Search Results (352)

Privacy preservation poses significant challenges in third-party data sharing, particularly when handling table data containing personal information such as demographic and behavioral records. Synthetic table data generation has emerged as a promising solution to enable data analysis while mitigating privacy risks. While Generative Adversarial Networks (GANs) are widely used for this purpose, they exhibit limitations in modeling table data due to challenges in handling mixed data types (numerical/categorical), non-Gaussian distributions, and imbalanced variables. To address these limitations, this study proposes a novel adversarial learning framework integrating gradient boosting trees for synthesizing table data, called Adversarial Gradient Boosting Decision Tree (AGBDT). Experimental evaluations on several datasets demonstrate that our method outperforms representative baseline models regarding statistical similarity and machine learning utility. Furthermore, we introduce a privacy-aware adaptation of the framework by incorporating k-anonymization constraints, effectively reducing overfitting to source data while maintaining practical usability. The results validate the balance between data utility and privacy preservation achieved by our approach. Full article

The present study was conducted in Dacope Upazila, a sub-district located within the Khulna District of the coastal region in Bangladesh. The research methods employed included the implementation of 350 household questionnaire surveys (HQSs), 12 focus group discussions (FGDs), and 20 key informant interviews (KIIs) to assess economic security status in disaster-vulnerable areas. The findings indicate that the economic well-being of the region is precarious due to a paucity of revenue sources and the occurrence of various calamitous events, induced risks, and vulnerabilities. To achieve long-term economic security for households, a considerable proportion of the population (approximately 22%) in the study areas is dependent on agricultural activities for their livelihoods. The study also revealed that approximately 22% of households in the study areas reported experiencing salinity intrusion. Furthermore, most of the households, around 68%, reported cyclones as their primary obstacle to building disaster-resilient communities. Consequently, the prevailing local and institutional strategies to ensure economic security were found to be inadequate and unsustainable in the study upazila. Therefore, the study resulted in the formulation of a conceptual framework intended to measure the contribution of economic security to the adaptability and sustainability of disaster-resilient communities in vulnerable coastal areas of Bangladesh. Full article

Calcium (Ca²⁺) is a macronutrient essential for the growth, development, yield, and quality of vegetables and fruits. It performs structural, enzymatic, and signaling functions in plants. This review examines Ca²⁺ translocation from soil to the fruit via the plant xylem network, emphasizing the importance of Ca²⁺ compartmentalization within fruit cell organelles in the development of calcium deficiency disorders such as blossom-end rot (BER). The underlying causes of BER and potential control measures are also discussed. Soil-available Ca²⁺, transported by water flow, enters the root apoplast through membrane channels and moves toward the xylem via apoplastic or symplastic routes. The transpiration force and the growth of organs determine the movement of Ca²⁺-containing xylem sap to aerial plant parts, including fruits. At the fruit level, the final step of Ca²⁺ regulation is intracellular partitioning among organelles and cellular compartments. This distribution ultimately determines the fruit’s susceptibility to Ca²⁺-deficiency disorders such as BER. Excessive sequestration of Ca²⁺ into organelles such as vacuoles may deplete cytosolic and apoplastic Ca²⁺ pools, compromising membrane integrity and leading to BER, even when overall Ca²⁺ levels are adequate at the blossom end. Effective BER management requires cultural and physiological practices that promote Ca²⁺ uptake, translocation to the fruit, and appropriate intracellular distribution. Additionally, the use of BER-resistant and Ca²⁺-efficient cultivars can help mitigate this disorder. Therefore, a comprehensive understanding of Ca²⁺ dynamics in plants is critical for managing BER, minimizing production loss and environmental impacts, and maximizing overall crop productivity. Full article

The implementation of chaotic behavior and a sensitivity assessment of the newly developed M-fractional Kuralay-II equation are the foremost objectives of the present study. This equation has significant possibilities in control systems, electrical circuits, seismic wave propagation, economic dynamics, groundwater flow, image and signal denoising, complex biological systems, optical fibers, plasma physics, population dynamics, and modern technology. These applications demonstrate the versatility and advantageousness of the stated model for complex systems in various scientific and engineering disciplines. One more essential objective of the present research is to find closed-form wave solutions of the assumed equation based on the $({\displaystyle \frac{G^{\prime }}{G^{\prime }+G+A}})$-expansion approach. The results achieved are in exponential, rational, and trigonometric function forms. Our findings are more novel and also have an exclusive feature in comparison with the existing results. These discoveries substantially expand our understanding of nonlinear wave dynamics in various physical contexts in industry. By simply selecting suitable values of the parameters, three-dimensional (3D), contour, and two-dimensional (2D) illustrations are produced displaying the diagrammatic propagation of the constructed wave solutions that yield the singular periodic, anti-kink, kink, and singular kink-shape solitons. Future improvements to the model may also benefit from what has been obtained as well. The various assortments of solutions are provided by the described procedure. Finally, the framework proposed in this investigation addresses additional fractional nonlinear partial differential equations in mathematical physics and engineering with excellent reliability, quality of effectiveness, and ease of application. Full article

