The current literature considers agritourism as a valid option for promoting the development of rural areas. This would be achieved by increasing agricultural incomes. However, numerous scientific studies have revealed the difficulty in reaching a consensus on the very concept of agritourism. In addition, the definition of agritourism is rarely related to the opinion of the demand. For this reason, this research aimed to understand the idea that tourists have about this variety. To this end, more than 500 surveys were carried out, from which the tourists’ conception of agritourism and the activities it entails were deduced. Other questions were also analyzed to determine whether the conception varies between those who have already performed this type of activity and those who have not yet had the opportunity to do so. From this, we can deduct the interest that visitors have in agritourism products, evidencing their potential. This interest is deduced through the visualization of different landscapes and activities of interest to tourists. Under these four central points, the aim was to understand the aims of agritourism in Extremadura (Spain). At the methodological level, a combination of descriptive statistics and spatial statistics was used, highlighting the use of cluster analysis. The results show a significant lack of knowledge of the meaning of agritourism, especially among those who have never practiced it, and of the activities associated with it. At the same time, the selection of landscapes preferred by tourists makes it possible to establish areas with potential for the development of these activities. Likewise, knowing which activities are of interest to tourists also helps to generate complementary activities and to better target the design of agrotourism products. Full article

The damage properties in the shear-punched surface layer, such as the strain-hardening increment, strain-induced martensite fraction, and initiated micro-crack/void characteristics at the shear and break sections, were experimentally evaluated to relate to the stretch-flangeability in three types of low-carbon high-strength TRIP-aided steel with different matrix structures. In addition, the surface layer damage properties were related to the mean normal stress developed on shear-punching and microstructural properties. The shear-punched surface damage of these steels was experimentally confirmed to be produced under the mean normal stress of negative to 0 MPa. TRIP-aided bainitic ferrite (TBF) steel had the smallest surface layer damage, featuring a significantly suppressed micro-crack/void initiation. This was due to the fine bainitic ferrite lath matrix structure, a low strength ratio of the second phase to the matrix structure, and the high mechanical stability of the retained austenite. On the other hand, the surface layer damage of TRIP-aided annealed martensite (TAM) steel was suppressed next to TBF steel and was smaller than that of TRIP-aided polygonal ferrite (TPF) steel. The surface layer damage was also characterized by a large plastic strain, a large amount of strain-induced martensite transformation, and a relatively suppressed micro-crack/void formation, which resulted from an annealed martensite matrix and a large quantity of retained austenite. The excellent stretch-flangeability of TBF steel might be caused by the suppressed micro-crack/void formation and high crack propagation/void connection resistance. The next high stretch-flangeability of TAM steel was associated with a small-sized micro-crack/void initiation and high crack growth/void connection resistance. Full article

The three-dimensional (3D) low-frequency lightning mapping system (LF-LMS) in north China has been updated. The lightning electric field derivative (dE/dt) sensor and continuous acquisition mode has been newly designed to ensure a capability of entire lightning processes detection, especially weak discharges during lightning the initiation process. The twice cross-correlation delay estimation and the grid iteration nested optimization location algorithm are used to realize the 3D location of the discharge channel, and the location resolution and calculation speed are balanced consequently. The location results of the rocket-triggered lightning demonstrated that the system achieved a high-resolution mapping of lightning discharge channels, which coincided well with the optical images. The horizontal and vertical location error for rocket triggered lightning was less than 40 m in both horizontal and vertical. Intracloud (IC) lightning flashes were observed to be initiated by three different discharge processes, initial breakdown pulse (IBP), narrow bipolar event (NBE), and initial E-change (IEC). The corresponding initial height was 10.5 km, 6.9 km, and 9.2 km, respectively. The upward negative leader was initially located, followed by scatter radiation sources and negative recoil leaders in the lower negative charge region for all cases. The electric field characteristics of the IEC and subsequent IBPs indicated that they are different discharge processes with the same current direction. The IEC process might correspond to the discharge process with continuous current and less noticeable current changes. Full article

