Dynamic Frame Research Articles

Numerical tests for tropical cyclone track prediction by the global WRF model

This work use the global WRF model containing quadruply nesting with which the highest resolution reached 10 km to simulate the typhoons landed on the coast of China in 2011. The model is driven by the reanalysis data fnl with the resolution of 1° x 1°. The study assess the feasibility and applicability of the global WRF model in the 1–7 days prediction of Tropical Cyclone (TC) track by comparing it with the regional WRF model containing the same setting (physical scheme, dynamical frame, model resolution and nesting grid domain). The global model obtain a similar forecast accuracy to the regional model in 1–7 days, with a difference less than 50 km. The forecast accuracy of the global model for 1, 2, 3, 4, 5, 6 and 7 days is about 70 km, 120 km, 180 km, 240 km, 320 km, 400 km, and 500 km, respectively. The reason of the significant TC track errors in the forecast more than 3 or 4 days is analyzed, it is due to the poor representation of typhoon and its steering flow under the situation of binary typhoon system. The study show that the global WRF model can be exploited to proceed the high resolution TC simulation and make the TC track forecast up to 7 days but not in the case of multiple typhoon.

Grouping based radio frequency identification anti-collision protocols for dense internet of things application

<span lang="EN-US">Radio frequency identification (RFID) is an important internet of things (IoT) enabling technology. In RFIDs collision occur among tags because tags share communication channel. This is called tag collision problem. The problem becomes catastrophic when dense population of tags are deployed like in IoT. Hence, the need to enhance existing dynamic frame slotted ALOHA (DFSA) based electronic product code (EPC) C1G2 media access control (MAC) protocol. Firstly, this paper validates through simulation the DFSA theory that efficiency of the RFID system is maximum when the number tags is approximately equal to the frame size. Furthermore, literature review shows tag grouping is becoming popular to improving the efficiency of the RFID system. This paper analyzes selected grouping-based algorithms. Their underlining principles are discussed including their tag estimation methods. The algorithms were implemented in MATLAB while extensive Monte Carlo simulation was performed to evaluate their strengths and weaknesses. Results show that with higher tag density, fuzzy C-means based algorithm (FCMBG) outperformed traditional DFSA by over 40% in terms of throughput rate. The results also demonstrate FCMBG bettered other grouping-based algorithms (GB-DFSA and GBSA) whose tag estimation method are based on collision slots in terms slot efficiency by over 10% and also in terms of identification time.</span>

4DGolden-Angle Radial MRI at Subsecond Temporal Resolution.

Intraframe motion blurring, as a major challenge in free-breathing dynamic MRI, can be reduced if high temporal resolution can be achieved. To address this challenge, this work proposes a highly accelerated 4D (3D + time) dynamic MRI framework with subsecond temporal resolution that does not require explicit motion compensation. The method combines standard stack-of-stars golden-angle radial sampling and tailored GRASP-Pro (Golden-angle RAdial Sparse Parallel imaging with imProved performance) reconstruction. Specifically, 4D dynamic MRI acquisition is performed continuously without motion gating or sorting. The k-space centers in stack-of-stars radial data are organized to guide estimation of a temporal basis, with which GRASP-Pro reconstruction is employed to enforce joint low-rank subspace and sparsity constraints. This new basis estimation strategy is the new feature proposed for subspace-based reconstruction in this work to achieve high temporal resolution (e.g., subsecond/3D volume). It does not require sequence modification to acquire additional navigation data, it is compatible with commercially available stack-of-stars sequences, and it does not need an intermediate reconstruction step. The proposed 4D dynamic MRI approach was tested in abdominal motion phantom, free-breathing abdominal MRI, and dynamic contrast-enhanced MRI (DCE-MRI). Our results have shown that GRASP-Pro reconstruction with the new basis estimation strategy enables highly-accelerated 4D dynamic imaging at subsecond temporal resolution (with five spokes or less for each dynamic frame per image slice) for both free-breathing non-DCE-MRI and DCE-MRI. In the abdominal phantom, better image quality with lower root mean square error and higher structural similarity index was achieved using GRASP-Pro compared with standard GRASP. With the ability to acquire each 3D image in less than 1 s, intraframe respiratory blurring can be intrinsically reduced for body applications with our approach, which eliminates the need for explicit motion detection and motion compensation.

