Centroid Position Research Articles

Experimental comparison of linear regression and LSTM motion prediction models for MLC-tracking on an MRI-linac.

Magnetic resonance imaging (MRI)-guided radiotherapy with multileaf collimator (MLC)-tracking is a promising technique for intra-fractional motion management, achieving high dose conformality without prolonging treatment times. To improve beam-target alignment, the geometric error due to system latency should be reduced by using temporal prediction. To experimentally compare linear regression (LR) and long-short-term memory (LSTM) motion prediction models for MLC-tracking on an MRI-linac using multiple patient-derived traces with different complexities. Experiments were performed on a prototype 1.0T MRI-linac capable of MLC-tracking. A motion phantom was programmed to move a target in superior-inferior (SI) direction according to eight lung cancer patient respiratory motion traces. Target centroid positions were localized from sagittal 2D cine MRIs acquired at 4Hz using a template matching algorithm. The centroid positions were input to one of four motion prediction models. We used (1) a LSTM network which had been optimized in a previous study on patient data from another cohort (offline LSTM). We also used (2) the same LSTM model as a starting point for continuous re-optimization of its weights during the experiment based on recent motion (offline+online LSTM). Furthermore, we implemented (3) a continuously updated LR model, which was solely based on recent motion (online LR). Finally, we used (4) the last available target centroid without any changes as a baseline (no-predictor). The predictions of the models were used to shift the MLC aperture in real-time. An electronic portal imaging device (EPID) was used to visualize the target and MLC aperture during the experiments. Based on the EPID frames, the root-mean-square error (RMSE) between the target and the MLC aperture positions was used to assess the performance of the different motion predictors. Each combination of motion trace and prediction model was repeated twice to test stability, for a total of 64 experiments. The end-to-end latency of the system was measured to be (389 ± 15)ms and was successfully mitigated by both LR and LSTM models. The offline+online LSTM was found to outperform the other models for all investigated motion traces. It obtained a median RMSE over all traces of (2.8 ± 1.3)mm, compared to the (3.2 ± 1.9)mm of the offline LSTM, the (3.3 ± 1.4)mm of the online LR and the (4.4 ± 2.4)mm when using the no-predictor. According to statistical tests, differences were significant (p-value <0.05) among all models in a pair-wise comparison, but for the offline LSTM and online LR pair. The offline+online LSTM was found to be more reproducible than the offline LSTM and the online LR with a maximum deviation in RMSE between two measurements of 10%. This study represents the first experimental comparison of different prediction models for MRI-guided MLC-tracking using several patient-derived respiratory motion traces. We have shown that among the investigated models, continuously re-optimized LSTM networks are the most promising to account for the end-to-end system latency in MRI-guided radiotherapy withMLC-tracking.

Real Time Volumetric MRI for MR-Guided 3D Motion Tracking via Sparse Prior-Augmented Neural Representation Learning

To reconstruct volumetric MRI from orthogonal cine acquisition aided by sparse priors of 2 static 3D MRI through implicit neural representation (NeRP) learning, with the goal of eliminating large-scale training datasets for data-driven sparse MRI reconstruction and supporting clinical workflow of real time 3D motion tracking during MR-guided radiotherapy. A multi-layer perceptron network was trained to learn the NeRP of a patient-specific MRI dataset, where the network takes 4D data coordinates of voxel locations and motion states as inputs and outputs corresponding voxel intensities. By first learning the NeRP of 2 static 3D MRI with different breathing motion states, prior knowledge of patient breathing motion was embedded into network weights through optimization. The prior knowledge was then augmented from 2 to 31 motion states by querying the optimized network at interpolated/extrapolated motion state coordinates. Starting from the prior-augmented network as an initialization point, the network was further trained using sparse samples of 2 orthogonal cine slices. The final volumetric reconstruction was obtained by querying the trained network at desired 3D spatial locations. We evaluated the proposed method using 5-minute volumetric MRI time series with 340 ms temporal resolution collected from 7 liver carcinoma patients. The time series was acquired using golden-angle radial MRI sequence and reconstructed through retrospective sorting. Two MRI with inhale and exhale states respectively were selected from the first 30 sec of the time series for prior embedding and augmentation. The remaining 4.5-min time series was used for volumetric reconstruction evaluation, where we retrospectively subsampled each MRI to 2 orthogonal slices and compared network-reconstructed images to ground truth images in terms of image quality and the capability of supporting 3D target motion tracking. Across the 7 patients evaluated, the peak signal to noise ratio between model reconstruction and ground truth was 54.66 ± 6.16 dB and the structural similarity index measure was 0.99 ± 0.01. Gross tumor volume (GTV) contours estimated by deforming a reference state MRI to model-reconstructed and ground truth MRI showed good consistency. The 95-percentile Hausdorff distance between GTV contours was 1.89 ± 1.13 mm, which is less than the voxel dimension. The mean GTV centroid position difference between ground truth and model estimation was less than 1 mm in all 3 orthogonal directions. Volumetric MRI from orthogonal cine acquisition with sparse priors is feasible by modeling prior knowledge through implicit neural representation learning. The model-reconstructed images showed sufficient accuracy in supporting 3D motion tracking of abdominal targets. By eliminating the need for large scale training datasets, the method promises to enable clinical implementation of 3D motion tracking for precision radiation therapy.