Background: Fever is one of the most frequent symptoms highlighted during medical assistance. Due to this great impact, our study has the purpose of analyzing the demographic and laboratory characteristics of patients hospitalized in our center and identifying predictive markers to make the differential diagnosis between infectious and non-infectious fever. Methods: Our population included 220 children, collected from January 2017 to August 2022, hospitalized for continuous fever (4 days or more in duration with at least one temperature peak ≥37.5 °C) and excluded cases of discharge against medical advice and/or transfer to other operating units. Demographic (mean age at the time of admission, frequency of hospitalization, and mean days of hospitalization), laboratory, and instrumental variables were analyzed in order to find correlation with fever etiology. Results: Older age at the time of hospitalization, family history of periodic fever, fever lasting more than 8 days, and longer hospitalization are strongly associated with non-infectious fever, together with anemia, high platelet count, high CRP and ferritin, and hyponatremia at the time of admission. Paracetamol is the preferred antipyretic treatment. Echocardiogram has shown anomalies in patients with infectious fever, while ECG anomalies were detected in non-infectious fever. Conclusions: Our data underline the importance of predictive markers, such as clinical and laboratory parameters, to differentiate infectious from non-infectious fevers, but further studies are necessary. Full article

This research investigates flood susceptibility in the mid- and downstream areas of Taiwan’s Wu River, historically prone to flooding in central Taiwan. The study integrates the Hydrologic Engineering Center—Hydrologic Modeling System (HEC-HMS) for flow simulations with unmanned aerial vehicle (UAV)-derived digital surface models (DSMs) at varying resolutions. Flood simulations, executed through the International River Interface Cooperative (iRIC), assess flood depths using diverse DSM resolutions. Notably, HEC-HMS simulations exhibit commendable Nash–Sutcliffe efficiency (NSE) exceeding 0.88 and a peak flow percentage error (PEPF) below 5%, indicating excellent suitability. In iRIC flood simulations, optimal results emerge with a 2 m resolution UAV-DSM. Furthermore, the study incorporates rainfall data at different recurrence intervals in iRIC flood simulations, presenting an alternative flood modeling approach. This research underscores the efficacy of integrating UAV-DSM into iRIC flood simulations, enabling precise flood depth assessment and risk analysis for flood control management. Full article

Cotton Verticillium wilt is a common fungal disease during the growth of cotton, leading to the yellowing of leaves, stem dryness, and root rot, severely affecting the yield and quality of cotton. Current monitoring methods for Verticillium wilt mainly rely on manual inspection and field investigation, which are inefficient and costly, and the methods of applying pesticides in cotton fields are singular, with issues of low pesticide efficiency and uneven application. This study aims to combine UAV remote sensing monitoring of cotton Verticillium wilt with the precision spraying characteristics of agricultural drones, to provide a methodological reference for monitoring and precision application of pesticides for cotton diseases. Taking the cotton fields of Shihezi City, Xinjiang as the research subject, high-resolution multispectral images were collected using drones. Simultaneously, 150 sets of field samples with varying degrees of Verticillium wilt were collected through ground data collection, utilizing data analysis methods such as partial least squares regression (PLSR) and neural network models; additionally, a cotton Verticillium wilt monitoring model based on drone remote sensing images was constructed. The results showed that the estimation accuracy of the PLSR and BP neural network models based on EVI, RENDVI, SAVI, MSAVI, and RDVI vegetation indices were 0.778 and 0.817, respectively, with of 0.126 and 0.117, respectively. Based on this, an analysis of the condition of the areas to be treated was performed, combining the operational parameters of agricultural drones, resulting in a prescription map for spraying against cotton Verticillium wilt. Full article

Renewable hydrogen is emerging as the key to a sustainable energy transition with multiple applications and uses. In the field of transport, in addition to fuel cell vehicles, it is necessary to develop an extensive network of hydrogen refueling stations (hereafter HRSs). The characteristics and properties of hydrogen make ensuring the safe operation of these facilities a crucial element for their successful deployment and implementation. This paper shows the outcomes of an analysis of hydrogen incidents and accidents considering their potential application to HRSs. For this purpose, the HIAD 2.0 was reviewed and a total of 224 events that could be repeated in any of the major industrial processes related to hydrogen refueling stations were analyzed. This analysis was carried out using a mixed methodology of quantitative and qualitative techniques, considering the following hydrogen value chain: production, storage, delivery and industrial use. The results provide general information segmented by event frequency, damage classes and failure typology. The analysis shows the main processes of the value chain allow the identification of key aspects for the safety management of refueling facilities. Full article

