Most fouling organisms have planktonic larval and benthic adult stages. Larval settlement, the planktonic–benthic transition, is the critical point when biofouling begins. However, our understanding of the molecular mechanisms of larval settlement is limited. In our previous studies, we identified that the AMP-activated protein kinase-silk gland factor 1 (AMPK-SGF1) pathway was involved in triggering the larval settlement in the fouling mussel M. sallei. In this study, to further confirm the pivotal role of SGF1, multiple targeted binding compounds of SGF1 were obtained using high-throughput virtual screening. It was found that the targeted binding compounds, such as NAD⁺ and atorvastatin, could significantly induce and inhibit the larval settlement, respectively. Furthermore, the qRT-PCR showed that the expression of the foot proteins’ genes was significantly increased after the exposure to 10 μM NAD⁺, while the gene expression was significantly suppressed after the exposure to 10 μM atorvastatin. Additionally, the production of the byssus threads of the adults was significantly increased after the exposure to 10–20 μM of NAD⁺, while the production of the byssus threads was significantly decreased after the exposure to 10–50 μM of atorvastatin. This work will deepen our understanding of SGF1 in triggering the larval settlement in mussels and will provide insights into the potential targets for developing novel antifouling agents. Full article

Driven by technological advances in various fields (AI, 5G, VR, IoT, etc.) together with the emergence of digital twins technologies (HDT, HAL, BIM, etc.), the Metaverse has attracted growing attention from scientific and industrial communities. This interest is due to its potential impact on people lives in different sectors such as education or medicine. Specific solutions can also increase inclusiveness of people with disabilities that are an impediment to a fulfilled life. However, security and privacy concerns remain the main obstacles to its development. Particularly, the data involved in the Metaverse can be comprehensive with enough granularity to build a highly detailed digital copy of the real world, including a Human Digital Twin of a person. Existing security countermeasures are largely ineffective and lack adaptability to the specific needs of Metaverse applications. Furthermore, the virtual worlds in a large-scale Metaverse can be highly varied in terms of hardware implementation, communication interfaces, and software, which poses huge interoperability difficulties. This paper aims to analyse the risks and opportunities associated with adopting digital replicas of humans (HDTs) within the Metaverse and the challenges related to managing digital identities in this context. By examining the current technological landscape, we identify several open technological challenges that currently limit the adoption of HDTs and the Metaverse. Additionally, this paper explores a range of promising technologies and methodologies to assess their suitability within the Metaverse context. Finally, two example scenarios are presented in the Medical and Education fields. Full article

Utilization of fish rest raw material for fish oil extraction has received interest with the increasing demand for sustainable food sources. Enzymatic hydrolysis is an efficient method for the extraction of value-added compounds, but its effectiveness may be enhanced by high-pressure processing (HPP). However, HPP can induce lipid oxidation, affecting the quality of the oil. This study aimed to evaluate the quality of fish oil obtained after enzymatic hydrolysis of a mixture of rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) rest raw material pretreated by HPP. Six pretreatments were tested prior to enzymatic hydrolysis; 200 MPa × 4 min, 200 MPa × 8 min, 400 MPa × 4 min, 400 MPa × 8 min, 600 MPa × 4 min, and 600 MPa × 8 min. The oil samples were analyzed for lipid oxidation parameters, free fatty acid content, fatty acid composition, and color changes over 8 weeks. The results confirmed that HPP may induce lipid oxidation and revealed significant influence of HPP parameters on lipid oxidation, with higher pressures leading to increased oxidation. Fatty acid composition varied among samples, but it was not substantially affected by HPP. Full article

