In recent years, there has been increasing interest in the joint modelling of compound extreme events such as high temperatures and low rainfall. The increase in the frequency of occurrence of these events in many regions has necessitated the development of models for estimating the concurrent probabilities of such compound extreme events. The current study discusses an application of copula models in predicting the concurrent probabilities of compound low rainfall and high-temperature events using data from the Lowveld region of the Limpopo province in South Africa. The second stage discussed two indicators for monitoring compound high temperature and low rainfall events. Empirical results from the study show that elevations ranging from 100–350 m, 350–700 m and 700–1200 m exhibit varying probabilities of experiencing drought, with mild droughts having approximately 64%, 66%, and 65% chances, moderate droughts around 36%, 39%, and 38%, and severe droughts at approximately 16%, 19%, and 18%, respectively. Furthermore, the logistic regression models incorporating the southern oscillation index as a covariate yielded comparable results of copula-based models. The methodology discussed in this paper is robust and can be applied to similar datasets in any regional setting globally. These findings could be useful to disaster management decision makers, helping them formulate effective mitigation strategies and emergency response plans. Full article

Cancer poses significant emotional challenges for children and adolescents, despite improvements in survival rates due to new therapies. However, there is growing concern about the long-term effects, including fertility issues. This review examines recent advancements and future directions in fertility preservation within a pediatric population subjected to oncological therapies. Worldwide, there is variability in the availability of fertility preservation methods, influenced by factors like development status and governmental support. The decision to pursue preservation depends on the risk of gonadotoxicity, alongside factors such as diagnosis, treatment, clinical status, and prognosis. Currently, options for preserving fertility in prepubertal boys are limited compared to girls, who increasingly have access to ovarian tissue preservation. Adolescents and adults have more options available, but ethical considerations remain complex and diverse. Full article

Several adverse maternal outcomes have been linked to the excessive consumption of caffeine during pregnancy. Tea is an important source of caffeine. Hypertensive disorders of pregnancy (HDP) are common pregnancy complications with unfavorable maternal and fetal complications. This study aimed to investigate the relationship between antenatal tea drinking and HDP using a meta-analysis of available evidence. We systematically retrieved eligible studies before computing the pooled odds ratio (OR) and 95% confidence interval (CI) of HDP for women who reported the highest versus the lowest frequencies of antenatal tea drinking. We used the I² statistic to measure heterogeneity across studies and the test for funnel plot asymmetry to evaluate publication bias. The results showed that the highest frequencies of antenatal tea drinking were associated with increased odds of HDP (pooled OR = 1.16, 95% CI: 1.01, 1.33). We identified no signs of heterogeneity across studies (I² = 0.0% and p-heterogeneity = 0.498) or publication bias (z = 0.791 and p-publication bias = 0.429). When the outcome was limited to (pre-)eclampsia, the association became statistically non-significant (pooled OR = 1.28, 95% CI: 0.86, 1.89, I² = 0.0%, and p-heterogeneity = 0.751). In conclusion, our results indicated that the highest frequency of antenatal tea drinking was positively associated with HDP. Pregnant women should be advised against excessive tea consumption. Still, future prospective cohort studies, considering the effects of different tea types and caffeine content, are needed to confirm our conclusions. Full article

Background: The aim of this study was to propose a new 3D printing method for attachment production and compare the reproduction accuracy of traditional attachments with the proposed 3D-printed attachments. Methods: A standardized 3D model attachment was created with the dimensions of 3, 2, and 2 mm for the apico-coronal, mesio-distal, and vestibulo-lingual dimensions, respectively. A 3D ideal model of the maxillary arch was used to apply four standardized attachments on the vestibular surface of selected teeth. The obtained model with placed attachments was used to reproduce composite attachments via the conventional method. A transfer template was used to bond with the flow composite resin 3D-printed attachment on a new arch model without attachments. The models with traditional attachments and 3D-printed attachments were scanned and overlapped with the original CAD model with attachments. To assess the attachment precision, vertical and horizontal cutting planes were used on the overlapped models. The outcome selection focused on puff analysis (excess composite material evaluation) and shape analysis (attachment accuracy evaluation). Results: The results indicated that the 3D-printed attachments showed significant differences (p < 0.05) compared to the traditional attachments. The descriptive statistics showed the higher discrepancies compared to the CAD model of the traditionally created attachments in the shape (0.85 mm) and puff dimension (1.02 mm). Conclusion: Custom 3D-printed attachment production is an effective method for achieving greater attachment precision. Full article

