Search Results (842)

Unmanned aerial vehicle (UAV) systems have recently become essential for mapping, surveying, and three-dimensional (3D) modeling applications. These systems are capable of providing highly accurate products through integrated advanced technologies, including a digital camera, inertial measurement unit (IMU), and Global Navigation Satellite System (GNSS). UAVs are a cost-effective alternative to traditional aerial photogrammetry, and recent advancements demonstrate their effectiveness in many applications. In UAV-based photogrammetry, ground control points (GCPs) are utilized for georeferencing to enhance positioning precision. The distribution, number, and location of GCPs in the study area play a crucial role in determining the accuracy of photogrammetric products. This research evaluates the accuracy of positioning techniques for image acquisition for photogrammetric production and the effect of GCP distribution models. The camera position was determined using real-time kinematic (RTK), post-processed kinematic (PPK), and precise point positioning-ambiguity resolution (PPP-AR) techniques. In the criteria for determining the GCPs, six models were established within the İstanbul Technical University, Ayazaga Campus. To assess the accuracy of the points in these models, the horizontal, vertical, and 3D root mean square error (RMSE) values were calculated, holding the test points stationary in place. In the study, 2.5 cm horizontal RMSE and 3.0 cm vertical RMSE were obtained with the model containing five homogeneous GCPs by the indirect georeferencing method. The highest RMSE values of all three components in RTK, PPK, and PPP-AR methods were obtained without GCPs. For all six models, all techniques have an error value of sub-decimeter. The PPP-AR technique yields error values that are comparable to those of the other techniques. The PPP-AR appears to be an alternative to RTK and PPK, which usually require infrastructure, labor, and higher costs. Full article

Background: Chemoresistance is an important issue to be solved in breast cancer. It is well known that the content and morphology of collagens in tumor tissues are drastically altered following chemotherapy, and discoidin domain receptor 2 (DDR2) is a unique type of receptor tyrosine kinase (RTK). This RTK is activated by collagens, playing important roles in human malignancies. However, the contribution to the chemoresistance of DDR2 in terms of the association with collagens remains largely unclear in breast cancer. Methods: We immunolocalized DDR2 and collagen type I in 224 breast cancer tissues and subsequently conducted in vitro studies to confirm the role of DDR2 in breast cancer chemoresistance using chemosensitive and chemoresistant cell lines. Results: DDR2 immunoreactivity was positively correlated with aggressive behaviors of breast cancer and was significantly associated with an increased risk of recurrence, especially in those who received chemotherapy. Moreover, in vitro experiments demonstrated that DDR2 promoted the proliferative activity of breast cancer cells, and cell viability after epirubicin treatment was significantly maintained by DDR2 in a collagen I-dependent manner. Conclusions: These data suggested that DDR2 could be a poor prognostic factor associated with cell proliferation and chemotherapy resistance in human breast cancer. Full article

The MET oncogene, encoding the hepatocyte growth factor (HGF) receptor, plays a key role in tumorigenesis, invasion, and resistance to therapy, yet its full biological functions and activation mechanisms remain incompletely understood. A feature of MET is its extensive interaction network, encompassing the following: (i) receptor tyrosine kinases (RTKs); (ii) co-receptors (e.g., CDCP1, Neuropilin1); (iii) adhesion molecules (e.g., integrins, tetraspanins); (iv) proteases (e.g., ADAM10); and (v) other receptors (e.g., CD44, plexins, GPCRs, and NMDAR). These interactions dynamically modulate MET’s activation, signaling, intracellular trafficking, and degradation, enhancing its functional versatility and oncogenic potential. This review offers current knowledge on MET’s partnerships, focusing on their functional impact on signaling output, therapeutic resistance, and cellular behavior. Finally, we evaluate emerging combination therapies targeting MET and its interactors, highlighting their potential to overcome resistance and improve clinical outcomes. By exploring the complex interplay within the MET network of interacting cell surface proteins, this review provides insights into advancing anti-cancer strategies and understanding the broader implications of RTK crosstalk in oncology. Full article

