arXiv subjects

Mingyang Lu

Publications and source records attributed to Mingyang Lu.

13 recordsLinked to original sources

arXiv2024

Real-time object detection and robotic manipulation for agriculture using a YOLO-based learning approach

The optimisation of crop harvesting processes for commonly cultivated crops is of great importance in the aim of agricultural industrialisation. Nowadays, the utilisation of machine vision has enabled the automated identification of crops, leading to the enhancement of harvesting efficiency, but challenges still exist. This study presents a new framework that combines two separate architectures of convolutional neural networks (CNNs) in order to simultaneously accomplish the tasks of crop detection and harvesting (robotic manipulation) inside a simulated environment. Crop images in the simulated environment are subjected to random rotations, cropping, brightness, and contrast adjustments to create augmented images for dataset generation. The you only look once algorithmic framework is employed with traditional rectangular bounding boxes for crop localization. The proposed method subsequently utilises the acquired image data via a visual geometry group model in order to reveal the grasping positions for the robotic manipulation.

cs.CV↗

arXiv2020

Decoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by Random Circuit Perturbation

Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not well understood. To address this question, we applied a recently developed computational method, Random Circuit Perturbation (RACIPE), to a nine-component gene regulatory network (GRN) governing stemness, from which we identified fifteen robust gene states. Among them, four out of the five most probable gene states exhibit gene expression patterns observed in single mouse embryonic cells at 32-cell and 64-cell stages. These gene states can be robustly predicted by the stemness GRN but not by randomized versions of the stemness GRN. Strikingly, we found a hierarchical structure of the GRN with the Oct4/Cdx2 motif functioning as the first decision-making module followed by Gata6/Nanog. We propose that stem cell populations, instead of being viewed as all having a specific cellular state, can be regarded as a heterogeneous mixture including cells in various states. Upon perturbations by external signals, stem cells lose the capacity to access certain cellular states, thereby becoming differentiated. The findings demonstrate that the functions of the stemness GRN is mainly determined by its well-evolved network topology rather than by detailed kinetic parameters.

q-bio.MN↗

arXiv2019

Custom Edge-Element FEM Solver and its Application to Eddy-Current Simulation of Realistic 2M-Element Human Brain Phantom

Extensive research papers of three-dimensional computational techniques are widely used for the investigation of human brain pathophysiology. Eddy current analyzing could provide an indication of conductivity change within a biological body. A significant obstacle to current trend analyses is the development of a numerically stable and efficiency-finite element scheme that performs well at low frequency and does not require a large number of degrees of freedom. Here, a custom finite element method (FEM) solver based on edge elements is proposed using the weakly coupled theory, which separates the solution into two steps. First, the background field (the magnetic vector potential on each edge) is calculated and stored. Then, the electric scalar potential on each node is obtained by FEM based on Galerkin formulations. Consequently, the electric field and eddy current distribution in the object can be obtained. This solver is more efficient than typical commercial solvers since it reduces the vector eddy current equation to a scalar one, and reduces the meshing domain to just the eddy current region. It can therefore tackle complex eddy current calculations for models with much larger numbers of elements, such as those encountered in eddy current computation in biological tissues. An example is presented with a realistic human brain mesh of 2 million elements. In addition, with this solver, the equivalent magnetic field induced from the excitation coil is applied, and therefore there is no need to mesh the excitation coil. In combination, these significantly increase the efficiency of the solver.

physics.med-ph↗

arXiv2019

An equivalent-effect phenomenon in eddy current non-destructive testing of thin structures

The inductance/impedance due to thin metallic structures in non-destructive testing (NDT) is difficult to evaluate. In particular, in Finite Element Method (FEM) eddy current simulation, an extremely fine mesh is required to accurately simulate skin effects especially at high frequencies, and this could cause an extremely large total mesh for the whole problem, i.e. including, for example, other surrounding structures and excitation sources like coils. Consequently, intensive computation requirements are needed. In this paper, an equivalent-effect phenomenon is found, which has revealed that alternative structures can produce the same effect on the sensor response, i.e. mutual impedance/inductance of coupled coils if a relationship (reciprocal relationship) between the electrical conductivity and the thickness of the structure is observed. By using this relationship, the mutual inductance/impedance can be calculated from the equivalent structures with much fewer mesh elements, which can significantly save the computation time. In eddy current NDT, coils inductance/impedance is normally used as a critical parameter for various industrial applications, such as flaw detection, coating and microstructure sensing. Theoretical derivation, measurements and simulations have been presented to verify the feasibility of the proposed phenomenon.

eess.SP↗

arXiv2019

A Novel Dual Modality Sensor With Sensitivities to Permittivity, Conductivity, and Permeability

