Short-term (with a lead time of about one week) earthquake (EQ) prediction is one of the most challenging subjects in geoscience and applied science; however, it is highly required by society because it is of essential importance in mitigating the human and economic losses associated with EQs. Electromagnetic precursors have recently been agreed to be the most powerful candidate for short-term prediction, because a lot of evidence has been accumulated on the presence of electromagnetic precursors (not only from the lithosphere, but also from the atmosphere and ionosphere) prior to EQs during the last three decades. On the other hand, unusual animal behavior associated with EQs, which is the main topic of this review, has been investigated as a macroscopic phenomenon for many years, with a much longer history than the study of seismo-electromagnetics. So, in this paper, we first summarize the previous research work on this general unusual animal behavior with reference to its relationship with EQs, and then we pay the greatest attention to our own previous work on dairy cows’ milk yield changes. We recommend this unusual animal behavior as an additional potential tool for short-term EQ prediction, which may be a supplement to the above seismo-electromagnetic effects. Finally, we will present our latest case study (as an example) on unusual changes of cows’ milk yields for a particular recent Tokyo EQ on 7 October 2021, and further propose that electromagnetic effects might be a possible sensory mechanism of unusual animal behavior, suggesting a close link between electromagnetic effects and unusual animal behavior. Full article

Every economic sector is susceptible to the direct or indirect effects of weather variability, and the tourism sector is no exception. In fact, the tourism industry is considered to be more vulnerable to the effects of weather variability than the general economy, with changes in weather patterns, extreme events, and environmental degradation offering substantial obstacles. Ethiopia’s tourism industry, like many others, faces challenges from weather variability. This study investigates the short- and long-term effects of weather variability on Ethiopia’s international tourism receipts. Utilizing data from 1995 to 2019, the research employs a vector error correction model to analyze the relationships between weather variables (temperature, rainfall), economic factors (GDP growth, inflation), political stability, and tourist arrivals. The findings reveal that in the long run, higher temperatures, rainfall, and inflation have negative impacts on tourism receipts, while political stability and past tourist arrivals have positive effects. Short-term trends mirror these, with the addition of GDP growth not showing a significant impact. To ensure the sustainability of tourism in Ethiopia, the study emphasizes the importance of understanding weather’s influence, developing adaptation strategies, and promoting sustainable tourism practices. Full article

With the widespread adoption of smart farms and continuous advancements in IoT (Internet of Things) technology, acquiring diverse additional data has become increasingly convenient. Consequently, studies relevant to deep learning models that leverage multimodal data for crop disease diagnosis and associated data augmentation methods are significantly growing. We propose a comprehensive deep learning model that predicts crop type, detects disease presence, and assesses disease severity at the same time. We utilize multimodal data comprising crop images and environmental variables such as temperature, humidity, and dew points. We confirmed that the results of diagnosing crop diseases using multimodal data improved 2.58%p performance compared to using crop images only. We also propose a multimodal-based mixup augmentation method capable of utilizing both image and environmental data. In this study, multimodal data refer to data from multiple sources, and multimodal mixup is a data augmentation technique that combines multimodal data for training. This expands the conventional mixup technique that was originally applied solely to image data. Our multimodal mixup augmentation method showcases a performance improvement of 1.33%p compared to the original mixup method. Full article

This study delves into the geomechanical responses of different sedimentary hydrodynamic cycles in deep tight sandstone formations. Employing core observation and thin section analysis, we quantitatively identified and characterized bedding planes, sedimentary microfacies, and tectonic fractures. Then, the intricate relationships between various architectural interfaces and geomechanical parameters were elucidated. Subsequently, utilizing finite element numerical simulation software, in situ stress and fracture parameters were derived. By identifying a fracture facies zone correlated with the sedimentary hydrodynamic cycle and production data, our findings unveil several key insights: (1) Geomechanical parameters (Young’s modulus, Poisson’s ratio, brittleness index) exhibited noteworthy variations within the T₃x²⁻⁵ sand group, indicative of weak elasticity and robust plasticity. (2) The effective distance, influenced by diverse reservoir architecture interfaces, displayed variability, with each transition between peak-valley-peak or valley-peak-valley pinpointed as a distinct sedimentary hydrodynamic cycle. (3) In environments characterized by strong sedimentary hydrodynamics (between two level 3 architecture interfaces), fractures with larger strike angles and lower dip angles were observed to be more prevalent. (4) Three significant fracture faces—level I, level II, and level III—were discerned within the study area. Notably, reservoirs associated with level III exhibited characteristics suggestive of medium porosity and permeability, indicative of a gas layer. By thoroughly understanding the geomechanical response characteristics of formations such as the Xujiahe Formation, it is possible to guide the exploration and development of energy resources such as oil and natural gas. This helps to improve the efficiency and safety of resource extraction, promoting the sustainable utilization of energy. Full article

