Axis Transformation Research Articles

Magnetic Anisotropy Induced by Orbital Occupation States in La0.67Sr0.33MnO3 FilmsSupported by the National Key Research Program of China (Grant Nos. 2017YFA0206200, 2016YFA0300701, and 2018YFA0208402), the National Natural Science Foundation of China (Grant Nos. 11934017, 11874413, 11574376, and 51972333), the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No. XDB33030200), and the Youth Innovation Promotion Association of the Chinese

Interface engineering is an effective and feasible method to regulate the magnetic anisotropy of films by altering interfacial states between films. Using the technique of pulsed laser deposition, we prepared La0.67Sr0.33MnO3 (LSMO) and La0.67Sr0.33MnO3/SrCoO2.5 (LSMO/SCO) films on (110)-oriented La0.3Sr0.7Al0.65Ta0.35O3 substrates. By covering the SCO film above the LSMO film, we transformed the easy magnetization axis of LSMO from the [001] axis to the [] axis in the film plane. Based on statistical analyses, we find that the corresponding Mn–Mn ionic distances are different in the two types of LSMO films, causing different distortions of Mn–O octahedron in LSMO. In addition, it also induces diverse electronic occupation states in Mn3+ ions. The e g electron of Mn3+ occupies 3z 2 – r 2 and x 2 – y 2 orbitals in the LSMO and LSMO/SCO, respectively. We conclude that the electronic spin reorientation leads to the transformation of the easy magnetization axis in the LSMO films.

Improved cotton transformation protocol mediated by Agrobacterium and biolistic combined-methods

The combined Agrobacterium- and biolistic-mediated methods of cotton transformation provide a straightforward and highly efficient protocol for obtaining transgenic cotton. Cotton (Gossypium spp.) is the most important crop for natural textile fiber production worldwide. Nonetheless, one of the main challenges in cotton production are the losses resulting from insect pests, pathogens, and abiotic stresses. One effective way to solve these issues is to use genetically modified (GM) varieties. Herein, we describe an improved protocol for straightforward and cost-effective genetic transformation of cotton embryo axes, merging biolistics and Agrobacterium. The experimental steps include (1) Agrobacterium preparation, (2) seed sterilization, (3) cotton embryo excision, (4) lesion of shoot-cells by tungsten bombardment, (5) Agrobacterium-mediated transformation, (6) embryo co-culture, (7) regeneration and selection of transgenic plants in vitro, and (8) molecular characterization of plants. Due to the high regenerative power of the embryonic axis and the exceptional ability of the meristem cells for plant regeneration through organogenesis in vitro, this protocol can be performed in approximately 4-10weeks, with an average plant regeneration of about 5.5% (± 0.53) and final average transformation efficiency of 60% (± 0.55). The transgene was stably inherited, and most transgenic plants hold a single copy of the transgene, as desirable and expected in Agrobacterium-mediated transformation. Additionally, the transgene was stably expressed over generations, and transgenic proteins could be detected at high levels in the T2 generation of GM cotton plants. The T2 progeny showed no phenotypic or productivity disparity compared to wild-type plants. Collectively, the use of cotton embryo axes and the enhanced DNA-delivery system by combining particle bombardment and Agrobacterium infection enabled efficient transgenic plant recovery, overcoming usual limitations associated with the recalcitrance of several cotton genotypes subjected to somatic embryogenesis. The improved approach states this method's success for cotton genetic modification, allowing us to obtain GM cotton plants carrying traits, which are of fundamental relevance for the advancement of global agribusiness.

Topochemical conversion of the discontinuous-zone-axis to form bismuth titanate oriented polycrystal nanocomposites

A topochemical transformation of discontinuous band axis has been found in the preparation of bismuth titanate.

CCNB2/SASP/Cathepsin B & PGE2 Axis Induce Cell Senescence Mediated Malignant Transformation.

Glioma is the most frequent and aggressive adult brain tumor with maximum mortality. However, the gene alteration and mechanism underlying malignant transformation of glioma remain largely unknown. We aimed to find key factors regulating tumor progression and malignant transformation of glioma. Here we compared the gene expression profiles of 693 glioma patients by HGG vs. LGG model, and identified a key factor CCNB2 for malignant transformation in glioma. CCNB2 induced a senescence-associated secretory phenotype (SASP) of glioma cells, and the malignant progression, such as invasion and excessive proliferation was mediated by secreting SASP cytokines, Cathepsin B and PGE2. These findings demonstrated a previously undiscovered link between senescence, CCNB2/SASP/Cathepsin B & PGE2 axis and malignant transformation in glioma. This might provide novel insights on developing new therapeutic regimens for abrogating aggressiveness of glioma.