In this paper, an electromagnetic sensor which can operate simultaneously in capacitive and inductive modalities with sensitivities to permittivity, conductivity, and permeability is developed, and a novel measurement strategy is proposed accordingly. The sensor is composed of two planar spiral coils with a track width of 4 mm, which promotes its capacitive mode. The capacitive coupling is measured in common mode, while the inductive coupling is measured in differential mode. In capacitive mode, the sensor is sensitive to changes in permittivity, i.e., the dielectric material distribution; while in inductive mode, it is sensitive to magnetically permeable material and electrically conductive material. Furthermore, it is demonstrated that the sensor can simultaneously measure dielectric and conductive materials. This novel sensing element has been designed and implemented. Experimental results verified its effectiveness in dual modality measurement.

eess.SP↗

arXiv2019

Measurement of permeability for ferrous metallic plates using a novel lift-off compensation technique on phase signature

Lift-off of sensor affects the prediction of electromagnetic properties for both ferrous and non-ferrous steel plates. In this paper, we developed a strategy to address this issue for ferrous plates. With increased lift-off, the phase of the measured impedance for steel plates reduces. Meanwhile, the magnitude of the impedance signal decreases. Based on these facts, a phase compensation algorithm is developed which corrects the phase change due to lift-off considering the magnitude of the impedance signal. Further, a new magnetic permeability prediction technique is presented, which has been validated by analytical and measured results. With this new technique, the error in permeability prediction is less than 2% within the range of lift-offs tested.

eess.SP↗

arXiv2019

Determination of the magnetic permeability, electrical conductivity, and thickness of ferrite metallic plates using a multi-frequency electromagnetic sensing system

In this paper, an inverse method was developed which can, in principle, reconstruct arbitrary permeability, conductivity, thickness, and lift-off with a multi-frequency electromagnetic sensor from inductance spectroscopic measurements. The system fives the error of "Bad character(s) in field Abstract" for no reason. Please refer to manuscript for the full abstract.

eess.SP↗

arXiv2019

A Novel Compensation Algorithm for Thickness Measurement Immune to Lift-Off Variations Using Eddy Current Method

Lift-off variation causes errors in the eddy current thickness measurements of metallic plates. In this paper, we have developed an algorithm that can compensate for this variation and produce an index that is linked to the thickness, but is virtually independent of lift-off. This index, termed as the compensated peak frequency, can be obtained from the measured multifrequency inductance spectral data using the algorithm we developed in this paper. This method has been derived through mathematical manipulation and verified by both the simulation and experimental data. Accuracy in the thickness measurements at different lift-offs proved to be within 2%.

eess.SP↗

arXiv2019

Reducing the Lift-Off Effect on Permeability Measurement for Magnetic Plates From Multifrequency Induction Data

Liftoff variation causes errors in eddy current measurement of nonmagnetic plates as well as magnetic plates. For nonmagnetic plates, previous work has been carried out to address the issue. In this paper, we follow a similar strategy, but try to reduce the lift-off effect on another index, zerocrossing frequency for magnetic plates. This modified index, termed as the compensated zero-crossing frequency, can be obtained from the measured multifrequency inductance spectral data using the algorithm we developed in this paper. Since the zero-crossing frequency can be compensated, the permeability of magnetic plates can finally be predicted by deriving the relation between the permeability and zero-crossing frequency from Dodd and Deeds method. We have derived the method through mathematical manipulation and verified it by both simulation and experimental data. The permeability error caused by liftoff can be reduced within 7.5%.

eess.SP↗

arXiv2017

Modularity of the metabolic gene network as a prognostic biomarker for hepatocellular carcinoma

Abnormal metabolism is an emerging hallmark of cancer. Cancer cells utilize both aerobic glycolysis and oxidative phosphorylation (OXPHOS) for energy production and biomass synthesis. Understanding the metabolic reprogramming in cancer can help design therapies to target metabolism and thereby to improve prognosis. We have previously argued that more malignant tumors are usually characterized by a more modular expression pattern of cancer-associated genes. In this work, we analyzed the expression patterns of metabolism genes in terms of modularity for 371 hepatocellular carcinoma (HCC) samples from the Cancer Genome Atlas (TCGA). We found that higher modularity significantly correlated with glycolytic phenotype, later tumor stages, higher metastatic potential, and cancer recurrence, all of which contributed to poorer overall prognosis. Among patients that recurred, we found the correlation of greater modularity with worse prognosis during early to mid-progression. Furthermore, we developed metrics to calculate individual modularity, which was shown to be predictive of cancer recurrence and patients' survival and therefore may serve as a prognostic biomarker. Our overall conclusion is that more aggressive HCC tumors, as judged by decreased host survival probability, had more modular expression patterns of metabolic genes. These results may be used to identify cancer driver genes and for drug design.

