Line Identification Research Articles

Advancements in Deep Learning for Minimally Invasive Surgery: A Journey through Surgical System Evolution

The surge in artificial intelligence (AI) applications across diverse fields owes much to advancements in deep learning and computational processing speed. In medicine, AI's reach extends to medical image analysis and genomic data interpretation. More recently, AI's role in analyzing minimally invasive surgery (MIS) videos has gained traction, with a growing body of research focusing on organ and anatomy identification, instrument recognition, procedure recognition, surgical phase delineation, surgery duration prediction, optimal incision line identification, and surgical education. Concurrently, the development of autonomous surgical robots, exemplified by the Smart Tissue Autonomous Robot (STAR) and RAVEN systems, has shown promising strides. Notably, STAR is currently employed in laparoscopic imaging to discern the surgical site from laparoscopic images and is undergoing trials for an automated suturing system, albeit in animal models. This review contemplates the prospect of fully autonomous surgical robots in the future.

Advancements in Deep Learning for Minimally Invasive Surgery: A Journey through Surgical System Evolution

The surge in artificial intelligence (AI) applications across diverse fields owes much to advancements in deep learning and computational processing speed. In medicine, AI's reach extends to medical image analysis and genomic data interpretation. More recently, AI's role in analyzing minimally invasive surgery (MIS) videos has gained traction, with a growing body of research focusing on organ and anatomy identification, instrument recognition, procedure recognition, surgical phase delineation, surgery duration prediction, optimal incision line identification, and surgical education. Concurrently, the development of autonomous surgical robots, exemplified by the Smart Tissue Autonomous Robot (STAR) and RAVEN systems, has shown promising strides. Notably, STAR is currently employed in laparoscopic imaging to discern the surgical site from laparoscopic images and is undergoing trials for an automated suturing system, albeit in animal models. This review contemplates the prospect of fully autonomous surgical robots in the future.

Identification of the optimal racing line for top male athletes on a segment of a World Cup downhill alpine ski slope using tracking data

Using tracking data we can identify the optimal racing line for top male athletes on the famous S-curved segment (Brueggli-S) of the downhill FIS world cup track “Lauberhorn” in Switzerland. For this, we have measured and analysed training runs, measured on a single day, of 10 world class athletes. Based on curvatures derived from the tracking data, a large variation in racing lines adopted by the athletes was observed. Each of the detected racing lines share a similar pattern: The maximum curvature in the first curve is strongly correlated with the minimum curvature of the second curve. We have found that, for the athletes under investigation, the overall best racing line is characterized by a defined ratio of the maximum curvature of the first to the second curve. We claim that the observed correlation, as well as the optimal ratio of curvatures, is universal for a class of athletes with nearly identical performance levels. If and how this ratio varies for different classes of athletes (i.e. U10, U12 or U16 athletes) is an as yet unanswered question and remains open to further investigation.

Large-scale relativistic calculations of spectral data in Zr XXVIII, Nb XXIX and Tc XXXI of tokamak interest

Large-scale relativistic multiconfiguration Dirac–Fock calculations of energy levels and lifetimes of the 206 states arising from the 3s23p, 3p3, 3s3p3d, 3p3d2, 3s24p, 3s24f, 3s3p2, 3s23d, 3s3d2, 3s24d, 3s24s, 3s3p4s, 3s3p4d, 3p23d, 3d3, and 3s3p4p configurations of Zr XXVIII, Nb XXIX, and Tc XXXI of tokamak interest are carried out. The active space approximation is employed for the calculations. To obtain accurate and convergent results, the calculations take into account the valence and core-valence correlations within the n= 9 complex, as well as the Breit interaction, self-energy corrections, and vacuum polarization corrections. Detailed information regarding the decay properties of these ions is provided, including the transition wavelengths, line strengths, and radiative transition rates for various types (electric dipole, electric quadrupole, magnetic dipole, and magnetic quadrupole transitions) of transitions among the levels of the aforementioned configurations. The uncertainties of each dipole transition are evaluated. The present data sets are compared to previous results and a good agreement is observed, which is valuable for emission line identification and fusion modeling, especially in situations where experimental data are scarce.