Small-scale farmers in sub-Saharan Africa (SSA) need to adopt and consistently practice sustainable agriculture to ensure sustainable livelihoods and food security. However, the adverse effects of climate change are threatening the achievement of this goal. Therefore, farmers within the sub-region need to embrace climate-smart agriculture (CSA) as a means for climate change adaptation and mitigation. This study was conducted to understand, on the one hand, how smart farming technologies are being promoted in sub-Saharan Africa, and on the other hand, how farmers are adopting the prevailing technologies. The Preferred Reporting Items for Systematic Reviews (PRISMA) procedures were followed to identify 48 scientific papers in sub-Saharan Africa. It was found that promoters of smart farming technologies in sub-Saharan Africa include CGSpace, FAO, National Research Institutions, individual researchers, local institutions, and private institutions. The approach to the smart farming technology discourse in sub-Saharan Africa starts by building on efforts to sustain CSA practices with a gradual shift towards the fourth agriculture revolution innovations. Even where there are efforts to push beyond conventional CSA practices by the private sector, farmers’ responses are still low. It is recommended that any intervention to promote modern smart farming technologies to smallholders should build on conventional CSA practices. Full article

The high-speed railway subgrade compaction quality is controlled by the compaction degree (K), with the maximum dry density (ρ_dmax) serving as a crucial indicator for its calculation. The current mechanisms and methods for determining the ρ_dmax still suffer from uncertainties, inefficiencies, and lack of intelligence. These deficiencies can lead to insufficient assessments for the high-speed railway subgrade compaction quality, further impacting the operational safety of high-speed railways. In this paper, a novel method for full-section assessment of high-speed railway subgrade compaction quality based on ML-interval prediction theory is proposed. Firstly, based on indoor vibration compaction tests, a method for determining the ρ_dmax based on the dynamic stiffness K_rb turning point is proposed. Secondly, the Pso-OptimalML-Adaboost (POA) model for predicting ρ_dmax is determined based on three typical machine learning (ML) algorithms, which are back propagation neural network (BPNN), support vector regression (SVR), and random forest (RF). Thirdly, the interval prediction theory is introduced to quantify the uncertainty in ρ_dmax prediction. Finally, based on the Bootstrap-POA-ANN interval prediction model and spatial interpolation algorithms, the interval distribution of ρ_dmax across the full-section can be determined, and a model for full-section assessment of compaction quality is developed based on the compaction standard (95%). Moreover, the proposed method is applied to determine the optimal compaction thicknesses (H₀), within the station subgrade test section in the southwest region. The results indicate that: (1) The PSO-BPNN-AdaBoost model performs better in the accuracy and error metrics, which is selected as the POA model for predicting ρ_dmax. (2) The Bootstrap-POA-ANN interval prediction model for ρ_dmax can construct clear and reliable prediction intervals. (3) The model for full-section assessment of compaction quality can provide the full-section distribution interval for K. Comparing the H₀ of 50~60 cm and 60~70 cm, the compaction quality is better with the H₀ of 40~50 cm. The research findings can provide effective techniques for assessing the compaction quality of high-speed railway subgrades. Full article

The use of biodegradable paper pulp pots has been gaining traction, especially among environmentally conscious consumers and horticultural practitioners who prioritize sustainability. The choice between paper pulp and polyethylene nursery pots in horticultural practices is a complex decision, involving considerations such as environmental impact, cost-effectiveness, durability, and overall sustainability. This study aims to provide practical insights into the comparative performance of paper pulp and polyethylene pots, specifically in terms of plant health, degradation, and techno-economic considerations. The study involved the growth performance assessment of four plant species, Cannonball Tomato, Celebrity Tomato, Parris Island Lettuce, and French Marigold, in a greenhouse experiment setup. Additionally, a degradation analysis was conducted to determine the average degradation rate and pattern. Finally, a techno-economic analysis compared the value of plant health and degradation with the market price. By evaluating the quality performance aspects of paper pulp pots, this study not only provides valuable insights but also identifies potential areas of improvement for other biodegradable pots, thereby contributing to the ongoing efforts to promote sustainable horticultural practices. Full article