Modeling and Representing Conceptual Change in the Learning of Successive Theories

AbstractMost educational literature on conceptual change concerns the process by which introductory students acquire scientific knowledge. However, with modern developments in science and technology, the social significance of learning successive theories is steadily increasing, thus opening new areas of interest to discipline-based education research, e.g., quantum logic, quantum information, and communication. Here, we present an initial proposal for modeling the transition from the understanding of a theory to the understanding of its successor and explore its generative potential by applying it to a concrete case—the classical-quantum transition in physics. In pursue of such task, we make coordinated use of contributions from research not only on conceptual change in education, but also on the history and philosophy of science, on the teaching and learning of quantum mechanics, and on mathematics education. By means of analytical instruments developed for characterizing conceptual trajectories at different representational levels, we review empirical literature in the search for the connections between theory change and cognitive demands. The analysis shows a rich landscape of changes and new challenges that are absent in the traditionally considered cases of conceptual change. In order to fully disclose the educational potential of the analysis, we visualize categorical changes by means of dynamic frames, identifying recognizable patterns that answer to students’ need of comparability between the older and the new paradigm. Finally, we show how the frame representation can be used to suggest pattern-dependent strategies to promote the understanding of the new content, and may work as a guide to curricular design.

Deep Hashing and Sparse Representation of Abnormal Events Detection

Abstract Due to its widespread application in the field of public security, anomaly detection in crowd scenes has recently become a hot topic. Some deep learning-based methods led to significant accomplishments in this field. Nevertheless, due to the scarcity of data and the misclassification of queries which most of them suffer to some extent from a sudden and infrequent overfitting. Though, we tried to solve the above problems, understand the long video streams and establish an accurate and reliable security system in order to improve its performance in detecting anomalies. We also referred to the hash technique, which has proven to be the most efficient method used when researching about large-scale image recovery. Thus, this article offers a smart video anomaly detection solution. In this paper, we combine the advantages of both deep hashing and deep auto-encoders to show that tracking changes in deep hash components across time and can be used to detect local anomalies. More precisely, we start with a new technique to minimize the mass of input data and information in order to decrease the time of calculation using a new dynamic frame skipping technique. Then, we propose to measure local anomalies by combining semantic with low-level optical flows to balance the performance and perceptibility. The experimental results illustrate that the proposed methods surpass these baselines for the detection and localization of anomalies.

How Ukraine Won the ‘#Like’ War with Russia Using Popular Mass Media – Dynamic Framing in Online Headlines in Poland

The entire world watched with horror when at the beginning of 2022, Russia attacked neighbouring Ukraine in order to fight with the alleged Nazism and the mistreatment of Russian citizens in Ukraine. The breakout of the conflict gave rise to varying media reports that have been flourishing in global and especially European media. This research analysed framing tendencies in the headlines of media reports from Onet.pl – one of the most popular and commonly visited news portals in Poland. The results of the study revealed strong framing leanings with two issue-specific frames dominating the discourse on top of a one-sided bias of the medium and its journalists in favour of Ukraine. At the same time particular framing trends and tendencies have been uncovered which suggest varying political and ideological skews that managed to influenced media reports in Poland, allowing for common support of the Ukrainian cause and what followed, a favourable reception of millions of Ukrainian refugees fleeing the country, to find shelter in Poland.

Human Motion Recognition With Spatial-Temporal-ConvLSTM Network Using Dynamic Range-Doppler Frames Based on Portable FMCW Radar

As a noncontact and noninvasive sensor, radar offers attractive modality for human motion recognition in many fields, such as surveillance, smart homes, and assisted living. As a dynamic process, a comprehensive multidomain analysis in stream is crucial for human motion recognition. In this article, a novel spatial–temporal convolution long short-term memory (ST-ConvLSTM) network using dynamic range-Doppler frames (DRDF) based on portable frequency-modulated continuous-wave (FMCW) radar is proposed to address this problem. First, DRDF is introduced to characterize different human motions in time, range, Doppler, and radar cross section (RCS) domains with a time-sequenced range-Doppler maps. Then, ConvLSTM cell is investigated to extract continuous 2-D image features by combining both convolution operation and LSTM cell. Furthermore, a spatial attention module is utilized to emphasize the spatial distribution of human motion in the range-Doppler domain, while a temporal attention module is designed to obtain optimal temporal weights considering behavior continuity. Finally, an extensive radar dataset from 16 volunteers demonstrated its feasibility and superiority in the classification of six typical daily human motions. The contributions of attention modules and its robustness facing individual diversity are also investigated and discussed.

