Search Results (1,140)

Handcrafted radiomics use predefined formulas to extract quantitative features from medical images, whereas deep neural networks learn de novo features through iterative training. We compared these approaches for predicting 3-month outcomes and hematoma expansion from admission non-contrast head CT in acute intracerebral hemorrhage (ICH). Training and cross-validation were performed using a multicenter trial cohort (n = 866), with external validation on a single-center dataset (n = 645). We trained multiscale U-shaped segmentation models for hematoma segmentation and extracted (i) radiomics from the segmented lesions and (ii) two latent deep feature sets—from the segmentation encoder and a generative autoencoder trained on dilated lesion patches. Features were reduced with unsupervised Non-Negative Matrix Factorization (NMF) to 128 per set and used—alone or in combination—for six machine-learning classifiers to predict 3-month clinical outcomes and (>3, >6, >9 mL) hematoma expansion thresholds. The addition of latent deep features to radiomics numerically increased model prediction performance for 3-month outcomes and hematoma expansion using Random Forest, XGBoost, Extra Trees, or Elastic Net classifiers; however, the improved accuracy only reached statistical significance in predicting >3 mL hematoma expansion. Clinically, these consistent but modest increases in prediction performance may improve risk stratification at the individual level. Nevertheless, the latent deep features show potential for extracting additional clinically relevant information from admission head CT for prognostication in hemorrhagic stroke. Full article

Quantitative precipitation estimation (QPE) is one of the primary applications of weather radar. Over the last several decades, dual-polarization radars have significantly improved QPE accuracy by providing additional observational variables that offer more microphysical information about precipitation particles. In this work, we review QPE methods for dual-polarization radars and summarize their advantages and disadvantages from both theoretical and practical perspectives. The development paths and current status of operational QPE systems in the United States, China, and France are examined. We demonstrate how dual-polarization radars have improved QPE accuracy in these systems not only directly through the application of polarimetric QPE methods, but also indirectly through the more accurate identification of non-meteorological echoes, the mitigation of the partial blockage effect, and the detection of melting layers. The challenges are discussed for dual-polarization radar QPE, including the quality of polarimetric variables, QPE quality in complex terrain, estimation of surface precipitation with observations within or above the melting layer, and polarimetric QPE methods for snow. Full article

Mountain catchments in Central Europe are highly susceptible to flash floods. To inform local adaptation, this study quantifies the future flood response of a Polish Carpathian catchment (Upper Skawa, 240.4 km²) to Intergovernmental Panel on Climate Change (IPCC) scenarios. A semi-distributed HEC-HMS model was calibrated and validated using observed flood events (2014–2019). Future hydrographs were then simulated using the delta change method for RCP4.5 and RCP8.5 (near- and long-term horizons). The validated model showed high predictive accuracy. Results indicate a consistent trend towards a polarized hydrological regime, with increased spring/autumn flood peaks and decreased summer flows. This trend is significantly amplified under the RCP8.5 scenario, with long-term peak flood increases approximately double those of RCP4.5. The catchment’s non-linear response further compounds these impacts. These findings suggest a future of heightened seasonal flood risk and emerging summer water scarcity, implying that existing infrastructure, designed for historical stationarity, may be insufficient. This study provides a quantitative evidence base for re-evaluating regional flood risk policies and developing integrated adaptation strategies. Full article

Biphasic calcium phosphate (BCP)scaffolds comprising hydroxyapatite (HA) and β-tricalcium phosphate (β-TCP) were produced from ultra-pure precursors and processed under an α-TCP–avoiding schedule (1100 °C, 2 h). Quantitative X-ray diffraction (Rietveld/Profex) detected no α-TCP above the ~1 wt% limit of detection and quantified post-sintering phase fractions (wt% HA/β-TCP): 99.26/0.74, 68.51/31.49, and 27.57/72.43. Across compositions, SEM/ImageJ yielded similar mean macropore sizes (≈71–80 µm), while open porosity increased with the HA fraction (27.5 ± 1.8%, 39.1 ± 2.0%, 57.1 ± 2.4%). Compressive strength decreased accordingly (1.07 ± 0.25, 0.24 ± 0.01, 0.05 ± 0.02 MPa), consistent with non-load-bearing use. In ISO-compliant simulated body fluid (28 d), medium pH remained stable (7.33–7.43); mass loss and early Ca²⁺ depletion increased with β-TCP content, consistent with more extensive surface apatite formation in β-TCP-rich scaffolds. Collectively, these data are consistent with a composition-dependent sequence—β-TCP content → densification/porosity → strength → degradation/apatite kinetics—within the tested conditions and inform parameter-based tuning of BCP scaffolds for non-load-bearing indications (e.g., alveolar ridge preservation, craniofacial void filling). Full article

