Search Results (2,676)

As a common signal sensing device in pulsed eddy current detection, coil sensors often have parameter offset problems in practical applications. The error in the receiving coil parameters will have a great impact on the early signal. In order to ensure the accuracy of the early signal, this paper first analyzes the response characteristics of the receiving coil and the influence of the coil parameters on the accuracy of signal deconvolution and establishes the mathematical relationship between the response signal and the characteristic parameters, and between the characteristic parameters and the receiving coil parameters under active underdamped oscillation. Subsequently, the parameter feature extraction errors under different state switching capacitors were compared through simulation analysis, the state switching capacitor value was determined, and the receiving coil parameter solution method based on the Levenberg–Marquardt (LM) algorithm was determined based on the parameter feature extraction results. The experimental results demonstrate that the proposed method achieves a capacitance estimation error of just 0.0159% and an inductance error of 0.158%, effectively minimizing early signal distortion and enabling precise identification of receiving coil parameters. Full article

Land use/cover (LUCC) change in arid oasis–desert ecotones has significant implications for spatial governance in ecologically fragile regions. To better capture the temporal and spatial complexity of land transitions, this study developed a vector tracing method by integrating time-series remote sensing data with vector-based transfer pathways. Analysis of northern Oman from 1995 to 2020 revealed the following: (1) Arable land and impervious surfaces expanded from 0.51% to 1.09% and from 0.31% to 0.98%, respectively, while sand declined from 99.03% to 97.01%. Spatially, arable land was concentrated in piedmont irrigation zones, impervious surfaces near coastal cities, and shrubland and grassland along the Al-Hajar Mountains, forming a complementary land use mosaic. (2) Human activities were the dominant driver, with typical one-way chains accounting for 69.76% of total change. Sand was mainly transformed into arable land (7_C1, 7_D1, 7_E1; where the first part denotes the original type, the letter denotes the year of change, and the last digit denotes the new type), impervious surfaces (7_C6, 7_D6, 7_E6), and shrubland (7_E4). (3) Water scarcity and an arid climate remained primary constraints, manifested in typical reciprocating chains in the oasis–desert interface (7_D1_E7, 7_A1_B7, 7_C1_D7) and in the arid vegetation zone along the Al-Hajar Mountain foothills (7_D3_E7, 7_C3_D7), together accounting for 24.50% of total change. (4) The region exhibited coordinated transitions among oasis, urban, and ecological land, avoiding the common conflict of cropland loss to urbanization. During the study period, transitions among arable land, impervious surfaces, forest, shrubland, and wetland were rare (Type 16: 3.31%, Type 82: 2.89%, Type 12: 0.04%, Type 18: 0.01%). The case of northern Oman provides a valuable reference for collaborative spatial governance in ecologically fragile arid zones. Future research should integrate socio-economic drivers, climate change projections, and higher-temporal-resolution data to enhance the applicability of the chain-spectrum method in other arid regions. Full article

Artificial intelligence (AI) is revolutionarily shaping the entire landscape of medicine and particularly the privileged field of radiology, since it produces a significant amount of data, namely, images. Currently, AI implementation in radiology is continuously increasing, from automating image analysis to enhancing workflow management, and specifically, pediatric neuroradiology is emerging as an expanding frontier. Pediatric neuroradiology presents unique opportunities and challenges since neonates’ and small children’s brains are continuously developing, with age-specific changes in terms of anatomy, physiology, and disease presentation. By enhancing diagnostic accuracy, reducing reporting times, and enabling earlier intervention, AI has the potential to significantly impact clinical practice and patients’ quality of life and outcomes. For instance, AI reduces MRI and CT scanner time by employing advanced deep learning (DL) algorithms to accelerate image acquisition through compressed sensing and undersampling, and to enhance image reconstruction by denoising and super-resolving low-quality datasets, thereby producing diagnostic-quality images with significantly fewer data points and in a shorter timeframe. Furthermore, as healthcare systems become increasingly burdened by rising demands and limited radiology workforce capacity, AI offers a practical solution to support clinical decision-making, particularly in institutions where pediatric neuroradiology is limited. For example, the MELD (Multicenter Epilepsy Lesion Detection) algorithm is specifically designed to help radiologists find focal cortical dysplasias (FCDs), which are a common cause of drug-resistant epilepsy. It works by analyzing a patient’s MRI scan and comparing a wide range of features—such as cortical thickness and folding patterns—to a large database of scans from both healthy individuals and epilepsy patients. By identifying subtle deviations from normal brain anatomy, the MELD graph algorithm can highlight potential lesions that are often missed by the human eye, which is a critical step in identifying patients who could benefit from life-changing epilepsy surgery. On the other hand, the integration of AI into pediatric neuroradiology faces technical and ethical challenges, such as data scarcity and ethical and legal restrictions on pediatric data sharing, that complicate the development of robust and generalizable AI models. Moreover, many radiologists remain sceptical of AI’s interpretability and reliability, and there are also important medico-legal questions around responsibility and liability when AI systems are involved in clinical decision-making. Future promising perspectives to overcome these concerns are represented by federated learning and collaborative research and AI development, which require technological innovation and multidisciplinary collaboration between neuroradiologists, data scientists, ethicists, and pediatricians. The paper aims to address: (1) current applications of AI in pediatric neuroradiology; (2) current challenges and ethical considerations related to AI implementation in pediatric neuroradiology; and (3) future opportunities in the clinical and educational pediatric neuroradiology field. AI in pediatric neuroradiology is not meant to replace neuroradiologists, but to amplify human intellect and extend our capacity to diagnose, prognosticate, and treat with unprecedented precision and speed. Full article