Effect of glenosphere lateralization with and without coracoacromial ligament transection on acromial and scapular spine strain in reverse shoulder arthroplasty.

Small changes in deltoid tension and moment arm due to glenosphere lateralization may be associated with an increase in acromion or scapular spine strain in reverse shoulder arthroplasty (RSA), which can lead to stress fracture. The coracoacromial ligament (CAL) may be protective and lower the strain seen on the acromion or scapular spine. This biomechanical study investigated the impact of glenosphere lateralization and CAL integrity on acromion and scapular spine strain after RSA. Ten cadaveric specimens were tested on a custom dynamic shoulder frame. Acromial and scapular spine strain were measured at 0°, 30°, and 60° of abduction using strain rosettes fixed to the acromion (Levy Type 2) and the scapular spine (Levy Type 3). Specimens were first tested with a standard commercially available RSA implant with zero lateralization and then subsequently with the+3 and+6 lateralizing glenospheres for that implant. The CAL was then cut in each specimen and testing was repeated with the 0,+3, and+6 glenospheres. Maximal strain was recorded at both the acromion and scapular spine and analysis of variance compared strain across various abduction angles and glenospheres with and without CAL transection. In the intact CAL group, maximal strain decreased significantly at the acromion with abduction from 0° to 30° and 0° to 60°, however, at the scapular spine abduction did not significantly impact strain. Maximal strain decreased significantly with increasing abduction from 0 to 30 and 0 to 60 at both the acromion and scapular spine in the cut CAL group. Average strain at the acromion was significantly higher in the cut group (844.7 με) versus the intact group (580.3 με), a difference of 31.3% (P=.0493). Average strain at the scapular spine, did not differ in the cut group (725 με) compared with the intact group (787 με) (P=.3666). There were no statistically significant differences in acromial or scapular spine strain between various levels of glenosphere lateralization in either the cut or intact state. In this biomechanical study, arm abduction decreased acromial and scapular spine strain following RSA. Cutting the CAL significantly increased strain at the acromion, and did not significantly alter strain at the scapular spine for all angles of abduction, differing from prior literature. Glenosphere lateralization did not have a significant effect on strain at the levels studied regardless of CAL status. Continued study of the complexion relationship between surgical and implant factors on strain following RSA is needed.

A scale space theory based motion correction approach for dynamic PET brain imaging studies