Molecular and Cytological Identification of Wheat-Thinopyrum intermedium Partial Amphiploid Line 92048 with Resistance to Stripe Rust and Fusarium Head Blight.

Thinopyrum intermedium (2n = 6x = 42, EeEeEbEbStSt or JJJsJsStSt) contains a large number of genes that are highly adaptable to the environment and immune to a variety of wheat diseases, such as powdery mildew, rust, and yellow dwarf, making it an important gene source for the genetic improvement of common wheat. Currently, an important issue plaguing wheat production and breeding is the spread of pests and illnesses. Breeding disease-resistant wheat varieties using disease-resistant genes is currently the most effective measure to solve this problem. Moreover, alien resistance genes often have a stronger disease-resistant effect than the resistance genes found in common wheat. In this study, the wheat-Th. intermedium partial amphiploid line 92048 was developed through hybridization between Th. intermedium and common wheat. The chromosome structure and composition of 92048 were analyzed using ND-FISH and molecular marker analysis. The results showed that the chromosome composition of 92048 (Octoploid Trititrigia) was 56 = 42W + 6J + 4Js + 4St. In addition, we found that 92048 was highly resistant to a mixture of stripe rust races (CYR32, CYR33, and CYR34) during the seedling stage and fusarium head blight (FHB) in the field during the adult plant stage, suggesting that the alien or wheat chromosomes in 92048 had disease-resistant gene(s) to stripe rust and FHB. There is a high probability that the gene(s) for resistance to stripe rust and FHB are from the alien chromosomes. Therefore, 92048 shows promise as a bridge material for transferring superior genes from Th. intermedium to common wheat and improving disease resistance in common wheat.

Benchmarking calculations of level energies, transition parameters and electron impact excitation cross sections of S-like Xe38+

Atomic structure parameters for levels corresponding to 2s22p63s23p4, 2s22p63s3p5, 2s22p63s23p23d2, 2s22p63s3p43d and 2s22p63s23p33d configurations of S-like Xe38+ are calculated using the fully relativistic multiconfiguration Dirac-Hatree-Fock (MCDHF) method followed by the subsequent relativistic configuration interaction (RCI) calculations. The parameters evaluated include energies of the lowest 75 levels and E1, M1, E2, and M2 transition parameters among these levels. The effect of the choice of virtual orbitals for generating the wavefunctions is discussed. The accuracy of our line strengths is established through the rigorous calculations of their associated uncertainties using three different methods. Another set of calculations using the many-body perturbation theory (MBPT) to validate the present MCDHF-RCI energies is carried out. Further, the electron impact excitation cross-sections using the relativistic distorted wave (RDW) theory are determined for all transitions from the ground and metastable states in the incident electron energy range from the excitation threshold to 10 keV. For plasma physics applications, the fitting parameters for these cross sections employing two distinct equations tailored for low and high-energy regimes are reported. Moreover, the rate coefficients are determined in the electron temperatures range of 15 eV to 100 eV by taking into account the Maxwellian electron energy distribution function and our computed cross-sections. In addition to addressing the atomic data gap in highly charged Xe ions, the present results are of good accuracy and can serve as benchmark tests for other theoretical evaluations. Moreover, they can also assist in line identification of the complex spectra of highly charged sulphur-like xenon ions.

Automatic Recognition Technology of Library Books Based on Convolutional Neural Network Model

Background: The development of technological devices has changed many facets of our lives, particularly the way we engage with information and learning. The advent of automated technology for identification has had a had a revolutionary effect on how we read and organize books within the context of books and data searches. It starts by solving the difficulties in analyzing photos of book pages by using methods such as distortion rectification and book separation. Objective: The research compares the effectiveness of the suggested method with traditional straight-line identification techniques using real-world testing. Methodology: The Skip-Gram model in Word2Vec is used to accurately represent spoken language, allowing word vectors to be generated and input data to be preprocessed for CNN. The results show that the methodology created regarding the present investigation works better than alternatives concerning accuracy and efficiency during line identification. Result:This work advances the field of book suggestion systems by presenting a strong and effective method that leverages CNNs. The findings demonstrate deep learning techniques may be used to optimize system recommendations and improve customer service and happiness in a variety of contexts. This technique creates a bridge between natural language processing and picture evaluation and opens up new possibilities for suggestion advancement along with user satisfaction. Doi: 10.28991/HIJ-2024-05-01-015 Full Text: PDF