Acute lymphoblastic leukemia (ALL) represents the most common type of cancer in the pediatric population. The (1;19)(q23;p13) translocation is a primary chromosomal abnormality present in 3–12% of ALL cases. The current study aims to develop a label-free innovative nanodevice for the ultrasensitive diagnosis of the TCF3-PBX1 chimeric oncogene, featuring simplified operation and rapid analysis using minimal sample volumes, which positions it as a superior alternative for clinical diagnostics and early leukemia identification. The biosensor system was engineered on a nanostructured platform composed of polypyrrole (PPy) and a novel chemically functionalized hybrid nanocomposite of platinum nanospheres and titanium dioxide nanoparticles (TiO₂@Pt). Single-stranded oligonucleotide sequences were chemically immobilized on the nanoengineered transducer to enable biospecific detection. Cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), ultraviolet-visible spectroscopy (UV-Vis), and atomic force microscopy (AFM) were used to characterize each stage of the biotechnological device fabrication process. The analytical properties of the sensing tool were explored using recombinant plasmids containing the TCF3-PBX1 oncogenic sequence and clinical specimens from pediatric patients with B-cell ALL. After exposing the molecular monitoring system to the genetic target, significant variations were observed in the voltammetric oxidation current (∆I = 33.08% ± 0.28 to 124.91% ± 17.08) and in the resistance to charge transfer (ΔR_CT = 19.73% ± 0.96 to 83.51% ± 0.84). Data analysis revealed high reproducibility, with a relative standard deviation of 3.66%, a response range from 3.58 aM to 357.67 fM, a detection limit of 19.31 aM, and a limit of quantification of 64.39 aM. Therefore, a novel nanosensor for multiparametric electrochemical screening of the TCF3-PBX1 chimeric oncogene was described for the first time, potentially improving the quality of life for leukemic patients. Full article

This study focuses on a comprehensive analysis of the common methods for road infrastructure monitoring, as well as the perspective of various fiber-optic sensor (FOS) realization solutions in road monitoring applications. Fiber-optic sensors are a topical technology that ensures multiple advantages such as passive nature, immunity to electromagnetic interference, multiplexing capabilities, high sensitivity, and spatial resolution, as well as remote operation and multiple physical parameter monitoring, hence offering embedment potential within the road pavement structure for needed smart road solutions. The main key factors that affect FOS-based road monitoring scenarios and configurations are analyzed within this review. One such factor is technology used for optical sensing—fiber Bragg grating (FBG), Brillouin, Rayleigh, or Raman-based sensing. A descriptive comparison is made comparing typical sensitivity, spatial resolution, measurement distance, and applications. Technological approaches for monitoring physical parameters, such as strain, temperature, vibration, humidity, and pressure, as a means of assessing road infrastructure integrity and smart application integration, are also evaluated. Another critical aspect concerns spatial positioning, focusing on the point, quasi-distributed, and distributed methodologies. Lastly, the main topical FOS-based application areas are discussed, analyzed, and evaluated. Full article