The cancer stem cell (SC) theory proposes that a population of SCs serves as the driving force behind fundamental tumor processes, including metastasis, recurrence, and resistance to therapy. The standard of care for patients with stage III and high-risk stage II colorectal cancer (CRC) includes surgery and adjuvant chemotherapy. Fluoropyrimidines and their combination with oxaliplatin increased the cure rates, being able to eradicate the occult metastatic SC in a fraction of patients. The treatment for unresectable metastatic CRC is based on chemotherapy, antibodies to VEGF and EGFR, and tyrosine-kinase inhibitors. Immunotherapy is used in MSI-H tumors. Currently used drugs target dividing cells and, while often effective at debulking tumor mass, these agents have largely failed to cure metastatic disease. SCs are generated either due to genetic and epigenetic alterations in stem/progenitor cells or to the dedifferentiation of somatic cells where diverse signaling pathways such as Wnt/β-catenin, Hedgehog, Notch, TGF-β/SMAD, PI3K/Akt/mTOR, NF-κB, JAK/STAT, DNA damage response, and Hippo-YAP play a key role. Anti-neoplastic treatments could be improved by elimination of SCs, becoming an attractive target for the design of novel agents. Here, we present a review of clinical trials assessing the efficacy of targeted treatment focusing on these pathways in CRC. Full article

Liquid-phase adsorption technology has been widely applied to address environmental problems related to the removal of pollutants from aqueous streams. Simple and effective methods for determining mass transfer parameters, including intra-particle and fluid-to-solid film resistances, are crucial for designing adsorption processes. The efficient simplified diffusion technique (ES technique), based on a completely mixed batch reactor (CMBR), is proposed in this study to address these needs. In this study, we compare three diffusivity (Ds) determination methods: the rigorous diffusion technique (R technique), the simplified diffusion technique (S technique), and the ES technique. Although the simulation results from the R technique are excellent, it is a very complicated and time-consuming approach that is not convenient for practical use. The S technique provides a much simpler approach, but its results are only valid in cases where the contribution of fluid film resistance is negligible (Biot number > 40). The ES technique proposed in this study can overcome those limitations. The estimation errors of the ES technique are significantly smaller than that of the S technique when compared with the R technique. The proposed ES technique would be very useful for field applications to determine diffusivity for aqueous adsorption systems. Full article

This paper aims to simplify the application of optical coherence tomography (OCT) for the examination of subsurface morphology in the oral cavity and reduce barriers towards the adoption of OCT as a biopsy guidance device. The aim of this work was to develop automated software tools for the simplified analysis of the large volume of data collected during OCT. Imaging and corresponding histopathology were acquired in-clinic using a wide-field endoscopic OCT system. An annotated dataset (n = 294 images) from 60 patients (34 male and 26 female) was assembled to train four unique neural networks. A deep learning pipeline was built using convolutional and modified u-net models to detect the imaging field of view (network 1), detect artifacts (network 2), identify the tissue surface (network 3), and identify the presence and location of the epithelial–stromal boundary (network 4). The area under the curve of the image and artifact detection networks was 1.00 and 0.94, respectively. The Dice similarity score for the surface and epithelial–stromal boundary segmentation networks was 0.98 and 0.83, respectively. Deep learning (DL) techniques can identify the location and variations in the epithelial surface and epithelial–stromal boundary in OCT images of the oral mucosa. Segmentation results can be synthesized into accessible en face maps to allow easier visualization of changes. Full article

The oasis serves as the primary supply of cultivable land, along with the hub for human production and habitation in Xinjiang. Accordingly, predicting the land use of these areas based on various goals is an effective instrument for encouraging the sensible distribution of resource space. The study investigated the creation of a land use-allocation optimization model based on the various objectives of ecological protection, food security, and urban growth using the Weigan–Kuche River oasis as an example. The GMOP-PLUS model’s restriction conversion area was adjusted to include the findings of the land suitability evaluation. Additionally, it optimized and simulated the spatial arrangement and quantitative structure of land usage in the Weigan–Kuche River oasis in 2035. The results indicate the following: (1) the model’s overall accuracy is 89.36%, and its Kappa coefficient is 0.872, more than 0.8. Thus, the model can be considered for adoption in the future when predicting changes in land use in the districts and counties of the Weigan–Kuche River oasis; (2) based on the results of the land suitability evaluation, the percentage of areas that are most suited for agricultural development, urban development, and ecological protection is 39.32%, 24.21%, and 14.06%, respectively; and (3) the three scenarios satisfy the various demands for growth within the oasis, and the land use structure of the oasis varies considerably in response to the various development objectives, with the construction and cultivated land undergoing the most substantial modifications. The multi-scenario simulation of land usage in the oasis can provide essential support and a range of perspectives for future land spatial planning and socioeconomic development decision-making in the Weigan–Kuche River oasis. This is essential for both the efficient use of land resources and sustainable development. Full article

