Low-consumption stepper motor controller with real-time target position change responsiveness based on field programmable gate array.

In response to the demand for low resource consumption, parallel control, and real-time response to target position changes in precision measurement and manufacturing of multi-axis stepper motor controllers, this paper proposes a field programmable gate array-based method for generating trapezoidal velocity profiles and pulse generation, which can easily keep parallelism and independence during multi-axis control. By avoiding using multiplication and division, this controller not only reduces resource consumption but also enhances the pulse output frequency. To address the real-time responsiveness of the velocity profile generation algorithm to changes in the target position during the control process, the algorithm introduces a novel real-time comparative state transition logic for speed control, which makes it capable of adjusting the acceleration within a single clock cycle, enabling its application in scenarios that require higher levels of real-time performance. Finally, the designed controller is applied to a four-axis positioning system for performance validation.

A Fully Convolutional Network-Based Tube Contour Detection Method Using Multi-Exposure Images.

The tube contours in two-dimensional images are important cues for optical three-dimensional reconstruction. Aiming at the practical problems encountered in the application of tube contour detection under complex background, a fully convolutional network (FCN)-based tube contour detection method is proposed. Multi-exposure (ME) images are captured as the input of FCN in order to get information of tube contours in different dynamic ranges, and the U-Net type architecture is adopted by the FCN to achieve pixel-level dense classification. In addition, we propose a new loss function that can help eliminate the adverse effects caused by the positional deviation and jagged morphology of tube contour labels. Finally, we introduce a new dataset called multi-exposure tube contour dataset (METCD) and a new evaluation metric called dilate inaccuracy at optimal dataset scale (DIA-ODS) to reach an overall evaluation of our proposed method. The experimental results show that the proposed method can effectively improve the integrity and accuracy of tube contour detection in complex scenes.

Rapid 3D reconstruction method based on the polarization-enhanced fringe pattern of an HDR object.

Measurement of high dynamic range objects is an obstacle in structured light 3D measurement. They entail both over-exposed and low-exposed pixels in a single exposure. This paper proposed a polarization-enhanced fringe pattern (PEFP) method that a high dynamic range image can be obtained within a single exposure time. The degree of linear polarization (DOLP) is calculated using the polarization properties of reflected light and a linear polarizer in fixed azimuth in this method. The DOLP is efficiently estimated by the projected polarization-state-encode (PSE) pattern, and it does not need to change the state of the polarizer. The DOLP depends on light intensity rather than the reflectivity of the object surfaces indicated in experimental results. The contrast of fringe patterns was enhanced, and the quality of fringe patterns was improved by the proposed method. More sufficient 3D point clouds and high-quality shape can be recovered using this method.

A Robust Laser Stripe Extraction Method for Structured-Light Vision Sensing.

Environmental sensing is a key technology for the development of unmanned cars, drones and robots. Many vision sensors cannot work normally in an environment with insufficient light, and the cost of using multiline LiDAR is relatively high. In this paper, a novel and inexpensive visual navigation sensor based on structured-light vision is proposed for environment sensing. The main research contents of this project include: First, we propose a laser-stripe-detection neural network (LSDNN) that can eliminate the interference of reflective noise and haze noise and realize the highly robust extraction of laser stripes region. Then we use a gray-gravity approach to extract the center of laser stripe and used structured-light model to reconstruct the point clouds of laser center. Then, we design a single-line structured-light sensor, select the optimal parameters for it and build a car-platform for experimental evaluation. This approach was shown to be effective in our experiments and the experimental results show that this method is more accurate and robust in complex environment.

Calibration method for a line-structured light vision sensor based on a single cylindrical target.

This paper presents a new, to the best of our knowledge, calibration method for line-structured light vision sensors. The laser stripe intersecting the cylindrical target and the line-structured light is captured by the camera, and the light plane parameters of the line-structured light are obtained by combining the cross-sectional characteristics of the ellipse. The nonlinear optimization of the light plane parameters use multiple locations to get the optimal solution of the light plane equation. This method requires only a single cylindrical target, which in turn greatly simplifies the calibration process. The results of simulation experiments and physical experiments show that the proposed calibration method can achieve higher calibration accuracy and measurement accuracy. The effectiveness of the new calibration method is verified.

An Embedded Multi-branch 3D Convolution Neural Network for False Positive Reduction in Lung Nodule Detection.