The objective of our research is to produce a digital elevation model (DEM) in a real-time domain. For this purpose, GNSS measurements are obtained from a kinematic trajectory in a clear location in New Aswan City, Egypt. Different real-time processing solutions are employed, including real-time precise point positioning (RT-PPP) and real-time kinematics (RTK); additionally, the widely used post-processed precise point positioning (PPP) processing scenario is used. Thereafter, the acquired positioning estimates are compared with the traditional kinematic differential GNSS solution counterparts. To achieve the RT-PPP mode, the instantaneous products from the Centre National d’Etudes Spatiales (CNES) are utilized. Our proposed models are validated for both kinematic positioning and DEM accuracies. For kinematic positioning accuracy validation, the findings indicate that the three-dimensional position is about 0.480 m, 0.101 m, and 0.628 for RT-PPP, RTK, and PPP solutions, respectively. Furthermore, the DEM accuracy investigation shows that the produced DEMs have accuracies within 0.249 m, 0.005 m, and 0.264 m for RT-PPP, RTK, and PPP solutions, respectively. Full article

Forests are crucial for biodiversity, climate regulation, and hydrological cycles, requiring sustainable management due to threats like deforestation and climate change. Traditional forest monitoring methods are labor-intensive and limited, whereas UAV LiDAR offers detailed three-dimensional data on forest structure and extensive coverage. This study primarily assesses individual tree segmentation algorithms in two forest ecosystems with different levels of complexity using high-density LiDAR data captured by the Zenmuse L1 sensor on a DJI Matrice 300RTK platform. The processing methodology for LiDAR data includes preliminary preprocessing steps to create Digital Elevation Models, Digital Surface Models, and Canopy Height Models. A comprehensive evaluation of the most effective techniques for classifying ground points in the LiDAR point cloud and deriving accurate models was performed, concluding that the Triangular Irregular Network method is a suitable choice. Subsequently, the segmentation step is applied to enable the analysis of forests at the individual tree level. Segmentation is crucial for monitoring forest health, estimating biomass, and understanding species composition and diversity. However, the selection of the most appropriate segmentation technique remains a hot research topic with a lack of consensus on the optimal approach and metrics to be employed. Therefore, after the review of the state of the art, a comparative assessment of four common segmentation algorithms (Dalponte2016, Silva2016, Watershed, and Li2012) was conducted. Results demonstrated that the Li2012 algorithm, applied to the normalized 3D point cloud, achieved the best performance with an F1-score of 91% and an IoU of 83%. Full article

During the past decade, a vast number of studies were dedicated to unravelling the obscurities of non-coding RNAs in all fields of the medical sciences. A great amount of data has been accumulated, and consequently a natural need for organization and classification in all subfields arises. The aim of this review is to summarize all reports on microRNAs that were delineated as prognostic biomarkers in laryngeal carcinoma. Additionally, we attempt to allocate and organize these molecules according to their association with key pathways and oncogenes affected in laryngeal carcinoma. Finally, we critically analyze the common shortcomings and biases of the methodologies in some of the published papers in this area of research. A literature search was performed using the PubMed and MEDLINE databases with the keywords “laryngeal carcinoma” OR “laryngeal cancer” AND “microRNA” OR “miRNA” AND “prognostic marker” OR “prognosis”. Only research articles written in English were included, without any specific restrictions on study type. We have found 43 articles that report 39 microRNAs with prognostic value associated with laryngeal carcinoma, and all of them are summarized along with the major characteristics and methodology of the respective studies. A second layer of the review is structural analysis of the outlined microRNAs and their association with oncogenes and pathways connected with the cell cycle (p53, CCND1, CDKN2A/p16, E2F1), RTK/RAS/PI3K cascades (EGFR, PI3K, PTEN), cell differentiation (NOTCH, p63, FAT1), and cell death (FADD, TRAF3). Finally, we critically review common shortcomings in the methodology of the papers and their possible effect on their results. Full article

Autonomous berthing is a critical phase in the fully autonomous navigation process of MASS (Maritime Autonomous Surface Ship). However, the autonomous berthing stage of MASS is significantly influenced by environmental factors and involves a wide range of technical fields, making the technology not yet fully mature. Therefore, this paper addresses three key technological challenges related to ship path planning, guidance and motion control, as well as position and state perception. Additionally, it explores the decision-making and control system architecture for autonomous berthing of MASS. An effective autonomous berthing solution for MASS is proposed. Based on vessel berthing maneuvering, a decision-making algorithm for autonomous berthing is designed. The A-star algorithm is optimized, and an expected path for unmanned boat experiments is designed offline using this algorithm. Subsequently, an indirect ship guidance and motion control program is proposed based on a CFDL-MFAC (Compact Form Dynamic Linearization based Model-Free Adaptive Control) algorithm. Experimental results show that the proposed autonomous berthing decision-making and control system architecture can effectively assist the unmanned boat in achieving autonomous berthing and help it to berth in a stable and desirable state. Full article