This study aims to empirically examine the relationship between cryptocurrency and various facets of the financial system. It seeks to provide a comprehensive understanding of how cryptocurrencies interact with, and influence, the stock market, the U.S. dollar’s strength, inflation rates, and traditional banking operations. This is carried out using linear regression models, Granger causality tests, case studies, including the collapse of the Futures Exchange (FTX), and the successful integration of Binance. The study unveiled a strong positive correlation between cryptocurrency market capitalization and key financial indicators like the Dow Jones Industrial Average, Consumer Price Index, and traditional banking operations. This indicates the growing significance of cryptocurrencies within the global financial landscape. However, a mild association was found with the U.S. dollar, suggesting a limited influence of cryptocurrencies on traditional fiat currencies currently. Despite certain limitations such as reliance on secondary data, methodological choices, and geographic focus, this research provides valuable insights for policymakers, financial industry stakeholders, and academic researchers, underlining the necessity for continued study into the complex interplay between cryptocurrencies and financial stability. Full article

The principle of the digital learning ecosystem is the application of the educational process through digital learning environment platforms that help users learn more effectively. Educational institutions, teachers and students must evolve to adapt and be ready for the new world of learning. The individual’s emotional quality can influence their readiness in the digital learning ecosystem. This study aimed to examine whether there is a significant relationship between students’ readiness in the digital learning ecosystem and their emotional intelligence levels. This study utilized a correlational research method and multiple linear regression analysis. For data collection, the primary tools used were Trait Emotional Intelligence Scale-Short Form (TEIS-SF) and the Online Learning Readiness Scale (OLRS). The questionnaires were administered to 103 students enrolled in seven different higher institutions in Brunei. The results of the research showed that there was a link between students’ online learning readiness levels and their emotional intelligence levels. This study found that students with a high well-being sub-dimension of emotional intelligence had high online learning readiness levels. Full article

Chinese cork oak (Quercus variabilis Blume) is a widespread tree species with high economic and ecological values. Chinese cork oak exhibits epicotyl dormancy, causing emergence heterogeneity and affecting the quality of seedling cultivation. Gibberellic acid-stimulated transcript (GAST) is a plant-specific protein family that plays a crucial regulatory role in plant growth, development, and seed germination. However, their evolution in Chinese cork oak and roles in epicotyl dormancy are still unclear. Here, a genome-wide identification of the GAST gene family was conducted in Chinese cork oak. Ten QvGAST genes were identified, and nine of them were expressed in seed. The physicochemical properties and promoter cis-acting elements of the selected Chinese cork oak GAST family genes indicated that the cis-acting elements in the GAST promoter are involved in plant development, hormone response, and stress response. Germinated seeds were subjected to gibberellins (GAs), abscisic acid (ABA), and fluridone treatments to show their response during epicotyl dormancy release. Significant changes in the expression of certain QvGAST genes were observed under different hormone treatments. QvGAST1, QvGAST2, QvGAST3, and QvGAST6 exhibited upregulation in response to gibberellin. QvGAST2 was markedly upregulated during the release of epicotyl dormancy in response to GA. These findings suggested that QvGAST2 might play an important role in epicotyl dormancy release. This study provides a basis for further analysis of the mechanisms underlying the alleviation of epicotyl dormancy in Chinese cork oak by QvGASTs genes. Full article

(1) Background: Due to the wide application in medicinal and pharmaceutical chemistry of flavonoid molecules, which are one of the most famous types of secondary plant metabolites, our work has come within the framework of bio-consulting to help in the identification of the molecule(s) responsible for the antibacterial effect which will be the active principle of a natural antibiotic developed from Algerian fir using bioinformatics tools. (2) Methods: The docking method was used to test the antiviral activity on SARS-CoV-2 virus and the antibacterial activity on Gram-positive Staphylococcus aureus and Gram-negative Escherichia coli of 12 polyphenolic molecules present in the ethyl acetate and n-butanol extracts of Numidian fir leaves, and identify the molecules responsible for these specific biological activities. (3) Results: The findings revealed that it is possible that two molecules, hyperoside and quercitrin, have a high capacity to inhibit SARS-CoV-2, and it is important to mention that they are the most quantitatively abundant molecules in the extract. The molecule luteolin-7-glucoside is probably responsible for the antibacterial activity in the extract against Gram-negative bacteria such as Escherichia coli, and the molecule hesperidin is responsible for the antibacterial activity in the extract against Gram-positive bacteria such as Staphylococcus aureus. Full article

