvement in amyloid-β plaque formation. Thus, the inhibition of BuChE is considered a valuable therapeutic strategy for the management of AD. The present study aimed to identify potential bioactive chemicals from naturally occurring dietary compounds that could improve neurocognitive function and appear as a viable treatment for AD by inhibiting the function of BuChE. A small library of 44 natural dietary chemicals from a variety of dietary plants was subjected to comprehensive in silico studies, including molecular docking, molecular mechanics generalized born surface area (MM-GBSA) calculations, pharmacokinetics assessments, toxicity profiles, molecular dynamics (MD) simulation, and density functional theory (DFT) analysis. These studies revealed that CID 129886986 and CID 115269 showed stronger binding affinities with drug-likeness and no toxicity than the FDA-approved standard drug, Donepezil. Additionally, they exhibited strong structural stability with fewer fluctuations throughout the simulation, making them promising candidates for Alzheimer’s disease treatment. Supplementary Information The online version contains supplementary material available at 10.1038/s41598-025-98092-y.

Forty-two species of tube-nosed bat, genus Murina, are distributed across Asia but none has hitherto been reported from Bangladesh. Here we document the first record of Murina from Bangladesh, based on an adult male specimen captured in Rema-Kalenga Wildlife Sanctuary, in July 2023, using a four-bank harp trap set in a forest trail. On the basis of external and cranial morphometrics, it is referred to the round-eared tube-nosed bat Murina cyclotis Dobson (Proc Asiat Soc Bengal 1872:208–210, 1872). The discovery of this forest-dependent insectivorous bat in Bangladesh not only increases the number of bat species known from the country to 36 but also contributes to the broader knowledge of bat distributions across South Asia.

Understanding and accurately predicting greenhouse gas concentrations, particularly CO2 and CH4, are critical for assessing climate change impacts and informing policy decisions. This study addresses the challenge of evaluating the performance of CMIP6 climate models in simulating these key greenhouse gases across Africa. By comparing model outputs with reanalysis data, we assess the accuracy and reliability of these models in capturing CO2 and CH4 concentrations, which are essential for understanding regional climate dynamics and informing adaptation strategies. Our evaluation utilized various statistical methods, including linear regression, Pearson's correlation (mean: 0.82 ± 0.05 for CO2, 0.67 ± 0.08 for CH4), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Relative Mean Bias (RMB), to determine model performance and variability. Results indicate that most CMIP6 models exhibit a strong correlation with reanalysis data for CO2 (mean RMSE: ± 5.3 ppm; MAE: ± 4.8 ppm), although models such as CESM2 and CESM2-FV2 show significant overestimation (RMB: + 15%). In contrast, CH4 simulations display substantial underestimation, particularly in northern Africa, with error margins ranging from ± 13.7 to ± 22.4 ppb, revealing difficulties in accurately representing CH4 emissions and sinks. These findings underscore the models’ strengths in CO2 simulations but highlight notable limitations in CH4 modelling. Future research should focus on improving model parameterizations and addressing regional biases to enhance the accuracy of climate projections and deepen our understanding of greenhouse gas impacts.

