Search Results (114)

Interferometric signals in space-borne Gravitational Wave Detectors are measured by digital phasemeters. The phasemeter processes signals generated by multiple interferometers, with its primary function being micro-radian level phase measurements. The Science Interferometer is responsible for inter-spacecraft measurements, including relative ranging, absolute ranging, laser communication, and clock noise transfer. Since the scientific interferometer incorporates multiple functions and various signals are simultaneously coupled into the heterodyne signal, establishing a suitable evaluation environment is a crucial foundation for achieving micro-radian level phase measurement during ground testing and verification. This paper evaluates the phase measurement noise of the science interferometer by simulating the heterodyne signal and establishing a test environment. The experimental results show that when the simulated heterodyne signal contains the main beat-note, upper and lower sideband beat-notes, and PRN modulation simultaneously, the phase measurement noise of the main beat-note, upper and lower sideband beat-notes all reach 2π μrad/Hz^1/2@(0.1 mHz–1 Hz), meeting the requirements of the space gravitational wave detection mission. An experimental verification platform and performance reference benchmark have been established for subsequent research on the impact of specific noise on phase measurement performance and noise suppression methods. Full article

Catalpa bungei C.A.Mey is an economically significant deciduous tree valued for timber production and landscaping applications. An efficient regeneration system is crucial for clonal propagation and serves as a foundation for future molecular breeding in C. bungei. This study established two in vitro regeneration pathways—indirect somatic embryogenesis and shoot organogenesis utilizing mature zygotic embryos as explants. Primary callus was induced from cotyledon, hypocotyl, and plumule explants. A high frequency (45.73%) of yellow-green compact callus was achieved on De-Klerk and Walton (DKW) medium supplemented with 2.0 mg/L 6-BA, 1.0 mg/L zeatin (ZT), and 0.1 mg/L NAA. Subsequent transfer to 1.5× Murashige and Skoog (MS) medium containing 1.5 mg/L 6-BA, 0.2 mg/L ZT, and 0.1 mg/L NAA yielded the highest embryogenic callus induction rate (16.67%). Embryogenic callus demonstrated bipotent potential, generating both adventitious shoots and somatic embryos under specific hormonal conditions. Histological analyses confirmed the typical developmental stages of somatic embryos, from globular to cotyledonary forms, validating the embryogenic origin of regenerated structures. Furthermore, hormone or osmotic additives such as abscisic acid (ABA), Phytagel, and polyethylene glycol 4000 (PEG4000) significantly enhanced somatic embryo induction, with Phytagel at 5.0 g/L achieving the highest rate (76.31%). For shoot organogenesis, the optimal hormonal combination of the 0.6 mg/L 6-BA, 0.4 mg/L KT, and 0.15 mg/L NAA achieved the highest bud induction rate (88.89%) and produced an average of 4.07 adventitious buds per explant. This study presents an efficient regeneration system for C. bungei, providing a practical platform for large-scale propagation and basis for biotechnological applications in woody plants. 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

Early and accurate identification of brain tumors is essential for determining effective treatment strategies and improving patient outcomes. Artificial intelligence (AI) and deep learning (DL) techniques have shown promise in automating diagnostic tasks based on magnetic resonance imaging (MRI). This study evaluates the performance of four pre-trained deep convolutional neural network (CNN) architectures for the automatic multi-class classification of brain tumors into four categories: Glioma, Meningioma, Pituitary, and No Tumor. The proposed approach utilizes the publicly accessible Brain Tumor MRI Msoud dataset, consisting of 7023 images, with 5712 provided for training and 1311 for testing. To assess the impact of data availability, subsets containing 25%, 50%, 75%, and 100% of the training data were used. A stratified five-fold cross-validation technique was applied. The CNN architectures evaluated include DeiT3_base_patch16_224, Xception41, Inception_v4, and Swin_Tiny_Patch4_Window7_224, all fine-tuned using transfer learning. The training pipeline incorporated advanced preprocessing and image data augmentation techniques to enhance robustness and mitigate overfitting. Among the models tested, Swin_Tiny_Patch4_Window7_224 achieved the highest classification Accuracy of 99.24% on the test set using 75% of the training data. This model demonstrated superior generalization across all tumor classes and effectively addressed class imbalance issues. Furthermore, we deployed and benchmarked the best-performing DL model on embedded AI platforms (Jetson AGX Xavier and Orin Nano), demonstrating their capability for real-time inference and highlighting their feasibility for edge-based clinical deployment. The results highlight the strong potential of pre-trained deep CNN and transformer-based architectures in medical image analysis. The proposed approach provides a scalable and energy-efficient solution for automated brain tumor diagnosis, facilitating the integration of AI into clinical workflows. Full article