The host’s physiological well-being is intricately associated with the gut microbiota. However, previous studies regarding the intestinal microbiota have focused on domesticated or captive birds. This study used high-throughput sequencing technology to identify the gut bacterial communities of sympatric bean geese, hooded cranes, and domestic geese. The results indicated that the gut bacterial diversity in domestic geese and hooded cranes showed considerably higher diversity than bean geese. The gut bacterial community compositions varied significantly among the three hosts (p < 0.05). Compared to the hooded crane, the bean goose and domestic goose were more similar in their genotype and evolutionary history, with less difference in the bacterial community composition and assembly processes between the two species. Thus, the results might support the crucial role of host genotypes on their gut microbiota. The gut bacteria of wild hooded cranes and bean geese had a greater capacity for energy metabolism compared to domestic geese, suggesting that wild birds may rely more on their gut microbiota to survive in cold conditions. Moreover, the intestines of the three hosts were identified as harboring potential pathogens. The relative abundance of pathogens was higher in the hooded crane compared to the other two species. The hooded crane gut bacterial community assemblage revealed the least deterministic process with the lowest filtering/selection on the gut microbiota, which might have been a reason for the highest number of pathogens result. Compared to the hooded crane, the sympatric bean goose showed the least diversity and relative abundance of pathogens. The intestinal bacterial co-occurrence network showed the highest stability in the bean goose, potentially enhancing host resistance to adverse environments and reducing the susceptibility to pathogen invasion. In this study, the pathogens were also discovered to overlap among the three hosts, reminding us to monitor the potential for pathogen transmission between poultry and wild birds. Overall, the current findings have the potential to enhance the understanding of gut bacterial and pathogenic community structures in poultry and wild birds. Full article

A methodology to study statistical properties of anomalous transport in fusion plasma is investigated. Three time traces generated by the full-f gyrokinetic code GKNET are analyzed for this purpose. The time traces consist of heat flux as a function of the radial position, which is studied in a novel manner using statistical methods. The simulation data exhibit transport processes with both medium and long correlation length along the radius. A typical example of a phenomenon with long correlation length is avalanches. In order to investigate the evolution of the turbulent state, two basic configurations are studied, one flux-driven and one gradient-driven with decaying turbulence. The information length concept in tandem with Boltzmann–Gibbs and Tsallis entropy is used in the investigation. It is found that the dynamical states in both flux-driven and gradient-driven cases are surprisingly similar, but the Tsallis entropy reveals differences between them. This indicates that the types of probability distribution function are nevertheless quite different since the higher moments are significantly different. Full article