Comparative study of sub-second temporal resolution 4D-MRI and 4D-CT for target motion assessment in a phantom model

To develop and investigate the feasibility of sub-second temporal resolution volumetric T1-weighted four-dimensional (4D-) MRI in comparison with 4D-CT for respiratory-correlated motion assessment using an MRI/CT-compatible phantom. Sub-second high temporal resolution (0.5 s) gradient-echo T1-weighted 4D-MRI was developed using a volumetric acquisition scheme with compressed sensing. An MRI/CT-compatible motion phantom (simulated liver tumor) with three sinusoidal movements of amplitudes and two respiratory patterns was introduced and imaged with 4D-MRI and 4D-CT to investigate the geometric accuracy of the target movement. The geometric accuracy, including centroid position, volume, similarity index of dice similarity coefficient (DSC), and Hausdorff distance (HD), was systematically evaluated. Proposed 4D-MRI achieved a similar geometric accuracy compared with 4D-CT regarding the centroid position, volume, and similarity index. The observed position differences of the absolute average centroid were within 0.08 cm in 4D-MRI and 0.03 cm in 4D-CT, less than the 1-pixel resolution for each modality. The observed volume difference in 4D-MRI/4D-CT was within 0.73 cm3 (4.5%)/0.29 cm3 (2.1%) for a large target and 0.06 cm3 (11.3%)/0.04 cm3 (11.6%) for a small target. The observed DSC values for 4D-MRI/4D-CT were at least 0.93/0.95 for the large target and 0.83/0.84 for the small target. The maximum HD values were 0.25 cm/0.31 cm for the large target and 0.21 cm/0.15 cm for the small target. Although 4D-CT potentially exhibit superior numerical accuracy in phantom studies, the proposed high temporal resolution 4D-MRI demonstrates sub-millimetre geometric accuracy comparable to that of 4D-CT. These findings suggest that the 4D-MRI technique is a viable option for characterizing motion and generating phase-dependent internal target volumes within the realm of radiotherapy.

Continuous motion of an electrically actuated water droplet over a PDMS-coated surface

Electrically actuated linear motion of a water droplet over PDMS-coated single active electrode is analyzed from detailed experiments and modeling. In an experiment, continuous motion of the droplet is achieved when it is located over an active electrode with a horizontal ground wire placed just above in an open-electrowetting-on-dielectric configuration. Using a CCD camera, the instantaneous centroid position of the droplet is determined and its velocity is inferred by numerical differentiation. The edge-detected image is also used to determine the advancing and receding contact angles of the moving drop relative to the substrate. Motion of 2, 6, and 10 µl water droplets for voltages in the range of 170–270 V DC is examined to investigate the effect of drop volume and voltage on drop deformation and velocity. The motion of the droplet is initiated by Young-Lippmann spreading at the three-phase contact line, followed by a nonuniform electric force field distributed between the active electrode and the ground wire localized at the droplet-air interface. Simulations carried out using COMSOL© Multiphysics with full coupling between the electric field and hydrodynamics are in conformity with experiments. A contact angle model with pinning and friction leads to close agreement between simulations and drop motion over a bare PDMS layer, particularly in terms of the relevant timescales. When contact line friction is neglected, the fully coupled numerical solution shows a good match with experimentally determined drop movement over a silicone oil-coated PDMS layer. Over both surfaces, continuous motion of the water droplet is seen to be achieved in three stages, namely, initial spreading, acceleration, and attainment of constant speed.