A Fuzzy-Based Hybrid Approach for Estimating Interdisciplinary Learning Efficiency

Students, industry, and departments of civil engineering are engaging interdisciplinary learning techniques to promote sustainability and meet the urgent requirements of human development. However, only a few pieces of literature discussed the learning efficiency and educational feedback of this trend. This may be resulted from the difficulty in estimating subjective engagement. Hence, this study surveyed 173 data from 6 departments that provided interdisciplinary courses based on three dimensional trapezoidal fuzzy numbers and Likert scale. The questionnaire factors were modified from the useful and common scales in Science, Technology, Engineering, and Mathematics (STEM) education. Existing studies tend to estimate students’ learning efficiency based on the hybrid approach of Data Envelopment Analysis (DEA) and Principal Component Analysis (PCA) methods. However, the meaning of variables may be changed in the PCA’s procedures of axis transformation. Hence, a new fuzzy DEA-Mahalanobis distance approach was proposed to solve this problem. Based on the student gains in the sustainability courses, three groups were clustered and compared. Feedback for students was suggested to improve learning strategies. The sensitivity analysis showed that “effective teaching practice” and “learning from other open courses or YouTube” are key factors in increasing learning efficiency in the sustainability courses for civil engineering students. Therefore, this paper provided a useful and easy approach to improve learning strategies for civil engineering students in sustainability education.

Performance analysis of packed U-cell based inverter-fed five-phase induction motor drive using SINPWM technique

Induction motor is the backbone of current industrial applications. Multiphase machines can handle high power application easily. With the use of five-phase induction motor, advantage of both multi-phase and induction motor can be achieved. This paper presents analysis of five-phase seven level-based Induction motor system fed by packed U-cell based inverter. Modelling of five-phase induction motor is done with the help of mathematical equations using d-q axis transformation. Inverter voltage output comes to be approximately sinusoidal with 18.07% Total Harmonic Distortion (THD). Induction motor with specified parameters is simulated under no-load condition and attains steady state conditions after transient state.

Efficient trochoidal milling based on medial axis transformation and inscribed ellipse

Trochoidal milling is a promising strategy for machining pockets with difficult-to-cut materials. Conventional trochoidal toolpath is composed of a set of circular curves and transition curves. However, the actual radial cutting width has a large variation along processing path due to geometric features of inscribed circles, which results in large fluctuation of cutting width and low material removal rate. In this paper, a new trochoidal toolpath based on elliptical curve is proposed to overcome the mentioned drawbacks. Medial axis transformation is adopted to represent the 2D pocket geometry. An algorithm is developed to determine a sequence of inscribed ellipses according to pre-defined machining parameters. Hermit curve is utilized to generate the transition curves between two adjacent elliptical curves. The overall toolpath length is significantly reduced. Machining experiments are conducted to validate the feasibility and efficiency of the proposed method. The experimental results showed an improvement of 12.7% in machining efficiency without increasing the maximum cutting force, compared with conventional trochoidal toolpath.

Optimization of the cutter size and tool orientation for reaching the critical state with multi-constraints in deep and narrow channel parts machining

Increasing the cutter size to enhance its stiffness is of great significance for improving the machining efficiency and precision of deep and narrow channel parts. In this paper, the concept of cutter size critical sphere (CSCS) is presented, which is a specified sphere and tangent to several geometric constraints of tool accessible regions. With this concept, the complex multi-constraints of the workpiece can be transformed into several simple but precise geometric conditions to optimize the size and tool orientation of a conical cutter. The conical cutter generated by CSCS can reach a critical state with multi-constraints simultaneously. Firstly, the mathematical principle of the conical cutter generated by a cylindrical cutter is deduced based on the motion envelope theory. Secondly, the concept of CSCS is proposed based on the deduced mathematical principle and the calculation method of the CSCS with the general situation is provided. Thirdly, the CSCS with special situations is discussed and the calculation method is proposed. Fourthly, the mathematical model and solving algorithm for the max-size CSCS is given. The solving algorithm is designed based on the 3D Medial Axis Transformation (3D MAT) theory. Finally, the proposed method is verified by three simulation experiments and a comparison experiment. The results show that the proposed method can efficiently and accurately calculate the max size and tool orientation of the conical cutter simultaneously. The optimized conical cutter can be tangent to the multi-constraints of the workpiece but do no interfer with them.