Cancer vasculogenesis is a pivotal focus of cancer research and treatment given its critical role in tumor development, metastasis, and the formation of vasculogenic microenvironments. Traditional approaches to investigating cancer vasculogenesis face significant challenges in accurately modeling intricate microenvironments. Recent advancements in three-dimensional (3D) bioprinting technology present promising solutions to these challenges. This review provides an overview of cancer vasculogenesis and underscores the importance of precise modeling. It juxtaposes traditional techniques with 3D bioprinting technologies, elucidating the advantages of the latter in developing cancer vasculogenesis models. Furthermore, it explores applications in pathological investigations, preclinical medication screening for personalized treatment and cancer diagnostics, and envisages future prospects for 3D bioprinted cancer vasculogenesis models. Despite notable advancements, current 3D bioprinting techniques for cancer vasculogenesis modeling have several limitations. Nonetheless, by overcoming these challenges and with technological advances, 3D bioprinting exhibits immense potential for revolutionizing the understanding of cancer vasculogenesis and augmenting treatment modalities. Full article

The role of artificial intelligence (AI) in healthcare is evolving, offering promising avenues for enhancing clinical decision making and patient management. Limited knowledge about lipedema often leads to patients being frequently misdiagnosed with conditions like lymphedema or obesity rather than correctly identifying lipedema. Furthermore, patients with lipedema often present with intricate and extensive medical histories, resulting in significant time consumption during consultations. AI could, therefore, improve the management of these patients. This research investigates the utilization of OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4), a sophisticated large language model (LLM), as an assistant in consultations for lipedema patients. Six simulated scenarios were designed to mirror typical patient consultations commonly encountered in a lipedema clinic. GPT-4 was tasked with conducting patient interviews to gather medical histories, presenting its findings, making preliminary diagnoses, and recommending further diagnostic and therapeutic actions. Advanced prompt engineering techniques were employed to refine the efficacy, relevance, and accuracy of GPT-4’s responses. A panel of experts in lipedema treatment, using a Likert Scale, evaluated GPT-4’s responses across six key criteria. Scoring ranged from 1 (lowest) to 5 (highest), with GPT-4 achieving an average score of 4.24, indicating good reliability and applicability in a clinical setting. This study is one of the initial forays into applying large language models like GPT-4 in specific clinical scenarios, such as lipedema consultations. It demonstrates the potential of AI in supporting clinical practices and emphasizes the continuing importance of human expertise in the medical field, despite ongoing technological advancements. Full article

China’s northern Hulun Lake is a significant body of water internationally. The issue of eutrophication has gained prominence in recent years. The achievement of precise chlorophyll-a (Chl-a) monitoring is crucial for safeguarding Hulun Lake’s ecosystem. The machine learning-based remote sensing inversion method has been shown to be effective in capturing the intricate relationship between independent and dependent variables; however, it lacks a priori knowledge and is limited by the quality of remote sensing data sources. The relationship between independent and dependent variables can be more accurately simulated with the use of suitable auxiliary variables. Therefore, three machine learning models—random forest (RF), adaptive boosting (AdaBoost), and extreme gradient boosting (XGBoost)—were established in this study using meteorological observation parameters as auxiliary variables combined with Sentinel-2 satellite image remote sensing band combinations as independent variables and measured Chl-a data as dependent variables. The estimation effects before and after the fusion of meteorological ground observation data were compared, and the best model was used to estimate the spatial–temporal variation trend of Chl-a in the regional water body. The results show that (1) the addition of meteorological parameters as auxiliary variables improved the precision of the three machine models; the decision coefficient (R2) rose by 7.25%, 5.71%, and 7.20%, respectively, to 0.76, 0.66, and 0.73. (2) The concentration of Chl-a in the lake region was projected from June to October 2019 to October 2021 using the RF optimal estimating model of meteorological fusion. The northeast, southwest, and south of the lake were where the comparatively high concentration values of Chl-a were located, whereas the lake’s center had a generally low concentration of the substance. Chromatically, Chl-a typically peaked in August after initially increasing and then declining. (3) The three rivers that feed into the river have varying levels of water pollution, with chemical oxygen demand (COD) and total nitrogen (TN) pollution being the most severe. This is what primarily caused the higher levels of Chl-a in the northeast, southwest, and south. This study is crucial for the preservation and restoration of Hulun Lake’s natural ecosystem and offers some technical support for the monitoring of the lake’s concentration of Chl-a. Full article