To address the reliability requirements for refrigerated container transport in the cold chain, this study established an experimental platform for phase change cold storage balls. A two-dimensional axisymmetric simplified heat transfer model of the three-dimensional cold storage ball was developed. The reliability of the model was verified through charging experiments. While ensuring a certain level of accuracy (average error less than 10%), the model significantly improved computational efficiency (completing calculations in only 49 s), offering a practical reference value. Based on the established 2D axisymmetric simplified heat transfer model, this study focused on the influence of secondary coolant (ethylene glycol solution) parameters on the charging performance. The results indicate that a smaller diameter of the cold storage ball and a higher flow rate lead to a higher freezing rate of the ball. Under the conditions set in this study, the optimal diameters were determined to be 80 mm and 60 mm, and the optimal inlet flow rate was 3.917 m³/h. This simplified model can provide a reference for the optimal design of phase change cold storage systems in refrigerated containers. Full article

The provision of food in pre-Inca/Inca cultures (1000 BC–≈1532 AD) in environments near Lake Titikaka (approximately 4000 m above sea level) was possible through an agricultural technique called “Waru-Waru”, which consists of filling the space (volume) between rows of land containing plants that are cultivated (a series of earth platforms surrounded by water canals) with water, using water as thermal energy storage to store energy during the day and to regulate the temperature of the soil and crop atmosphere at night. The problem is that these cultures left no evidence in written documents that have been preserved to this day indicating the mathematical models, the physics involved, and the experimental part they performed for the research, development, and innovation of the “Waru-Waru” technique. From a review of the existing literature, there is (1) bibliography that is devoted to descriptive research (about the geometry, dimensions, and shapes of the crop fields (and more based on archaeological remains that have survived to the present day) and (2) studies presenting complex mathematical models with many physical parameters measured only with recently developed instrumentation. The research objectives of this paper are as follows: (1) develop a mathematical model that uses finite differences in fluid mechanics, thermodynamics, and heat transfer to explain the experimental and theory principles of this pre-Inca/Inca technique; (2) the proposed mathematical model must be in accordance with the mathematical calculation tools available in pre-Inca/Inca cultures (yupana and quipu), which are mainly based on arithmetic operations such as addition, subtraction, and multiplication; (3) develop a mathematical model in a sequence of steps aimed at determining the best geometric form for thermal energy storage and plant cultivation and that has a simple design (easy to transmit between farmers); (4) consider the assumptions necessary for the development of the mathematical model from the point of view of research on the geometry of earth platforms and water channels and their implantation in each cultivation area; (5) transmit knowledge of the construction and maintenance of “Waru-Waru” agricultural technology to farmers who have cultivated these fields since pre-Hispanic times. The main conclusion is that, in the mathematical model developed, algebraic mathematical expressions based on addition and multiplication are obtained to predict and explain the evolution of soil and water temperatures in a specific crop field using crop field characterization parameters for which their values are experimentally determined in the crop area where a “Waru-Waru” is to be built. Therefore, the storage of thermal energy in water allows crops to survive nights with low temperatures, and indirectly, it allows the interpretation that the Inca culture possessed knowledge of mathematics (addition, subtraction, multiplication, finite differences, approximation methods, and the like), physics (fluids, thermodynamics, and heat transfer), and experimentation, with priority given to agricultural techniques (and in general, as observed in all archaeological evidence) that are in-depth, exact, practical, lasting, and easy to transmit. Understanding this sustainable energy storage technique can be useful in the current circumstances of global warming and climate change within the same growing areas and/or in similar climatic and environmental scenarios. This technique can help in reducing the use of fossil or traditional fuels and infrastructure (greenhouses) that generate heat, expanding the agricultural frontier. Full article