Aim/Introduction: Patient head motion poses a significant challenge when performing dynamic PET brain studies. In response, we developed a fast, robust, easily implementable and tracer-independent brain motion correction technique that facilitates accurate alignment of dynamic PET images.Materials and methods: Correction of head motion was performed using motion vectors derived by the application of Gaussian scale-space theory. A multiscale pyramid consisting of three different resolution levels (1/4x: coarse, 1/2x: medium, and 1x: fine) was applied to all image frames (37 frames, framing of 12 × 10s, 15 × 30s, 10 × 300s) of the dynamic PET sequence. Frame image alignment was initially performed at the coarse scale, which was subsequently used to initialise coregistration at the next finer scale, a process repeated until the finest possible scale, that is, the original resolution was reached. In addition, as tracer distribution changes during the dynamic frame sequence, a mutual information (MI) score was used to identify the starting frame for motion correction that is characterised by a sufficiently similar tracer distribution with the reference (last) frame. Validation of the approach was performed based on a simulated F18-fluoro-deoxy-glucose (FDG) dynamic sequence synthesised from the digital Zubal phantom. Inter-frame motion was added to each dynamic frame (except the reference frame). Total brain voxel displacement based on the added motion was constrained to 25 mm, which included both translation (0–15 mm in x, y and z) and rotation (0–0.3 rad for each Euler angle). Twenty repetitions were performed for each dataset with arbitrarily simulated motion, resulting in 20 synthetic datasets, each consisting of 36 dynamic frames (frame 37 was the reference frame). Assessment of motion correction accuracy across the dynamic sequence was performed based on the uncorrected/residual displacement remaining after the application of our algorithm. To investigate the clinical utility of the developed algorithm, three clinically cases that underwent list-mode PET imaging utilising different tracers ([18F]-fluoro-deoxy-glucose [18F]FDG [18F]-fluoroethyl-l-tyrosine [18F]FET [11C]-alpha-methyl-tryptophan [11C]AMT), each characterised by a different temporal tracer distribution were included in this study. Improvements in the Dice score coefficient (DSC) following frame alignment were evaluated as the correlation significance between the identified displacement for each frame of the clinical FDG, FET and AMT dynamic sequences.Results: Sub-millimetre accuracy (0.4 ± 0.2 mm) was achieved in the Zubal phantom for all frames after 5 min p. i., with early frames (30 s–180 s) displaying a higher residual displacement of ∼3 mm (3.2 ± 0.6 mm) due to differences in tracer distribution relative to the reference frame. The effect of these differences was also seen in MI scores; the MI plateau phase was reached at 35s p. i., 2.0 and 2.5 min p. i. At the coarse, medium and fine resolution levels, respectively. For the clinical images, a significant correlation between the identified (and corrected) displacement and the improvement in DSC score was seen in all dynamic studies (FET: R = 0.49, p < 0.001; FDG: R = 0.82, p < 0.001; AMT: R = 0.92, p < 0.001).Conclusion: The developed motion correction method is insensitive to any specific tracer distribution pattern, thus enabling improved correction of motion artefacts in a variety of clinical applications of extended PET imaging of the brain without the need for fiducial markers.

Dynamical dual frames with an application to quantization

We prove that every redundant finite frame for Fd, where F=R or C, has infinitely many dynamical dual frames, and introduce a low complexity error diffusion quantization algorithm based on dynamical dual frames.

Research on Surface Defect Detection of Camera Module Lens Based on YOLOv5s-Small-Target

For the problem of low resolution of camera module lens surface defect image, small target and blurred defect details leading to low detection accuracy, a camera module lens surface defect detection algorithm YOLOv5s-Defect based on improved YOLOv5s is proposed. Firstly, to solve the problems arising from the anchor frame generated by the network through K-means clustering, the dynamic anchor frame structure DAFS is introduced in the input stage. Secondly, the SPP-D (Spatial Pyramid Pooling-Defect) improved from the SPP module is proposed. The SPP-D module is used to enhance the reuse rate of feature information in order to reduce the loss of feature information due to the maximum pooling of SPP modules. Then, the convolutional attention module is introduced to the network model of YOLOv5s, which is used to enhance the defective region features and suppress the background region features, thus improving the detection accuracy of small targets. Finally, the post-processing method of non-extreme value suppression is improved, and the improved method DIoU-NMS improves the detection accuracy of small targets in complex backgrounds. The experimental results show that the mean average precision mAP@0.5 of the YOLOv5s-Small-Target algorithm is 99.6%, 8.1% higher than that of the original YOLOv5s algorithm, the detection speed FPS is 80 f/s, and the model size is 18.7M. Compared with the traditional camera module lens surface defect detection methods, YOLOv5s-Small-Target can detect the type and location of lens surface defects more accurately and quickly, and has a smaller model volume, which is convenient for deployment in mobile terminals, meeting the demand for real-time and accuracy of camera module lens surface defect detection.