The germination and elongation of maize in the early growth stage are closely related to the elongation of the mesocotyl, which is one of the first parts to sense external temperature, aside from the coleoptile. Low-temperature (LT, 10~15 °C) stress can significantly affect the survival and growth of maize seedlings. Additionally, brassinosteroids (BRs) have been used in recent years to help alleviate damage caused by LT in various plants. However, the interaction among LT, BRs, and sugar remains unclear. Therefore, we examined the relationships among the contents of glucose, sucrose, and starch, along with the changes in differentially expressed genes (DEGs) involved in starch and sucrose metabolism and glycolysis/gluconeogenesis pathways. Compared to CK (0 μM 24-epibrassinolide (EBR) application at 25 °C), the contents of glucose and sucrose increased by 0.26, 0.47, and 0.70 mg g⁻¹ FW and 0.80, 0.30, and 0.61 mg g⁻¹ FW, respectively, under the CKE (2.0 μM 24-epibrassinolide (EBR) application at 25 °C), LT (0 μM 24-epibrassinolide (EBR) application at 10 °C), and LTE (2.0 μM 24-epibrassinolide (EBR) application at 10 °C) treatments. However, starch contents decreased under LT and LTE treatments, by −20.54% and −0.20%, respectively, compared to CK. This suggests that sugar signaling and metabolism play key roles in regulating LT tolerance, and the application of EBR may alleviate LT damage by regulating sugar accumulation levels. Furthermore, 108 DEGs were identified in the starch and sucrose metabolism pathways, along with 23 in glycolysis, with 65 DEGs at the transcriptome level. The common Zm00001d042146 (hexokinase-3) in both pathways is usually down-regulated, and the degree of down-regulation when EBR is added is less than under LT alone. Additionally, key genes such as Zm00001d021598 (glucan endo-1,3-beta-glucosidase 3), Zm00001d034017 (uncharacterized LOC541703), and Zm00001d029091 (sucrose synthase 2) were differentially expressed under LT, with their expression levels decreasing further when EBR was added. In conclusion, our results provide a new direction into the molecular mechanisms by which exogenous EBR application enhances low-temperature tolerance in maize seedlings. Full article

Preventive conservation (PC) of built heritage has proved to be one of the most efficient and sustainable approaches to ensure its long-term preservation. Nevertheless, the management of all the areas involved in a PC project is complex, often resulting in poor interaction between them. This research proposes a GIS-based methodology for integrating data from different PC areas into a centralised digital model, establishing a Common Data Environment (CDE) to optimise PC strategies for heritage systems in complex contexts. Applying this method to the pavilions of the 1929 Ibero-American Exhibition in Seville (Spain), the study addresses five key PC areas: active follow-up, damage detection and assessment, risk analysis, maintenance, and dissemination and valorisation. The approach involved designing a robust relational database structure—using PostgreSQL—tailored for heritage management, defining several data standardisation criteria, and testing semi-automated procedures for generating multi-scale 2D and 3D GIS (LOD2 and LOD4) entities using remote sensing data sources. The proposed spatial database has been designed to function seamlessly with major GIS platforms (QGIS and ArcGIS Pro), demonstrating successful integration and interoperability for data management, analysis, and decision-making. Geographic web services derived from the database content were created and uploaded to a WebGIS platform. While limitations exist, this research demonstrates that simplified GIS models are sufficient for managing PC data across various working scales, offering a resource-efficient alternative compared to more demanding existing methods. Full article

Anti-resonant hollow-core fibers have exhibited excellent performance in applications such as high-power pulse transmission, network communication, space exploration, and precise sensing. Employing anti-resonant hollow-core fibers instead of light guiding arms for transmitting laser energy at the 2.79 μm band can significantly enhance the flexibility of medical laser handles, reduce system complexity, and increase laser transmission efficiency. Nevertheless, common anti-resonant hollow-core fibers do not have the ability to maintain the polarization state of light during laser transmission, which greatly affects their practical applications. In this paper, we propose a polarization-maintaining anti-resonant hollow-core fiber applicable for transmission at the mid-infrared 2.79 μm band. This fiber features a symmetrical geometric structure and an asymmetric refractive index cladding composed of quartz and a type of mid-infrared glass with a higher refractive index. Through optimizing the fiber structure at the wavelength scale, single-polarization transmission can be achieved at the 2.79 μm wavelength, with a polarization extinction ratio exceeding 1.01 × 10⁵, indicating its stable polarization-maintaining performance. Simultaneously, it possesses low-loss transmission characteristics, with the loss in the x-polarized fundamental mode being less than 9.8 × 10⁻³ dB/m at the 2.79 µm wavelength. This polarization-maintaining anti-resonant hollow-core fiber provides a more reliable option for the light guiding system of the 2.79 μm Er; Cr: YSGG laser therapy device. Full article