Plant height is a critical biophysical trait indicative of plant growth and developmental conditions and is valuable for biomass estimation and crop yield prediction. This study examined the effects of flight altitude and camera angle in quantifying cotton plant height using unmanned aerial system (UAS) imagery. This study was conducted in a field with a sub-surface irrigation system in Lubbock, Texas, between 2022 and 2023. Images using the DJI Phantom 4 RTKs were collected at two altitudes (40 m and 80 m) and three sensor angles (45°, 60°, and 90°) at different growth stages. The resulting images depicted six scenarios of UAS altitudes and camera angles. The derived plant height was subsequently calculated as the vertical difference between the apical region of the plant and the ground elevation. Linear regression compared UAS-derived heights to manual measurements from 96 plots. Lower altitudes (40 m) outperformed higher altitudes (80 m) across all dates. For the early season (4 July 2023), the 40 m altitude had r² = 0.82–0.86 and RMSE = 2.02–2.16 cm compared to 80 m (r² = 0.66–0.68, RMSE = 7.52–8.76 cm). Oblique angles (45°) yielded higher accuracy than nadir (90°) images, especially in the late season (24 October 2022) results (r² = 0.96, RMSE = 2.95 cm vs. r² = 0.92, RMSE = 3.54 cm). These findings guide optimal UAS parameters for plant height measurement. Full article

This technical note aims to present a method for developing a Digital Terrain Model (DTM) of the coastal zone based on topobathymetric data from remote sensors. This research was conducted in the waterbody adjacent to the Vistula Śmiała River mouth in Gdańsk, which is characterised by dynamic changes in its seabed topography. Bathymetric and topographic measurements were conducted using an Unmanned Aerial Vehicle (UAV) and two hydrographic methods (a Single-Beam Echo Sounder (SBES) and a manual survey using a Global Navigation Satellite System (GNSS) Real-Time Kinematic (RTK) receiver). The result of this research was the development of a topobathymetric chart based on data recorded by the above-mentioned sensors. It should be emphasised that bathymetric data for the shallow waterbody (less than 1 m deep) were obtained based on high-resolution photos taken by a UAV. They were processed using the “Depth Prediction” plug-in based on the Support Vector Regression (SVR) algorithm, which was implemented in the QGIS software as part of the INNOBAT project. This plug-in allowed us to generate a dense cloud of depth points for a shallow waterbody. Research has shown that the developed DTM of the coastal zone based on topobathymetric data from remote sensors is characterised by high accuracy of 0.248 m (p = 0.95) and high coverage of the seabed with measurements. Based on the research conducted, it should be concluded that the proposed method for developing a DTM of the coastal zone based on topobathymetric data from remote sensors allows the accuracy requirements provided in the International Hydrographic Organization (IHO) Special Order (depth error ≤ 0.25 m (p = 0.95)) to be met in shallow waterbodies. Full article

The growing demand for high-accuracy mapping and 3D modeling using unmanned aerial vehicles (UAVs) has accelerated advancements in flight dynamics, positioning accuracy, and imaging technology. Structure from motion (SfM), a computer vision-based approach, is increasingly replacing traditional photogrammetry through facilitating the automation of processes such as aerial triangulation (AT), terrain modeling, and orthomosaic generation. This study examines methods to enhance the accuracy of SfM-based AT through real-time kinematic (RTK) UAV imagery, focusing on large-scale infrastructure applications, including a dam and its entire basin. The target area, primarily consisting of homogeneous water surfaces, poses considerable challenges for feature point extraction and image matching, which are crucial for effective SfM. To overcome these challenges and improve the AT accuracy, a constraint equation was applied, incorporating weighted 3D coordinates derived from RTK UAV data. Furthermore, oblique images were combined with nadir images to stabilize AT, and confidence-based filtering was applied to point clouds to enhance geometric quality. The results indicate that assigning appropriate weights to 3D coordinates and incorporating oblique imagery significantly improve the AT accuracy. This approach presents promising advancements for RTK UAV-based AT in SfM-challenging, large-scale environments, thus supporting more efficient and precise mapping applications. Full article