Motion correction and its impact on quantification in dynamic total-body 18F-fluorodeoxyglucose PET

BackgroundThe total-body positron emission tomography (PET) scanner provides an unprecedented opportunity to scan the whole body simultaneously, thanks to its long axial field of view and ultrahigh temporal resolution. To fully utilize this potential in clinical settings, a dynamic scan would be necessary to obtain the desired kinetic information from scan data. However, in a long dynamic acquisition, patient movement can degrade image quality and quantification accuracy.MethodsIn this work, we demonstrated a motion correction framework and its importance in dynamic total-body FDG PET imaging. Dynamic FDG scans from 12 subjects acquired on a uEXPLORER PET/CT were included. In these subjects, 7 are healthy subjects and 5 are those with tumors in the thorax and abdomen. All scans were contaminated by motion to some degree, and for each the list-mode data were reconstructed into 1-min frames. The dynamic frames were aligned to a reference position by sequentially registering each frame to its previous neighboring frame. We parametrized the motion fields in-between frames as diffeomorphism, which can map the shape change of the object smoothly and continuously in time and space. Diffeomorphic representations of motion fields were derived by registering neighboring frames using large deformation diffeomorphic metric matching. When all pairwise registrations were completed, the motion field at each frame was obtained by concatenating the successive motion fields and transforming that frame into the reference position. The proposed correction method was labeled SyN-seq. The method that was performed similarly, but aligned each frame to a designated middle frame, was labeled as SyN-mid. Instead of SyN, the method that performed the sequential affine registration was labeled as Aff-seq. The original uncorrected images were labeled as NMC. Qualitative and quantitative analyses were performed to compare the performance of the proposed method with that of other correction methods and uncorrected images.ResultsThe results indicated that visual improvement was achieved after correction of the SUV images for the motion present period, especially in the brain and abdomen. For subjects with tumors, the average improvement in tumor SUVmean was 5.35 ± 4.92% (P = 0.047), with a maximum improvement of 12.89%. An overall quality improvement in quantitative Ki images was also observed after correction; however, such improvement was less obvious in K1 images. Sampled time–activity curves in the cerebral and kidney cortex were less affected by the motion after applying the proposed correction. Mutual information and dice coefficient relative to the reference also demonstrated that SyN-seq improved the alignment between frames over non-corrected images (P = 0.003 and P = 0.011). Moreover, the proposed correction successfully reduced the inter-subject variability in Ki quantifications (11.8% lower in sampled organs). Subjective assessment by experienced radiologists demonstrated consistent results for both SUV images and Ki images.ConclusionTo conclude, motion correction is important for image quality in dynamic total-body PET imaging. We demonstrated a correction framework that can effectively reduce the effect of random body movements on dynamic images and their associated quantification. The proposed correction framework can potentially benefit applications that require total-body assessment, such as imaging the brain-gut axis and systemic diseases.

Pharmacophore Modeling of Targets Infested with Activity Cliffs via Molecular Dynamics Simulation Coupled with QSAR and Comparison with other Pharmacophore Generation Methods: KDR as Case Study.

Activity cliffs (ACs) are defined as pairs of structurally similar compounds with large difference in their potencies against certain biotarget. We recently proposed that potent AC members induce significant entropically-driven conformational modifications of the target that unveil additional binding interactions, while their weakly-potent counterparts are enthalpically-driven binders with little influence on the protein target. We herein propose to extract pharmacophores for ACs-infested target(s) from molecular dynamics (MD) frames of purely "enthalpic" potent binder(s) complexed within the particular target. Genetic function algorithm/machine learning (GFA/ML) can then be employed to search for the best possible combination of MD pharmacophore(s) capable of explaining bioactivity variations within a list of inhibitors. We compared the performance of this approach with established ligand-based and structure-based methods. Kinase inserts domain receptor (KDR) was used as a case study. KDR plays a crucial role in angiogenic signalling and its inhibitors have been approved in cancer treatment. Interestingly, GFA/ML selected, MD-based, pharmacophores were of comparable performances to ligand-based and structure-based pharmacophores. The resulting pharmacophores and QSAR models were used to capture hits from the national cancer institute list of compounds. The most active hit showed anti-KDR IC50 of 2.76 μM.