In this study, we investigate the fractional Tzitzéica equation, a nonlinear evolution equation known for modeling complex phenomena in various scientific domains such as solid-state physics, crystal dislocation, electromagnetic waves, chemical kinetics, quantum field theory, and nonlinear optics. Using the (G′/G, 1/G)-expansion approach, we derive different categories of exact solutions, like hyperbolic, trigonometric, and rational functions. The beta fractional derivative is used here to generalize the classical idea of the derivative, which preserves important principles. The derived solutions with broader nonlinear wave structures are periodic waves, breathers, peakons, W-shaped solitons, and singular solitons, which enhance our understanding of nonlinear wave dynamics. In relation to these results, the findings are described by showing the solitons’ physical behaviors, their stabilities, and dispersions under fractional parameters in the form of contour plots and 2D and 3D graphs. Comparisons with earlier studies underscore the originality and consistency of the (G′/G, 1/G)-expansion approach in addressing fractional-order evolution equations. It contributes new solutions to analytical problems of fractional nonlinear integrable systems and helps understand the systems’ dynamic behavior in a wider scope of applications. Full article

Background/Objectives: Differentiated Thyroid Cancer (DTC), comprising papillary and follicular carcinomas, is the most common type of thyroid cancer. This is highly infectious and increasing at a higher rate. Some patients experience recurrence even after undergoing successful treatment. Early signs of recurrence can be hard to identify, and the existing health care system cannot always identify it on time. Therefore, predicting its recurrence accurately and in its early stage is a significant clinical challenge. Numerous advanced technologies, such as machine learning, are being used to overcome this clinical challenge. Thus, this study presents a novel approach for predicting the recurrence of DTC. The key objective is to improve the prediction accuracy through hyperparameter optimization. Methods: In order to achieve this, we have used a metaheuristic algorithm, the whale optimization algorithm (WOA) and its modified version. The modifications that we introduced in the original WOA algorithm are a piecewise linear chaotic map for population initialization and inertia weight. Both of our algorithms optimize the hyperparameters of the Extreme Gradient Boosting (XGBoost) model to increase the overall performance. The proposed algorithms were applied to the dataset collected from the University of California, Irvine (UCI), Machine Learning Repository to predict the chances of recurrence for DTC. This dataset consists of 383 samples with a total of 16 features. Each feature captures the critical medical and demographic information. Results: The model has shown an accuracy of 99% when optimized with WOA and 97% accuracy when optimized with the modified WOA. Conclusions: Furthermore, we have compared our work with other innovative works and validated the performance of our model for the prediction of DTC recurrence. Full article

The world’s largest mangrove, Sundarbans, Bangladesh, is the habitat of the euryhaline catfish Nona Tengra (Mystus gulio). This study aimed to assess the stock status of M. gulio and provide reference points for sustainable fisheries’ management. One-year length–frequency (LF) data were collected from the Sundarbans region of Bangladesh and analyzed using the Length-Based Bayesian Biomass (LBB) method and the Length-Based Spawning Potential Ratio (LBSPR) model. The findings showed healthy biomass (B/B_MSY = 1.2), with 57% of the wild stock of this species being harvested (B/B₀ = 0.43). The calculated fishing mortality ratio indicated the underfishing conditions (F/M = 0.9). Safe exploitation (E = 0.46) was depicted, as E was smaller than the permitted level of 0.5. The value of capture length (L_c = 12.8 cm) was larger than the optimum capture length (L_{c_opt} = 10.0 cm) and the optimum length for maximum yield per recruit (L_opt = 12.0 cm) and larger than the maturity length (L_m = 9.16 cm), indicating the capture of mature individuals. The calculated Spawning Potential Ratio (SPR = 48%) was higher than the target reference points (SPR = 40%). This research evaluated the sustainable stock status. Although the margin between L_{c_opt} and L_m is very narrow, setting the minimum capture size at L_opt would be a conservative buffer to ensure long-term sustainability. The recommended minimum harvest size is 12 cm for M. gulio. Current fishing gear selectivity can ensure the sustainability of M. gulio in Sundarbans, Bangladesh; however, maintaining current fishing practice through careful management is suggested. Further assessments with length-based and other low-data methods should be conducted to refine exploitation estimates and trends. Full article