The propagation of Crocus sativus L. relies exclusively on corm multiplication. As underground storage organs, corms are susceptible to a wide range of pathogens, environmental stresses, and diseases, making traditional propagation methods often ineffective with the loss of valuable material. In vitro propagation offers an alternative for the saffron culture under controlled conditions. In particular, the innovative application of the Temporary Immersion System (TIS) represents a technological advancement for enhancing biomass production with a reduction in operational costs. The current study utilized the Plantform™ bioreactor to propagate in vitro saffron corms from the ‘Abruzzo’ region (Italy), integrating machine learning models to assess its performance. The evaluation of saffron explants after 30, 60, and 90 days of culture showed a marked improvement in growth and microcorm production compared to conventional in vitro culture on semisolid medium, supported by the machine learning analysis. Indeed, the Random Forest algorithm revealed a predictive accuracy with an R² value of 0.81 for microcorm number, showcasing the capability of machine learning models to forecast propagation outcomes effectively. These results confirm that applying TIS in saffron culture could lead to economically viable, large biomass production within a controlled environment, irrespective of seasonality. This study represents the first endeavor to use TIS technology to enhance the in vitro propagation of saffron in conjunction with machine learning, suggesting an innovative approach for cultivating high-value crops like saffron. Full article

We introduce a quasi-solid-state electrolyte lithium-sulfur (Li–S) battery (QSSEB) based on a novel Li-argyrodite solid-state electrolyte (SSE), Super P–Sulfur cathode, and Li-anode. The cathode was prepared using a water-based carboxymethyl cellulose (CMC) solution and styrene butadiene rubber (SBR) as the binder while Li₆PS₅F_0.5Cl_0.5 SSE was synthesized using a solvent-based process, via the introduction of LiF into the argyrodite crystal structure, which enhances both the ionic conductivity and interface-stabilizing properties of the SSE. Ionic liquids (IL) were prepared using lithium bis(trifluoromethyl sulfonyl)imide (LiTFSI) as the salt, with pre-mixed pyrrolidinium bis(trifluoromethyl sulfonyl)imide (PYR) as solvent and 1,3-dioxolane (DOL) as diluent, and they were used to wet the SSE–electrode interfaces. The effect of IL dilution, the co-solvent amount, the LiTFSI concentration, the C rate at which the batteries are tested and the effect of the introduction of SSE in the cathode, were systematically studied and optimized to develop a QSSEB with higher capacity retention and cyclability. Interfacial reactions occurring at the cathode–SSE interface during cycling were also investigated using electrochemical impedance spectroscopy, cyclic voltammetry, and X-ray photoelectron spectroscopy supported by ab initio molecular dynamics simulations. This work offers a new insight into the intimate interfacial contacts between the SSE and carbon–sulfur cathodes, which are critical for improving the electrochemical performance of quasi-solid-state lithium–sulfur batteries. Full article

The safety and well-being of learners with special educational needs in South Africa remain a paramount concern, significantly impacting their constitutional rights and dignity. Despite legislative commitments aimed at fostering inclusive education, a pervasive absence of adequate fire safety measures in special needs schools (SNSs) in South Africa has persisted, leading to the vulnerability of these learners. Tragic incidents, such as fatal fires in these schools, as reported in the literature, underscore the urgent need for immediate intervention to ensure the safety and security of these learners, especially with regards to fire hazards. This study, conducted within the Northwest Province of South Africa, assessed the state of fire safety management in SNSs by applying a series of chi-squared (χ²) tests of independence for categorical variables, descriptive statistics, and regression analysis using the Statistical Package for Social Scientists (SPSS), Version 20 and found that limited access to power is the potential root cause of fires in these schools; also, the limited amount of fire safety initiatives was a problem. In addition, the ordinal regression showed a statistically significant relationship when the question of to what extent the learners in the sampled schools are involved in fire safety programs was regressed with the questions of whether management and stakeholders were involved in fire safety programs and also on taking part in the physical fire safety programs (χ² = 47.412; df = 2; p < 0.001; R² = 70.5%). Furthermore, fire safety management was not sufficiently implemented in the sampled schools and the safety legislations of the country were not implemented accordingly when it came to fire safety. This study identified root causes of fire risks, gauged stakeholders’ awareness and involvement in fire safety management, and advocated for more stringent safety policies and practices within the SNS based on the above findings. Full article