Study of radiative shocks using 2D interferometry and XUV spectroscopy

We report new experimental results on radiative shocks obtained in Xenon and Argon in gas cells at two different pressures below 1 bar. These shock waves are generated by the interaction of the PALS iodine laser on a CH–Au foil with a typical velocity in the range of 50–100 km/s depending on the variable laser intensity, pressure, and gas. Attention is paid to the morphology and the dynamics of the radiative precursor over large time scales up to 30 ns, using 2D sub-picosecond visible interferometry, illustrating the complex interplay of hydrodynamic and radiation absorption for different initial conditions. The comparison between 1D and 2D simulations confirms the role played by lateral radiative losses in the ionization wave and the necessity of state-of-the-art integrated opacities. This study is complemented by the first XUV analysis of the shock emission between 5 and 20 nm obtained with a grating spectrometer, with line identification, which is compatible with the ionization stages deduced from interferometry and simulations.

An Adaptive Reclosing Scheme for All-Parallel Autotransformer Traction Network of High-Speed Railway Based on Multisource Information

In high-speed railway (HSR), directly reclosing a circuit breaker after a fault trip can result in a large second overcurrent, causing insulation degradation, equipment damage, and even system instability. Meanwhile, existing direct reclosing schemes fail to simultaneously identify the faulty line, fault property, and fault type, especially for all-parallel autotransformer traction networks (AATNs). Therefore, an adaptive reclosing scheme for AATNs based on multi-source information is proposed in this paper, including two critical methods of faulty line identification, and fault property and type identification. Specifically, a multi-source fault impedance angles integrated faulty line identification method is proposed to effectively distinguish the faulty line and healthy line. Moreover, a novel approach is developed to incorporate multi-source line-to-line induced voltages obtained by reclosing the healthy line, which facilitates the fault property and type identification. The effectiveness and superiority of the proposed reclosing scheme are demonstrated using field tests and simulation experiments. In addition, the proposed scheme not only shortens the power outage time of healthy line, but also completely avoids second damages to equipment, and prevents power outages when the feeder is permanently faulted to the ground, presenting its remarkable robustness benefiting from multi-source information.

“Defining the Isoelectric Line in Electrocardiography”: A Comprehensive Review

Electrocardiography (ECG or EKG) is a fundamental tool in cardiovascular diagnosis, relying on the accurate identification of the isoelectric line as a reference point. However, the definition of the isoelectric line has encountered controversies and nuances, particularly regarding its association with the TP segment, the ST segment under specific conditions, and the PQ junction in select circumstances. This comprehensive review navigates through these complexities, addressing clinical implications, methodological challenges, and potential future directions. Understanding the isoelectric line’s intricacies is essential for precise EKG interpretation and informed clinical decision-making in cardiology.

Construction and identification of a stable CT26 cell line expressing CD19-FLUC-GFP

Solid tumors lack well-defined targets for chimeric antigen receptor T-cell (CAR-T) therapy. Therefore, introducing a known target molecule, CD19, into solid tumor cell lines via lentiviral transduction to investigate the cytotoxicity of CD19 CAR-T cells can potentially support CAR-T cell therapy against solid tumors. In this study, a stable colon cancer CT26 cell line, CT26-CD19-FLUC-GFP, expressing CD19, firefly luciferase (FLUC), and green fluorescent protein (GFP), was constructed using a triple-plasmid lentiviral system. The growth characteristics of this cell line were consistent with those of the CT26 cell line. Subsequent flow cytometry analysis confirmed stable expression of CD19 and GFP in CT26-CD19-FLUC-GFP cells after serial passaging up to the 5th, 10th, and 22nd generations. Further validation revealed significantly higher levels of CD19 mRNA and FLUC expression in CT26-CD19-FLUC-GFP cells continuously passaged up to the 22nd generation compared to the control CT26 cells. In comparison to T cells, CD19 CAR-T cells demonstrated substantial cytotoxicity against CT26-CD19-FLUC-GFP cells and MC38-CD19 cells. One week after intraperitoneal implantation of CT26-CD19-FLUC-GFP cells into mice, FLUC expression in the peritoneal region could be detected. These results indicate the successful establishment of a stable CT26 cell line expressing CD19-FLUC-GFP, which can be specifically targeted by CD19 CAR-T cells.

