Search Results (105)

Existing Simultaneous Localization and Mapping (SLAM) algorithms provide precise local pose estimation and real-time scene reconstruction, widely applied in autonomous navigation for land vehicles. However, the odometry of SLAM algorithms exhibits localization drift and error divergence over long-distance operations due to the lack of inherent global constraints. In this paper, we propose a real-time geo-localization method for land vehicles, which only relies on a LiDAR-inertial-visual SLAM (LIV-SLAM) and a referenced image. The proposed method enables long-distance navigation without requiring GPS or loop closure, while eliminating accumulated localization errors. To achieve this, the local map constructed by SLAM is real-timely projected onto a downward-view image, and a highly efficient cross modal matching algorithm is proposed to estimate the global position by aligning the projected local image to a geo-referenced satellite image. The cross-modal algorithm leverages dense texture orientation features, ensuring robustness against cross-modal distortion and local scene changes, and supports efficient correlation in the frequency domain for real-time performance. We also propose a novel adaptive Kalman filter (AKF) to integrate the global position provided by the cross-modal matching and the pose estimated by LIV-SLAM. The proposed AKF is designed to effectively handle observation delays and asynchronous updates while simultaneously rejecting the impact of erroneous matches through an Observation-Aware Gain Scaling (OAGS) mechanism. We verify the proposed algorithm through R³LIVE and NCLT datasets, demonstrating superior computational efficiency, reliability, and accuracy compared to existing methods. Full article

The Living Well with Dementia (LivDem) group intervention aims to support people to adjust following a diagnosis of dementia and is delivered across the UK and abroad. However, LivDem was designed for older people with dementia and may not address the needs of younger adults. This study aimed to identify the perspectives of LivDem facilitators on adapting the LivDem course for younger adults. Data was collected as part of an online facilitator survey and included questions requiring either ordinal or free-text responses. Responses from fifteen facilitators were analysed using descriptive statistics and Reflexive Thematic Analysis. The former indicated that participants believed that LivDem could be beneficial for younger adults and were in favour of it being adapted. Qualitative analysis generated two main themes, the first of which (‘The domino effect’: Unique Challenges for Younger Adults) had two subthemes: ‘Life and opportunities stripped away’ and ‘Impacting on everyone’. Theme 2, ‘Good to be with peers’: The Importance of Age-Appropriate Support, also had two subthemes: Groups ‘full of old people’ and Groups ‘specifically for younger people’. These findings reinforce the argument for creating age-appropriate services for people with young-onset dementia and will inform an adapted version of LivDem that provides age-appropriate support. Full article

Lightning-induced voltages (LIVs) computation is crucial for lightning protection of power systems and equipment, yet the effect of complex terrain on LIVs remains not fully evaluated. This study establishes a three-dimensional finite-difference time-domain model to investigate the LIVs over Gaussian-shaped mountainous terrain, considering different lightning strike locations. Simulation results show that the influence of Gaussian-shaped mountains on LIVs is directly related to the lightning strike location. Compared with the flat ground scenario, the LIVs’ amplitude can increase by approximately 56% when lightning strikes the mountain top. However, for lightning strikes to the ground adjacent to the mountain, the LIVs’ amplitude is attenuated to varying degrees due to the shielding effect of the mountain. Additionally, the influences of line configuration, as well as mountain height and width on the LIVs, are evaluated. Full article

We reanalyze the spectral lag data for 56 Gamma-Ray Bursts (GRBs) in the cosmological rest frame to search for Lorentz Invariance Violation (LIV) using frequentist inference. For this purpose, we use the technique of profile likelihood to deal with the nuisance parameters, corresponding to a constant time lag in the GRB rest frame and an unknown intrinsic scatter, while the parameter of interest is the energy scale for LIV ($E_{QG}$). With this method, we do not obtain a global minimum for ${\chi }^2$ as a function of $E_{QG}$ up to the Planck scale. Thus, we can obtain one-sided lower limits on $E_{QG}$ in a seamless manner. Therefore, the 95% c.l. lower limits which we thus obtain on $E_{QG}$ are then given by $E_{QG}\ge 2.07\times {10}^{14}$ GeV and $E_{QG}\ge 3.71\times {10}^5$ GeV, for linear and quadratic LIV, respectively. Full article