Arsenic contamination in water poses a significant global health risk, necessitating efficient and sustainable remediation strategies. Arsenic contamination affects groundwater in at least 106 countries, potentially exposing over 200 million people to elevated levels, primarily through contaminated drinking water. Among the most affected regions, Bangladesh remains a critical case study, where widespread reliance on shallow tubewells has resulted in one of the largest mass poisonings in history. Bio-based nanomaterials have emerged as promising solutions due to their eco-friendly nature, cost-effectiveness, and high adsorption capabilities. These nanomaterials offer a sustainable approach to arsenic remediation, utilizing materials like biochar, modified biopolymers, and bio-based aerogels, which can effectively adsorb arsenic and other pollutants. The use of environmentally friendly nanostructures provides a potential option for improving the efficiency and sustainability of arsenic remediation from groundwater. This review explores the mechanisms underlying arsenic remediation using such nanomaterials, including adsorption, filtration/membrane technology, photocatalysis, redox reactions, complexation, ion exchange, and coagulation–flocculation. Despite their potential, challenges such as scalability, stability, and regeneration hinder widespread application. We discuss recent advancements in material design, surface modifications, and hybrid systems that enhance performance. Finally, future perspectives are highlighted, including the integration of these bio-derived systems with smart sensing technologies, sustainable water-treatment frameworks, smart design, and life-cycle integration strategies, particularly for use in resource-constrained regions like Bangladesh and other globally impacted areas. Full article

Encephalitis, a severe neurological condition caused by human-to-human (H2H) transmitted viruses, such as herpes simplex virus (HSV), requires a rigorous mathematical framework to understand its transmission dynamics. This study develops a nonlinear compartmental model, SEITR (Susceptible–Exposed–Infected–Treated–Recovered), to characterize the progression of viral encephalitis. The basic reproduction number (R₀) is derived using the next-generation matrix method, serving as a threshold parameter determining disease persistence. The local and global stability of the disease-free and endemic equilibria are established through a rigorous mathematical analysis. Additionally, a sensitivity analysis quantifies the impact of key parameters on R₀, offering more profound insights into their mathematical significance. Numerical simulations validate the theoretical results, demonstrating the system’s dynamical behavior under varying epidemiological conditions. This study provides a mathematically rigorous approach to modeling viral encephalitis transmission, filling a gap in the literature and offering a foundation for future research in infectious disease dynamics. Full article

Noninvasive blood glucose monitoring is crucial for diabetes management, and photoacoustic spectroscopy (PAS) offers a promising solution by detecting glucose levels through human skin. However, weak acoustic signals in PAS systems require optimized resonator designs for enhanced detection sensitivity. Designing such resonators physically is complex, requiring the precise identification of critical parameters before practical implementation. This study focused on optimizing a T-shaped photoacoustic resonator using finite element modeling in a COMSOL Multiphysics environment. By systematically varying the geometric design parameters of the T-cell resonator, a maximum increase in the pressure amplitude of 12.76 times with a quality factor (Q-factor) of 47.5 was achieved compared to the previously designed reference acoustic resonator. This study took a significant step forward by identifying key geometric parameters that influence resonator performance, paving the way for more sensitive and reliable noninvasive glucose monitoring systems. Full article

Introduction: Decursin is a pyranocoumarin natural phytochemical found in the Angelica gigas Nakai herb, which shows various therapeutic properties and beneficial effects against various diseases. Objective: The aim of this study was to find the anticancer potential of decursin and its molecular mechanisms involved with different anticancer effects. Methodology: All of the relevant data concerning this compound and cancer were collected using different scientific search engines, including PubMed, Scopus, Springer Link, Wiley Online, Web of Science, Scifinder, ScienceDirect, and Google Scholar. Results: This study found that decursin shows anticancer properties through various mechanisms, such as apoptosis, cell cycle arrest, inhibition of cell proliferation, autophagy, inhibition of angiogenesis, cytotoxicity, and the inhibition of invasion and migration against a number of cancers, including breast, bladder, lung, colon, skin, ovarian, prostate, pancreatic, and bone cancers. This study also discovered that decursin has the ability to affect several signaling pathways in the molecular anticancer mechanisms, such as the PI3K/AKT/mTOR, JAK/STAT, and MAPK signaling pathways. Findings also revealed that decursin expresses poor oral bioavailability. Conclusions: Based on the data analysis from this literature-based study, decursin has properties to be considered as a potential candidate in the treatment of cancer. However, more clinical research is suggested to establish proper efficacy, safety, and human dosage. Full article