Background/Objectives: Long non-coding RNA (lncRNA) was structurally similar to mRNAs, yet they could not be translated into proteins. While an increasing number of reports have systematically identified and described lncRNA in model species, information about non-model species remains scarce. Sea cucumber Holothuria leucospilota could be used for both medicinal and food purposes, which have high economic value, gradually attracting the attention of researchers. Methods: In this research, we constructed lncRNA library and compared the difference in lncRNA expression profiles between testis and ovary of sea cucumber H. leucospilota. To elucidate the molecular interactions between lncRNA and mRNA, we computationally predicted potential complementary binding sites through analysis of both cis- and trans-acting antisense mechanisms. Subsequent Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses demonstrated that the identified target genes are potentially involved in the regulatory pathways governing gonad development. Results: Quantitative reverse transcription PCR analysis showed that MSTRG.32831.1-sox9 and MSTRG.57315.1-mthfr exhibited a high expression pattern in testis; while MSTRG.11041.1-mafa and MSTRG.11074.1-macf1 showed a high expression pattern in the ovary. Conclusions: Deciphering lncRNA–mRNA expression patterns may uncover fundamental principles governing reproductive regulation in marine invertebrates. This discovery not only deepens understanding in this field but also provides valuable comparative insights for developmental biology. Full article

Rolling is a critical step in the processing of black tea, marking the beginning of fermentation. At this stage, the formation of tea pigments causes significant changes in the color of the processed leaves, laying the essential groundwork for the development of color and flavor quality components in subsequent fermentation processes. However, the rapid and non-destructive sensing of tea pigments during black tea rolling remains challenging. This study focused on black tea products undergoing rolling as its research subject, utilizing electrical characteristic detection technology to collect time-series electrical parameters of rolling leaves at various testing frequencies. The original electrical parameters were preprocessed using multiplicative scatter correction (MSC), min-max normalization (Min-Max), and smoothing (Smooth). Various selection methods, including the competitive adaptive reweighting algorithm (CARS), uninformative variable elimination (UVE), and the variable combination population analysis and iterative retained information variable algorithm (VCPA-IRIV), were employed to identify electrical parameters relevant to the targeted attributes. Quantitative prediction models for the content of tea pigments were established using partial least squares regression (PLSR) and support vector machine regression (SVR). The results demonstrated that the Smooth-VCPA-IRIV-SVR model exhibited superior performance in predicting the contents of theaflavins (TFs), thearubigins (TRs), and theabrownins (TBs). Correlation coefficients of prediction (R_p) all exceeded 0.99, and Relative prediction deviation (RPD) values were all above 6.5, indicating that the model enables rapid and non-destructive detection of tea pigment content during black tea rolling. These findings provide preliminary technical support and reference for the digital production of black tea. Full article