The integration of Virtual Reality with radiology is the focus of this study. A narrative review has been proposed to delve into emerging themes within the integration of Virtual Reality in radiology by scrutinizing reviews gathered from PubMed and Scopus. The proposed approach was based on a standard narrative checklist and a qualification process. The selection process identified 20 review studies. Integration of Virtual Reality (VR) in radiology offers potential transformative opportunities also integrated with other emerging technologies. In medical education, VR and AR, using 3D images from radiology, can enhance learning, emphasizing the need for standardized integration. In radiology, VR combined with Artificial Intelligence (AI) and Augmented Reality (AR) shows promising prospectives to give a complimentary contribution to diagnosis, treatment planning, and education. Challenges in clinical integration and User Interface design must be addressed. Innovations in medical education, like 3D modeling and AI, has the potential to enable personalized learning, but face standardization challenges. While robotics play a minor role, advancements and potential perspectives are observed in neurosurgery and endovascular systems. Ongoing research and standardization efforts are crucial for maximizing the potential of these integrative technologies in healthcare. In conclusion, the synthesis of these findings underscores the opportunities for advancements in digital radiology and healthcare through the integration of VR. However, challenges exist, and continuous research, coupled with technological refinements, is imperative to unlock the full potential of these integrative approaches in the dynamic and evolving field of medical imaging. Full article

With the emergence of Industry 4.0 in intralogistics, the need for flexible material handling solutions is increasing. While conventional conveyor systems are often too inflexible to meet changing requirements. Automated guided vehicles offer an answer, additional solutions are required for companies relying on already busy and crowded shop floors. This paper presents a concept for a periphery-free electrified monorail system (PEMS) that enables flexible material transport with minimal floor requirements. The PEMS is based on classic electrified monorail technology, and requires no additional peripheral devices within the rail system. Installation and maintenance costs are kept to a minimum through simplified branching elements and a battery-powered energy supply for the vehicles. The modular design of the rail elements further allows transport on standardized Euro-pallets. Moreover, a taxonomy for evaluating the passivity of branching elements of electrified monorail systems is introduced. The functionality of the PEMS was validated by conducting real experiments using a prototype, The results show that the PEMS provides high flexibility in terms of layout design and usage, allowing for fast adaption to the changing requirements of intralogistics. Full article

Tropical cyclones (TCs) are characterized by robust vortical motion and intense thermodynamic processes, often causing damage in coastal cities as they result in landfall. Accurately estimating the ensemble mean of TC precipitation is critical for forecasting and remains a foremost global challenge. In this study, we develop an ensemble algorithm based on the feature-oriented mean (FM) suitable for spatially discrete variables in precipitation ensembles. This method can adjust the locations of ensemble precipitation fields to reduce the location-related deviations among ensemble members, ultimately enhancing the ensemble mean forecast skill for TC precipitation. To evaluate the feasibility of the FM in TC precipitation ensemble forecasting, 18 landing TC cases in China from 2019 to 2021 were selected for validation. For precipitation forecasts of the landing TCs with a varying leading time, we conducted a comprehensive quantitative evaluation and comparison of the precipitation forecast skills of the FM and arithmetic mean (AM) algorithms. The results indicate that the field adjustment algorithm in the FM can effectively align with the TC precipitation structure and the location of the ensemble mean, reducing the spatial divergence among precipitation fields. The FM method demonstrates superior performance in the equitable threat score, probability of detection, and false alarm ratio compared with the AM, exhibiting an overall improvement of around 10%. Furthermore, the FM ensemble mean shows a higher pattern of the correlation coefficient with observations and has a smaller root mean square error than the AM ensemble mean, signifying that the FM method can better preserve the characteristics of the precipitation structure. Additionally, an object-based diagnostic evaluation method was used to verify forecast results, and the results suggest that the attribute distribution of FM forecast objects more closely resembles that of observed precipitation objects (including the area, longitudinal and latitudinal centroid locations, axis angle, and aspect ratio). Full article