Rice is a staple food for nearly half the world population. Rice cultivation relies heavily on urea fertilization. However, the use of urea is prone to significant losses and contributes to environmental pollution. This study was aimed at fabricating nitrogen-rich chitin nanomaterials and assessing their effects on the growth and yield of rice. Chitin nanofibers (ChNF), with widths ranging from 10 to 30 nm, were successfully isolated from shrimp shells by chemical pretreatment and mechanical fibrillation. Pot-grown rice plants were treated with various concentrations of ChNF and urea in a completely randomized design with five replicates. ChNF treatment resulted in plant height (97.33 ± 1.53 cm), tiller number (17.67 ± 1.15 hill⁻¹), straw yield (30.40 ± 1.93 g hill⁻¹), and harvest indexes comparable to those achieved with urea treatment at harvest (97.33 ± 1.53 cm, 17.00 ± 1.73 hill⁻¹, 26.47 ± 2.39 g hill⁻¹ and 44.12%, respectively). The grain yield using urea (22.70 g hill⁻¹) was almost identical to that achieved with 0.01% ChNF (22.22 g hill⁻¹), which may be attributable to the increased nitrate-nitrogen (N) and ammonium-N availability, reduced nitrogen loss, and enhanced microbial activity associated with 0.01% ChNF. The study findings indicate that shrimp-derived ChNF is a promising functional nanomaterial for rice cultivation, with potential as a partial or full replacement for urea in sustainable rice production. Full article

Polymer nanocomposites (PNCs) are a versatile class of materials known for their enhanced mechanical, thermal, electrical, and barrier properties, with the latter referring to resistance against the permeation of gases and liquids. Achieving optimal nanoparticle dispersion within the polymer matrix is essential to fully realizing these advantages. This study investigates strategies for improving nanoparticle dispersion and examines the impact of controlled dispersion on the resulting nanocomposite properties. Various methods, including in situ polymerization, twin screw extrusion, sol–gel processes, nanoparticle surface modification, solution casting, and advanced compounding techniques such as additive manufacturing and self-healing composites were explored to enhance dispersion and improve the compatibility between nanoparticles and polymers. The synergy between improved dispersion and enhanced functionalities—such as increased mechanical strength, thermal stability, conductivity, and chemical resistance—makes these nanocomposites highly valuable for industrial applications in sectors such as the automotive, aerospace, electronics, pharmaceuticals, and packaging industries. The key recommendations based on our findings highlight how customized nanocomposites can address specific industrial challenges, fostering innovation in materials science and engineering. Full article

Bangladesh, one of the most vulnerable countries to climate change, has been experiencing significant climate change-induced risks. Particularly, the northwest region of the country has been severely affected by climate extremes, including droughts and heat waves. Therefore, proper understanding and assessment of future climate change scenarios is crucial for the adaptive management of water resources. The current study used the statistical downscaling model (SDSM) to downscale and analyze climate change-induced future changes in temperature and precipitation based on multiple global climate models (GCMs), including HadCM3, CanESM2, and CanESM5. A quantitative approach was adopted for both calibration and validation, showing that the SDSM is well-suited for downscaling mean temperature and precipitation. Furthermore, bias correction was applied to enhance the accuracy of the downscaled climate variables. The downscaled projections revealed an upward trend in mean annual temperatures, while precipitation exhibited a declining trend up to the end of the century for all scenarios. The observed data periods for the CanESM5, CanESM2, and HadCM3 GCMs used in SDSM were 1985–2014, 1975–2005, and 1975–2001, respectively. Based on the aforementioned periods, the projections for the next century indicate that under the CanESM5 (SSP5-8.5 scenario), temperature is projected to increase by 0.98 °C, with a 12.4% decrease in precipitation. For CanESM2 (RCP8.5 scenario), temperature is expected to rise by 0.94 °C, and precipitation is projected to decrease by 10.3%. Similarly, under HadCM3 (A2 scenario), temperature is projected to increase by 0.67 °C, with a 7.0% decrease in precipitation. These downscaled pathways provide a strong basis for assessing the potential impacts of future climate change across the northwestern region of Bangladesh. Full article

Jute fiber-reinforced composites have become a promising alternative to synthetic fiber composites because of their favorable environmental characteristics, cost efficiency, and good mechanical properties. The present review provides a comprehensive examination of the manufacturing processes and mechanical properties of polymer composites reinforced with jute fibers. This study investigates the influence of several fabrication methods, such as hand lay-up, compression molding, injection molding, pultrusion, etc., on the mechanical properties of the composites. It also provides SWOT analyses of various manufacturing processes of jute fiber-reinforced composites. Important aspects, including fiber orientation, fiber/matrix adhesion, and the effects of different surface treatments on improving mechanical characteristics, such as tensile strength, flexural strength, and impact resistance, are discussed. The difficulties associated with moisture absorption, degradation, and the lack of uniformity in jute fibers, as well as approaches to alleviate these problems, are presented. The goal of this study is to establish a basis for future investigation and advancement in enhancing the mechanical properties of jute fiber-reinforced composites. Full article