Cooperative navigation is a fundamental enabling technology for unlocking the full potential of Unmanned Underwater Vehicle (UUV) clusters in GNSS-denied environments. However, the severe constraints of the underwater acoustic channel, such as high latency, low bandwidth, and non-Gaussian noise, pose significant challenges to designing robust and efficient state estimation and information fusion algorithms. While numerous surveys have cataloged the available techniques, they have remained largely descriptive, lacking a rigorous, quantitative comparison of their performance trade-offs under realistic conditions. This paper provides a comprehensive and critical review that moves beyond qualitative descriptions to establish a novel quantitative comparison framework. Through a standardized benchmark scenario, we provide the first data-driven, comparative analysis of key frontier algorithms—from recursive filters like the Maximum Correntropy Kalman Filter (MCC-KF) to batch optimization methods like Factor Graph Optimization (FGO)—evaluating them across critical metrics including accuracy, computational complexity, communication load, and robustness. Our results empirically reveal the fundamental performance gaps and trade-offs, offering actionable insights for system design. Furthermore, this paper provides in-depth technical analyses of advanced topics, including distributed fusion architectures, intelligent strategies like Deep Reinforcement Learning (DRL), and the unique challenges of navigating in extreme environments such as the polar regions. Finally, leveraging the insights derived from our quantitative analysis, we propose a structured, data-driven research roadmap to systematically guide future investigations in this critical domain. Full article

Background/Objectives: Persons identifying as lesbian, gay, bisexual, pansexual, omnisexual, queer, questioning, fluid, asexual, or other non-heterosexual orientations (LGB+ persons) have been identified as a risk group for sexual victimization (SV), which can have long-lasting negative effects on well-being and physical, mental, sexual, and reproductive health. Othering-Based Stress (OBS)—reflecting societal processes of othering and resulting from stigma, prejudice, and discrimination—may contribute to increased vulnerability to SV and its consequences in LGB+ persons and affect help-seeking behavior following victimization. This study examines the impact of SV on LGB+ persons and their help-seeking behavior after victimization. Methods: Using a mixed-methods explanatory sequential design, first survey data from a nationally representative sample of the Belgian population on SV, its consequences, and subsequent help-seeking behavior were collected from 4632 individuals. Of these, 2965 participants (2601 heterosexual and 364 LGB+ individuals) experienced SV and represented the final sample for the quantitative analyses. In a second phase, in-depth interviews were conducted with 40 LGB+ victims to explore their experiences more thoroughly. Results: LGB+ individuals reported more negative consequences following SV than heterosexual persons, particularly regarding identity-related processes such as questioning gender expression and decreases in self-esteem. They also reported additional barriers to disclosing SV and seeking help from professional services or the police, including fears of stigma, invalidation, and concerns about professionals’ LGB+ competence. No significant differences were found between LGB+ persons who explicitly identified as belonging to a sexual minority group and those who did not, neither in the perceived consequences of SV nor in help-seeking barriers. Conclusions: LGB+ victims of sexual violence experienced more severe identity-related consequences and faced greater barriers to professional support than heterosexual victims. These results highlight the urgent need for trauma-informed, LGB+-inclusive services and structural policy measures to improve access to appropriate care. Full article

Contrast-enhanced ultrasound (CEUS) is increasingly applied in veterinary medicine as a safe, rapid, and non-invasive imaging technique for assessing renal disorders. Despite its expanding use, the literature on its application in feline renal trauma remains scarce. This retrospective study aimed to describe CEUS findings in cats with suspected traumatic renal injuries. Medical records were reviewed for cats that underwent both B-mode ultrasonography and CEUS, with findings confirmed by follow-up, surgery, or cytology. Three cats met the inclusion criteria. Two presented focal or multifocal renal lesions ranging from 10 to 20 mm in diameter, with heterogeneous echotexture, distortion of renal contours, and non-enhancing areas on CEUS consistent with hematomas or lacerations. The third cat showed a circumferential subcapsular halo (approximately 3–5 mm thick) with evidence of contrast leakage, compatible with limited active hemorrhage. CEUS appeared effective in identifying and characterizing renal injuries, offering valuable information to support clinical decision-making and guide both conservative and surgical management. Nevertheless, due to the limited sample size and the absence of quantitative data, these results should be considered preliminary. Further prospective studies are warranted to confirm the diagnostic performance and clinical utility of CEUS in feline renal trauma. Full article