A low-cost vision-based weld-line detection and measurement technique for robotic welding

ABSTRACT To make robotic welding more flexible and intelligent, artificial intelligence-based systems are one of the most important developments. This paper introduces a computer vision-based algorithm for weld path detection, gap measurement, and weld length calculation. The proposed innovative approach employs various image processing techniques and mathematical operations, accurately determining weld attributes at seam points. Using the YOLO-based object detection algorithm, the model attains a remarkable average precision of 99.5% in identifying atypical weld regions. The study also introduces an efficient boundary line elimination method based on the Probabilistic Hough transform and mathematical logic. Methodology for classifying weld lines with or without significant gaps has been proposed, followed by adapting distinct set of algorithms for weld line identification and gap measurement. Rigorous testing on butt joints of diverse shapes (e.g., straight, zig-zag, and curve) and sizes verifies the robustness of the algorithm, with errors well within ±1 mm for length measurements. In testing conducted at three different points along the individual weld profile, the maximum error in estimating the weld gap was observed to be 0.11 mm. Weld seam information can be extracted effectively with the proposed algorithm, which proves its viability for industrial applications.

Usability of Light-Linking Technology for Infusion Line Identification: A Simulation Study With ICU Nurses.

Critical care nurses are faced with increasing task loads due to increasing patient complexity. In addition to this complexity, most critical care patients have a maze of infusion and monitoring lines that must be navigated when administering medications. Task load is escalated when a nurse must identify an injection port and administer a medication rapidly. This study tested a commercially available light-linking infusion line identification device. Researchers compared standard labeling practices to the light-linking technology on time to injection, error rate, usability, and task load. Forty-seven intensive care nurses completed 188 critical care simulations using a randomized cross-over design. Simulations were carried out in both daylight and low-light conditions. The light-linking technology reduced overall time to injection compared to standard labeling practices and demonstrated a significant decrease in time to injection in low-light settings, greater perceived usability, and lower perceived task load. Injection error rate could not be adequately assessed, but 6 of 8 errors were committed in low-light conditions.

Line identification of extreme ultraviolet spectra from aluminum ions in EAST Tokamak plasmas

Extreme ultraviolet (EUV) spectra emitted from aluminum in the 5-340 Å wavelength range were observed in Experimental Advanced Superconducting Tokamak (EAST) discharges. Several spectral lines from aluminum ions with different degrees of ionization were successfully observed with sufficient spectral intensities and resolutions using three fast-time-response EUV spectrometers. The line identification uses three independent state-of-art computational codes for the atomic structure calculations, which provide the wavelengths and the collisional and radiative transition rate coefficients. These programs are hullac (Hebrew University—Lawrence Livermore Atomic Code), autostructure, and fac (Flexible Atomic Code). Using three different codes allows us to resolve some ambiguities in identifying certain spectral lines and assess the validity of the theoretical predictions.

Enhanced encoder–decoder architecture for visual perception multitasking of autonomous driving

Visual perception plays a vital role in autonomous driving systems, demanding high accuracy and real-time inference speed to ensure safety. In this paper, we propose a multi-task framework that simultaneously performs object detection, drivable area segmentation, and lane line identification, addressing the requirements of accurate and efficient visual perception. Our approach utilizes a shared-encoder architecture with three separate decoders, targeting each specific task. We investigate three configurations for the shared encoder: a Convolutional Neural Network (CNN), a Polyp Vision Transformer (PVT), and a hybrid CNN+PVT model. Through extensive experimentation and comparative analysis on the challenging BD100K dataset, we evaluate the performance of these shared-encoder models and provide valuable insights into their strengths and weaknesses. Our research contributes to the advancement of multi-task visual perception for autonomous driving systems by achieving competitive results in terms of accuracy and efficiency. The source code is publicly available on GitHub to facilitate further research in this domain.

Simultaneous Plate-Reader Characterization of Promoter Activity and Cell Growth in Engineered Mammalian Cells.