COVID-19 vaccination strategies, including heterologous prime–boost regimens and additional booster doses, aim to optimize immune responses. However, seroepidemiological studies on immune responses to different COVID-19 vaccine types and schedules remain limited. This study investigated antibody levels following homologous and heterologous prime-and-boost COVID-19 vaccination in Bangladesh. In a cohort of 606 participants who received first/second/booster doses of vaccines (AstraZeneca, Moderna, Pfizer-BioNTech, and Sinopharm), anti-spike IgG and anti-nucleocapsid IgG levels were measured. Antibody titer variations with respect to age, gender, intervals between doses, and prior infection status were analyzed. mRNA vaccines elicited the highest antibody levels after homologous and heterologous boosting. The AstraZeneca booster resulted in a sharp titer decline rate of ~0.04 units per day. Second or booster vaccine doses significantly increased antibody levels, especially in males (p < 0.05). Older age correlated with higher titers, likely reflecting previous infection, which was further confirmed by the elevation of anti-nucleocapsid IgG levels. About 95.5% of non-Sinopharm recipients were anti-nucleocapsid IgG positive, suggesting prior exposure exceeding self-reported infections (12.5%). mRNA and heterologous COVID-19 boosting enhances humoral immunity over homologous prime–boost vector/inactivated vaccination. However, waning immunity merits further investigation across vaccine platforms. Full article

Obtaining accurate basic parameters for long hole blasting is challenging, and the resulting vibration damage significantly impacts key surface facilities. Predicting ground vibration velocity accurately and mitigating the harmful effects of blasting are crucial aspects of controlled blasting technology. This study focuses on the prediction of ground vibration velocity induced by underground long hole blasting tests. Utilizing the fitting equation based on the US Bureau of Mines (USBM) formula as a baseline for predicting peak particle velocity, two machine learning models suitable for small sample data, Support Vector Regression (SVR) machine and Random Forest (RF), were employed. The models were optimized using the particle swarm optimization algorithm (PSO) to predict peak particle velocity with multiple parameters specific to long hole blasting. Mean absolute error (MAE), mean Squared error (MSE), and coefficient of determination (R²) were used to assess the model predictions. Compared with the fitting equation based on the USBM model, both the Support Vector Regression (SVR) and Random Forest (RF) models accurately and effectively predict peak particle velocity, enhancing prediction accuracy and efficiency. The SVR model exhibited slightly superior predictive performance compared to the RF model. Full article

Recent years have witnessed unprecedented progress in therapeutic gene editing, revolutionizing the approach to treating genetic disorders. In this comprehensive review, we discuss the progression of milestones leading to the emergence of the clustered regularly interspaced short palindromic repeats (CRISPR)-based technology as a powerful tool for precise and targeted modifications of the human genome. CRISPR-Cas9 nuclease, base editing, and prime editing have taken center stage, demonstrating remarkable precision and efficacy in targeted ex vivo and in vivo genomic modifications. Enhanced delivery systems, including viral vectors and nanoparticles, have further improved the efficiency and safety of therapeutic gene editing, advancing their clinical translatability. The exploration of CRISPR-Cas systems beyond the commonly used Cas9, such as the development of Cas12 and Cas13 variants, has expanded the repertoire of gene editing tools, enabling more intricate modifications and therapeutic interventions. Outstandingly, prime editing represents a significant leap forward, given its unparalleled versatility and minimization of off-target effects. These innovations have paved the way for therapeutic gene editing in a multitude of previously incurable genetic disorders, ranging from monogenic diseases to complex polygenic conditions. This review highlights the latest innovative studies in the field, emphasizing breakthrough technologies in preclinical and clinical trials, and their applications in the realm of precision medicine. However, challenges such as off-target effects and ethical considerations remain, necessitating continued research to refine safety profiles and ethical frameworks. Full article

By leveraging a multiscale geographically weighted regression (MGWR) model, this paper delves into the intricate factors that influence housing prices in the prototypical mountainous cityscape of Chongqing’s central urban area. The key findings are as follows: Firstly, the distribution of housing prices in the study region exhibits pronounced spatial heterogeneity, with the core area exhibiting a distinct “high-high” clustering pattern and manifesting characteristics of a multicenter group distribution. Secondly, the MGWR model effectively assigns an individual bandwidth to each feature quantity, allowing for a more nuanced portrayal of the varying influence scales exerted by diverse variables. Lastly, the study reveals that factors such as property cost, greening rate, building age, and proximity to rivers have a notable negative impact on housing prices, whereas, educational facilities exert a marked positive influence. Elevation, floor area ratio, and distance from the Central Business District (CBD) exhibit a more complex influence on housing prices. Full article