With advancements in remote sensing technology and very-large-scale integration (VLSI) circuit technology, the Earth observation capabilities of spaceborne synthetic aperture radar (SAR) have continuously improved, leading to significantly increased performance demands for on-board SAR real-time imaging processors. Currently, the low data access efficiency of traditional direct memory access (DMA) engines remains a critical technical bottleneck limiting the real-time processing performance of SAR imaging systems. To address this limitation, this paper proposes a dedicated instruction set for spaceborne SAR data transfer control, leveraging the memory access characteristics of DDR4 SDRAM and common data read/write address jump patterns during on-board SAR real-time imaging processing. This instruction set can significantly reduce the number of instructions required in DMA engine data access operations and optimize data access logic patterns. While effectively reducing memory resource usage, it also substantially enhances the data access efficiency of DMA engines. Based on the proposed dedicated instruction set, we designed a DMA engine optimized for efficient data access in on-board SAR real-time imaging processing scenarios. Module-level performance tests were conducted on this engine, and full-process imaging experiments were performed using an FPGA-based SAR imaging system. Experimental results demonstrate that, under spaceborne SAR imaging processing conditions, the proposed DMA engine achieves a receive data bandwidth of 2.385 GB/s and a transmit data bandwidth of 2.649 GB/s at a 200 MHz clock frequency, indicating excellent memory access bandwidth and efficiency. Furthermore, tests show that the complete SAR imaging system incorporating this DMA engine processes a 16 k × 16 k SAR image using the Chirp Scaling (CS) algorithm in 1.2325 s, representing a significant improvement in timeliness compared to existing solutions. Full article

This paper reviews the integration of artificial intelligence (AI) and machine learning in biorefineries and bioprocessing, with applications in biocatalysis, enzyme optimization, real-time monitoring, and quality assurance. AI contributes to predictive modeling and allows the precise forecasting of process outcomes, resource management, and energy utilization. AI models, including supervised, unsupervised, and reinforcement learning, support improvements in important bioprocess stages, such as fermentation, purification, and microbial biosynthesis. Digital twins and soft-sensing technologies enable real-time control and increase operational precision in complex bioprocess environments. Hybrid modeling integrates data-driven AI techniques with common scientific principles, improving scalability and adaptability under dynamic operational conditions. This review addresses challenges in AI implementation, such as data standardization, model transparency, and the need for interdisciplinary collaboration. The discussion concludes with future directions and sustainable AI strategies, highlighting the potential of AI to strengthen scalable, efficient, and environmentally sustainable biorefinery operations. These findings highlight how AI-driven methodologies improve operational efficiency, reduce resource waste, and facilitate sustainable innovation in bioprocesses, thereby strengthening sustainability within the bioeconomy. Full article

Wittgenstein’s philosophy has influenced the philosophy of religion quite considerably. This is hardly due to his rather few remarks on religion. Instead, Wittgenstein’s influence seems to be connected to a certain, without doubt common, interpretation of his later philosophy, mainly of Philosophical Investigations. I speak about one interpretation because in my view the purportedly different interpretations of the sense in which certain key-concepts in the Philosophical Investigations are supposed to be fruitful for understanding religious language, in fact have a common, unacknowledged presupposition: that Wittgenstein’s account of language rotates around the quite traditional, philosophical concepts of subjectivity and objectivity. In the interpretations at stake, these concepts form the backdrop of questions about what “can” intelligibly be assessed by an individual and what “has to be” accounted for in “our” common language. There are discussions in the Philosophical Investigations that do give rise to such questions. However, what I take to be the main direction in Wittgenstein’s later philosophy is the movement away from the concepts of subjectivity and objectivity. Most clearly, this is visible in the second volume of Last Writings on the Philosophy of Psychology, where Wittgenstein dissolves the idea of the inscrutable inner of the other. As I will show, these remarks are in tension both with the views that his followers, such as Peter Winch, put forth and with his own remarks on religion in Culture and Value. Full article

Human personality (HP) is seen as an individual’s consistent patterns of feeling, thinking, and behaving by today’s psychological studies, in which HPs are characterized in terms of traits—in particular, as relatively enduring characteristics that influence human behavior across many situations. In this sense, more generally, artificial personality (AP) is studied in computer science to develop AI agents who should behave more like humans. However, in this paper, we suggest another approach by which the APs of individual agents are distinguishable based on their behavioral characteristics in achieving tasks and not necessarily in their human-like performance. As an initial step toward AP, we propose an approach to extract human decision-making characteristics as a generative resource for encoding the variability in agent personality. Using an application example, we demonstrate the feasibility of grouping APs, divided into several steps consisting of (1) defining a feature space to measure the commonality of decision making between individual and a group of people; (2) grouping APs by using multidimensional orthogonal features in the feature space to guarantee inter-individual differences between APs in achieving for the same task; and (3) evaluating the consistency of grouping APs by performing a cluster-stability analysis. Finally, our thoughts for the future implementation of APs are discussed and presented. Full article