Background/Objectives: Proximal junctional kyphosis (PJK) is one of the most frequently discussed complications following corrective surgery in patients with neuromuscular scoliosis (NMS). Despite its clinical relevance, the etiology of PJK remains incompletely understood and appears to be multifactorial. Biomechanical and limited clinical studies suggest that preoperative hyperkyphosis, resection of the spinous processes with consequent disruption of posterior ligamentous structures, and rod contouring parameters may contribute as risk factors. Methods: To validate these findings, we retrospectively analyzed 99 NMS patients who underwent posterior spinal fusion using a standardized screw-rod system between 2009 and 2017. Radiographic assessments were conducted at three time points: preoperatively (preOP), postoperatively (postOP), and at a mean follow-up (FU) of 29 months. Clinical variables collected included patient age, weight, height, sex, and Risser sign. Radiographic evaluations encompassed Cobb angles, thoracic kyphosis (TK), lumbar lordosis, the levels of the upper (UIV) and lower (LIV) instrumented vertebrae, the total number of fused segments, parameters of sagittal alignment, the rod contour angle (RCA), and the postoperative mismatch between RCA and the proximal junctional angle (PJA). Based on the development of proximal junctional kyphosis, patients were categorized into PJK and non-PJK groups. Results: The overall incidence of PJK was 23.2%. In line with previous biomechanical findings, spinous process resection was significantly associated with PJK development. Furthermore, the PJK group demonstrated significantly higher preoperative TK (59.3° ± 29.04° vs. 34.5° ± 26.76°, p < 0.001), greater RCA (10.2° ± 4.01° vs. 7.7° ± 4.34°, p = 0.021), and a larger postoperative mismatch between PJA and RCA (PJA−RCA: 3.8° ± 6.76° vs. −1.8° ± 6.55°, p < 0.001) compared to the non-PJK group. Conclusions: Spinous process resection, a pronounced mismatch between postoperative PJA and RCA (odds ratio [OR] = 1.19, p = 0.002), excessive rod bending (i.e., high RCA), and severe preoperative thoracic hyperkyphosis with an expected increase in the risk of PJK of approximately 6.5% per degree of increase in preoperative TK are significant risk factors for PJK. These variables should be carefully considered during the surgical planning and execution of deformity correction in NMS patients. Full article

The spread of biometric systems utilizing fingerprints has increased the need for advanced spoof detection techniques, but training convolutional neural networks (CNNs) with the limited number of images available in fingerprint datasets poses significant challenges. In this paper, we propose a lightweight network architecture which addresses the challenges inherent in small fingerprint datasets by employing a moderately deep network architecture which is sufficient for extracting essential features from fingerprint images. We apply a hyperbolic tangent activation to the final feature map, which has features from local receptive fields, and average the responses into a single value. Thus, our architecture reduces overfitting by increasing the number of effective labels during training. Additionally, the incorporation of the spatial attention module enhances feature representation, culminating in improved accuracy. The evaluation results show that the proposed model, with only 0.14 million parameters, outperforms existing techniques including lightweight models and transfer-learning-based models, achieving superior average test accuracies of 98.30% and 95.57% on the LivDet-2015 and -2017 datasets, respectively. It also delivers state-of-the-art cross-material performance, with corresponding average classification error values of 0.81% and 1.91%, making it highly effective for on-device fingerprint authentication. Full article