This article presents a non-linear deterministic mathematical model that captures the evolving dynamics of HIV disease spread, considering three levels of infection in a population. The model integrates fractal-fractional order derivatives using the Caputo operator and undergoes qualitative analysis to establish the existence and uniqueness of solutions via fixed-point theory. Ulam-Hyer stability is confirmed through nonlinear functional analysis, accounting for small perturbations. Numerical solutions are obtained using the fractional Adam-Bashforth iterative scheme and corroborated through MATLAB simulations. The results, plotted across various fractional orders and fractal dimensions, are compared with integer orders, revealing trends towards HIV disease-free equilibrium points for infective and recovered populations. Meanwhile, susceptible individuals decrease towards this equilibrium state, indicating stability in HIV exposure. The study emphasizes the critical role of controlling transmission rates to mitigate fatalities, curb HIV transmission, and enhance recovery rates. This proposed strategy offers a competitive advantage, enhancing comprehension of the model’s intricate dynamics. Full article

The transition from traditional to renewable energy sources is a critical issue in current energy-generation systems, which aims to address climate change and the increased demand for energy. This shift, however, imposes additional burdens on control systems to maintain power system stability and quality within predefined limits. Addressing these challenges, this paper proposes an innovative Modified Hybrid Fractional-Order (MHFO) automatic voltage regulator (AVR) equipped with a fractional-order tilt integral and proportional derivative with a filter plus a second-order derivative with a filter FOTI-PDND²N² controller. This advanced controller combines the benefits of a (FOTI) controller, known for enhancing dynamic performance and steady-state response, with a (PDND²N²) controller to improve system robustness and adaptability. The proposed MHFO controller stands out with its nine tunable parameters, providing more extensive control options than the conventional three-parameter PID controller and the five-parameter FOPID controller. Furthermore, a recent optimization approach using a growth optimizer (GO) has been formulated and applied to optimally adjust the MHFO controller’s parameters simultaneously. The performance of the proposed AVR based on the MHFO-GO controller is scrutinized by contrasting it with various established and developed optimization algorithms. The comparative study shows that the AVR based on the MHFO-GO controller surpasses other AVR controllers from the stability, robustness, and dynamic response speed points of view. Full article

This paper shows solicitude for the generalized projective synchronization of Caputo fractional-order uncertain memristive neural networks (FOUMNNs) with multiple delays. By extending the constant scale factor to the time-varying function matrix, we establish an extraordinary synchronization mode called time-varying function matrix projection synchronization (TFMPS), which is a generalized version of traditional matrix projection synchronization, modified projection synchronization, complete synchronization, and anti-synchronization. To achieve the goal of TFMPS, we design a novel mixed controller including the open loop feedback control and impulsive control, which employs the state information in the time-delayed interval and the sampling information at the impulse instants. It has a prominent advantage that impulse intervals are not restricted by time delays. To establish the connection between the error system and the auxiliary system, a generalized fractional-order comparison theorem with time-varying coefficients and impulses is established. Applying the stability theory, the comparison theorem, and the Laplace transform, new synchronization criteria of FOUMNNs are acquired under the mixed impulsive control schemes, and the derived synchronization theorem and corollary can effectively expand the correlative synchronization achievements of fractional-order systems. Full article

An efficient treatment plan using a temporary anchorage device should be built following the principle of reducing the number of tads to obtain a multiple biomechanical advantage. The following case report concerns the Biga system, a strategy that supports orthodontists during class II corrections and vertical control through treatment. A 12-year-old girl with a high angle of skeletal class II was selected. A novel biomechanical strategy was effectively applied using two tads on the upper arch to obtain sequential distalization of the upper teeth and to correct the lower arch spee curve using third-class elastics. Eventually, on the same tads, a double cantilever was applied to control the overbite and intrusion during incisors’ retraction. The Biga system is an easy biomechanical strategy that ensures the three-dimensional control of treatment mechanics in class II patients. Full article