Numerous lung nodule candidates can be produced through an automated lung nodule detection system. Classifying these candidates to reduce false positives is an important step in the detection process. The objective during this paper is to predict real nodules from a large number of pulmonary nodule candidates. Facing the challenge of the classification task, we propose a novel 3D convolution neural network (CNN) to reduce false positives in lung nodule detection. The novel 3D CNN includes embedded multiple branches in its structure. Each branch processes a feature map from a layer with different depths. All of these branches are cascaded at their ends; thus, features from different depth layers are combined to predict the categories of candidates. The proposed method obtains a competitive score in lung nodule candidate classification on LUNA16 dataset with an accuracy of 0.9783, a sensitivity of 0.8771, a precision of 0.9426, and a specificity of 0.9925. Moreover, a good performance on the competition performance metric (CPM) is also obtained with a score of 0.830. As a 3D CNN, the proposed model can learn complete and three-dimensional discriminative information about nodules and non-nodules to avoid some misidentification problems caused due to lack of spatial correlation information extracted from traditional methods or 2D networks. As an embedded multi-branch structure, the model is also more effective in recognizing the nodules of various shapes and sizes. As a result, the proposed method gains a competitive score on the false positive reduction in lung nodule detection and can be used as a reference for classifying nodule candidates.

Effect of Catadioptric Component Postposition on Lens Focal Length and Imaging Surface in a Mirror Binocular System.

The binocular vision system is widely used in three-dimensional measurement, drone navigation, and many other fields. However, due to the high cost, large volume, and inconvenient operation of the two-camera system, it is difficult to meet the weight and load requirements of the UAV system. Therefore, the study of mirror binocular with single camera was carried out. Existing mirror binocular systems place the catadioptric components in front of the lens, which makes the volume of measurement system still large. In this paper, a catadioptric postposition system is designed, which places the prism behind the lens to achieve mirror binocular imaging. The influence of the post prism on the focal length and imaging surface of the optical system is analyzed. The feasibility of post-mirror binocular imaging are verified by experiments, and it is reasonable to compensate the focal length change by changing the back focal plane position. This research laid the foundation for the subsequent research on the 3D reconstruction of the novel mirror binocular system.

Automatic classification of lung nodule candidates based on a novel 3D convolution network and knowledge transferred from a 2D network.

OBJECTIVE: In the automatic lung nodule detection system, the authenticity of a large number of nodule candidates needs to be judged, which is a classification task. However, the variable shapes and sizes of the lung nodules have posed a great challenge to the classification of candidates. To solve this problem, we propose a method for classifying nodule candidates through three-dimensional (3D) convolution neural network (ConvNet) model which is trained by transferring knowledge from a multiresolution two-dimensional (2D) ConvNet model. METHODS: In this scheme, a novel 3D ConvNet model is preweighted with the weights of the trained 2D ConvNet model, and then the 3D ConvNet model is trained with 3D image volumes. In this way, the knowledge transfer method can make 3D network easier to converge and make full use of the spatial information of nodules with different sizes and shapes to improve the classification accuracy. RESULTS: The experimental results on 551 065 pulmonary nodule candidates in the LUNA16 dataset show that our method gains a competitive average score in the false-positive reduction track in lung nodule detection, with the sensitivities of 0.619 and 0.642 at 0.125 and 0.25 FPs per scan, respectively. CONCLUSIONS: The proposed method can maintain satisfactory classification accuracy even when the false-positive rate is extremely small in the face of nodules of different sizes and shapes. Moreover, as a transfer learning idea, the method to transfer knowledge from 2D ConvNet to 3D ConvNet is the first attempt to carry out full migration of parameters of various layers including convolution layers, full connection layers, and classifier between different dimensional models, which is more conducive to utilizing the existing 2D ConvNet resources and generalizing transfer learning schemes.

Combining proton and silaborane-based superhalogen anions - an effective route to new superacids as verified via systematic DFT calculations.

Based on systematic DFT calculations, silaborane-based superhalogen anions, which obey the Wade-Mingos rule, are shown to be capable of giving rise to superacids via their combination with protons. Compared to previous carborane-based systems, the acidities of the composites here are stronger in both the gas phase and solution phase. Thus, the potential of candidates based on silaborane could be greater than those based on carborane in the search for ultra-strong acidic systems. Within a given group, a higher superhalogen anion vertical electron detachment energy (VDE) generally leads to stronger acidity. This consistency arises from the dominant role of the VDE, as established through the decomposition of the gas-phase acidity into different contributions. Thus, constructing superacids from superhalogens is a rational route whose future should be positive. Besides the VDE, other effects, i.e., the deformation energy (DE) and bond dissociation energy (BDE), could also be crucial, especially in terms of the differences between the acidities of composites belonging to different groups. A comparison between the results in the gas phase and solution phase indicates that complete calculations of both gas-phase ΔGacid and solution-phase pKa values are necessary to obtain an unbiased description of the acidity. The solvation free energies of the participants in the deprotonation process, especially the conjugate acid, are responsible for the discrepancies between gas phase and solution phase behavior.