Berries have been gaining in popularity among consumers and producers due to their natural bioactive compounds that have beneficial effects on human health. This review aimed to identify effective techniques for the extraction of bioactive compounds from berries, consolidate the findings of recent studies using various extraction technologies, and provide a global perspective on the research trends in this field. These extraction techniques include pulsed electric field, ultrasound-assisted extraction, pressurized liquid extraction, microwave-assisted extraction, and supercritical CO₂ extraction. The solid waste generated during the industrial berry juice production process is assumed to be a less expensive source of raw materials for the natural extraction of bioactive compounds. The main aim of modern techniques is to produce more of the desired compound and find a method to extract bioactive compounds from berries without the use of hazardous solvents. These include flavonoids, phenols, anthocyanins, and antioxidants. Regarding the characterization of the bioactive compounds that are isolated from berries, aspects such as scanning electron microscopy, X-ray powder diffraction, Fourier transform infrared spectroscopy, and nuclear magnetic resonance were reviewed. Full article

Bi₂S₃ has gained considerable attention as a semiconductor for its versatile functional properties, finding application across various fields, and liquid phase exfoliation (LPE) serves as a straightforward method to produce it in nano-form. Till now, the commonly used solvent for LPE has been N-Methyl-2-pyrrolidone, which is expensive, toxic and has a high boiling point. These limitations drive the search for more sustainable alternatives, with water being a promising option. Nonetheless, surfactants are necessary for LPE in water due to the hydrophobic nature of Bi₂S₃, and organic molecules with amphoteric characteristics are identified as suitable surfactants. However, systematic studies on the use of ionic surfactants in the LPE of Bi₂S₃ have remained scarce until now. In this work, we used sodium dodecyl sulfate (SDS), sodium dodecylbenzene sulfonate (SDBS) and sodium hexadecyl sulfonate (SHS) as representative species and we present a comprehensive investigation into their effects on the LPE of Bi₂S₃. Through characterizations of the resulting products, we find that all surfactants effectively exfoliate Bi₂S₃ into few-layer species. Notably, SDBS demonstrates superior stabilization of the 2D layers compared to the other surfactants, while SHS becomes the most promising surfactant for obtaining products with high yield. Moreover, the resulting nano-inks are used for fabricating films using spray-coating, reaching a fine tuning of band gap by controlling the number of cycles, and paving the way for the utilization of 2D Bi₂S₃ in optoelectronic devices. Full article

The mold Aspergillus fumigatus employs two high-affinity uptake systems, reductive iron assimilation (RIA) and siderophore-mediated iron acquisition (SIA), for the acquisition of the essential trace element iron. SIA has previously been shown to be crucial for virulence in mammalian hosts. Here, we show that a lack of AcuK or AcuM, transcription factors required for the activation of gluconeogenesis, decreases the production of both extra- and intracellular siderophores in A. fumigatus. The lack of AcuM or AcuK did not affect the expression of genes involved in RIA and SIA, suggesting that these regulators do not directly regulate iron homeostasis genes, but indirectly affect siderophore production through their influence on metabolism. Consistent with this, acetate supplementation reversed the intracellular siderophore production defect of ΔacuM and ΔacuK. Moreover, ΔacuM and ΔacuK displayed a similar growth defect under iron limitation and iron sufficiency, which suggests they have a general role in carbon metabolism apart from gluconeogenesis. In agreement with a potential role of the glyoxylate cycle in adaptation to iron starvation, transcript levels of the malate synthase-encoding acuE were found to be upregulated by iron limitation that is partially dependent on AcuK and AcuM. Together, these data demonstrate the influence of iron availability on carbon metabolism. Full article