Cortisol is a key biomarker for stress detection, and its levels can be monitored using point-of-care devices with sensors such as nanoparticles and interdigitated array electrodes (IDEs). This study developed an IDE platform using barium titanate (BaTiO₃) particles synthesized via colloidal precipitation with titanium tetraisopropoxide, barium chloride, and Pluronic^® P123. The calcination temperatures varied between 160 °C and 340 °C, with optimal results observed at 160 °C. Scanning electron microscopy revealed particles with an average size of 26 nm, and Fourier transform infrared spectroscopy confirmed the molecular composition after the removal of P123. X-ray diffraction analysis revealed anatase and brookite phases. Brunauer-Emmett-Teller analysis indicated changes in pore morphology, with samples treated at 160 °C exhibiting a type IV(a) mesoporous structure, a surface area of 163 m²/g, and an average pore diameter of 5.24 nm. Higher temperatures led to transitions to type IV(b) at 260 °C and type V at 340 °C, with reduced pore size. Electrochemical impedance spectroscopy was employed to evaluate the performance of the IDE sensor integrated with BaTiO₃ nanoparticles and albumin across cortisol concentrations ranging from 5.0 to 20 ng/mL. Impedance measurements revealed a significant decrease in impedance (Z′) with increasing cortisol concentrations, indicating increased conductivity. Specifically, Nyquist plots for a saliva sample containing 5 ng/mL cortisol—within the typical physiological range—exhibited a marked increase in charge-transfer resistance (Rct), confirming the sensor’s ability to detect low hormone levels in biological fluids. These findings underscore the potential of BaTiO₃-based IDE platforms at 160 °C for stress biomarker monitoring. Full article

To address the high-precision measurement requirements for container pose on dual-trolley quayside crane-transfer platforms, this paper proposes a machine vision-based measurement method that resolves the challenges of multi-scale lockhole detection and precision demands caused by complex illumination and perspective deformation in port operational environments. A hardware system comprising fixed cameras and edge computing modules is established, integrated with an adaptive image-enhancement preprocessing algorithm to enhance feature robustness under complex illumination conditions. A multi-scale adaptive frequency object-detection framework is developed based on YOLO11, achieving improved detection accuracy for multi-scale lockhole keypoints in perspective-distortion scenarios (mAP@0.5 reaches 95.1%, 4.7% higher than baseline models) through dynamic balancing of high–low-frequency features and adaptive convolution kernel adjustments. An enhanced EPnP optimization algorithm incorporating lockhole coplanar constraints is proposed, establishing a 2D–3D coordinate transformation model that reduces pose-estimation errors to millimeter level (planar MAE-P = 0.024 m) and sub-angular level (MAE-$\theta$ = 0.11°). Experimental results demonstrate that the proposed method outperforms existing solutions in container pose-deviation-detection accuracy, efficiency, and stability, proving to be a feasible measurement approach. Full article

Social media (SM) platforms allow users to communicate rapidly, exchange information, and create and share real-time content. Currently, 4.5 billion people use social media worldwide, making it an influential part of daily life. Beyond information sharing, social media facilitates communication, transfers information, and serves as a platform for advertising and shaping public opinion. Researchers analyse these aspects to understand and describe societal realities. The primary purpose of this paper is to analyse social media’s impact on global research. The research included an analysis of the most popular social platforms, considering the number of Web of Science (WoS) articles relating to them and the year in which the platform was established or the Monthly Active Users (MAU) factor. Data were collected based on the WoS database in the topic (which contains texts of title, abstract, author keywords, and Keywords Plus) of the articles, where phrases containing names of SM platforms were used. Quantitative research is a type of research that analyses data numerically to find relationships and statistical regularities of searched phrases. The impact of social media on the dissemination of research and findings was analysed based on the results of the study and also on the literature data. This research reveals a lack of correlation between the number of articles indexed in the WoS and the MAU of individual social media platforms. This observation raises an important question: do social media researchers focus on studying the platforms used by the majority, thereby providing a more accurate representation of current social dynamics? This article is helpful for researchers, policymakers, and social media platform developers seeking to understand the role of social media in shaping modern communication and public discourse. The most important finding of the paper is the low correlation between the number of SM users and the impact of social media platforms on learning, as exemplified by the Twitter (Note: Twitter was an American social networking service rebranded as X in 2023. As the period of data analysed in this paper covered the years up to 2022, the authors decided to stay with the name Twitter) platform, which is the 17th largest SM platform but is the 2nd (after Facebook) in implications for science. Full article