The rapidly growing mangrove fruit Sonneratia apetala, native to the deltaic region of Bangladesh, holds promise in traditional medicine due to its bioactivity and antimicrobial properties. Sample collections from Nijum Dwip, Hatiya, Noakhali in Bangladesh were divided into pericarps and seeds, subsequently fractionated with methanol, n-hexane, ethyl acetate, and chloroform. Bioactivity assays involved Swiss albino mice, acquired from ICDDR, B, in compliance with FELASA standards. Standard agents such as diclofenac sodium, loperamide, diazepam, and glibenclamide were used to evaluate antidiarrheal, antidepressant, hypoglycaemic, and analgesic effects, while ciprofloxacin served as a reference for antibacterial and antifungal testing. Methanolic extracts (ME) of the seed and pericarp exhibited notable peripheral and central analgesic effects at 200 and 400 mg/kg dosages. The ME of seeds demonstrated the strongest antidiarrheal efficacy at 400 mg/kg after 1 hour, and the pericarp at 200 mg/kg after 2 hours. The ME also showed significant antidiabetic potential in both seed (99%) and pericarp extracts. GC-MS analysis disclose seven bioactive compounds in the n-hexane, ethyl acetate, and chloroform fractions, including N-Ethyl-2-methylbenzenesulfonamide, 3,6-Pyridazinedione, 1,2-dihydro-1-(4-nitrophenyl), N-Acetyl-alpha-aminooxybutyric acid (methyl), 2H-Phenanthro[2,1-b] azepin-2-one (1,3,4,5,5a), and Undecane. These compounds have established anticancer and antimicrobial properties. Both pericarp and seed extracts displayed strong antifungal activity against Saccharomyces cerevisiae, Candida albicans, and Aspergillus niger, while moderate antibacterial effects were noted against gram-negative strains like Pseudomonas aeruginosa and Salmonella Typhi as well as gram-positive bacteria such as Staphylococcus aureus. These findings underscore S. apetala’s potential as a valuable bioactive source for traditional medicinal applications.

Why do resistance movements align with declining powers? This paper examines how Indian Muslims engaged with the waning Ottoman Empire to contest British colonial rule, despite the absence of material support. Drawing on theories of hierarchy, international order, and resistance, we introduce the concept of “resistance-oriented order” to highlight how subordinate actors construct alternative hierarchies through ideological and normative affiliations. Rather than seeking tangible aid, Indian Muslims leveraged the Ottoman Khilafat to delegitimize colonial authority and foster a new political identity. We argue that decline does not preclude order construction but can serve as a catalyst for mobilization and resistance. By advancing a bottom-up perspective on hierarchy and international order, this study contributes to broader debates on legitimacy, non-state agency, and ideological power in global politics.

Background Long-acting reversible and permanent contraceptive methods (LARC/PM) with high efficacy and continuity of use are highly effective pregnancy prevention methods. However, most sexually active women do not use it and end up with unintended pregnancies and unsafe abortions in Bangladesh. This study aims to assess the prevalence of LARC/PM use and its determinants among sexually active women who desire no more children in Bangladesh. Methods The study used Bangladesh Demographic and Health Survey (BDHS) 2017-18 data, which employed a two-stage cluster sampling design. This study extracted 6422 married women of reproductive age who desired no more children. Descriptive statistics were used to present the characteristics of the women. Chi-square and binary logistic regression were also used to identify the factors associated with LARC/PM use. Results A total of 20.2% of women use LARC/PM who desire no more children. Women aged 25–34 (aOR = 1.52, 95% CI: 1.10–2.09) and 35 years and above (aOR = 1.99, 95% CI: 1.41–2.81), women from Rangpur (aOR = 2.27, 95% CI = 1.57–3.28), Rajshahi (aOR = 2.15, 95% CI = 1.49–3.11), Khulna (aOR = 2.17, 95% CI = 1.48–3.17), Sylhet (aOR = 1.66, 95% CI = 1.07–2.58) and Dhaka (aOR = 1.97, 95% CI = 1.37–2.83) divisions, who were non-Muslims (aOR = 1.72, 95% CI = 1.40–2.11), having a desired number of children (2+) (aOR = 1.27, 95% CI = 1.08–1.49), whose contraceptive decision solely made by husband (aOR = 3.61, 95% CI = 2.73–1.77) or jointly (aOR = 1.59, 95% CI = 1.32–1.92) were more likely to use LARC/PM. On the other hand, women with primary education (aOR = 0.78, 95% CI = 0.65–0.92), secondary education (aOR = 0.59, 95% CI = 0.47–0.72) and higher education (aOR = 0.64, 95% CI = 0.43–0.95) belonging to richest wealth index (aOR = 0.73, 95% CI = 0.55–0.97), having at least two living children (aOR = 0.62, 95% CI = 0.44–0.85), partner with secondary education (aOR = 0.79 95% CI = 0.65–0.97) and women who were visited by family planning (FP) visitors (aOR = 0.34, 95% CI = 0.29–0.40) were less likely to use LARC/PM. Conclusion The LARC/PM use rate among women in Bangladesh is low. It must be increased to meet the targets of the Sustainable Development Goals (SDGs). To increase LARC/PM use in Bangladesh, attention should be given to factors like women’s age, education, partner’s education, religion, wealth index, division, number of living children, and desired number of children.