Three-dimensional properties of the viscous boundary layer in turbulent Rayleigh–Bénard convection

We report an experimental study of the viscous boundary layer (BL) properties of turbulent Rayleigh–Bénard convection in a cylindrical cell. The velocity profile with all three components was measured from the centre of the bottom plate by an integrated home-made particle image velocimetry system. The Rayleigh number $Ra$ varied in the range $1.82 \times 10^8 \le Ra \le 5.26 \times 10^9$ and the Prandtl number $Pr$ was fixed at $Pr = 4.34$ . The probability density function of the wall-shear stress indicates that using the velocity component in the mean large-scale circulation (LSC) plane alone may not be sufficient to characterise the viscous BL. Based on a dynamic wall-shear frame, we propose a method to reconstruct the measured full velocity profile which eliminates the effects of complex dynamics of the LSC. Various BL properties including the eddy viscosity are then obtained and analysed. It is found that, in the dynamic wall-shear frame, the eddy viscosity profiles along the centre line of the convection cell at different $Ra$ all collapse on a single master curve described by $\nu _t^d / \nu = 0.81 (z / \delta _u^d) ^{3.10 \pm 0.05}$ . The Rayleigh number dependencies of several BL quantities are also determined in the dynamic frame, including the BL thickness $\delta _u^d$ ( ${\sim } Ra^{-0.21}$ ), the Reynolds number $Re^d$ ( ${\sim }Ra^{-0.46}$ ) and the shear Reynolds number $Re_s^d$ ( ${\sim } Ra^{0.24}$ ). Within the experimental uncertainty, these scaling exponents are the same as those obtained in the static laboratory frame. Finally, with the measured full velocity profile, we obtain the energy dissipation rate at the centre of the bottom plate $\varepsilon _{w}$ , which is found to follow $\langle \varepsilon _{w} \rangle _t \sim Ra^{1.25}$ .

P120. Augmented reality navigation for percutaneous thoracolumbar pedicle screws: a prospective clinical study

<h3>BACKGROUND CONTEXT</h3> Conventional navigation systems depend on a separate imaging system and use of passive infra-red cameras with a bulky dynamic reference frame (DRF) attached to the spine and to the instruments for live tracking. This often leads to 1) issues with line of sight 2) need for an invasive procedure to attach the DRF 3) lowered accuracy due to inadvertent bumping of the DRF and when point of interest is further from the location of the DRF and 4) a need for repeated re-registrations that can affect the surgical workflow and impact the procedure time. These common issues that impede the adoption of navigation can be bypassed using an Augmented Reality Surgical Navigation system (ARSN), that combines the use of superior quality 3D intra-operative imaging and optical camera based Augmented Reality Navigation (ARN), noninvasive dynamic patient monitoring and on-shaft optical trackers on the Jamshidi needles to provide real time visual feedback of instrument location, without relying on fluoroscopy. <h3>PURPOSE</h3> To determine the accuracy of percutaneous pedicle screw placement when using ARSN. <h3>STUDY DESIGN/SETTING</h3> A single-arm, prospective multicenter clinical study. <h3>PATIENT SAMPLE</h3> A total of 211 pedicle screws were placed percutaneously in 39 patients between levels T2 and S1. The predominant indication was trauma (42%). However, patients with instability of the spine due to degenerative and neoplastic diseases were also included. <h3>OUTCOME MEASURES</h3> Accuracy of pedicle screw placement according to Gertzbein grading (Grade 0: no breach; Grade 1: 4mm breach) determined by three independent reviewers. The median time required to insert the pedicle screw in the right location when using the system was also noted. <h3>METHODS</h3> Navigation was performed in a hybrid OR including surgical table, motorized flat detector C-arm with intraoperative 2D/3D imaging capabilities, optical video cameras integrated in the detector for ARN, and patient motion tracking using skin markers. The C-arm rotated 180 degrees in 10 seconds during acquisition, creating a 3D Cone-Beam CT (CBCT) of the area of interest of 4-8 levels. A disposable Jamshidi needle with optical markers etched on the shaft was used to guide the needle to the desired location in the vertebral body using ARN. <h3>RESULTS</h3> Overall accuracy (Gertzbein 0-1) was 98.1% (95% CI 95.2-99.5). For thoracic screws (n=69), accuracy was 95.7%, for lumbar screws (n=126) 99.2%. Grade 0 screws (no breach) were 93% overall (86% in thoracic and 96% in lumbar levels). Four screws were graded as 2 (2-4 mm breach), with a medial positioning. Three of them were in the upper thoracic spine. None was associated with a neurological consequence. No screw was highly misplaced (> 4mm error). Six screws (2.7%) were intraoperatively revised. Median time per screw was 6 minutes and 25 sec (± 3.3 min). <h3>CONCLUSIONS</h3> Use of ARN leads to a high rate of accurate pedicle screw placement. The use of ARSN favorably compares to screw placement times reported in literature. <h3>FDA DEVICE/DRUG STATUS</h3> ClarifEye surgical navigation system (Philips Healthcare) (Approved for this indication)