Thrust Pointing Adjustment of Electric Propulsion System

The satellite uses an electric propulsion system (EPS) to complete the north-south station-keeping (NSSK) work. Due to the change of satellite centroid position during the whole life period, electric propulsion thrust pointing adjustment is required to minimize the deviation between the thrust vector and the satellite centroid, to avoid the additional interference torque and the decrease of the position protection efficiency of the EPS. In this paper, the electric propulsion thrust pointing adjustment method is designed, the mathematical model of the pointing adjustment angle is established, the conformity of the thrust pointing adjustment during the whole life of the spacecraft is analyzed, and the ground integration test verification and the on-orbit electric propulsion thrust pointing adjustment verification are completed. The analysis and verification data show that the adjustment range and accuracy of the EPS can meet the requirements of the NSSK mission.

Effect of three-dimensional geometric structure and surface wettability on two-phase flow behavior in a proton exchange membrane fuel cell gas flow channel: modeling and simulation

Improving water management capability is crucial for enhancing the performance and extending the lifespan of a proton exchange membrane fuel cell (PEMFC). To achieve this goal, this study investigates the coupling effects of geometric features induced by actual gas flow channel (GFC) manufacturing processes and the surface wettability on the dynamic droplet change by simulating 32 cases using the volume of fluid (VOF) method. In addition, the simulated dynamic characteristics of the droplets, such as the centroid position and droplet height, have been verified by comparing them with experimental observations. The reliable results of the simulation show that varied draft angles contribute to different local vortices in the flow channels, arousing two drainage mechanisms—spontaneous and overflow drainage. Besides, the compared results of velocity contours suggest that the curvature effect along the water movement direction could strengthen the speed-up effect around a water droplet, thereby facilitating its detachment. By contrast, a cross-section with filleted corners could cause velocity loss and poor drainage efficiency. A geometric structure with a draft angle of 30° and a bend radius of 1 mm of wavy GFC is beneficial to shorten the water removal time and minimize gas diffusion layer (GDL) water coverage. The hydrophobic treatment of the GDL and channel wall meets both criteria of rapidly reducing liquid water coverage on both the GDL surface and the entire channel. This study's findings are expected to guide the target of both geometric manufacturing and surface treatment processes.

Prediction of the distribution of tractor driver’s eye positions

A predictive model of tractor driver’s eye positions based on the anthropometric parameters and tractor cab layout parameters was established using the statistical approach. To our knowledge, this model is the first published predictive model of tractor drivers’ eye positions that takes account of their body dimensions and tractor types. In order to predict the distribution of the drivers’ eye positions precisely, the fore-and-aft positions of the driving seat determined by 180 tractor drivers in three different tractors and the relative positions of the eyes to the designated reference points were recorded to quantitatively demonstrate the distribution rule of their eye positions. The multiple linear regression and principal component analysis were adopted to processing the feature parameters of human and tractor, and the prediction effect of the model was assessed according to the proportion of the driver’s eye positions from side view those were within the range of the eyellipse model. The experimental result revealed that the centroid positions and principal axis dip angle of the model differed from each other respectively, while the axis lengths were the same. The principal axis dip angle was horizontal or oblique forward-and-upward. And the tractor layout parameters had a significant impact on the centroid coordinate and principal axis dip angle of the model, while the dimension of the model was associated with the anthropometric parameters mainly. The prediction accuracy of the model exceeded 80%. The regression predictive model provides a reference tool for the visual field design of tractor displays and cab layouts.

A detection method of wormhole attack in power communication sensor networks based on hops

Aiming at the problems of low accuracy of determining attack nodes and large detection error in the wormhole attack detection method of power communication sensor networks, a wormhole attack detection method based on hops is proposed. Firstly, the working process of power communication sensor network nodes is analyzed; Regard the node area as a closed circle, set the distance between nodes and communication radius in the area, and determine the wormhole attack location; Then, introduce the hop number, replace the linear distance between attack nodes with the hop distance of hop number, the centroid position is calculated by polygon calculation, the node hop distance is determined, and the wormhole attack probability is calculated; Finally, the average hop distance between wormhole attack nodes is calculated, and the path hop distance of attack behavior is corrected with the help of objective function and minimum mean square error criterion to complete attack detection. The experimental results show that the detection accuracy of this method is 98%, and the detection error is only 2.6%, so it has application value.