Ground segmentation in LiDAR point clouds is a foundational capability for autonomous systems, enabling safe navigation in applications ranging from urban self-driving vehicles to planetary exploration rovers. Reliably distinguishing traversable surfaces in geometrically irregular or sensor-sparse environments remains a critical challenge. This paper introduces a hybrid framework that synergizes multi-resolution polar discretization with sparse convolutional neural networks (SCNNs) to address these challenges. The method hierarchically partitions point clouds into adaptive sectors, leveraging PCA-derived geometric features and dynamic variance thresholds for robust terrain modeling, while a SCNN resolves ambiguities in data-sparse regions. Evaluated in structured (SemanticKITTI) and unstructured (Rellis-3D) environments, two different versions of the proposed method are studied, including a purely geometric method and a hybrid approach that exploits deep learning techniques. A comparison of the proposed method with its purely geometric version is made for the purpose of highlighting the strengths of each approach. The hybrid approach achieves state-of-the-art performance, attaining an F1-score of 95.4% in urban environments, surpassing the purely geometric (91.4%) and learning-based baselines. Conversely, in unstructured terrains, the geometric variant demonstrates superior metric balance (80.8% F1) compared to the hybrid method (75.8% F1), highlighting context-dependent trade-offs between precision and recall. The framework’s generalization is further validated on custom datasets (UMH-Gardens, Coimbra-Liv), showcasing robustness to sensor variations and environmental complexity. The code and datasets are openly available to facilitate reproducibility. Full article

Background: Epizootics of largemouth bass ranavirus (LMBRaV) in largemouth bass (Micropterus salmoides) populations are associated with elevated mortality and significant financial losses. Given the lack of effective and safe medication to treat this disease, oral vaccination, which directly targets the intestinal mucosal immune system, is crucial for disease resistance. Methods: This study utilized carboxymethyl cellulose (CMC) to coat LMBRaV inactivated vaccine (LIV) (micro-CMC@LIV). The morphology and characteristics of the CMC microcapsules were determined. In vitro simulated gastric and intestinal conditions were used to validate that the microcapsules could tolerate gastric conditions and subsequently release their contents in the intestinal tract. This was confirmed using CMC-coated coumarin 6 (C6) fluorescence microcapsules. Results: After the oral administration of micro-CMC@LIV, the detection of LMBRaV major capsid protein confirmed effective antigen release and absorption in the midgut and hindgut. Neutralizing antibody titers were significantly higher (1:81.71) in the micro-CMC@LIV group compared to the uncoated vaccine group (1:21.69). The expression of genes linked to the innate and adaptive immune systems was upregulated post-micro-CMC@LIV treatment. Following the LMBRaV challenge, the micro-CMC@LIV group exhibited a relative percent survival (RPS) of 82.14%, significantly higher than the uncoated vaccine group (61.61%). Droplet digital PCR analysis revealed significantly lower viral loads in the liver, spleen, and head kidney of the micro-CMC@LIV group compared to the control group and the uncoated vaccine group. Conclusions: These results collectively suggest that the CMC-coated LIV can be effectively delivered to the intestinal tract and induce robust antibody and immune responses, providing a reliable method for preventing and controlling LMBRaV disease in the largemouth bass industry. Full article

In this paper, we address the challenge of fingerprint liveness detection by proposing a dual pre-trained model approach that combines VGG16 and ResNet50 architectures. While existing methods often rely on a single feature extraction model, they may struggle with generalization across diverse spoofing materials and sensor types. To overcome this limitation, our approach leverages the high-resolution feature extraction of VGG16 and the deep layer architecture of ResNet50 to capture a more comprehensive range of features for improved spoof detection. The proposed approach integrates these two models by concatenating their extracted features, which are then used to classify the captured fingerprint as live or spoofed. Evaluated on the Livedet2013 and Livedet2015 datasets, our method achieves state-of-the-art performance, with an accuracy of 99.72% on Livedet2013, surpassing existing methods like the Gram model (98.95%) and Pre-trained CNN (98.45%). On Livedet2015, our method achieves an average accuracy of 96.32%, outperforming several state-of-the-art models, including CNN (95.27%) and LivDet 2015 (95.39%). Error rate analysis reveals consistently low Bonafide Presentation Classification Error Rate (BPCER) scores with 0.28% on LivDet 2013 and 1.45% on LivDet 2015. Similarly, the Attack Presentation Classification Error Rate (APCER) remains low at 0.35% on LivDet 2013 and 3.68% on LivDet 2015. However, higher APCER values are observed for unknown spoof materials, particularly in the Crossmatch subset of Livedet2015, where the APCER rises to 8.12%. These findings highlight the robustness and adaptability of our simple dual-model framework while identifying areas for further optimization in handling unseen spoof materials. Full article