A numerical method is used to solve the thermal analysis of natural convection in enclosures. This paper proposes the use of an implicit artificial-compressibility model in conjunction with the Radial Point Interpolation Meshless (RPIM) method to mimic laminar natural convective heat transport. The technique couples the pressure with the velocity components using an artificial compressibility model. The RPIM is used to discretize the spatial terms of the governing equation. We solve the semi-algebraic system implicitly in backward Euler pseudo-time. The proposed method solves two test problems—natural convection in the annulus of concentric circular cylinders and trapezoidal cavity. Additionally, the results are validated using experimental and numerical data available in the literature. Excellent agreement was seen between the numerical results acquired with the suggested method and those obtained through the standard techniques found in the literature. Full article

Lichens, a diverse group of organisms, have a unique structure consisting of fungal filaments and photosynthetic partner cells. This research conducted a comprehensive chemical analysis and evaluation of the anti-inflammatory and antioxidant properties of methanolic and acetone extracts from Umbilicaria crustulosa lichen, along with its isolated metabolites. The process involved separating atranorin and chloratranorin fractions, physodic acid, and gyrophoric acid. Secondary metabolites were identified using chromatographic and spectroscopic data. The total polyphenols content was determined spectrophotometrically. This study examined the antioxidant activity of extracts of the lichen U. crustulosa and the isolated fractions using three methods: DPPH scavenging activity, ABTS scavenging activity, and reducing power. This study also evaluated the acute oral toxicity and the anti-inflammatory activity of the extracts in Wistar albino rats. A higher content of the total phenolic compounds was found in the acetone extract, but antioxidant and anti-inflammatory activities were more prominent in the methanolic extract. The isolated atranorin and chloratranorin fractions and compound physodic acid showed the highest antioxidant activity. No toxic effects were noted in the acute oral toxicity study. This study highlights the potential of the investigated lichen as a valuable source of novel biological agents. Full article

To enhance comprehension of the impact of mixed fermentation using Torulaspora delbrueckii Bio-119667 (TD) on the aroma composition of Munage grape base-wine (MGBW), we analysed the aroma composition of MGBW using HS-SPME-GC-MS widely targeted metabolomics. The levels of volatile aroma components, including terpenes, higher alcohols, aldehydes, heterocyclic compounds, and esters, were significantly higher in MGBW produced by mixed fermentation compared to the pure Saccharomyces yeast control fermentation. The study found that the content of esters increased by 26.3% after mixed fermentation, indicating the contribution of TD to the formation of ester flavour components during the fermentation of MGBW. After analysing aroma activity values, we discovered that 49 out of 115 esters (25.5% of the total) significantly contributed to the aroma profile of MGBW (rOAV > 1). Of these esters, 16 were identified as key aroma compounds (rOAV > 1, VIP > 1) produced by mixed fermentation with the participation of TD. This finding further supports the contribution of TD to the improvement of MGBW’s aroma composition. This study reveals the role of non-Saccharomyces yeast strain Torulaspora delbrueckii Bio-119667 in improving the aroma composition of MGBW produced by mixed culture fermentation and the biosynthetic pathways of key aroma components therein. Full article

Over the last several decades, the European Union (EU) has championed recycling and sustainable waste management through Directives 2008/98/EC and 2018/851, shaping practices across its member states. Currently, 30% of the EU’s municipal waste is recycled, 19% composted, 23% incinerated, and 23% landfilled. However, regional variations exist within the EU, with Greece and other Mediterranean/Balkan nations favoring landfilling, while Germany and other Western/Central EU nations prioritize recycling and composting, and Nordic countries lean toward incineration. To address these differences, a new sustainability point system was created in order to evaluate and compare all different municipal waste management strategies of EU members. Notably, countries like Germany, the Netherlands, and Sweden score the highest due to low municipal waste generation, high recycling rates (>35%), minimal landfilling (<1%), and significant incineration. In contrast, Cyprus, Malta, and Greece score lower due to landfill reliance and lower recycling rates. Therefore, this study introduces a novel sustainability point system to mitigate disparities, highlighting the need for targeted interventions and policy initiatives at the national and EU levels. By leveraging these insights, policymakers can allocate resources effectively, foster collaboration, and motivate citizens to achieve common environmental goals as well as the Sustainable Development Goals (SDGs). Full article