Study on the spatial regularity of rammed pits of the Ming Great Wall using 3D scanning technique and Random Forest algorithm

In Northwestern China, the Ming Great Wall generally involves multiple layers of rammed earth, and rammed pits with regular spatial characteristics are always distributed on the horizontal interfaces between rammed layers. Obviously, the spatial regularity of rammed pits cannot only reflect the level of ramming technique in the Ming dynasty, but also control the geotechnical properties of rammed layer interfaces (RLIs). Hence, in the present study, one typical RLI with visible rammed pits was obtained from the Ming Great Wall in Yongchang County, Northwestern China, and the corresponding point cloud data were collected by 3D scanning technique. Then, this RLI was reconstructed using numerous micro slopes in ArcGIS, and the distribution maps of micro-slope heights, angles, plan curvatures and profile curvatures were produced as well. Based on these distribution maps and Random Forest (RF) algorithm, those micro slopes which can reflect the true rammed pit morphology (called the representative micro slopes) were identified, and ten zones where the representative micro slopes concentrate were selected as effective analysis domains. Furthermore, within effective analysis domains, the contour lines were generated to show the outline features of rammed pits, and the values of micro-slope heights, angles, plan curvatures and profile curvatures were statistically analyzed to reveal the surface features of rammed pits. Moreover, the distribution features of rammed pits were exhibited by their centroid positions, which can be calculated by the corresponding contour line shapes. Ultimately, this study indicates that rammed pits of the Ming Great Wall show more regularity than randomness in terms of geometric shapes and spatial distribution. Concretely, the outlines of most rammed pits approximate the circular or elliptical shapes. All the rammed pit surfaces are rough rather than smooth, and most of them can be mathematically expressed by quadratic polynomial equations. As for the distribution features, rammed pits are overall distributed in the triangular shapes, and distances between the equivalent centroids of adjacent rammed pits range from 8.95 cm to 17.86 cm. These findings prove that standardized ramming technique was applied in the Ming dynasty, resulting in high-quality construction of the Great Wall. Meanwhile, the rammers used to compact earthen materials possess rounded heads. However, the imperfect polishing of rammers and the inevitable operational errors could also lead to slight spatial randomness of rammed pits.

Research on numerical simulation of submunition dispenser under different dispersion state

In order to study the process of submunition airbag dispersal under different dispersion state, the p-t curve of gas generator combustion obtained by closed bomb test was transformed into the mass flow rate-time curve to simulate the process of airbag inflation. As the initial condition, it was input into the finite element model of submunition dispersal established by LS-DYNA software, and the results were compared with the literature data to verify the accuracy of the calculation method. Then, through the numerical simulation of airbag dispersion of submunition with different centroid positions and initial placement angles, the simulation results show that the dispersal velocity of the submunition decreases with the increase of the offset of the centroid in the x direction and the placement angle. The peak overload decreases with the increase of centroid offset and placement angle. The angular velocity of the submunition rotating around the y axis increases with the increase of the offset of the centroid in the x direction; the velocity of submunition rotating around x axis increases with the increase of the offset of centroid in y direction.

Study on Impact Response of Typical Powder in Confined Space

A novel experiment combined with simulation method was developed to investigate the impact response of the powder which was put into a submunition. The powder’s material model parameter was determined by powder mechanical test. Machete hammer test platform was built to apply 20kG~30kG load to the submunition. The submunition was recycled and the powder state was observed after impacting by the Machete hammer. What’s more, nonlinear dynamics analysis software (AUTODYN) was applied to clarify the impact response and density distribution process of the powder. A verified ideal model was carried out to simulate the explosive impact loading process of the submunition. The powder density distribution was reconstructed by MATLAB. Meanwhile, a law of the powder’s centroid with the over loading was successfully established based on the simulation data. The results shows that the peak value of the impact loading has a linear relationship with the relative offset of the centroid position.