A PD-L1-Based Cancer Vaccine Elicits Antitumor Immunity in a Mouse Melanoma Model.

Engagement of programmed death 1 receptor (PD-1) and its ligand PD-L1/2 induces a signal transduction pathway that inhibits the activity of tumor-infiltrating cytotoxic T lymphocytes and promotes tumor growth and metastasis. Antibodies blocking PD-1 or PD-L1 can restore antitumor T cell responses and cause long-term remission in a subset of cancer patients with advanced or refractory tumors. In this study, we asked whether PD-L1 vaccination could confer tumor control in mouse tumor models. To address the central tolerance toward self-molecules, we fused the extracellular domain of PD-L1 (PD-L1E) to the C-terminal of the translocation domain of diphtheria toxin (DTT). DTT is able to elicit CD4+ T cell responses required for inducing robust immune responses against self-molecules. The fusion molecule is called DPDL1E. When formulated with incomplete Freund's adjuvant (IFA), DPDL1E elicited robust immune responses biased toward the Th1 type and inhibited tumor growth in both preventive and therapeutic mouse tumor models. We further showed that the anti-DPDL1E sera blocked PD-L1 binding to PD-1 in vitro. The DPDL1E vaccination increased the levels of tumor-infiltrating T lymphocytes (TILs) and reduced the levels of myeloid-derived suppressor cells (MDSCs) as well as exhausted LAG3+PD-1+ CD8+ T cells. All of these data suggest that DPDL1E vaccination reverses the suppressive phenotype of the tumor microenvironment and that it is a promising strategy for cancer therapy.

Constructing organic superacids from superhalogens is a rational route as verified by DFT calculations.

The construction route of organic superacids from the combination of organic superhalogens and protons is verified to be a rational one based on a systematic theoretical study covering different planar conjugated backbones, e.g., [C5H5]- and [BC5H6]-, and electron-withdrawing substituents, e.g., -F, -CN and -NO2. In both the gas phase and the solution phase, the acidities of the composites here have a consistent strengthening with the increase of the vertical electron detachment energy of the superhalogen part. Decomposition of the acidity into different contributions further verifies the dominant role of the superhalogen part in the variation of the acidity. Thus, tuning of the acidity of systems of this type could be achieved via rational design of the constituent part of the superhalogen. That is to say, the design of a novel organic superacid with enhanced properties could be guided by the search for a new strong superhalogen of organic nature eventually. Having provided important contributions to the topic of superhalogens, theoretical calculation should be trusted to provide useful guidance for the research of organic superacids and could be expected to promote related experimental studies in the near future.

A New Dictionary Construction Based Multimodal Medical Image Fusion Framework.

Training a good dictionary is the key to a successful image fusion method of sparse representation based models. In this paper, we propose a novel dictionary learning scheme for medical image fusion. First, we reinforce the weak information of images by extracting and adding their multi-layer details to generate the informative patches. Meanwhile, we introduce a simple and effective multi-scale sampling to implement a multi-scale representation of patches while reducing the computational cost. Second, we design a neighborhood energy metric and a multi-scale spatial frequency metric for clustering the image patches with a similar brightness and detail information into each respective patch group. Then, we train the energy sub-dictionary and detail sub-dictionary, respectively by K-SVD. Finally, we combine the sub-dictionaries to construct a final, complete, compact and informative dictionary. As a main contribution, the proposed online dictionary learning can not only obtain an informative as well as compact dictionary, but can also address the defects, such as superfluous patch issues and low computation efficiency, in traditional dictionary learning algorithms. The experimental results show that our algorithm is superior to some state-of-the-art dictionary learning based techniques in both subjective visual effects and objective evaluation criteria.

Why do higher VDEs of superhalogen not ensure improved stabilities of the noble gas hydrides promoted by them? A high-level ab initio case study.