Background and Aims: Accurate recognition of endoscopic instruments facilitates quantitative evaluation and quality control of endoscopic procedures. However, no relevant research has been reported. In this study, we aimed to develop a computer-assisted system, EndoAdd, for automated endoscopic surgical video analysis based on our dataset of endoscopic instrument images. Methods: Large training and validation datasets containing 45,143 images of 10 different endoscopic instruments and a test dataset of 18,375 images collected from several medical centers were used in this research. Annotated image frames were used to train the state-of-the-art object detection model, YOLO-v5, to identify the instruments. Based on the frame-level prediction results, we further developed a hidden Markov model to perform video analysis and generate heatmaps to summarize the videos. Results: EndoAdd achieved high accuracy (>97%) on the test dataset for all 10 endoscopic instrument types. The mean average accuracy, precision, recall, and F1-score were 99.1%, 92.0%, 88.8%, and 89.3%, respectively. The area under the curve values exceeded 0.94 for all instrument types. Heatmaps of endoscopic procedures were generated for both retrospective and real-time analyses. Conclusions: We successfully developed an automated endoscopic video analysis system, EndoAdd, which supports retrospective assessment and real-time monitoring. It can be used for data analysis and quality control of endoscopic procedures in clinical practice. Full article

Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate disease diagnosis and progression assessment. However, acquiring high-quality annotated data at the pixel level poses a significant challenge due to the resource-intensive nature of this process. This scarcity of high-quality annotated data results in few-shot scenarios, which are highly prevalent in clinical applications. To address this obstacle, this paper introduces Agent-Guided SAM (AGSAM), an innovative approach that transforms the Segment Anything Model (SAM) into a fully automated segmentation method by automating prompt generation. Capitalizing on the pre-trained feature extraction and decoding capabilities of SAM-Med2D, AGSAM circumvents the need for manual prompt engineering, ensuring adaptability across diverse segmentation methods. Furthermore, the proposed feature augmentation convolution module (FACM) enhances model accuracy by promoting stable feature representations. Experimental evaluations demonstrate AGSAM’s consistent superiority over other methods across various metrics. These findings highlight AGSAM’s efficacy in tackling the challenges associated with limited annotated data while achieving high-quality medical image segmentation. Full article

This research investigates the suitability of printed polyamide 12 (PA12) and its dyed version to support cells in bioengineering applications. For this purpose, human gingival fibroblasts (hGF06) were cultured on PA-12 scaffolds that were 3D-printed by Multi Jet Fusion (MJF). The study examined the direct cultivation of cells on MJF-printed cell culture scaffolds and the effect of leachate of PA-12 printed by MJF on the cultured cells. The article presents research on the surface treatment of PA12 material used in 3D printing and the effect of automatic staining on cell vitality and proliferation in vitro. The study presents a unique device designed exclusively for staining prints made of the biocompatible material PA12 and demonstrates the compatibility of 3D-printed polyamide 12 parts stained in the novel device with a nutrient culture medium and cells. This novel PA12 surface treatment for biomedical purposes does not affect the compatibility with the culture medium, which is essential for cell viability and proliferation. Fluorescence microscopy revealed that mitochondrial fitness and cell survival were not affected by prolonged incubation with clear or dyed PA12 3D-printed parts. Full article