Dim and Small Space-Target Detection and Centroid Positioning Based on Motion Feature Learning

The detection of dim and small space-targets is crucial in space situational awareness missions; however, low signal-to-noise ratio (SNR) targets and complex backgrounds pose significant challenges to such detection. This paper proposes a space-target detection framework comprising a space-target detection network and a k-means clustering target centroid positioning method. The space-target detection network performs a three-dimensional convolution of an input star image sequence to learn the motion features of the target, reduces the interference of noise using a soft thresholding module, and outputs the target detection result after positioning via the offsetting branch. The k-means centroid positioning method enables further high-precision subpixel-level centroid positioning of the detection network output. Experiments were conducted using simulated data containing various dim and small space-targets, multiple noises, and complex backgrounds; semi-real data with simulated space-targets added to the real star image; and fully real data. Experiments on the simulated data demonstrate the superior detection performance of the proposed method for multiple SNR conditions (particularly with very low false alarm rates), robustness regarding targets of varying numbers and speeds, and complex backgrounds (such as those containing stray light and slow motion). Experiments performed with semi-real and real data both demonstrate the excellent detection performance of the proposed method and its generalization capability.

Numerical Simulation Investigation on Parameter Optimization of Deep-Sea Mining Vehicles

The four-track walking mining vehicle can better cope with the complex terrain of cobalt-rich crusts on the seabed. To explore the influence of different parameters on the obstacle-crossing ability of mining vehicles, this paper took a certain type of mine vehicle as an example and establish a mechanical model of the mine vehicle. Through this model, the vehicle’s traction coefficient variation could be analyzed during the obstacle-crossing process. It also reflected the relationship between the obstacle-crossing ability and the required traction coefficient. Many parameters were used for this analysis including the radius of the guide wheel radius, ground clearance of the driving wheel, the dip angle of the approaching angular and the position of centroid. The result showed that the ability to cross the obstacles requires adhesion coefficient as support. When the ratio between obstacle height and ground clearance of the guide wheel was greater than 0.7, the required adhesion coefficient increased sharply. The ability to cross obstacles will decrease, if the radius of the guide wheel increases, the height of the driving wheel increases or the dip angle of the approaching angular increases. It was most beneficial to cross the obstacle when the ratio of the distance between the center of mass and the front driving wheel to the wheelbase is between 0.45‒0.48. The results of this paper could provide reference for structural parameter design and performance research for mining vehicles.

Solute cloud evolution in channels with suspended vegetation of different configurations

Suspended vegetation's ability to handle solute accumulation in natural waters through their roots has sparked significant interest and research in using them to improve water quality. This research semi-analytically investigates the unsteady solute cloud evolution in channels with suspended vegetation after the point source release on the water surface, by solving the solute transport model with spatially variable flow field coefficients. Results show that regardless of gap ratio (the ratio of the height of the gap region to the water depth) and vegetation density, the solute cloud evolution in the preasymptotic stage (the dimensionless time ⟨Dz*⟩t*/h*2<1, where ⟨Dz*⟩ is the depth-averaged vertical turbulent diffusion coefficient. t* is the time, and h* is water depth.) can be featured by: the cloud centroid shifts upstream; the longitudinal dispersion coefficient increases; the solute cloud is positively skewed; and the solute accumulates in the vegetation layer on the upstream side and the bottom boundary layer on the downstream side. At around ⟨Dz*⟩t*/h*2∼1, the cloud centroid position and the longitudinal dispersion coefficient approach their asymptotic values, and the solute cloud is basically considered to follow the normal distribution longitudinally. In terms of the influences of configurations on the solute cloud during the whole dispersion process, the cloud centroid moves faster and reaches a farther asymptotic location due to a more serious blockage effect for a smaller gap ratio or larger vegetation density. In addition, a small gap ratio enhances the skewness and kurtosis of the cloud, while the vegetation density has little effect on them. Benefiting from the combined action of the violent velocity shear and the strong shear-scale diffusion which dominates the vertical mixing, the smallest gap ratio or highest vegetation density promotes the vertical mixing and yields the largest asymptotic longitudinal dispersion coefficient. Consequently, the vertical concentration distribution is the most uniform and the longitudinal concentration distribution is the flattest in these two cases.