A series of 20 composite structures, consisting of superhalogen and noble gas (Ng) hydrides, was explored via high-level coupled-cluster single, double and perturbative triple excitations calculations in this work. The existence of these composites, as local minima on the potential energy surface, arises from the charge transfer from the Ng hydride part to the superhalogen moiety. Clearly, this transfer could lead to stabilizing the interaction of the ionic type between the two components. The driving force of the charge transfer should be the high vertical electron detachment energy (VDE) of the superhalogen part leading to its enough capability of extracting the electron from the Ng hydride moiety. However, except triggering the ionic attractive interaction, there is nomonotonic correlation between the VDE value and the thermodynamic stability of the whole composite. This counter-intuitive result actually originates from the fact that, irrespective of various superhalogens, only two of their F ligands interact with the Ng atoms directly. Thus, although leading to higher VDE values, the increase in the number of electronegative ligands of the superhalogen moiety does not affect the stabilizing interaction of the composites here directly. In other words, with the necessary charge transfer generated, further increase of the VDE does not ensure the improvement of the thermodynamic stabilities of the whole composite. Moreover, in the transition state of the exothermic dissociation channel, more F atoms will give rise to higher probability of additional attractions between the F and H atoms which should lower the energy barrier. That is to say, increasing VDE, i.e., having more F atoms in many cases, will probably reduce the kinetic stability. Knowing the inevitable existence of the exothermic channel, kinetic stability is crucial to the ultimate goal of experimental observation of these Ng hydrides. Thus, in some cases, only the superhalogen itself may not provide enough information for the correct prediction on the properties of the whole composites. The understanding of the superhalogen-based composites will provide valuable information on the functional properties as well as the application potential of superhalogen clusters. Thus, the corresponding researches should focus on not only the superhalogen itself but also other related aspects, especially the details of the interaction between different parts.

Double distortion correction method in a catadioptric vision system with a conic mirror.

Because of the low calibration precision caused by reflector distortion in catadioptric vision systems with conic mirrors, we proposed a double distortion correction model based on the panoramic image rectification. The lens distortion and the reflector distortion are analyzed independently in the mathematic model of the double distortion correction. Moreover, the modified model in this paper added the trigonometric functions into the polynomial model to solve the combined distortion. Additionally, extensive experiments, both simulative and real data, have been carried out and show that the proposed model achieves comparable measurement accuracy in contrast with the traditional distortion method.

Could the increased structural versatility imposed by non-halogen ligands bring something new for polynuclear superhalogens? A case study on binuclear [Mg2L5]- (L = -OH, -OOH and -OF) anions.

A combined ab initio and DFT study is performed in this work to explore the superhalogen properties of polynuclear structures based on the ligands of -OH, -OOH and -OF. According to high-level CCSD(T) results, all the structures here are superhalogens whose properties are superior to the corresponding mononuclear ones. Although inferior to similar structures based on F ligands, some of the superhalogens here are capable of transcending the traditional ones based on Cl atoms. Therefore the superhalogen properties of the anions here are still promising and they have an important advantage of high safety, which is crucial for practical applications. An increased degree of structural versatility is imposed by these non-halogen ligands because of the various ways in which they connect the central atoms and their multiple orientations. It is important that this increased versatility will bring new factors, e.g., the larger spatial extent of the whole cluster and the existence of intra-molecular hydrogen bonds, which should favour high VDE values. These factors are not available in traditional halogen-based systems and they may play an important role in the future search for novel superhalogens. (HF + MP2)/2, ωB97XD as well as M06-2X are capable of providing accurate VDE values, close to the CCSD(T) results, and their absolute errors are even lower than that of the OVGF. Due to the good balance between the accuracy and efficiency, these methods could provide reliable predictions on large systems which cannot be treated with CCSD(T) or even with the OVGF. Balanced distribution of the extra electron, between the terminal and bridging ligands, is also shown to be favourable to realize a high VDE value.

The Combination of Superhalogens and Brønsted Acids HX (X = F, Cl, Br): An Effective Strategy for Designing Strong Superacids.

A series of 27 composite structures, consisting of superhalogen and Brønsted acid, is designed and systematically studied based on combined ab initio and DFT calculations focusing on their potentials as novel superacids. As indicated by high-level CCSD(T) results, all the composites here fulfill the theoretical criterion for superacid and the acidities of two of them are close to the strongest superacid ever reported. The influences of various factors on the superacid properties of these composites were analyzed in detail. Our results demonstrate that the acidity of these superacids is mainly determined by the superhalogen components while the effect of Brønsted acids, irrespective of their number or type, is relatively mild. Therefore, it is probable to design novel composite superacid with enhanced property through the regulation of the superhalogen component. It is encouraging that MP2 and DFT could also provide reliable results when compared with the high-level CCSD(T) method. The reliability of these low-cost methods implies the capability of theoretical calculations for future composite superacid of enlarged size, and thus it is highly probable that an effective guide to the related experimental research could be provided by the theory.