Aim: This study aimed to compare the torque loss, fracture load, compressive strength, and failure types of selective-laser-sintered cobalt chromium (SLM-Co-Cr), computer-aided design and computer-aided manufacturing zirconium oxide (CAD-CAM-ZrO), and machined titanium (Ti) implant abutments. Methods: Thirty endosseous dental implants were vertically embedded with machined Ti (control group), CAD-CAM-ZrO, and SLM-Co-Cr abutments. Abutment fabrication involved CAD-CAM milling and SLM technology. The de-torque assessment included preload reverse torque values (RTVs), cyclic loading, and post-RTVs using a customized protocol. Fracture load assessment employed ISO-14801 standards, and statistical analysis was conducted using ANOVA and Tukey Post hoc tests (p < 0.05). Results: In pre-load RTVs, SLM-Co-Cr showed the lowest mean torque loss (24.30 ± 2.13), followed by machined Ti (27.33 ± 2.74) and CAD-CAM-ZrO (22.07 ± 2.20). Post-load RTVs decreased for all groups. Fracture load and compressive strength were highest for SLM-Co-Cr, with significant differences among groups (p < 0.001). Fracture types included abutment failures in SLM-Co-Cr and machined Ti, while CAD-CAM-ZrO exhibited crown separation with deformation. Conclusion: SLM-Co-Cr-fabricated implant abutments exhibited superior stability and resistance to rotational forces, higher fracture loads, and greater compressive strength compared to CAD-CAM-ZrO and machined Ti. Full article

The field of peripheral nerve regeneration is a dynamic and rapidly evolving area of research that continues to captivate the attention of neuroscientists worldwide. The quest for effective treatments and therapies to enhance the healing of peripheral nerves has gained significant momentum in recent years, as evidenced by the substantial increase in publications dedicated to this field. This surge in interest reflects the growing recognition of the importance of peripheral nerve recovery and the urgent need to develop innovative strategies to address nerve injuries. In this context, this article aims to contribute to the existing knowledge by providing a comprehensive review that encompasses both biomaterial and clinical perspectives. By exploring the utilization of nerve guidance conduits and pharmacotherapy, this article seeks to shed light on the remarkable advancements made in the field of peripheral nerve regeneration. Nerve guidance conduits, which act as artificial channels to guide regenerating nerves, have shown promising results in facilitating nerve regrowth and functional recovery. Additionally, pharmacotherapy approaches have emerged as potential avenues for promoting nerve regeneration, with various therapeutic agents being investigated for their neuroprotective and regenerative properties. The pursuit of advancing the field of peripheral nerve regeneration necessitates persistent investment in research and development. Continued exploration of innovative treatments, coupled with a deeper understanding of the intricate processes involved in nerve regeneration, holds the promise of unlocking the complete potential of these groundbreaking interventions. By fostering collaboration among scientists, clinicians, and industry partners, we can accelerate progress in this field, bringing us closer to the realization of transformative therapies that restore function and quality of life for individuals affected by peripheral nerve injuries. Full article

Medical image segmentation is crucial for clinical applications, but challenges persist due to noise and variability. In particular, accurate glottis segmentation from high-speed videos is vital for voice research and diagnostics. Manual searching for failed segmentations is labor-intensive, prompting interest in automated methods. This paper proposes the first deep learning approach for detecting faulty glottis segmentations. For this purpose, faulty segmentations are generated by applying both a poorly performing neural network and perturbation procedures to three public datasets. Heavy data augmentations are added to the input until the neural network’s performance decreases to the desired mean intersection over union (IoU). Likewise, the perturbation procedure involves a series of image transformations to the original ground truth segmentations in a randomized manner. These data are then used to train a ResNet18 neural network with custom loss functions to predict the IoU scores of faulty segmentations. This value is then thresholded with a fixed IoU of 0.6 for classification, thereby achieving 88.27% classification accuracy with 91.54% specificity. Experimental results demonstrate the effectiveness of the presented approach. Contributions include: (i) a knowledge-driven perturbation procedure, (ii) a deep learning framework for scoring and detecting faulty glottis segmentations, and (iii) an evaluation of custom loss functions. Full article

Excessive fibrosis and resultant poor control of intraocular pressure (IOP) reduce the efficacy of glaucoma surgeries. Historically, corticosteroids and anti-fibrotic agents, such as mitomycin C (MMC) and 5-fluorouracil (5-FU), have been used to mitigate post-surgical fibrosis, but these have unpredictable outcomes. Therefore, there is a need to develop novel treatments which provide increased effectiveness and specificity. This review aims to provide insight into the pathophysiology behind wound healing in glaucoma surgery, as well as the current and promising future wound healing agents that are less toxic and may provide better IOP control. Full article