Cinnamomum tamala belongs to the Lauraceae family, which has diverse traditional and pharmacological roles for treating toothache, diarrhea, gastrointestinal disorders, vomiting, fever, diabetes, hyperlipidemia, and others. This research aims to evaluate its protective effects against paracetamol‐induced hepatotoxicity in mice. For this, ethanolic leaf extract of C. tamala (ECT) at different doses was administered via oral gavage with or without the standard hepatoprotective drug silymarin, and liver biochemical and histopathological profiles were checked. Gas chromatography‐mass spectrometry (GC‐MS) analysis and molecular docking studies were performed to check the possible molecular mechanisms behind its hepatoprotective effect. Results suggest that ECT significantly enhances antioxidant capability with lower animal N ‐acetyl‐p‐benzoquinone imine metabolites. The histopathological slides showed minimum inflammation, inflammatory cell infiltrations, and vascular edematous congestion for the ECT individual and co‐administration groups. Computational drug discovery approaches validated these results, and the identified compounds from the GC‐MS study were subjected to molecular docking, with the top docking score found against the CYP2E1 protein. In molecular dynamics simulation, 1,3‐dioxolane, 2‐pentadecyl, and butyl 14‐methylhexadecanoate showed more root mean square deviation and root‐mean‐square fluctuation values than silymarin. In conclusion, ECT and its key compounds, butyl 14‐methylhexadecanoate (CID 91693030) and 1,3‐dioxolane, 2‐pentadecyl (CID 552019), may potentially act against paracetamol‐induced hepatotoxicity in animals.

Nuclear and Atomic Physics Lab, Jagannath University, Dhaka-1100

Purpose- This study aims to investigate and assess methods for the sustained revival of Asia’s tourism industry in the aftermath of the pandemic. It evaluates the repercussions of COVID-19 on the tourism industry and pinpoints essential strategies for rejuvenating the industry, with an emphasis on long-lasting sustainability. Methodology- The researchers examined a large number of studies utilizing three major databases: Scopus (Science Direct), Web of Science, and Google Scholar. The search keywords include “COVID-19”, “digitalization”, “digital transformation”, “pandemic effect”, “responsible tourism”, “tourism sustainability”, “tourism sector”, and “post-pandemic strategies”, yielding a total of 128 articles as an initial selection from 2018 to June 2024. Finally, after screening and filtering, 36 articles relevant to the study’s focus were selected for in-depth analysis. The articles were retrieved from the databases and then screened and filtered according to inclusion and exclusion criteria. The key inclusion criteria included relevance to the scope of the study, publication year, and full-text article availability. Findings- The study proposes a comprehensive strategic plan for Asia’s tourism industry after the pandemic, balancing economic development with local welfare and environmental sustainability, and promoting innovation and strategic partnerships. Limitations- The use of terms like “COVID-19,” “pandemic,” “digital transformation,” “responsible tourism,” “tourism sector,” and “sustainability” may have overlooked other relevant articles. Implications- The study implied that the rights of unfair treatment and integration of persons in rehabilitation programs are the focus of the research. It endorses struggling groups and aims at narrowing down the gap between people in society. The study also offers a way of restoring the Asiatic touring business after the epidemic dented it severely. Originality/Value- The study compiles existing literature on how to sustainably support the recovery of Asia’s tourist industry from the epidemic. It seeks to establish the problems and prospects that emerge. As a result of the collection of information from various sources, it seeks to present an overview of the Asian market’s tourist recovery measures. Drawing from various academic publications, it provides a holistic perspective and highlights effective strategies for policymakers and stakeholders to revitalize the tourism industry sustainably. Keywords: COVID-19, Digital Transformation, Pandemic, Responsible Tourism, Sustainability, Tourism Sector