Adjacent Frame Difference with Dynamic Threshold Method in Underwater Flash Imaging LiDAR

During the underwater LiDAR imaging process, the images achieved by the conventional constant threshold adjacent frame difference (AFD) method normally loses the distance information of targets. This is mainly due to the Gaussian distribution of the laser light intensity field, which leads to the inhomogeneous intensity distribution in the frame from the target acquired by intensity charge-coupled devices (ICCD). In order to overcome this issue, the novel dynamic threshold adjacent frame difference (DTAFD) method was proposed in this paper. The DTAFD method modifies the intensity threshold following the pixel intensities in the different parts of the single frame intensity image acquired by ICCD. After the detailed theoretical demonstration of the DTAFD method, with the purpose of verifying its feasibility, the self-developed range-gated flash imaging LiDAR has been employed to construct the distance images of the rectangular and circular shaped targets at different distances. The distance between the rectangular target and the LiDAR system is 25.7 m, and the circular target is 70 cm further away from the rectangular target. The full distance information of these two targets is obtained by the DTAFD method with an effectively suppressing noise and the PSNR is increased from 6.95±0.0426 dB to 7.62±0.0264 dB. The experimental results indicate that the DTAFD method efficiently solves the AFD method’s drawback on the target information loss caused by the unequal optical field distribution, which makes it more suitable for the scenarios with uneven laser distribution such as the underwater imaging environment.

THE The Virtuosity of Traditional Africa and the Plasticity of Its Affects: The Cross-Cultural Fertilization of “Yela” in the Western Sahel and Savanah

Throughout the poetic image and imaginative construction of the self, the Yela embodies a protrusive source of vindication within the intellective and creative process of understanding become an object of perception. From an ingenuous beget to a more compound whole of a convention of representation and the association of experience, the Yela inside the Puular language becomes a structural material. Thus, the constituent of conservative imagery and the colonialist dynamic influences frame an innovative eccentric variety that appraises the formation of reality, memory, and symbol. Therefore, the domain of Yela through its cultural and artistic body, and within its existing essentiality of Gaandal and Demngal overtakes the principles of basic linguistics and the colonialist conventional perception of productivity. In effect, the Yela art through the all-encompassing relation of the Puular language with the whole performance of time and space, emphasizes on a cosmopolitan wholesome recombination, settlement and re-appropriation of material imagination and objective reality of intellection. The foundation of intellectual and artistic image, and imaginative expression, the corresponding inventiveness of the Yela art, and the musical nationalism arrange move beyond comatose understanding. Therefore, the commitment of this article underlines the question of the effective temperature of the Yela indigenous value of imagination, and its transformative experience as regard language, sociolinguistic and ecological reflectivity, and then its emphasis on its contemporary stylistic compass of performance.

Case Report: Modulation of Effective Connectivity in Brain Networks after Prosthodontic Tooth Loss Repair