The role of critical infrastructures in maintaining the functioning of the economy and society and ensuring national security, particularly their durability in delivering essential services during crises, including natural disasters such as earthquakes, is critical. This work introduces an analytical methodology to quantify potential earthquake damage to power stations and evaluate the cost-effectiveness of measures to enhance their seismic resistance. By employing fragility curves and probabilistic risk analyses, this approach provides a structured framework for the comprehensive assessment of risks and the identification of economically practical mitigation strategies. A detailed examination of strategies to protect critical power station components against seismic activity is presented, revealing that a minor investment relative to the overall project budget for earthquake-proofing measures is economically effective. This investment, representing a marginal fraction of 0.5% of the total project expenditure significantly reduces the seismic risk of power station failure by 36%. Reinforcing essential elements, including switching stations, water treatment facilities, and water tanks, is emphasized to ensure their continued operation during and after an earthquake. This research highlights the critical significance of integrating risk assessment with benefit-to-cost analysis in strategic decision-making processes, supporting the prioritization of investments in infrastructure enhancements. These enhancements promise substantial reductions of risks at minimal costs, thus protecting essential services against the impacts of natural disasters. This research contributes to state-of-the-art research in critical infrastructures resilience. Full article

Post-traumatic stress disorder (PTSD) is a debilitating psychological condition that may develop in certain individuals following exposure to life-threatening or traumatic events. Distressing symptoms, including flashbacks, are characterized by disrupted stress responses, fear, anxiety, avoidance tendencies, and disturbances in sleep patterns. The enduring effects of PTSD can profoundly impact personal and familial relationships, as well as social, medical, and financial stability. The prevalence of PTSD varies among different populations and is influenced by the nature of the traumatic event. Recently, zebrafish have emerged as a valuable model organism in studying various conditions and disorders. Zebrafish display robust behavioral patterns that can be effectively quantified using advanced video-tracking tools. Due to their relatively simple nervous system compared to humans, zebrafish are particularly well suited for behavioral investigations. These unique characteristics make zebrafish an appealing model for exploring the underlying molecular and genetic mechanisms that govern behavior, thus offering a powerful comparative platform for gaining deeper insights into PTSD. This review article aims to provide updates on the pathophysiology of PTSD and the genetic responses associated with psychological stress. Additionally, it highlights the significance of zebrafish behavior as a valuable tool for comprehending PTSD better. By leveraging zebrafish as a model organism, researchers can potentially uncover novel therapeutic interventions for the treatment of PTSD and contribute to a more comprehensive understanding of this complex condition. Full article

Anthracnose, caused by the fungus Colletotrichum lindemuthianum, poses a significant and widespread threat to the common bean crop. The use of plant genetic resistance has proven to be the most effective strategy for managing anthracnose disease. The Amendoim Cavalo (AC) Andean cultivar has resistance against multiple races of C. lindemuthianum, which is conferred by the Co-AC gene. Fine mapping of this resistance gene to common bean chromosome Pv01 enabled the identification of Phvul.001G244300, Phvul.001G244400, and Phvul.001G244500 candidate genes for further validation. In this study, the relative expression of Co-AC candidate genes was assessed, as well as other putative genes in the vicinity of this locus and known resistance genes, in the AC cultivar following inoculation with the race 73 of C. lindemuthianum. Gene expression analysis revealed significantly higher expression levels of Phvul.001G244500. Notably, Phvul.001G244500 encodes a putative Basic Helix–Loop–Helix transcription factor, suggesting its involvement in the regulation of defense responses. Furthermore, a significant modulation of the expression of defense-related genes PR1a, PR1b, and PR2 was observed in a time-course experiment. These findings contribute to the development of improved strategies for breeding anthracnose-resistant common bean cultivars, thereby mitigating the impact of this pathogen on crop yields and ensuring sustainable bean production. Full article

Animal-sourced foods are important for human nutrition and health, but they can have a negative impact on the environment. These impacts can result in land use tensions associated with population growth and the loss of native forests and wetlands during agricultural expansion. Increased greenhouse gas emissions, and high water use but poor water quality outcomes can also be associated. Life cycle analysis from cradle-to-distribution has shown that novel plant-based meat alternatives can have an environmental footprint lower than that of beef finished in feedlots, but higher than for beef raised on well-managed grazed pastures. However, several technologies and practices can be used to mitigate impacts. These include ensuring that grazing occurs when feed quality is high, the use of dietary additives, breeding of animals with higher growth rates and increased fecundity, rumen microbial manipulations through the use of vaccines, soil management to reduce nitrous oxide emission, management systems to improve carbon sequestration, improved nutrient use efficacy throughout the food chain, incorporating maize silage along with grasslands, use of cover crops, low-emission composting barns, covered manure storages, and direct injection of animal slurry into soil. The technologies and systems that help mitigate or actually provide solutions to the environmental impact are under constant refinement to enable ever-more efficient production systems to allow for the provision of animal-sourced foods to an ever-increasing population. Full article