The concept of our research is related to the use of stems from S. aromaticum L. in the fermentation process in order to obtain new cosmetic raw materials with high antioxidant potential that are safe for human fibroblasts (HDFs) and keratinocytes (HaCaTs). This evaluation involves treating cell lines with different concentrations of fermented extracts to establish a noncytotoxic dose range. The focus was on evaluating antioxidant activity (AA), total polyphenol content (TPC), and lactic acid efficiency (LA_e). For this purpose, the most favourable technological parameters of the fermentation process of stems were determined, including the type of microorganisms, initial sugar content, plant raw material content, and fermentation time. In the present study, lactic acid was obtained with maximum efficiency by stem fermentation in the presence of lactic acid bacteria (LAB) and molasses as a source of six-carbon sugars. In addition, fermentation kinetics was investigated, the essence of which was to identify the technological parameters that allow the highest values of the main functions describing the process (AA, TPC LA_e). Two kinetic models were used to determine the kinetics of process function changes during fermentation. The most favourable fermentation conditions for maximum antioxidant activity (26.88 mmol Tx/L ± 0.19), total polyphenol content (5.96 mmol GA/L ± 0.19), and lactic acid efficiency (88% ± 1) were: type of microorganism L. rhamnosus MI-0272, initial sugar content 3.20%, plant raw material content 6.40%, and a fermentation time of 9 days. The values of chelating activity (ChA), AA, and TPC in the fermented stems increased more than two-fold compared to the non-fermented extracts. Reducing activity (RA) and LA_e increased to 46.22 mmol Fe³⁺/L ± 0.29 and 88% ± 1, respectively. Of the kinetic models adopted, follow-up reaction equations and first-order equations best described the time-dependent changes taking place. This study shows that the process function values of AA and LA_e are dependent on the LAB strain and the content of the plant material, and the rate of change of TPC may largely depend on the forms of phenolic compounds formed during fermentation. Full article

Heart failure (HF) admissions are burdensome, and the mainstay of prevention is the timely detection of impending fluid retention, creating a window for medical treatment intensification. This study evaluated the accuracy and performance of a Triage-HF-guided carepath in real-world ambulatory HF patients in daily clinical practice. In this prospective, observational study, 92 adult HF patients (71 males (78%), with a median age of 69 [IQR 59–75] years) with the Triage-HF algorithm activated in their cardiac implantable electronic devices (CIEDs), were monitored. Following high-risk alerts, an HF nurse contacted patients to identify signs and symptoms of fluid retention. The sensitivity and specificity were 83% and 97%, respectively. The positive predictive value was 89%, and negative predictive value was 94%. The unexplained alert rate was 0.05 alerts/patient year, and the false negative rate was 0.11 alerts/patient year. Ambulatory diuretics were initiated or escalated in 77% of high-risk alert episodes. In 23% (n = 6), admission was ultimately required. The median alert handling time was 2 days. Fifty-eight percent (n = 18) of high-risk alerts were classified as true positives in the first week, followed by 29% in the second–third weeks (n = 9), and 13% (n = 4) in the fourth–sixth weeks. Common sensory triggers included an elevated night ventricular rate (84%), OptiVol (71%), and reduced patient activity (71%). The CIED-based Triage-HF algorithm-driven carepath enables the timely detection of impending fluid retention in a contemporary ambulatory setting, providing an opportunity for clinical action. Full article

Advertising has been one of brands’ main allies in successfully promoting their products and services, creating trends and changing consumer mindsets, which allows them to increase sales and consequently achieve commercial success. The advertising medium has been evolving, increasingly encompassing new technologies as well as expanding its areas of intervention. This research article uses the Systematic Bibliometric Literature Review methodology, and its main objective is to clarify the state of the art regarding advertising and sustainability, since if advertising is one of the main allies for the success of brands, sustainability has become one of its main strategies. The starting question is whether advertising has been used to communicate sustainability. The methodology used in this study is a systematic bibliometric literature review (LRSB) to collect, analyze and synthesize data on advertising and sustainability, and covers a period of publications from the year 2007 to 2024, with the support of visual maps of the research indexed in the Scopus Database, created with VOSViewer. The aim was to give an overview of the studies published in this scientific area. The qualitative results of the analysis suggest that the theme of sustainability has been studied and associated with brands and sectors of activity such as luxury brands. The analysis leads to the suggestion of a reduced connection between sustainability and advertising, with studies on “green advertising” being mentioned, which allows us to affirm that this is an area that requires more in-depth studies, despite the fact that these initial results, on the one hand, help professionals in the field of digital marketing to make decisions, as well as clarifying the topic from a research point of view. Full article