Visual Detection and Association Tracking of Dim Small Ship Targets from Optical Image Sequences of Geostationary Satellite Using Multispectral Radiation Characteristics

By virtue of the merits of wide swath, persistent observation, and rapid operational response, geostationary remote sensing satellites (e.g., GF-4) show tremendous potential for sea target system surveillance and situational awareness. However, ships in such images appear as dim small targets and may be affected by clutter, reef islands, clouds, and other interferences, which makes the task of ship detection and tracking intractable. Considering the differences in visual saliency characteristics across multispectral bands between ships and jamming targets, a novel approach to visual detecting and association tracking of dense ships based on the GF-4 image sequences is proposed in this paper. First, candidate ship blobs are segmented in each single-spectral image of each frame through a multi-vision salient features fusion strategy, to obtain the centroid position, size, and corresponding spectral grayscale information of suspected ships. Due to the displacement of moving ships across multispectral images of each frame, multispectral association with regard to the positions of ship blobs is then performed to determine the final ship detections. Afterwards, precise position correction of detected ships is implemented for each frame in image sequences via multimodal data association between GF-4 detections and automatic identification system data. Last, an improved multiple hypotheses tracking algorithm with multispectral radiation and size characteristics is put forward to track ships across multi-frame corrected detections and estimate ships’ motion states. Experiment results demonstrate that our method can effectively detect and track ships in GF-4 remote sensing image sequences with high precision and recall rate, yielding state-of-the-art performance.

Toward Imaging Defect-Mediated Energy Transfer between Single Nanocrystal Donors and Single Molecule Acceptors.

Defect-mediated energy transfer is an energy transfer process between midgap electronic states in a semiconductor nanocrystal (NC) and molecular acceptors, such as fluorescent dye molecules. Super-resolution fluorescence microscopy represents an exciting technique for pinpointing the nanoscale positions of lattice defect sites in, for example, a micrometer-sized particle or thin film sample by spatially resolving the location of the acceptor dye molecules with nanometer resolution. Toward this goal, our group performed ensemble-level, time-resolved fluorescence spectroscopy measurements of ZnO NC/Alexafluor 555 (A555) mixtures and calculated that the emissive defect sites are located, on average, 0.5 nm from the NC surface [Nilsson Z. N.; J. Chem. Phys.2021, 154 ( (5), ), 054704]. However, ensemble-level measurements cannot spatially resolve the defect sites on single particles, nor can they distinguish between surface-adsorbed dye molecules that participate in the energy transfer (EnT) process from those that do not. In this work, we compared the photoluminescence intensity trajectories of 789 isolated, single ZnO NC donors to those of 73 non-specifically bound and five specifically bound ZnO NC/A555 pairs, where the donor and acceptor centroid positions were separated by a distance that was smaller than our localization precision (40 nm). We observed minor fluorescence intensity fluctuations in the donor and defect channels instead of clear anticorrelated intensity fluctuations, which could be explained by (1) the presence of multiple emissive defect sites per NC, (2) donor-acceptor separation distances slightly larger than the Förster radius (R 0 = 3.1 nm; defined as the distance at which EnT is 50% efficient), and/or (3) poor dipole-dipole coupling. The single molecule imaging methodology we developed, an alternating ultraviolet-visible excitation sequence combined with multicolor photon detection, successfully distinguishes specifically bound and non-specifically bound NC/dye pairs and can be applied to study a wide range of hybrid NC/dye energy transfer systems.

Parameter estimation of the shell transfer arm of a loading mechanism

The shell transfer arm is a key component of gun automatic loading mechanism, the coordination speed and positioning accuracy have an important impact on gun ammunition delivery effect. Establishing an accurate dynamic model is the foundation for better control and prediction, therefore, it is necessary to identify the dynamic parameters of the shell transfer arm. In this paper, the dynamic model is established based on the topology method. The parameter identification model of the shell transfer arm is constructed by applying the dynamic model and unscented Kalman filter theory. Dynamic parameters of the shell transfer arm such as the mass, inertia and centroid position are estimated under unscented Kalman filter scheme. By comparing the parameter estimation results with the nominal design values, the feasibility and effectiveness of applying the proposed method to identify the dynamic parameters of the shell transfer arm are verified.