Improving basic and membrane protein MS detection of the culture filtrate proteins from Mycobacterium tuberculosis H37Rv by biomimetic affinity prefractionation.

The culture filtrate proteins (CFPs) from Mycobacterium tuberculosis have been shown to induce protective immune responses in human and animal models, making them a promising source of candidate targets for tuberculosis drugs, vaccines, and diagnostics. The constituents of the M. tuberculosis CFP proteome are complex and vary with growth conditions. To effectively profile CFPs, gel-based prefractionation is usually performed before MS analysis. In this study, we describe a novel prefractionation approach by which the proteome is divided into seven partially overlapping fractions by biomimetic affinity chromatography (BiAC) using a six-column cascade. The LC-MS/MS analysis of individual fractions identified a total of 541 CFPs, including 61 first-time identifications. Notably, ∼1/3 (20/61) of these novel CFPs are membrane proteins, among which nine proteins have 2-14 transmembrane domains. In addition, ∼1/4 (14/61) of the CFPs are basic proteins with pI values greater than 9.0. Our data demonstrate that biomimetic affinity chromatography prefractionation markedly improves protein detection by LC-MS/MS, and the coverage of basic and hydrophobic proteins in particular is remarkably increased.

Probing the potential of halogen-free superhalogen anions as effective electrolytes of Li-ion batteries: a theoretical prospect from combined ab initio and DFT studies.

The potential of 23 superhalogen anions of halogen-free structures as high-performance electrolytes of Li-ion batteries is theoretically explored here. According to high-level ab initio results at the CCSD(T) level, eight candidates, obeying the Wade-Mingos rule, should be capable of forming electrolytes, which are better than the currently used commercial products. When comparing different methods, MP2 was found to be in good agreement with CCSD(T) in the calculation of ΔELi+ and ΔEH2O, which are parameters describing the performance of potential electrolytes. Thus, MP2 represents a good choice for such calculations, particularly for large potential electrolyte systems wherein CCSD(T) calculations are actually impractical. The five functionals selected here (ωB97XD, B2GP-PLYP, B2K-PLYP, B2T-PLYP and B3LYP) are also capable of reproducing the variational trends of the relative values of different structures at the CCSD(T) level. However, the actual DFT values of ΔELi+ are usually different from those of CCSD(T) by more than 1 eV. These significant deviations may be a problem when accurate ΔELi+ values are required.

Omnidirectional stereo vision sensor based on single camera and catoptric system.

An omnidirectional stereo vision sensor based on one single camera and catoptric system is proposed. As crucial components, one camera and two pyramid mirrors are used for imaging. The omnidirectional measurement towards different directions in the horizontal field can be performed by four pairs of virtual cameras, with a consummate synchronism and an improved compactness. Moreover, the perspective projection invariance is ensured in the imaging process, which avoids the imaging distortion reflected by the curved mirrors. In this paper, the structure model of the sensor was established and a sensor prototype was designed. The influences of the structural parameters on the field of view and the measurement accuracy were also discussed. In addition, real experiments and analyses were performed to evaluate the performance of the proposed sensor in the measurement application. The results proved the feasibility of the sensor, and exhibited a considerable accuracy in 3D coordinate reconstruction.

Could the description on polynuclear superhalogens by DFT be comparable with high-level ab initio results? A comparison between DFT and CCSD(T).

A systematic density functional theory study including 17 exchange-correlation functionals was performed on different types of superhalogens with high level coupled-cluster single double including perturbative triple excitations (CCSD(T)) results as the reference. The superhalogens selected here cover the ranges from mononuclear to polynuclear structures and from structures with halogen-atom ligands to those with non-halogen ligands, e.g., [MgX3](-), [Mg2X5](-), and [Mg3X7](-) (X = F, Cl, CN). It is clearly indicated that three double-hybrid functionals B2T-PLYP, B2GP-PLYP, B2K-PLYP as well as the range-separated hybrid functional ωB97X are capable of providing results which approach the accuracy at the CCSD(T) level. The basis set effect is usually moderate and, in most cases, it is enough to utilize the basis set of triple-ξ quality, e.g., Def2-TZVP. In addition, the results of the HF and MP2 method are also acceptable here, especially for polynuclear superhalogens where CCSD(T) is probably unpractical.