Hellenic Open University has developed Onlabs, a virtual biology laboratory designed to safely and effectively prepare its students for hands-on work in the university’s on-site labs. This platform simulates key experimental processes, such as 10X TBE solution preparation, agarose gel preparation and electrophoresis, which involve liquid transfers between bottles. However, accurately depicting liquid volumes and their flow within complex-shaped laboratory vessels, such as Erlenmeyer flasks and burettes, remains a challenge. This paper addresses this limitation by introducing a unified parametric framework for modeling circular cross-section pipes, including straight pipes with a constant diameter, curved pipes with a constant diameter and straight conical pipes. Analytical expressions are developed to define the position and orientation of points along a pipe’s central axis, as well as the surface geometry of composite pipes formed by combining these elements in planar configurations. Moreover, the process of surface discretization with finite triangular elements is analyzed with the aim of optimizing their representation during the algorithmic implementation. The functions of the current length with respect to the volume of each considered container shape are developed. Finally, the methodology for handling and combining the analytical expressions during the filling of a composite pipe is explained, the filling of certain characteristic bottles is implemented and the results of the implementations are presented. The primary goal is to enable the precise algorithmic generation of 3D graphics representing the surfaces of liquids within various laboratory vessels and, subsequently, the simulation of their flow. By leveraging these parametric models, liquid volumes can be accurately visualized, reflecting the vessels’ geometries and improving the realism of simulations and the filling of various vessels can be realistically simulated. Full article

Background/Objectives: To date, no information is available on the complete mitochondrial genome of the genus Dianema (Siluriformes: Callichthyidae), a callichthyid catfish. In this study, we report on two complete mitochondrial genome sequences of Dianema longibarbis Cope, 1872, and Dianema urostriatum Miranda Ribeiro, 1912, the only two recognized species within the genus Dianema. Methods: DNA sequencing was performed using the HiSeq platform to obtain their complete mitogenomes. To confirm phylogenetic distance, two phylogenetic trees were established using maximum-likelihood and Bayesian inference methods with all concatenated protein-coding sequences (PCGs) and two ribosomal RNA (rRNA) genes from the D. longibarbis and D. urostriatum mitogenomes, along with 32 mitogenomes retrieved from Siluriformes. Results: The complete mitogenomes of D. longibarbis and D. urostriatum are 16,493 and 16,495 base pairs in length, respectively. Their nucleotide compositions are 31.79% A, 27.53% T, 25.86% C, and 14.82% G for D. longibarbis, and 31.69% A, 27.04% T, 26.36% C, and 14.91% G for D. urostriatum. Both mitogenomes contain 13 PCGs, 22 transfer RNA (tRNA) genes, and two rRNA genes. Phylogenetic results based on all PCGs and two rRNAs genes confirm D. longibarbis as a sister species to D. urostriatum in the subfamily Callichthyinae. Conclusions: In contrast to the extensive mitochondrial studies on species in the Corydoradinae, species in the Callichthyinae have been largely understudied. This study provides valuable insights into genetic diversity and evolutionary complexity by presenting the first mitochondrial genome analysis of two Dianema species, a genus within the Callichthyinae. Full article

We established a real-time Förster resonance energy transfer (FRET) based assay to evaluate targeted drug delivery using polymeric micelles. Red fluorescent protein (RFP)-expressing E. coli cells were used as a test system to monitor the delivery of drug-fluorophore such as curcumin and umbelliferones (MUmb and AMC) encapsulated in the polymeric micellar formulations. The efficiency of the drug delivery was quantified using the FRET efficiency, measured as the degree of energy transfer from the drug to the RFP. FRET efficiency directly provides the determination of the delivery efficacy, offering a versatile platform adaptable to various drugs and cell types. We used polymer micelles as a carrier for targeted delivery of fluorescent drugs to bacterial cells expressing RFP. The physicochemical characterization of the interaction between the drugs and the micelles including spectral properties, and the solubility and binding constants, were determined. We revealed a stronger affinity of MUmb for heparin-based micelles (K_d~10⁻⁵ M) compared to chitosan-based micelles (K_d~10⁻⁴ M), underscoring the influence of polymer composition on drug loading efficiency. For micelles containing MUmb, a FRET efficiency significantly exceeds (by three times) the efficiency for non-micellar MUmb, which have minimal penetration into bacterial cells. The most noticeable effect was observed with the use of the micellar curcumin providing pronounced activation of the RPF fluorescence signal, due to the interaction with curcumins (fluorophore-donor). Curcumin delivery using Chit5-OA micelle resulted in a 115% increase in RFP fluorescence intensity, and Hep-LA showed a significant seven-fold increase. These results highlight the significant effect of micellar composition on the effectiveness of drug delivery. In addition, we have developed a visual platform designed to evaluate the effectiveness of a pharmaceutical product through the visualization of the fluorescence of a bacterial culture on a Petri dish. This method allows us to quickly and accurately assess the penetration of a drug into bacteria, or those located inside other cells, such as macrophages, where the intercellular latent forms of the infection are located. Micellar formulations show enhanced antibacterial activity compared to free drugs, and formulations with Hep-OA micelles demonstrate the most significant reduction in E. coli viability. Synergistic effects were observed when combining curcumin and MUmb with moxifloxacin, resulting in a remarkable 40–50% increase in efficacy. The presented approach, based on the FRET test system with RFP expressed in the bacterial cells, establishes a powerful platform for development and optimizing targeted drug delivery systems. Full article