Automated high-throughput methods that support tracking of mammalian cell growth are currently needed to advance cell line characterization and identification of desired genetic components required for cell engineering. Here, we describe a high-throughput noninvasive assay based on plate reader measurements. The assay relies on the change in absorbance of the pH indicator phenol red. We show that its basic and acidic absorbance profiles can be converted into a cell growth index consistent with cell count profiles, and that, by adopting a computational pipeline and calibration measurements, it is possible to identify a conversion that enables prediction of cell numbers from plate measurements alone. The assay is suitable for growth characterization of both suspension and adherent cell lines when these are grown under different environmental conditions and treated with chemotherapeutic drugs. The method also supports characterization of stably engineered cell lines and identification of desired promoters based on fluorescence output.

Three-core Cable Fault Line Identification Based on Ground Wire Current and BiGRU-ResNet-MA

Three-core Cable Fault Line Identification Based on Ground Wire Current and BiGRU-ResNet-MA

Comparative Analysis of Algorithms for Laser Line Identification for 3D Scanning Devices

A comparative analysis of algorithms for laser line center determination and recognition has been conducted. The issues in this area are described, outlining the principles, pros, and cons of each method. Additionally, the possibilities of their application using programming code are demonstrated. Algorithm testing was performed using Python language tools and the OpenCV library. It is shown that the quality of the result in the extremum method significantly depends on the quality of the selected parameters for the Butterworth filter. In contrast, the gray gravity method substantially relies on the accuracy of determining the laser incidence angle. The computational efficiency and accuracy for each algorithm are also analyzed.

Numerical sensitivity analysis for stress-strain simulation and flow liquefaction assessment of tailings storage facilities using the NorSand constitutive model

With the advent of critical state Soil Mechanics (CSSM), the void ratio began to be recognized as a key parameter, along with the stress state, which defines the mechanical behavior of soils and other particulate geomaterials by using the state parameter. The state parameter is the difference between the current and critical void ratio so that its definition requires the critical state line (CSL) identification. This work presents numerical calibration results, using the NorSand constitutive model, from three sets of triaxial compression tests selected from the literature. The SIGMA/W module of the Geostudio® System was adopted to perform the simulations of the triaxial compression tests, and the results showed adequate fit between real tests and numerical simulations. The parameters necessary for the modeling with NorSand model, defined from the numerical calibration, were used in a stress-strain evaluation of a hypothetical upstream tailings dam. These simulations allowed the evaluation of the differences in the tailings storage facility (TSF) responses in terms of both deformation behavior and flow liquefaction instability. Flow liquefaction instability is described in the literature as a complete loss in shear strength and the development of excessive strains due to the contractive response of tailings when subjected to low confining stress. The results suggest that the use of the NorSand model is, in general, a good option to reproduce the typical strain-softening behavior of such structures. Furthermore, it was clear the high sensitivity of the constitutive model parameters, drawing attention to the importance of best laboratory practices for carrying out triaxial tests to obtain reliable parameters for NorSand modeling.

Influence Line Identification Method Based on VMD Combined with Improved Wavelet Threshold Denoising

The influence line of bridge can reflect the performance of the bridge under the moving vehicle load. It has a wide range of applications in structural damage detection, performance evaluation, model correction and bridge weigh-in-motion. Fast moving vehicles will cause the dynamic effect of the bridge, resulting in the change of the bridge response curve and the difficulty of identifying the influence line. In this paper, an influence line identification method based on variational mode decomposition (VMD) combined with improved wavelet threshold denoising is proposed. Firstly, the mathematical model of influence line identification is established based on vehicle load matrix and bridge response. Then, VMD combined with improved wavelet threshold denoising method is used to eliminate dynamic fluctuation effect and noise. Finally, the elastic net penalty term is introduced in the influence line identification problem, and the B-spline basis function is used to reconstruct the influence line. In order to verify the effectiveness of the proposed method, a vehicle-bridge coupling model is established for numerical calculation, and the identification of bridge displacement influence lines under different conditions such as vehicle speed, noise level, road roughness and vehicle weight is investigated. The results show that the proposed method can effectively eliminate the dynamic fluctuation components and noise of the bridge response. In the case of good road roughness, the influence line can still be accurately identified when the vehicle speed reaches 15 m/s.