Considerable variation in soil often occurs within and across production fields, which can significantly impact farming input management strategies. Optimizing resource utilization while enhancing crop productivity is critical for achieving Sustainable Development Goals (SDGs). This paper proposes a low-cost retrofittable Variable Rate Applicator Controller (VRAC) designed to leverage soil variability and facilitate the adoption of Variable Rate Technologies. The controller operates using a Raspberry Pi platform, RTK—Global Navigation Satellite System (GNSS), a stepper motor, and an anti-slip wheel encoder. The VRAC allows precise, on-the-fly control of the Variable Rate application of farming inputs utilizing an accurate GNSS to pinpoint geographic coordinates in real time. A wheel encoder measures accurate distance travel, providing a real-time calculation of speed with a slip-resistant wheel design for precise RPM readings. The Raspberry Pi platform processes the data, enabling dynamic adjustments of variability based on predefined maps, while the motor driver controls the motor’s RPM. It is designed to be plug-and-play, user-friendly, and accessible for a broader range of farming practices, including seeding rates, dry fertilizer, and liquid fertilizer application. Data logging is performed from various field sensors. The controller exhibits an average of 0.864 s for rate changes from 267 to 45, 45 to 241, 241 to 128, 128 to 218, and 218 to 160 kg/ha at speeds of 8, 11, 16, 19, 24, and 32 km/h. It has an average coefficient of variation of 4.59, an accuracy of 97.17%, a root means square error (RMSE) of 4.57, an R square of 0.994, and an average standard deviation of 1.76 kg for seeding discharge. The cost-effectiveness and retrofitability of this technology offer an increase in precision agriculture adoption to a broader range of farmers and promote sustainable farming practices. Full article

The Sprouty (SPRY) proteins are evolutionary conserved modulators of receptor tyrosine kinase (RTK) signaling. SPRY2 inhibits fibroblast growth factor (FGF) signaling, whereas it enhances epidermal growth factor (EGF) signaling through inhibition of EGF receptor (EGFR) endocytosis, ubiquitination, and degradation. In this study, we analyzed the effects of SPRY2 on endocytosis and degradation of FGF receptor 1 (FGFR1) using two human glioblastoma (GBM) cell lines with different endogenous SPRY2 levels. SPRY2 overexpression (SPRY2-OE) inhibited clathrin- and caveolae-mediated endocytosis of FGFR1, reduced the number of caveolin-1 vesicles and the uptake of transferrin. Furthermore, FGFR1 protein was decreased by SPRY2-OE, whereas EGFR protein was increased. SPRY2-OE enhanced FGFR1 degradation by increased c-casitas b-lineage lymphoma (c-CBL)-mediated ubiquitination, but it diminished binding of phospholipase Cγ1 (PLCγ1) to FGFR1. Consequently, SPRY2-OE inhibited FGF2-induced activation of PLCγ1, whereas it enhanced EGF-induced PLCγ1 activation. Despite the reduction of FGFR1 protein and the inhibition of FGF signaling, SPRY2-OE increased cell viability, and knockdown of SPRY2 enhanced the sensitivity to cisplatin. These results demonstrate that the inhibitory effect of SPRY2-OE on FGF signaling is at least in part due to the reduction in FGFR1 levels and the decreased binding of PLCγ1 to the receptor. Full article

This study addresses the challenges associated with single-system long-baseline real-time kinematic (RTK) navigation, including limited positioning accuracy, inconsistent signal reception, and significant residual atmospheric errors following double-difference corrections. This study explores the effectiveness of long-baseline RTK navigation using an integrated system of the BeiDou Navigation Satellite System (BDS), Global Positioning System (GPS), and Galileo Satellite Navigation System (Galileo). A long-baseline RTK approach that incorporates Kalman filtering and partial ambiguity resolution is applied. Initially, error models are used to correct ionospheric and tropospheric delays. The zenith tropospheric and inclined ionospheric delays and additional atmospheric error components are then regarded as unknown parameters. These parameters are estimated together with the position and ambiguity parameters via Kalman filtering. A two-step method based on a success rate threshold is employed to resolve partial ambiguity. Data from five long-baseline IGS monitoring stations and real-time measurements from a ship were employed for the dual-frequency RTK positioning experiments. The findings indicate that integrating additional GNSSs beyond the BDS considerably enhances both the navigation precision and the rate of ambiguity resolution. At the IGS stations, the integration of the BDS, GPS, and Galileo achieved navigation precisions of 2.0 cm in the North, 5.1 cm in the East, and 5.3 cm in the Up direction while maintaining a fixed resolution exceeding 94.34%. With a fixed resolution of Up to 99.93%, the integration of BDS and GPS provides horizontal and vertical precision within centimeters in maritime contexts. Therefore, the proposed approach achieves precise positioning capabilities for the rover while significantly increasing the rate of successful ambiguity resolution in long-range scenarios, thereby enhancing its practical use and exhibiting substantial application potential. Full article