An oxidizing and harmful pollutant gas, tropospheric ozone is a product of a complex set of photochemical reactions that can make it difficult to enact effective control measures. A better understanding of its precursors including volatile organic compounds (VOCs) and nitrogen oxides (NO_x) and their spatial distribution can enable policymakers to focus their control efforts. In this study we used low-cost sensors (LCSs) to increase the spatial resolution of an existing NO₂ monitoring network in addition to VOC sampling to better understand summer ozone formation in Maricopa County, Arizona, and observed that afternoon O₃ values at the downwind sites were significantly correlated, ~0.27, to the morning NO₂ × rate values at the urban sites. Additionally, we looked at the impact of wildfire smoke on ozone exceedances and compared non-smoke days to smoke days. The average O₃ on smoke days was approximately 20% higher than on non-smoke days, however, the average NO₂ concentration multiplied by estimated photolysis rate (NO₂ × rate) values were only 2% higher on smoke days. Finally, we evaluated the ozone sensitivity of the region by calculating HCHO/NO₂ ratios using three different datasets: ground, satellite, and model. Although the satellite dataset produced higher HCHO/NO₂ ratios than the other datasets, when the proper regime thresholds are applied the three datasets consistently show transition and VOC-limited O₃ production regimes over the Phoenix metro area. This suggests a need to implement more VOC emission controls in order to reach O₃ attainment in the county. Full article

The adaptive potential of plants in urban environments, responding to factors like air pollution, electromagnetic radiation, and specific microclimates, remains insufficiently understood. Our study focused on two evergreen Cupressaceae family species, Thuja occidentalis L. and Platycladus orientalis L. Franco, which are commonly found in Kazakhstan’s urban landscapes. Conducted in Almaty, one of Kazakhstan’s most polluted cities, our comparative analysis examined the anatomical features, photosynthetic activity, and secondary metabolite composition of these conifers. Both species exhibited xeromorphic traits, such as submerged stomata, resin passages, and a prominent leaf cuticle. T. occidentalis displayed higher photosynthetic activity values (quantum yield of photosystem II (YII), electron transport rate (ETR), and quantum yield of non-photochemical quenching (Y(NPQ))) than P. orientalis, while P. orientalis exhibited a higher quantum yield of non-regulated energy dissipation in PSII (Y(NO)) values. Chemical analysis revealed 31 components in T. occidentalis and 33 in P. orientalis, with T. occidentalis containing three times more thujone (16.42% and 5.18%, respectively) and a higher monosaccharide content (17.33% and 6.98%, respectively). T. occidentalis also contained 14.53% steroids, whereas P. orientalis showed no steroid presence. The cytotoxic activity of essential oils was determined by the survival of Artemia salina aquatic crustaceans, whereas tested essential oils from both species exhibited acute lethal toxicity to A. salina aquatic crustaceans across all tested concentrations. The connection between physiological traits, adaptation strategies, and cytotoxic effects offers a comprehensive view of the ecological and pharmacological importance of these two observed conifer species, highlighting their diverse roles in urban environments, as well as their potential medical uses. Full article

The qualitative impact of pollutants on water quality is mainly related to their nature and their concentration, but in any case, they determine a strong impact on the involved ecosystems. In particular, refractory organic compounds represent a critical challenge, and several degradation processes have been studied and developed for their removal. Among them, heterogeneous Fenton treatment is a promising technology for wastewater and liquid waste remediation. Here, we have developed mono- and bimetallic formulations based on Co, Cu, Fe, and Mn, which were investigated for the degradation of three model organic dyes (methylene blue, rhodamine B, and malachite green). The treated samples were then analyzed by means of UV-vis spectrophotometry techniques. Bimetallic iron-based materials achieved almost complete degradation of all three model molecules in very short time. The Mn-Fe catalyst resulted in the best formulation with an almost complete degradation of methylene blue and malachite green at pH 5 in 5 min and of rhodamine B at pH 3 in 30 min. The results suggest that these formulations can be applied for the treatment of a broad range of liquid wastes comprising complex and variable organic pollutants. The investigated catalysts are extremely promising when compared to other systems reported in the literature. Full article