Soybean Embryonic Axis Transformation: Combining Biolistic and Agrobacterium-Mediated Protocols to Overcome Typical Complications of In Vitro Plant Regeneration.

The first successful attempt to generate genetically modified plants expressing a transgene was preformed via T-DNA-based gene transfer employing Agrobacterium tumefaciens-mediated genetic transformation. Limitations over infectivity and in vitro tissue culture led to the development of other DNA delivery systems, such as the biolistic method. Herein, we developed a new one-step protocol for transgenic soybean recovery by combining the two different transformation methods. This protocol comprises the following steps: agrobacterial preparation, seed sterilization, soybean embryo excision, shoot-cell injury by tungsten-microparticle bombardment, A. tumefaciens-mediated transformation, embryo co-cultivation in vitro, and selection of transgenic plants. This protocol can be completed in approximately 30–40 weeks. The average efficiency of producing transgenic soybean germlines using this protocol was 9.84%, similar to other previously described protocols. However, we introduced a more cost-effective, more straightforward and shorter methodology for transgenic plant recovery, which allows co-cultivation and plant regeneration in a single step, decreasing the chances of contamination and making the manipulation easier. Finally, as a hallmark, our protocol does not generate plant chimeras, in contrast to traditional plant regeneration protocols applied in other Agrobacterium-mediated transformation methods. Therefore, this new approach of plant transformation is applicable for studies of gene function and the production of transgenic cultivars carrying different traits for precision-breeding programs.

A novel centerline extraction algorithm for a laser stripe applied for turbine blade inspection

Line-laser 3D scanning is a novel and promising automation technique for turbine blade inspection. One key task encountered in line-laser 3D scanning is centerline extraction of the laser stripes. In some regions, there is asymmetry of the line profiles caused by high curvature, such as the leading and trailing edges of a blade. According to the asymmetric Gaussian distribution line profile, this paper presents a new algorithm to extract the centerline of a laser stripe based on sub-pixel boundary extraction and medial axis transformation. The candidate boundary points of the laser stripe are extracted by zero crossing. Based on Taylor expansion and interpolation, the gray gradient distribution of the boundary can be estimated accurately. Following this, the accurate boundary points are extracted by extreme values of the gray gradient, and the centerline is calculated by medial axis transformation of the accurate boundary points. The proposed method can effectively reduce errors caused by the asymmetry of line profiles in areas of high curvature. The effectiveness of this method is verified using simulation and measuring experiments. The experiment results show that the extraction error of the asymmetric Gaussian line profile is within ± 0.15 pixels, and the root mean square error in measurement accuracy experiments does not exceed 0.015 mm.

Firefly-Based Approaches of Image Recognition

The main aim of the reported work is to solve the registration problem for recognition purposes. We introduce two new evolutionary algorithms (EA) consisting of population-based search methods, followed by or combined with a local search scheme. We used a variant of the Firefly algorithm to conduct the population-based search, while the local exploration was implemented by the Two-Membered Evolutionary Strategy (2M-ES). Both algorithms use fitness function based on mutual information (MI) to direct the exploration toward an appropriate candidate solution. A good similarity measure is the one that enables us to predict well, and with the symmetric MI we tie similarity between two objects A and B directly to how well A predicts B, and vice versa. Since the search landscape of normalized mutual information proved more amenable for evolutionary computation algorithms than simple MI, we use normalized mutual information (NMI) defined as symmetric uncertainty. The proposed algorithms are tested against the well-known Principal Axes Transformation technique (PAT), a standard evolutionary strategy and a version of the Firefly algorithm developed to align images. The accuracy and the efficiency of the proposed algorithms are experimentally confirmed by our tests, both methods being excellently fitted to registering images.

Attitude kinematics using slewing transformation of a single axis

Attitude kinematics using a single axis was developed to establish the relationships among the axis trajectory, enclosed solid angle and the associated attitude transformation. An arbitrary transformation due to a sequence of finite rotations or due to propagation consisting of an infinite number of infinitesimal rotations is equivalent to the product of a slewing transformation along a great circle arc linking the initial and final orientations of the axis followed by a rotational transformation about the axis. A key finding of this work is that the slewing transformation commutes with the rotational transformation, if the trajectory of the slewing transformation is fixed in space and the axis orientation is accounted for in the rotational transformation. The results were used to establish two new kinematic theorems. The new theorems provided simple derivations of Ishlinskii’s theorem, the Goodman-Roberson theorem and a result found by Montgomery. The findings in this work were applied to attitude propagation by separating attitude rotational increments that are normal to the axis with those that are parallel to the axis. The normal and parallel angular increments were integrated separately to form the slewing transformation and rotational transformation, respectively. The product of the two commuting transformations formed the total propagation transformation. The findings were validated by using them to create and implement a propagation algorithm. Numerical testing showed that the new algorithm has accuracy comparable to traditional attitude propagation algorithms when stress tested with pure coning motion.