When mooring a ship near the quay, it is important to monitor its speed at the time of contact with the quay to ensure the safe execution of the mooring operation. During mooring, the speed of the ship must not exceed specified values; therefore, it is very important to have the possibility to measure it with high accuracy and its appropriate adjustment. This article aims to present the assessment methodology of the forces acting on quay equipment when a ship is mooring using data provided by the real-time kinematic (RTK) application of the navigation satellite system, as well as a way to calculate the comparative index, which can show the advantages of using data provided by high-accuracy measurement systems compared with the typical one. The methodology of assessing the forces acting on quay equipment when the ship is mooring using data provided by high-precision systems was applied. To verify the developed methodology, the experiments were carried out on real ships and using a calibrated simulator. Based on the research results, it was stated that when planning and managing ships’ mooring operations in ports using data provided by the RTK application, it is possible to reduce the planned energy absorption of quay fenders up to 1.5–1.8 times while preparing the investment in quay development. The implementation of the developed methodology may contribute to the improvement of navigation safety when ships are mooring near the quays and thus allow for the reduction in the probability of undesirable situations occurring. The research results may be of interest to representatives of seaports authorities, traffic management offices, shipowners and other institutions involved in safe ships’ navigation in seaports and approaches to them. Full article

Purpose of Review: This review aims to describe the role of limbic system-associated membrane protein (LSAMP) in normal- and pathophysiology, and its potential implications in oncogenesis. We have summarized research articles reporting the role of LSAMP in the development of a variety of malignancies, such as clear cell renal cell carcinoma, prostatic adenocarcinoma, lung adenocarcinoma, osteosarcoma, neuroblastoma, acute myeloid leukemia, and epithelial ovarian cancer. We also examine the current understanding of how defects in LSAMP gene function may contribute to oncogenesis. Finally, this review discusses the implications of future LSAMP research and clinical applications. Recent Findings: LSAMP has been originally described as a surface adhesion glycoprotein expressed on cortical and subcortical neuronal somas and dendrites during the development of the limbic system. It is categorized as part of the IgLON immunoglobulin superfamily of cell-adhesion molecules and is involved in regulating neurite outgrowth and neural synapse generation. LSAMP is both aberrantly expressed and implicated in the development of neuropsychiatric disorders due to its role in the formation of specific neuronal connections within the brain. Additionally, LSAMP has been shown to support brain plasticity via the formation of neuronal synapses and is involved in modulating the hypothalamus in anxiogenic environments. In murine studies, the loss of LSAMP expression was associated with decreased sensitivity to amphetamine, increased sensitivity to benzodiazepines, increased hyperactivity in new environments, abnormal social behavior, decreased aggressive behavior, and decreased anxiety. Findings have suggested that LSAMP plays a role in attuning serotonergic activity as well as GABA activity. Given its importance to limbic system development, LSAMP has also been studied in the context of suicide. In malignancies, LSAMP may play a significant role as a putative tumor suppressor, the loss of which leads to more aggressive phenotypes and mortality from metastatic disease. Loss of the LSAMP gene facilitates epithelial-mesenchymal transition, or EMT, where epithelial cells lose adhesion and gain the motile properties associated with mesenchymal cells. Additionally, LSAMP and the function of the RTK pathway have been implicated in tumorigenesis through the modulation of RTK expression in cell membranes and the activation of second messenger pathways and β-catenin. Summary: Beyond its many roles in the limbic system, LSAMP functions as a putative tumor suppressor protein. Loss of the LSAMP gene is thought to facilitate epithelial-mesenchymal transition, or EMT, where cells lose adhesion and migrate to distant organs. LSAMP’s role in modulating RTK activity and downstream ERK and Akt pathways adds to a large body of data investigating RTK expression in oncogenesis. The characteristics of LSAMP defects and their association with aggressive and metastatic disease are evident in reports on clear cell renal cell carcinoma, prostatic adenocarcinoma, lung adenocarcinoma, osteosarcoma, neuroblastoma, acute myeloid leukemia, and epithelial ovarian cancer. Full article