To study air pollution in the North China Plain (NCP), the Air Chemistry Research in Asia (ARIAs) campaign conducted airborne measurements of air pollutants in spring 2016. High pollutant concentrations, with O₃ > 100 ppbv, CO > 500 ppbv, and NO₂ > 10 ppbv, were observed. CMAQ simulations with the 2010 EDGAR emissions capture the spatial and temporal variations in ozone and its major precursors such as NO₂ and VOCs, with significant underestimation. Differences between CMAQ simulations and satellite observations reflect changes in anthropogenic emissions, decreased NO_x emissions in megacities such as Beijing, but slight increases in other cities and rural areas. CMAQ also underestimates HCHO and CO, suggesting adjustments of the 2010 EDGAR emissions are necessary. HCHO/NO₂ column ratios derived from OMI measurements and CMAQ simulations show that VOC-sensitive chemistry dominates the ozone photochemical production in eastern China, suggesting the importance of tightening regulations on anthropogenic VOC emissions. After adjusting emissions based on satellite observations, better model performance was achieved. Because of the VOC-sensitive environment in ozone chemistry over the NCP, the underestimation of anthropogenic emissions could be important for CMAQ simulations, while future study and regulations should focus on VOC emissions with continuous controls on NO_x emissions in China. Full article

Pregnant women, considered at risk of COVID-19 complications because of the immunosuppressive and physiological changes in pregnancy, were initially hesitant to receive COVID-19 vaccination. This study assessed the association between COVID-19 vaccination uptake, psychological determinants (health belief model (HBM) constructs, anticipated regret, trust in health authorities), and provider recommendation among pregnant women in Kenya. Using data from a cross-sectional study, we conducted correlations, binary and multivariable logistic regressions, and moderation analysis to explore relationships between COVID-19 vaccination and psychological variables. Of the 115 pregnant women, 64% reported receiving provider recommendations for COVID-19 vaccination. There were weak positive correlations between the variables. Participants with high anticipated regret scores were more likely to receive COVID-19 vaccination compared to their peers (AOR = 4.27; 95% CI, 1.23–14.85), while provider recommendation increased the odds of COVID-19 vaccination (OR = 3.70; 95% CI, 1.53–8.92). None of the HBM constructs were significantly associated with COVID-19 vaccination. The findings related to psychological variables require the reconceptualization of theory-informed interventions to streamline healthcare provision. The critical role of healthcare providers in COVID-19 vaccination recommendations suggests a need to empower health practitioners with effective communication skills to improve maternal health outcomes. Full article

This study explores the development of a terramechanics-based model for non-pneumatic tire–terrain interaction, focusing on different spoke designs. The research investigates how four spoke shapes (honeycomb, modified honeycomb, re-entrant honeycomb, and straight spokes) affect non-pneumatic tire performance in off-road conditions. Using the finite element method (FEM) to model non-pneumatic tires, and smoothed-particle hydrodynamics (SPH) to model dry, loose soil, simulations were conducted to replicate real-world loading conditions. This study utilizes virtual environment solution finite element analysis software to examine the interaction between a non-pneumatic tire and dry, loose soil, with a focus on calculating longitudinal and vertical forces. These forces play a pivotal role in determining the motion resistance coefficient. The results show distinct variations in the motion-resistance coefficients among the spoke designs on dry, loose soil. This analysis helps to identify the spoke configurations that optimize energy efficiency and fuel consumption. By comparing and evaluating the four spoke designs, this study shows the effect of spoke design on tire motion resistance. This study concluded that the modified honeycomb spoke design is the most stable and the least sensitive to operating conditions. Full article