Recently there have been several studies devoted to the investigation of the fate of fundamental relativistic symmetries at the foreseen unification of gravity and quantum regime, that is the Planck scale. In order to preserve covariance of the formulation even if in an amended formulation, new mathematical tools are required. In this work, we consider DSR theories that modify covariance by introducing a non-trivial structure in momentum space. Additionally, we explore the possibility of investigating both universal quantum gravity corrections and scenarios where different particle species are corrected differently within the framework of these models. Several astroparticle phenomena are then analyzed to test the phenomenological predictions of DSR models. Full article

Background/Objectives. Correction of thoracolumbar/lumbar curvature in adolescent idiopathic scoliosis (AIS) patients with Lenke 1-2 B and C is still controversial, with regard to extension of the caudal side to the lowest instrumented vertebra (LIV) and method of correction. We assessed the association between change in thoracolumbar/lumbar curvature after surgery with counterrotate technique (CRT) and clinical factors in 45 thoracic AIS patients. Methods. Forty-five AIS patients (mean follow-up 5.1 y, age 15 y, Type B: 28, Type C: 17) were analyzed. Posterior spinal fusion was performed by the placing of segmental uni-planar screws, concave rod rotation, differential rod countering, and segmental CRT. Association between change in thoracolumbar/lumbar curvature after surgery with counter-rotate technique and clinical factors was analyzed in 45 thoracic AIS patients. Results. Mean main thoracic Cobb angle was 52°, and mean thoracolumbar/lumbar curvature Cobb angle was 35°. Postoperative thoracolumbar/lumbar Cobb was 10.1, and final follow-up was 8.2. Multi logistic regression analysis of change in thoracolumbar/lumbar Cobb after surgery was performed. Age (p < 0.05), Risser sign (p < 0.05), and postoperative thoracolumbar/lumbar Cobb (p < 0.0001) were significantly associated with a change in Cobb angle. Conclusions. Correction of thoracolumbar/lumbar curvature using CRT showed significant improvement of thoracolumbar/lumbar curvature, LIV tilting angle, and vertebral rotation. Postoperative thoracolumbar/lumbar Cobb angle (1st erect) was the most significant factor associated with deterioration of thoracolumbar/lumbar curvature after surgery. Subsequent rotational correction of thoracolumbar/lumbar curvature is likely to prevent the deterioration of thoracolumbar/lumbar Cobb after surgery. Full article

The European subtype of tick-borne encephalitis virus (TBEV-Eur; species Orthoflavivirus encephalitidis, family Flaviviridae) was the only tick-borne flavivirus present in central Europe known to cause neurologic disease in humans and several animal species. Here, we report a tick-borne flavivirus isolated from Alpine chamois (Rupicapra rupicapra rupicapra) with encephalitis and attached ticks, present over a wide area in the Alps. Cases were detected in 2017 in Salzburg, Austria, and 2023 in Lombardy and Piedmont, Italy. The virus strains exhibit 94.8–97.3% nucleotide identities to each other and are more closely related to Louping ill viruses (LIV; Orthoflavivirus loupingi; 90–92% identities) than to TBEV-Eur (less than 88%). The chamois-derived virus strains, tentatively termed “Alpine chamois encephalitis virus”, form a well-supported independent genetic clade with Spanish goat encephalitis virus, clearly separated from other LIV. This supports its designation as a new virus subtype with the proposed shared taxonomic name “Spanish goat and Alpine chamois encephalitis virus subtype” within the species Orthoflavivirus loupingi. The zoonotic potential of this newly identified virus subtype as well as its host range in other animal species including farm animals needs to be further investigated. Full article