A Life Cycle Assessment (LCA) quantifies the environmental impacts during the life of a product from cradle to grave. It evaluates energy use, material flow, and emissions at each stage of life. This report addresses the challenges and potential solutions related to the surge in electric vehicle (EV) batteries in the United States amidst the EV market’s exponential growth. It focuses on the environmental and economic implications of disposal as well as the recycling of lithium-ion batteries (LIBs). With millions of EVs sold in the past decade, this research highlights the necessity of efficient recycling methods to mitigate environmental damage from battery production and disposal. Utilizing a Life Cycle Assessment (LCA) and Life Cycle Cost Assessment (LCCA), this research compares emissions and costs between new and recycled batteries by employing software tools such as SimaPro V7 and GREET V2. The findings indicate that recycling batteries produces a significantly lower environmental impact than manufacturing new units from new materials and is economically viable as well. This research also emphasizes the importance of preparing for the upcoming influx of used EV batteries and provides suggestions for future research to optimize the disposal and recycling of EV batteries. Full article

Modern research has made the search for high-performance, sustainable, and efficient energy storage technologies a main focus, especially in light of the growing environmental and energy-demanding issues. This review paper focuses on the pivotal role of biomass-derived carbon (BDC) materials in the development of high-performance metal-ion hybrid supercapacitors (MIHSCs), specifically targeting sodium (Na)-, potassium (K)-, aluminium (Al)-, and zinc (Zn)-ion-based systems. Due to their widespread availability, renewable nature, and exceptional physicochemical properties, BDC materials are ideal for supercapacitor electrodes, which perfectly balance environmental sustainability and technological advancement. This paper delves into the synthesis, functionalization, and structural engineering of advanced biomass-based carbon materials, highlighting the strategies to enhance their electrochemical performance. It elaborates on the unique characteristics of these carbons, such as high specific surface area, tuneable porosity, and heteroatom doping, which are pivotal in achieving superior capacitance, energy density, and cycling stability in Na-, K-, Al-, and Zn-ion hybrid supercapacitors. Furthermore, the compatibility of BDCs with metal-ion electrolytes and their role in facilitating ion transport and charge storage mechanisms are critically analysed. Novelty arises from a comprehensive comparison of these carbon materials across metal-ion systems, unveiling the synergistic effects of BDCs’ structural attributes on the performance of each supercapacitor type. This review also casts light on the current challenges, such as scalability, cost-effectiveness, and performance consistency, offering insightful perspectives for future research. This review underscores the transformative potential of BDC materials in MIHSCs and paves the way for next-generation energy storage technologies that are both high-performing and ecologically friendly. It calls for continued innovation and interdisciplinary collaboration to explore these sustainable materials, thereby contributing to advancing green energy technologies. Full article

Vector quantization (VQ) is a block coding method that is famous for its high compression ratio and simple encoder and decoder implementation. Linde–Buzo–Gray (LBG) is a renowned technique for VQ that uses a clustering-based approach for finding the optimum codebook. Numerous algorithms, such as Particle Swarm Optimization (PSO), the Cuckoo search algorithm (CS), bat algorithm, and firefly algorithm (FA), are used for codebook design. These algorithms are primarily focused on improving the image quality in terms of the PSNR and SSIM but use exhaustive searching to find the optimum codebook, which causes the computational time to be very high. In our study, our algorithm enhances LBG by minimizing the computational complexity by reducing the total number of comparisons among the codebook and training vectors using a match function. The input image is taken as a training vector at the encoder side, which is initialized with the random selection of the vectors from the input image. Rescaling using bilinear interpolation through the nearest neighborhood method is performed to reduce the comparison of the codebook with the training vector. The compressed image is first downsized by the encoder, which is then upscaled at the decoder side during decompression. Based on the results, it is demonstrated that the proposed method reduces the computational complexity by 50.2% compared to LBG and above 97% compared to the other LBG-based algorithms. Moreover, a 20% reduction in the memory size is also obtained, with no significant loss in the image quality compared to the LBG algorithm. Full article