q-bio.MN↗

arXiv2017

Distinguishing Mechanisms Underlying EMT Tristability

Background: The Epithelial-Mesenchymal Transition (EMT) endows epithelial-looking cells with enhanced migratory ability during embryonic development and tissue repair. EMT can also be co-opted by cancer cells to acquire metastatic potential and drug-resistance. Recent research has argued that epithelial (E) cells can undergo either a partial EMT to attain a hybrid epithelial/mesenchymal (E/M) phenotype that typically displays collective migration, or a complete EMT to adopt a mesenchymal (M) phenotype that shows individual migration. The core EMT regulatory network - miR-34/SNAIL/miR-200/ZEB1 - has been identified by various studies, but how this network regulates the transitions among the E, E/M, and M phenotypes remains controversial. Two major mathematical models - ternary chimera switch (TCS) and cascading bistable switches (CBS) - that both focus on the miR-34/SNAIL/miR-200/ZEB1 network, have been proposed to elucidate the EMT dynamics, but a detailed analysis of how well either or both of these two models can capture recent experimental observations about EMT dynamics remains to be done. Results: Here, via an integrated experimental and theoretical approach, we first show that both these two models can be used to understand the two-step transition of EMT - E-E/M-M, the different responses of SNAIL and ZEB1 to exogenous TGF-b and the irreversibility of complete EMT. Next, we present new experimental results that tend to discriminate between these two models. We show that ZEB1 is present at intermediate levels in the hybrid E/M H1975 cells, and that in HMLE cells, overexpression of SNAIL is not sufficient to initiate EMT in the absence of ZEB1 and FOXC2. Conclusions: These experimental results argue in favor of the TCS model proposing that miR-200/ZEB1 behaves as a three-way decision-making switch enabling transitions among the E, hybrid E/M and M phenotypes.

q-bio.CB↗

arXiv2015

OPUS-Beta: A Statistical Potential for Beta-Sheet Contact Pattern in Proteins

Developing an accurate scoring function is essential for successfully predicting protein structures. In this study, we developed a statistical potential function, called OPUS-Beta, for energetically evaluating beta-sheet contact pattern (the entire residue-residue beta-contacts of a protein) independent of the atomic coordinate information. The OPUS-Beta potential contains five terms, i.e., a self-packing term, a pairwise inter-strand packing term, a pairwise intra-strand packing term, a lattice term and a hydrogen-bonding term. The results show that, in recognizing the native beta-contact pattern from decoys, OPUS-Beta potential outperforms the existing methods in literature, especially in combination with a method using 2D-recursive neural networks (about 5% and 23% improvements in top-1 and top-5 selections). We expect OPUS-Beta potential to be useful in beta-sheet modeling for proteins.

q-bio.BM↗

arXiv2015

Implications of the hybrid epithelial/mesenchymal phenotype in metastasis

Understanding cell-fate decisions during tumorigenesis and metastasis is a major challenge in modern cancer biology. One canonical cell-fate decision that cancer cells undergo is Epithelial-to-Mesenchymal Transition (EMT) and its reverse Mesenchymal-to-Epithelial Transition (MET). While transitioning between these two phenotypes - epithelial and mesenchymal - cells can also attain a hybrid epithelial/mesenchymal (i.e. partial or intermediate EMT) phenotype. Cells in this phenotype have mixed epithelial (e.g. adhesion) and mesenchymal (e.g. migration) properties, thereby allowing them to move collectively as clusters of Circulating Tumor Cells (CTCs). If these clusters enter the circulation, they can be more apoptosis-resistant and more capable of initiating metastatic lesions than cancer cells moving individually with wholly mesenchymal phenotypes, having undergo a complete EMT. Here, we review the operating principles of the core regulatory network for EMT/MET that acts as a three-way switch giving rise to three distinct phenotypes - epithelial, mesenchymal and hybrid epithelial/mesenchymal. We further characterize this hybrid E/M phenotype in terms of its capabilities in terms of collective cell migration, tumor-initiation, cell-cell communication, and drug resistance. We elucidate how the highly interconnected coupling between these modules coordinates cell-fate decisions among a population of cancer cells in the dynamic tumor, hence facilitating tumor-stoma interactions, formation of CTC clusters, and consequently cancer metastasis. Finally, we discuss the multiple advantages that the hybrid epithelial/mesenchymal phenotype have as compared to a complete EMT phenotype and argue that these collectively migrating cells are the primary 'bad actors' of metastasis.

q-bio.CB↗