Wavelength-dependent three-dimensional single-molecule superlocalization imaging for yoctomole detection of thyroid-stimulating hormone on a quantum dot nanobiosensor

A wavelength-dependent three-dimensional (3D) superlocalization imaging method on gold nanoislands (GNIs) chip was developed as a supersensitive single-molecule thyroid-stimulating hormone (TSH) nanobiosensor. Scattered and fluorescent signals from gold nanoislands on the substrate and quantum dots (QDs) nanoprobes were simultaneously isolated and acquired within an evanescent field layer generated by total internal reflection (TIR) of incident light using a dual-view device. The 3D TIR fluorescence images of TSH-bound QDs on the GNIs were obtained using z-axis optical sectioning at 10 nm intervals before/after immunoreaction to identify the optimal conditions for detection. The localized centroid position of QD nanoprobes and GNI were distinguished at a subdiffraction limit resolution using 3D Gaussian fitting to the point spread function. The QD TSH nanobiosensor using wavelength-dependent 3D TIR fluorescence-based single-molecule localization microscopy (3D TIRF-SLM) imaging technique showed an excellent detection limit of 90 yoctomoles (∼54 molecules) and a wide linear dynamic range of 1.14 zmol/L − 100 pmol/L for TSH. The detection sensitivity was about 4.4 × 109 times higher than conventional enzyme-linked immunosorbent assay and could successfully quantify TSH in human serum. The wavelength-dependent 3D TIRF-SLM technique may emerge as a reliable platform for ultrahigh-sensitive nanobiosensors at the single-molecule level and early diagnosis with quantification of disease-related ultra-trace biomolecules.

Scaphoid kinematics in scapholunate instability: a dynamic CT study

ObjectiveThe scaphoid is proposed to be driven by the distal carpal row in scapholunate instability (SLI) as it is dissociated from the proximal row. The aim of this study was to describe the 6 degrees of freedom kinematics of the scaphoid using dynamic CT in the normal and SLI wrists. We hypothesised that the SLI scaphoid would demonstrate kinematic evidence conforming to distal row motion.Materials and methodsWe studied dynamic CT scans of 17 SLI and 17 normal wrists during ulnar to radial deviation and extension to flexion. The radio-scaphoid angles in three anatomic planes were calculated in the wrist neutral position and during wrist motion. The centroid position was also calculated in the wrist neutral position and during wrist motion. The scapho-capitate motion index (SCI) was calculated as a ratio between the scaphoid and the capitate motion.ResultsIn the neutral position of the wrist, the SLI scaphoid was flexed, internally rotated, and radially translated compared to the normal scaphoid. During wrist motion, the SLI scaphoid had more ‘in-plane’ motion and less ‘out-of-plane’ motion with a higher SCI during wrist neutral to radial deviation and extension to neutral.ConclusionWe have described the malalignment of the SLI scaphoid in the neutral position of the wrist and 6 degrees of freedom kinematics during wrist motion of the SLI scaphoid compared to the normal. The SLI scaphoid conformed more to the distal row motion than the normal scaphoid. This information may help define the surgical reconstruction techniques for SLI.

An error compensation scheme for polar coordinate glass edging machines using the contour registration method

This paper proposes a comprehensive error compensation method for the glass edging machine using polar coordinates. An error model is established to evaluate the error source of the contour deviation from the ideal position after glass installation. According to the simulation results, it is determined that the misalignment of the linear axis and the rotary table and the inaccuracy of the fixture are the main reasons for the installation error of the work-piece. Then, a two-step contour registration method is introduced to accomplish the task of error identification. The glass contour is first measured by a laser displacement sensor after being installed on the rotary table. The coarse registration is presented to align the centroid positions of the measured and the ideal contours, and the fine registration is developed to match them precisely. After that, the installation error can be extracted from the transformation parameters by the least square method. Furthermore, a compensation model is proposed to map the original contour to the actual installation position using the transformation matrix constructed by the identified errors. Finally, a verification experiment is implemented that compares the grind edge without and with compensation to validate the efficiency and accuracy of the proposed method. After error compensation, the mean value and the variance value of the polar diameter deviation of the glass work-piece decreased by 87.5% and 83.0%, respectively. This paper provides a simple way to identify and compensate the installation errors online with high accuracy and efficiency. The proposed method can improve the machining accuracy of the polar coordinate glass edging machines and reduce glass waste.