Calicioids form a research field that has encompassed ascomycetous fungi with stalked ascomata similar to those of the lichen genus Calicium. Early generic circumscriptions of calicioid lichens and fungi were mainly based on morphological and secondary chemistry information. After the introduction of molecular data, taxonomy in the group has been reconsidered. Here, based on a broad geographical sampling, Coniocybe Ach. was revised using molecular and morphological features. Three loci (ITS, LSU and rpb1) were compared to infer its phylogenetic position, and a total of 52 new sequences (14 ITS, 24 LSU and 14 rpb1) were produced. Apart from its type C. furfuracea, Coniocybe was revised and emended to also include C. brachypoda and C. confusa. In addition, a new species, Coniocybe eufuracea, was described, and a key to the species of Coniocybe was provided. Full article

Wound-invasive fungal diseases (WIFDs), especially mucormycosis, have emerged as life-threatening infections during recent military combat operations. Many combat-relevant fungal pathogens are refractory to current antifungal therapy. Therefore, animal models of WIFDs are urgently needed to investigate new therapeutic solutions. Our study establishes combat-relevant murine models of wound mucormycosis using Rhizopus arrhizus and Lichtheimia corymbifera, two Mucorales species that cause wound mucormycosis worldwide. These models recapitulate the characteristics of combat-related wounds from explosions, including blast overpressure exposure, full-thickness skin injury, fascial damage, and muscle crush. The independent inoculation of both pathogens caused sustained infections and enlarged wounds. Histopathological analysis confirmed the presence of necrosis and fungal hyphae in the wound bed and adjacent muscle tissue. Semi-quantification of fungal burden by colony-forming units corroborated the infection. Treatment with liposomal amphotericin B, 30 mg/kg, effectively controlled R. arrhizus growth and significantly reduced residual fungal burden in infected wounds (p < 0.001). This study establishes the first combat-relevant murine model of wound mucormycosis, paving the way for developing and evaluating novel antifungal therapies against combat-associated WIFDs. Full article

The fermentation of a soil-derived fungus Acremonium sp. led to the isolation of thirteen ascochlorin congeners through integrated genomic and Global Natural Product Social (GNPS) molecular networking. Among the isolated compounds, we identified two unusual bicyclic types, acremochlorins O (1) and P (2), as well as two linear types, acremochlorin Q (3) and R (4). Compounds 1 and 2 contain an unusual benzopyran moiety and are diastereoisomers of each other, the first reported for the aschlorins. Additionally, we elucidated the structure of 5, a 4-chloro-5-methylbenzene-1,3-diol with a linear farnesyl side chain, and confirmed the presence of eight known aschlorin analogs (6–13). The structures were determined by the detailed interpretation of 1D and 2D NMR spectroscopy, MS, and ECD calculations. Compounds 3 and 9 showed potent antibacterial activity against Staphylococcus aureus and Bacillus cereus, with MIC values ranging from 2 to 16 μg/mL. Full article

Over the years, the concentration of cadmium in soil has increased due to industrialization. Cadmium in the soil enters the human body through plant accumulation, seriously endangering human health. In the current study, two types of hydrogels were successfully synthesized using a free radical polymerization method: an ion-type hydrogel referred to as DMAPAA (N-(3-(Dimethyl amino) propyl) acrylamide)/DMAPAAQ (N,N-Dimethyl amino propyl acrylamide, methyl chloride quaternary) and a non-ion-type hydrogel known as DMAA (N,N-Dimethylacrylamide). In the experiment carried out in this study, the ion-type hydrogel DMAPAA/DMAPAAQ was introduced to cadmium-contaminated soil for vegetable cultivation. The study found that at cadmium levels of 0 and 2 mg/kg in soil, when exposed to a pH 2 solution, cadmium wasn’t detected in the filtrate using ICP. As the amount of cadmium increased to 500 mg/kg, hydrogel addition gradually reduced the filtrate cadmium concentration. Notably, the use of the 4% hydrogel resulted in 0 mg/L of cadmium. For the 0% hydrogel, vegetable cadmium absorption was determined to be 0.07 mg/g, contrasting with 0.03 mg/g for the 4% hydrogel. The DMAPAA/DMAPAAQ hydrogel significantly boosts vegetable growth by efficiently absorbing nitrate ions through ion exchange, releasing them for plant uptake. In contrast, the DMAA hydrogel, used as a control, does not enhance plant growth despite its water absorption properties. In summary, the composite hydrogel shows great potential for enhancing vegetable yield and immobilizing heavy metals in soil. Full article