A Method for Generating the Centerline of an Elongated Polygon on the Example of a Watercourse

The centerlines of polygons can be generated with the use of various methods. The aim of this study was to propose an algorithm for generating the centerline of an elongated polygon based on the transformation of vector data. The proposed method involves the determination of base points denoting the direction of river flow. These points were also used to map two polygon boundaries. A Triangulated Irregular Network (TIN) was created based on the polygon’s breakpoints. Edges that intersect the river channel in a direction perpendicular to river flow (across) were selected from a set of TIN edges. The polygon was partitioned into segments with the use of the selected TIN edges. The midpoints of selected TIN edges were used to generate the polygon’s centerline based on topological relations. The presented methodology was tested on a polygon representing a 15-km-long section of a river intersecting the city of Olsztyn (a university center). The analyzed river is a highly meandering watercourse, and its channel is narrowed down by hydraulic structures. The river features an island and distributary channels. The generated centerline effectively fits the polygon, and, unlike the solution modeled with the Medial Axis Transformation (MAT) algorithm, it does not feature branching streams.

Automatic Fiber Length Measurements with a Multi-Stencil Fast Marching Method on Microscopy Images.

Fiber length has a strong impact on the mechanical properties of composite materials. It is one of the most important quantitative features in characterizing microstructures for understanding the material performance. Studies conducted to determine fiber length distribution have primarily focused on sample preparation and fiber dispersion. However, the subsequent image analysis is frequently performed manually or semi-automatically, which either requires careful sample preparation or manual intervention in the image analysis and processing. In this article, an image processing and analysis method has been developed based on medial axis transformation via the multi-stencil fast marching method for fiber length measurements on acquired microscopy images. The developed method can be implemented fully automatically and without any user induced delays. This method offers high efficiency, sub-pixel accuracy, and excellent statistical representativity.

Proportional multi‐resonant‐based controller design method enhanced with a lead compensator for stand‐alone mode three‐level three‐phase four‐leg advanced T‐NPC inverter system

This study presents an inverter current sampled double-loop proportional multi-resonant (PMR)-based control technique for three-level (3L) three-phase four-leg (3P4L) advanced T-type neutral point clamped (AT-NPC) stand-alone mode inverter. Apart from the conventional linear controller the PMR controller has the ability to track a sinusoidal reference and does not require any axis transformation. Therefore, the main advantage of the proposed control technique for a 3P4L inverter is to independently control the output phase voltages when feeding a single phase and/or three phase loads. This is achieved by the inverter current sampled double-loop controller with a lead compensator in order to increase the control system phase margin unlike the capacitor current sampled controller. Thus, the harmonic compensation capability of the controller is increased which strengthens the controller against highly non-linear load types. The design procedures of the controller for the system are analytically explained. Then, the steady-state and dynamic performance of the controller is tested in a 3L 3P4L AT-NPC inverter system through many simulations and experimental studies. The results verify the fast-dynamic performance and the achievement of the low total harmonic distortion with a maximum of 2.89% for the 3L 3P4L AT-NPC inverter system even under serious non-linear load type.

Interval-Based Modeling of High-Temperature Fuel Cells for a Real-Time Control Implementation Under State Constraints

Interval-based state estimation techniques represent promising approaches for the quantification of worst-case bounds of those sets of state variables that are reachable over a finitely long time horizon under the consideration of bounded uncertainty. In previous work, it has been shown that such estimation techniques cannot only be employed for the class of linear uncertain systems but also for nonlinear ones if they are reformulated in terms of quasi-linear state-space representations. However, naive polytopic uncertainty models may lead to quite conservative enclosures of the reachable states. Those, in turn, lead to conservative control strategies if the aforementioned interval enclosures are combined with strategies for the design of robust feedforward and feedback controllers. Therefore, this paper aims at the reduction of pessimism during interval-based state estimation by means of novel uncertainty models, relying on a parameter bounding approach that is implemented by means of a correlation analysis as well as a suitable principle axes transformation of the parameter space. The practical applicability of the proposed procedure is visualized for an experimentally validated thermal model of a solid oxide fuel cell stack, for which the computed interval bounds of reachable states represent a fundamental requirement for the design of a combined feedforward and feedback control allowing for preventing the violation of upper temperature limits in a guaranteed way.