Carboxymethyl cellulose (CMC) films, derived from sugarcane bagasse agricultural waste (SCB) incorporated with Betalains-nitrogen-doped carbon dots (Betalains-N–CQDs), derived from beet root waste (BR), offer a sustainable, smart and naked-eye sensor for strawberry packaging due to their excellent fluorescent and shape memory properties. These CMC-Betalains-N–CQDs aim to enhance strawberry preservation and safety by enabling visual detection of common food contaminants such as bacteria, fungi and Pb(II). Crucially, the CMC-Betalains-N–CQD film also exhibits excellent shape memory properties, capable of fixing various shapes under alkaline conditions and recovering its original form in acidic environments, thereby offering enhanced physical protection for delicate produce like strawberries. Optical studies reveal the Betalains-N–CQDs’ pH-responsive fluorescence, with distinct emission patterns observed across various pH levels, highlighting their potential for sensing applications. Scanning Electron Microscopy (SEM) confirms the successful incorporation of Betalains-N–CQDs into the CMC matrix, revealing larger pores in the composite film that facilitate better interaction with analytes such as bacteria. Crucially, the CMC-Betalains-N–CQD film demonstrates significant antibacterial activity against common foodborne pathogens like Escherichia coli, Staphylococcus aureus, and Candida albicans, as evidenced by inhibition zones and supported by molecular docking simulations showing strong binding interactions with bacterial proteins. Furthermore, the film functions as a fluorescent sensor, exhibiting distinct color changes upon contact with different microorganisms and Pb(II) heavy metals, enabling rapid, naked-eye detection. The film also acts as a pH sensor, displaying color shifts (brown in alkaline, yellow in acidic) due to the betalains, useful for monitoring food spoilage. This research presents a promising, sustainable, and multifunctional intelligent packaging solution for enhanced food safety and extended shelf life. Full article

Peatland is a difficult landscape to map due to its challenging conditions. Remote sensing lends itself to mapping efforts, but can be hampered by common weather conditions in peatland locations. Sentinel-1 Synthetic Aperture Radar technology penetrates prevalent cloud cover. Techniques used to detect water surfaces using Sentinel-1 backscatter intensity have been applied in this study to delineate peatland land cover. This application was then extended with the aim of identifying the relative conditions of peatland within an area of interest. A peatland study site was selected at Winter Hill, near Bolton in Lancashire, UK, where a nationally significant wildfire occurred in 2018. Sentinel-1 imagery captured in the winter after the wildfire quite accurately reflected the fire damage extent. From further examination, it was found that in frozen conditions there are significant statistical differences between peatland surfaces and visually similar land cover, such as fields used for livestock grazing. Using the inter-quartile range of land cover samples to identify suitable backscatter thresholds, a surface map was produced depicting peatland of varying conditions and other land cover categories. This was compared with field visit photographic records to ascertain accuracy of representation. Further analysis detected correlation between backscatter and temperature for peatland surfaces that was not evident for other land cover classes. Steeper terrain can though affect this relationship. Conversely, no significant connection could be found in areas where surface water is most likely to be retained. Aggregating Sentinel-1 backscatter according to sub-catchment zones presented the potential to further delineate by condition within a peatland land cover sample. Therefore, the use of Sentinel-1 imagery in frozen conditions in context with terrain and sub-catchment level hydrological zoning provides the opportunity to aid environmental monitoring by delineating peatland from other land cover, identifying climate-change effects such as wildfires and assessing relative condition at scale. Full article

Background: Bullying is a significant problem worldwide and in Lithuania, especially among children and adolescents. This study aimed to assess the associations of bullying with adolescents’ subjective sense of happiness and general health. Methods: A cross-sectional study was conducted using an anonymous written questionnaire. Adolescents at various schools across Lithuanian cities and districts were surveyed to investigate the frequency of bullying among them over the past six months and its impact on their subjective sense of happiness and well-being. Results: This study included 4124 students from seventh to tenth grade; their average age was 14.48 ± 1.15 years, with 49.35% being boys. Over the past six months, the highest bullying incidence occurred at school, accounting for 25.79% of the cases. Only half of the respondents (48.81%) felt happy, and a little more than half felt healthy (63.11%). It was found that bullying at school (ρ_s = −0.224; ρ_s = −0.197), outside school (ρ_s = −0.207; ρ_s = −0.180), and online (ρ_s = −0.175; ρ_s = −0.110) is associated with adolescents’ sense of happiness and health. Conclusion: Bullying is common among Lithuanian adolescents and has a negative impact on their subjective happiness and well-being. It is crucial to develop prevention initiatives to decrease bullying in schools and within the community. Full article