Background/Objectives: In this study, we report the complete mitochondrial genome sequence of Hoplisoma concolor Weitzman, 1961 (Siluriformes: Callichthyidae), a callichthyid catfish. Methods: DNA sequencing was performed to obtain its complete mitogenome using the HiSeq platform. To assess the phylogenetic relationships, maximum-likelihood and Bayesian inference phylogenetic trees were constructed using two ribosomal RNA (rRNA) genes and all protein-coding sequences (PCGs) concatenated from the H. concolor mitogenome, along with 31 other Siluriformes mitogenomes. Results: The complete mitogenome of H. concolor is 16,579 base pairs in length, with a nucleotide composition of 32.2% A, 26.0% T, 15.3% G, and 26.5% C. It contains 13 PCGs, 22 transfer RNA genes, and 2 rRNA genes. Phylogenetic analysis based on all PCGs and two rRNAs of the complete mitogenome confirms H. concolor as a sister species of H. panda within the subfamily Corydoradinae. In addition, intergenic sequences between atp6 and cox3 of 21 species of Corydoradinae provide further support for their phylogenetic relationship. Conclusions: Given the lack of detailed descriptions regarding the length and nucleotide composition of these intergenic sequences, our study contributes valuable insights into the genetic diversity and evolutionary complexity of Callichthyidae. Full article

The transcription of historical manuscripts aims at making our cultural heritage more accessible to experts and also to the larger public, but it is a challenging and time-intensive task. This paper contributes an automated solution for text layout recognition, segmentation, and recognition to speed up the transcription process of historical manuscripts. The focus is on transcribing Portuguese municipal documents from the Middle Ages in the context of the iForal project, including the contribution of an annotated dataset containing Portuguese medieval documents, notably a corpus of 67 Portuguese royal charter data. The proposed system can accurately identify document layouts, isolate the text, segment, and transcribe it. Results for the layout recognition model achieved 0.98 mAP@0.50 and 0.98 precision, while the text segmentation model achieved 0.91 mAP@0.50, detecting 95% of the lines. The text recognition model achieved 8.1% character error rate (CER) and 25.5% word error rate (WER) on the test set. These results can then be validated by palaeographers with less effort, contributing to achieving high-quality transcriptions faster. Moreover, the automatic models developed can be utilized as a basis for the creation of models that perform well for other historical handwriting styles, notably using transfer learning techniques. The contributed dataset has been made available on the HTR United catalogue, which includes training datasets to be used for automatic transcription or segmentation models. The models developed can be used, for instance, on the eSriptorium platform, which is used by a vast community of experts. Full article

The hemispherical resonator gyroscope is a gyroscope based on the principle of Coriolis vibration, widely used in inertial measurement systems of spacecraft. This article decomposes the gyroscope into two parts: the resonator shell and the gyroscope head, establishes the energy dissipation mechanism of the gyroscope, and conducts experimental verification. Firstly, based on the working principle of the gyroscope, a mechanical analysis model of the hemispherical resonator gyroscope head with a resonator spherical shell containing quality defects under second-order vibration state was established. The unbalanced force applied by the resonator spherical shell to the hemispherical resonator gyroscope head was analyzed, and the energy transfer path and dissipation mechanism from the spherical shell to the hemispherical resonator gyroscope head were explained. Finally, through the constructed testing platform, the circumferential quality factor test of the hemispherical resonator gyroscope before and after assembly was completed according to the designed experimental plan, and the consistency between theory and experimental phenomena was verified experimentally. Full article