INTRODUCTION. Recent neuroimaging studies suggest that dental loss replacements induce changes in neuroplasticity as well as in correlated connectivity between brain networks. However, as the typical temporal delay in detecting brain activity by neuroimaging cannot account for the influence one neural system exerts over another in a context of real activation (“effective” connectivity), it seems of interest to approach this dynamic aspect of brain networking in the time frame of milliseconds by exploiting electroencephalographic (EEG) data. MATERIAL AND METHODS. The present study describes one subject who received a new prosthodontic provisional implant in substitution for previous dental repairs. Two EEG sessions led with a portable device were recorded before and after positioning the new dental implant. By following MATLAB-EEGLAB processing supported by the plugins FIELDTRIP and SIFT, the independent component analysis (ICA) derived from EEG raw signals was rendered as current density fields and interpolated with the dipoles generated by each electrode for a dynamic study of the effective connectivity. One more recording session was undertaken six months after the placement of the final implant. RESULTS. Compared to the baseline, the new prosthodontic implant induced a novel modulation of the neuroplasticity in sensory-motor areas which was maintained following the definitive implant after six months, as revealed by changes in the effective connectivity from the basal strong enslavement of a single brain area over the others, to an equilibrate inter-related connectivity evenly distributed along the frontotemporal regions of both hemispheres. CONCLUSIONS. The rapid shift of the effective connectivity after positioning the new prosthodontic implant and its substantial stability after six months suggest the possibility that synaptic modifications, induced by novel sensory motor conditions, modulate the neuroplasticity and reshape the final dynamic frame of the interarea connectivity. Moreover, given the viability of the EEG practice, this approach could be of some interest in assessing the association between oral pathophysiology and neuronal networking.

Multi-aspect detection and classification with multi-feed dynamic frame skipping in vehicle of internet things

Consumer demand for automobiles is changing because of the vehicle’s dependability and utility, and the superb design and high comfort make the vehicle a wealthy object class. The creation of object classes necessitates the creation of more sophisticated computer vision models. However, the critical issue is image quality, determined by lighting conditions, viewing angle, and physical vehicle construction. This work focuses on creating and implementing a deep learning-based traffic analysis system. Using a variety of video feeds and vehicle information, the developed model recognizes, categorizes, and counts vehicles in real-time traffic flow. The dynamic skipping method offered in the developed model speeds up the processing of a lengthy video stream while ensuring that the video picture is delivered accurately to the viewer. In real-time traffic, standard vehicle retrieval may assist in determining the make, model, and year of the vehicle. Previous MobileNet and VGG19 models achieved F-values of 0.81 and 0.91, respectively. However, the proposed solution raises MobileNet’s frame rate from 71.2 to 89.17 and VGG19’s frame rate from 48.2 to 59.14. The method may be applied to a wide range of applications that require a dedicated zone to monitor real-time data analysis and normal multimedia operations.

The impact of misplaced percutaneous iliac dynamic reference frame pins used during navigated spine surgery: incidence and outcomes.

Image guidance requires placement of a dynamic reference frame (DRF), often either onto local spinous process or by freehand intraosseous DRF placement into the ilium via the posterior superior iliac spine (PSIS). There is a paucity of studies in the literature that describe the complications of intraosseous DRF placement. The aim of this study was to describe the radiographic location, prevalence and nature of complications, and long-term clinical outcomes of attempted DRF placement into the PSIS. All lumbosacral spine surgical procedures performed between August 2019 and February 2021 at a single institution were queried, and operations in which a DRF was targeted to the PSIS were included. Patient demographic characteristics, indications for surgery, surgical outcomes, and complications were extracted. Intraoperative CT scans were reviewed by 2 independent researchers to determine the accuracy of DRF placement into the PSIS and to assess for DRF malposition. Of 497 lumbar spine operations performed between August 2019 and February 2021 by 4 surgeons, 85 utilized intraoperative navigation with a PSIS pin. Thirteen operations were excluded due to an inability to visualize the entirety of the pin on intraoperative CT. Of 72 DRFs evaluated, 77.8% had been correctly placed in the PSIS. Of the 22.2% of DRFs not placed into the PSIS, 11 entered the sacrum, 6 crossed the sacroiliac joint, and 2 were deep enough to enter the pelvis. Pain at the pin site was present in 4 patients, of whom 3 had resolution of pain at the last follow-up evaluation. There were no significant complications due to DRF placement: no sacral fractures, significant navigation errors, retroperitoneal hematomas, or neurological deficits. Over a mean ± SD follow-up period of 9 ± 5.2 months, there were no incidences of pin site infection. Interrater reliability between the reviewers was 95.8%. This was the first study to examine radiological and clinical outcomes after DRF placement in the PSIS. In this study, a majority of pins were correctly placed within the PSIS, although 22.2% of pins were malpositioned. There were no serious complications, and a majority of those patients with persistent pin site pain had resolution at last follow-up.