Spiral toolpath generation method for pocket machining

Spiral toolpath plays a significant role in 2.5D pocket machining with the advantages of free of sharp corners and without unwanted un-cutting materials. Technically, efficiency of pocket machining toolpath is determined by its smoothness and total length. Most of existing spiral toolpath generation methods pay more attention on acquiring a smooth toolpath without tool retractions, lacking consideration of total length minimization. In this work, an improved spiral toolpath generation method based on medial axis (MA) transformation is developed to decrease the total length of toolpath, so as to improve the machining performance. The proposed method can be applied to pockets with arbitrary geometries. To avoid unwanted interference between cutting tool and pocket boundary, cutting tool accessibility analysis is firstly conducted. MA sub-cycle for each layer is acquired by trimming the original MA of the pocket. Toolpath of each layer is determined by the envelope curve of a set of disks with various diameters that located on its MA sub-cycle. Toolpath between adjacent layers is guaranteed to be free of intersections. The spiral toolpath is generated by connecting the isolated toolpaths of all layers based on partially linear morphing. Then a toolpath modification algorithm is developed to smooth the spiral toolpath around root node of pocket MA. Finally, machining experiment is conducted to validate the advantages of the proposed method on machining efficiency improvement.

Improved Generalized Procedure for Determining Critical State of a Thin-Walled Beam Under Combined Symmetric Loads

This paper presents an improved generalized procedure for dealing with the stability of thin-walled beams under combined symmetric loads based on the energy method. The differential equations for the case of complex loading conditions were developed using an axis transformation matrix. The work caused by external loads was related to the work of internal forces to simplify the computational procedure. The thin-walled beam subjected to axial force [Formula: see text], bending moment [Formula: see text] at both ends, and concentrated load [Formula: see text] at midspan was studied. The case of a concentrated load [Formula: see text] replaced by a distributed load [Formula: see text] over partial beam length was also examined. The stability region boundary of the beam was derived by two approaches: one was to estimate an approximate angle of twist prior to determination of the deflection and the other was to do it in the reverse way. Numerical results reveal that the first approach yields less error than the second; however, the outcome obtained by the former was more cumbersome than the latter. Above all, both approaches provided feasible results and are useful for further applications dealing with the stability analysis of thin-walled beams.

Deep Learning-Based Automatic Endometrium Segmentation and Thickness Measurement for 2D Transvaginal Ultrasound.

Endometrial thickness is closely related to gyneco-logical function and is an important biomarker in transvaginal ultrasound (TVUS) examinations for assessing female reproductive health. Manual measurement is time-consuming and subject to high inter- and intra- observer variability. In this paper, we present a fully automated endometrial thickness measurement method using deep learning. Our pipeline consists of: 1) endometrium segmentation using a VGG-based U-Net, and 2) endometrial thickness estimation using medial axis transformation. We conducted experimental studies on 137 2D TVUS cases (74/63 secretory phase/proliferative phase). On a test set of 27 cases/277 images, the segmentation Dice score is 0.83. For thickness measurement, we achieved mean absolute error of 1.23/1.38 mm and root mean squared error of 1.79/1.85 mm on two different test sets. The results are considered well within the clinically acceptable range of ±2 mm. Furthermore, our phase-stratified analysis shows that the measurement variance from the secretory phase is higher than that from the proliferative phase, largely due to the high variability of the endometrium appearance in the secretory phase. Future work will extend our current algorithm toward different clinical outcomes for a broader spectrum of clinical applications.

Minimizing neutral currents in distribution microgrids using smart loads

This article presents a strategy for minimizing neutral current in distribution microgrids using electric spring-based smart loads. A dual loop control scheme is proposed – the outer loop generates reference voltages for the individual electric spring in each phase using a simple voltage division concept that results in zero neutral current, while in the inner loop, the output voltage and current of the electric spring are controlled using repetitive controllers. The control system features a simple structure and systematic design and is minimally reliant on exact knowledge of parameters, making it robust in the presence of uncertainties. The electric spring in each phase is controlled independently and identical to the other phases without requiring any axis transformation. Detailed design of the proposed solution is presented and its performance is tested by simulating it on a benchmark low-voltage distribution microgrid to show its effectiveness and validity.