Purpose: This research aimed to ascertain how artificial intelligence (AI) is revolutionizing electronic markets, the associated benefits, and ethical issues. Design/Methodology/Approach: The methodology used in this study was a systematic review design, including the review of numerous scholarly articles on AI in e-commerce. In five academic bibliometric databases such as Scopus, Research Gate, Sage, Harvard Business Review, and Google Scholar, the articles that would serve the purposes of this study were sought. Keywords such as e-commerce, AI, sustainability, and ethics were used to search the related databases. Findings: The results demonstrated that AI in e-commerce has so many benefits, such as automation, customization, and efficiency. Artificial intelligence algorithms, through intelligent assistance and recommendation engines, also recommend how to optimize resources. Moreover, AI encourages logistics improvement relative to customer satisfaction. In addition, it is equally important for AI to help achieve sustainability by increasing the efficiency of resource consumption and promoting the circular economy. However, concerns about the misuse of AI due to biased algorithms, violations of data privacy, or loss of jobs call for the responsible use of AI tools and constraints on their manipulation during the development processes. Limitations: The study focused on modern literature primarily and missed key findings in some previous research works. In addition, the choice of databases and search keywords restricted the scope of assessment. Implications: Further research opportunities include a comprehensive literature assessment, user experience, real-world experiences, and case studies on the application of these knowledge areas, as well as a closer inspection of ethical frameworks across each domain mentioned in this paper, along with further technical coverage on the creation and use of artificial intelligence. Originality/Value: Specifically, this research will provide a broader understanding of how AI affects businesses and consumers in e-commerce. The research identifies both the positive and negative aspects of AI, thus helping in the responsible creation and deployment of AI technologies, furthering a thriving e-commerce market from an ethical perspective. Keywords: Artificial intelligence · Chatbots · E-Commerce · Sustainability · Sustainable development · Technology

The recirculating aquaculture system is a modern method for managing indoor fish culture and ensuring maximum output. The focus of this research was to see how water physical and chemical characteristics influenced the productivity of tilapia in fish tanks (size: dia-3.35 m and depth-1.5 m) of constant water capacity (10,000 l) using three stocking densities such as 1200 fish/tank (89 fish per m³), 1000 fish/tank (74 fish per m³), and 800 fish/tank (59 fish per m³) in Treatments I, II, and III, respectively. Ninety fish samples were randomly obtained every 2 weeks over 4 months; they were weighed, measured, and returned to the tank. The average range of different physical–chemical parameters was within the limit, with some variations observed in certain readings. It was noted how much weight the fish gained on average and their specific growth rates (SGR) for Treatments I, II, and III at the end of the experiment. The treatments indicated statistically substantial differences $(P<0.05)$ considering the specific growth rate, final mean weight, and weight gain. Treatment III which was the controlled group had a significantly higher SGR than the other treatments. Correlation between length, weight, specific growth rate (based on weight), and physical–chemical parameters was observed and tabulated. The regression between fish growth and physical–chemical parameters was also calculated. The results of this study consistently indicate that stocking density is a more important factor in determining the overall yield than water quality indicators in RAS.

This review presents a comprehensive and precise summary of the hydrothermal synthesis and morphology control of zinc oxide (ZnO) nanomaterials, the advantages of hydrothermal synthesis, and the wide range of applications. ZnO nanomaterials have garnered significant attention in recent years for their diverse applications across various industries owing to their unique properties and versatility, with practical applications in healthcare, cosmetics, textiles, automotive, and other sectors. Specifically, the ability of ZnO-based nanomaterials to promote the production of reactive oxygen species, release of Zn²⁺ ions, and induce cell apoptosis makes them well-suited for bio-medicinal applications such as cancer treatment and microorganism control. Hydrothermal technique offers precise control over the synthesis of ZnO, metal/non-metal-doped ZnO, and related composites, enabling the tailoring of properties for specific applications. The significant feature of the hydrothermal technique is the use of water as a solvent, which is cheap, available, and environmentally benign. In the last section, we discussed the potential future direction of ZnO-based research.