To meet the needs of English learners (ELs) and the call of the Next Generation Science Standards to engage all students in communicating science ideas, a collaboration between science, second language acquisition, and disciplinary literacy teacher educators resulted in a trifocal approach within a reformed science teacher education program. The purpose of this study is to explore how TeachLivE^TM, a mixed-reality simulation technology, was used to prepare preservice teachers (PSTs) to support ELs in communicating science ideas through questioning. Findings from transcribed lessons, coaching sessions, and PST self-reports show that TeachLivE^TM provided opportunities to practice questioning and reflect on challenges, and was a collaborative learning context. The significance for secondary science teacher education and inservice teacher professional development is presented. Full article

Antibody–drug conjugates (ADCs) have revolutionized the treatment landscape for metastatic breast cancer, offering targeted delivery of cytotoxic agents with improved efficacy and tolerability compared to conventional chemotherapy. This narrative review explores key predictive factors influencing the efficacy of ADCs, focusing on HER2-targeted therapies, such as trastuzumab emtansine and trastuzumab deruxtecan, as well as sacituzumab govitecan for triple-negative breast cancer. HER2 expression, TROP-2 levels, hormone receptor status, and the tumor microenvironment emerge as critical biomarkers for patient selection and therapeutic outcomes. Additionally, we discuss resistance mechanisms, such as antigen loss, impaired drug internalization, and the role of circulating tumor DNA in predicting ADC response. Finally, future perspectives on the sequential use of ADCs and potential combination therapies are highlighted, along with emerging agents targeting alternative antigens like HER3 and LIV-1. Overall, identifying predictive biomarkers and overcoming resistance mechanisms are essential for optimizing the use of ADCs in metastatic breast cancer, thereby improving patient outcomes. Full article

Although rice is highly sensitive to salinity, it is considered one of the best crops to grow in salt-affected mudflat soils to alleviate the salinity problem. Applying chemical compounds for an increase in leaf CO₂ and nutrient levels can help mitigate the negative impact of salinity on plants in a cost-effective manner. To identify the benefits of using lithovit (Liv), ethanol (Eth), and potassium carbonate (KC) as a source of CO₂ and K to enhance rice production in salt-affected soils, a field study was conducted to assess the effects of these compounds on the agro-physiological parameters of two rice genotypes (Giza178 and Giza179) in saline soils. The compounds were applied as a foliar spray at a concentration of 30 mM each before and after the heading growth stage. The results indicated that the genotype, application time, compounds, and their potential two-way interactions significantly influenced all agro-physiological parameters, with only a few exceptions. The genotype Giza 179 exhibited higher pigment contents, photosynthetic capacity, relative water content (RWC), grain yield, and most yield components compared to Giza 178, with increases ranging from 2.1% to 37.9%. Foliar application of different compounds resulted in a 9.7–37.9% increase in various parameters and a 34.6–43.2% decrease in the number of unfilled grains (NUFG) per panicle compared to untreated treatment. Foliar application of different compounds before heading resulted in an increase in various parameters by 4.8–16.1% and a decrease in the NUFG per panicle by 22.9% compared to those applied after heading. Heatmap clustering analysis revealed that foliar application of Liv before heading was the most effective treatment in enhancing various parameters for both genotypes and mitigating the negative effects of salinity stress on the NUFG. This was followed by Eth and KC before heading for Giza 179. Applying Eth and KC to the leaves after heading had a moderate positive impact on most parameters for Giza 179, outperforming the application after heading for Giza 178. Overall, our findings indicate that spraying readily available compounds that elevate CO₂ and K levels in rice leaves can help alleviate the negative impacts of salt stress and improve rice production in salt-affected soils in a cost-effective manner. Full article