Leukemia stem cells (LSCs) in numerous hematologic malignancies are generally believed to be responsible for disease initiation, progression/relapse and resistance to chemotherapy. It has been shown that non-leukemic hematopoietic cells are affected molecularly and biologically by leukemia cells in the same bone marrow environment where both non-leukemic hematopoietic stem cells (HSCs) and LSCs reside. We believe the molecular and biological changes of these non-leukemic HSCs should be accompanied by the morphological changes of these cells. On the other hand, the quantity of these non-leukemic HSCs with morphological changes should reflect disease severity, prognosis and therapy responses. Thus, identification of non-leukemic HSCs in the leukemia bone marrow environment and monitoring of their quantity before, during and after treatments will potentially provide valuable information for correctly handling treatment plans and predicting outcomes. However, we have known that these morphological changes at the stem cell level cannot be extracted and identified by microscopic visualization with human eyes. In this study, we chose polycythemia vera (PV) as a disease model (a type of human myeloproliferative neoplasms derived from a hematopoietic stem cell harboring the JAK2V617F oncogene) to determine whether we can use artificial intelligence (AI) deep learning to identify and quantify non-leukemic HSCs obtained from bone marrow of JAK2V617F knock-in PV mice by analyzing single-cell images. We find that non-JAK2V617F-expressing HSCs are distinguishable from LSCs in the same bone marrow environment by AI with high accuracy (>96%). More importantly, we find that non-JAK2V617F-expressing HSCs from the leukemia bone marrow environment of PV mice are morphologically distinct from normal HSCs from a normal bone marrow environment of normal mice by AI with an accuracy of greater than 98%. These results help us prove the concept that non-leukemic HSCs undergo AI-recognizable morphological changes in the leukemia bone marrow environment and possess unique morphological features distinguishable from normal HSCs, providing a possibility to assess therapy responses and disease prognosis through identifying and quantitating these non-leukemic HSCs in patients. Full article

Objective: This study aims to determine how intestinal obstruction influences the tumor immune microenvironment (TIME) and its impact on prognosis in colorectal cancer (CRC). Methods: Immune cell densities (CD4⁺, CD8⁺, CD20⁺, CD68⁺) within central tumor (CT) and invasive margin (IM) compartments were quantitatively analyzed using immunohistochemistry (IHC) and QuPath digital pathology in surgical resection samples from 328 patients (164 obstructed colon cancer [OCRC] vs. 164 non-obstructed [NOCRC], cohorts matched by propensity scoring). Findings on tumor-infiltrating immune cell spatial distribution were integrated with peripheral blood immune cell counts and clinicopathological characteristics to characterize the obstructed colon cancer immune microenvironment. Associations with disease-free survival (DFS) and overall survival (OS) were evaluated. Results: OCRC exhibited higher lymphocytic infiltration, particularly in the CT compartment, compared to NOCRC, with significantly elevated CT-CD8⁺ T cell density in T4-stage OCRC (p < 0.005). Obstruction enhanced immune cell correlations across compartments, especially in T4 tumors, and the CD68⁺/CD8⁺ ratio effectively discriminated obstruction status (CT area under the curve (AUC): T4 = 0.879). Peripheral lymphocytopenia was pronounced in obstructive cases (p = 0.003). Critically, T4 OCRC showed a complete loss of all correlations between tumor-infiltrating immune cells and peripheral parameters. Despite increased infiltration, high CD8⁺ density in OCRC correlated with worse prognosis, indicating a paradoxical role influenced by obstruction context. CD68⁺ macrophages in the invasive margin consistently predicted improved survival (Disease-free survival [DFS]: Hazard ratio [HR] = 0.59, p = 0.008). Conclusions: Intestinal obstruction in CRC, particularly in T4-stage tumors, may represent an immunologically active state that alters local immune infiltration and systemic–local immune crosstalk. These findings suggest that obstruction status could refine prognostic stratification and inform therapeutic strategies, although validation in larger cohorts is warranted. Full article