Purpose: Uterine carcinosarcomas are highly aggressive tumors of the endometrium and are associated with a poor prognosis. The optimal adjuvant treatment for both early and advanced-stage patients remains unclear. Methods: Cases of uterine carcinosarcoma were identified in our institution’s pathology database between 2000 and 2022. Kaplan–Meier estimates were calculated for the local and distant recurrence-free, disease-free and overall survival; hazard ratios were calculated using Cox proportional hazards modelling for independent prognostic factors including the stage and treatment. Results: A total of 48 patients were identified as having uterine carcinosarcoma, of whom 70.8% were surgically staged. In total, 43 patients had pelvic-confined disease, while five had positive omental or peritoneal biopsies at surgery. There were 10 pelvic (20.8%) and 19 (39.6%) distant recurrences. None of the patients with stage IA disease who received chemotherapy and brachytherapy experienced disease recurrence. The local recurrence-free survival was 54.95%, the distant recurrence-free survival was 44.7%, and the overall survival was 59.6% at 5 years. Local recurrence-free survival and overall survival were inversely associated with advanced-stage OR 1.23 (p = 0.005) and OR 1.28 (p = 0.017), respectively, and no chemotherapy was associated with OR 1.96 (p = 0.06) and OR 2.08 (p = 0.056), respectively. Conclusion: The local and distant recurrence rates were high for advanced=stage patients even when treated with aggressive adjuvant therapy regimens. Chemotherapy may improve recurrence and survival. Early-stage patients may perform well with vaginal vault brachytherapy and chemotherapy. Further prospective comparisons are required between sequential, sandwich, and concurrent approaches to chemotherapy and radiotherapy, to optimize outcomes in this high-risk population. Full article

In the context of increasing online health misinformation, several new approaches have been deployed to reduce the spread and increase the quality of information consumed. This systematic review examines how source credibility labels and other nudging interventions impact online health information choices. PubMed, Embase, Scopus, and Web of Science were searched for studies that present empirical evidence on the impact of interventions designed to affect online health-information-seeking behavior. Results are mixed: some interventions, such as content labels identifying misinformation or icon arrays displaying information, proved capable of impacting behavior in a particular context. In contrast, other reviewed strategies around signaling the source’s credibility have failed to produce significant effects in the tested circumstances. The field of literature is not large enough to draw meaningful conclusions, suggesting that future research should explore how differences in design, method, application, and sources may affect the impact of these interventions and how they can be leveraged to combat the spread of online health misinformation. Full article

The combined application of Cathodoluminescence (CL) with Scanning Electron Microscopy (SEM) on paintings and painted surfaces has the potential to identify both organic and inorganic pigments on a micrometre or even nanometre scale. Additionally, the combination with Energy-Dispersive Spectrometry (EDS) allows for a more holistic, elemental, and mineralogical characterization of pigments. In addressing the need for the creation of a robust, open access database of characteristic CL spectra of pigments, a large project has been undertaken, focusing primarily on common organic and inorganic pigments. The present paper focuses on the CL characterization of 10 significant blue pigments in pure powder form: cerulean blue, Egyptian blue, Han blue, indigo, lapis lazuli, Maya blue, phthalo blue, vivianite, ultramarine blue, and zirconium blue. The CL spectra present characteristic bands for most of the pigments, allowing their secure identification, especially when combining the results with the EDS analyses. The effect of binding media and of the mixture of different pigments was also studied, via the analysis of mixtures of pigments with oil painted over canvas. Overall, both the binding medium and the mixture of pigments do not appear to create significant differences in the occurring spectra, thus allowing the identification of individual pigments. EDS and RAMAN spectra are included in order to facilitate comparison with other databases. Full article

This is a systematic literature review of the application of machine learning (ML) algorithms in geosciences, with a focus on environmental monitoring applications. ML algorithms, with their ability to analyze vast quantities of data, decipher complex relationships, and predict future events, and they offer promising capabilities to implement technologies based on more precise and reliable data processing. This review considers several vulnerable and particularly at-risk themes as landfills, mining activities, the protection of coastal dunes, illegal discharges into water bodies, and the pollution and degradation of soil and water matrices in large industrial complexes. These case studies about environmental monitoring provide an opportunity to better examine the impact of human activities on the environment, with a specific focus on water and soil matrices. The recent literature underscores the increasing importance of ML in these contexts, highlighting a preference for adapted classic models: random forest (RF) (the most widely used), decision trees (DTs), support vector machines (SVMs), artificial neural networks (ANNs), convolutional neural networks (CNNs), principal component analysis (PCA), and much more. In the field of environmental management, the following methodologies offer invaluable insights that can steer strategic planning and decision-making based on more accurate image classification, prediction models, object detection and recognition, map classification, data classification, and environmental variable predictions. Full article