Over one million international students from 207 countries study in the United States to pursue their academic goals. Transitioning to an unfamiliar country presents numerous challenges, and existing support structures often fail to fully support international students. Pet companionship may support students in alleviating homesickness and enhancing mental well-being. However, there is a lack of research exploring the experience of international students in the U.S. living with pets and what unique barriers they face. This quantitative survey recruited 662 international students to explore why they may or may not choose to live with pets while they are in the U.S. and the challenges they face regarding having pets while studying abroad. Participants reported barriers such as financial and housing restrictions, as well as concerns about pet care during travel or vacations and uncertainty about their future plans, which deter them from committing to long-term pet ownership. However, most of the participants who had experience living with pets or planned to have a pet believed that the benefits of having a pet outweighed the challenges. More than 60% of the participants were committed to keeping their pets permanently, even if they needed to move back to their home country or to another foreign country. While results are limited to a non-representative sample of international students, this research provides insights that may inform how to enrich support systems for both international students and animal welfare by highlighting the unique challenges and benefits of human–animal interactions for international students. Full article

Underwater imagery exhibits markedly more severe visual degradation than their terrestrial counterparts, manifesting as pronounced color aberration, diminished contrast and luminosity, and spatially non-uniform haze. To surmount these challenges, we propose the graph-aware framework for underwater image enhancement (GA-UIE), integrating specialized modules for color correction and texture restoration, a unified framework that explicitly utilizes the intrinsic graph information of underwater images to achieve high-fidelity color restoration and texture enhancement. The proposed algorithm is architected in three synergistic stages: (1) graph feature generation, which distills color and texture graph feature priors from the underwater image; (2) graph-aware enhancement, performing joint color restoration and texture sharpening under explicit graph priors; and (3) graph-aware fusion, harmoniously aggregating the graph-aware color and texture joint representations to yield the final visually coherent output. Comprehensive quantitative evaluations reveal that the output from our novel framework achieves the significant scores across a broad spectrum of metrics, including PSNR, SSIM, LPIPS, UCIQE, and UIQM on the UIEB and U45 datasets. These results decisively exceed those of all existing benchmark techniques, thereby validating the method’s exceptional efficacy in the enhancement of underwater imagery. Full article

Aging water pipelines are increasingly prone to structural failure, leakage, and ground subsidence, creating critical risks to urban infrastructure. Closed-circuit television endoscopy is widely used for internal assessment, but it depends on manual interpretation and lacks reliable quantitative defect information. Traditional vanishing point detection techniques, such as the Hough Transform, often fail under practical conditions due to irregular lighting, debris, and deformed pipe surfaces, especially when pipes are water-filled. To overcome these challenges, this study introduces a deep learning-based method that estimates inverse projection parameters from monocular endoscopic images. The proposed approach reconstructs a spatially accurate two-dimensional projection of the pipe interior from a single frame, enabling defect quantification for cracks, scaling, and delamination. This eliminates the need for stereo cameras or additional sensors, providing a robust and cost-effective solution compatible with existing inspection systems. By integrating convolutional neural networks with geometric projection estimation, the framework advances computational intelligence applications in pipeline condition monitoring. Experimental validation demonstrates high accuracy in pose estimation and defect size recovery, confirming the potential of the system for automated, non-disruptive pipeline health evaluation. Full article

Innovation in university education has become a key pillar for improving learning quality and ensuring faculty adaptation to the challenges of the 21st century. This study aims to analyze the innovative competence profile of university faculty, exploring their disposition toward innovation, the use of advanced pedagogical methodologies, and their integration of information and communication technologies (ICT). A quantitative, non-experimental, cross-sectional design was employed, using a validated questionnaire administered to a sample of 136 faculty members at the University of Murcia. Findings indicate that educational innovation in higher education is influenced by both individual and institutional factors. Female faculty members demonstrate greater openness to innovation, particularly in development and training, while those with intermediate teaching experience (11–20 years) report higher implementation of innovative methodologies compared to those with less than 10 years or more than 20 years of experience. Additionally, the Faculty of Education stands out for its integration of innovative strategies, in contrast to other faculties where adoption is more limited. Despite a generally positive attitude toward innovation, shortcomings were identified in the evaluation and dissemination of these methodologies, which hinder their consolidation within the academic community. The results highlight the need for institutional strategies that enhance teacher training, promote effective evaluation, and foster interfaculty collaboration to share experiences and best practices. Full article