Layers Of Slices Research Articles

Activation of α 2A and α 2B -adrenergic receptors inhibits tactile stimulation-evoked parallel fiber-Purkinje cell synaptic transmission in mouse cerebellar cortex.

The mechanism by which α2-adrenergic receptors (ARs) modulate the cerebellar parallel fiber-Purkinje cell (PF-PC) synaptic transmission is unclear. We investigated this issue using electrophysiological and neuropharmacological methods. Six- to eight-week-old ICR mice were used in the study. Under in vivo conditions, PF-PC synaptic transmission was evoked by facial stimulation of ipsilateral whisker pad, and recorded using cell-attached patch from PCs. Under in-vitro conditions, PF-PC synaptic transmission was evoked by electrical stimulation of the molecular layer in cerebellar slices, and was recorded using whole-cell recording from PCs. SR95531 (20 µM) was added to the ACSF during all recordings to prevent GABAA receptor-mediated inhibition. Air-puff stimulation of the ipsilateral whisker pad in-vivo evoked simple spike (eSS) firing of cerebellar PCs. Microapplication of noradrenaline (15 µM) to the molecular layer significantly decreased the numbers and frequency of eSS, an effect abolished by the α2-AR antagonist. Microapplication of an α2-AR agonist, UK14304 (1 µM), significantly decreased the numbers of eSS in PCs, which was abolished by either α2A- or α2B-AR antagonist, but not by α2C-AR antagonist. Under in-vitro conditions, application of UK 14304 significantly decreased the amplitude of PF-PC EPSCs and increased the paired-pulse ratio, which were abolished by either α2A- or α2B-AR antagonist. The present results indicate that activation of presynaptic α2A- and α2B-AR downregulates PF-PC synaptic transmission in mouse cerebellar cortex.

Phenobarbital does not worsen outcomes of neonatal hypoxia on hippocampal LTP on rats.

Neonatal hypoxia is a common cause of early-life seizures. Both hypoxia-induced seizures (HS), and the drugs used to treat them (e.g., phenobarbital, PB), have been reported to have long-lasting impacts on brain development. For example, in neonatal rodents, HS reduces hippocampal long-term potentiation (LTP), while PB exposure disrupts GABAergic synaptic maturation in the hippocampus. Prior studies have examined the impact of HS and drug treatment separately, but in the clinic, PB is unlikely to be given to neonates without seizures, and neonates with seizures are very likely to receive PB. To address this gap, we assessed the combined and separate impacts of neonatal HS and PB treatment on the development of hippocampal LTP. Male and female postnatal day (P)7 rat pups were subjected to graded global hypoxia (or normoxia as a control) and treated with either PB (or vehicle as a control). On P13-14 (P13+) or P29-37 (P29+), we recorded LTP of the Schaffer collaterals into CA1 pyramidal layer in acute hippocampal slices. We compared responses to theta burst stimulation (TBS) and tetanization induction protocols. Under the TBS induction protocol, female rats showed an LTP impairment caused by HS, which appeared only at P29+. This impairment was delayed compared to male rats. While LTP in HS males was impaired at P13+, it normalized by P29+. Under the tetanization protocol, hypoxia produced larger LTP in males compared to female rats. PB injection, under TBS, did not exacerbate the effects of hypoxia. However, with the tetanization protocol, PB - on the background of HS - compensated for these effects, returning LTP to control levels. These results point to different susceptibility to hypoxia as a function of sex and age, and a non-detrimental effect of PB when administered after hypoxic seizures.

Placenta segmentation in magnetic resonance imaging: Addressing position and shape of uncertainty and blurred placenta boundary

Automatic segmentation of the placenta in MRI facilitates quantitative measurements and further analysis. Automatic segmentation of the placenta in magnetic resonance imaging (MRI) is challenging due to the fact that (1) the position of the placenta varies greatly in different views of MRI. In addition, the shape of the placenta changes layer by layer in different MRI slices. The position and shape of the placenta are highly uncertain. (2) PAS results in a blurred placental boundary. To address the above issues, a refinement fusion based on the U-Net (RFU-Net) is proposed for the segmentation of the placenta with variable position and shape in MR images, and the boundary de-precision explores the distribution of blood vessels around the placental boundary. In RFU-Net, ResNet34 is used as a feature extractor, and a fusion multiscale feature (FMF) is proposed to extract multiscale features and their contextual information to solve the problem of variable placental shape. A refinement segmentation module (RSM) is designed to provide information about the position of the placenta to solve the problem of variable placental position, which effectively improves the segmentation of the placenta. The mean intersection over union (MIoU), hausdorff distance (HD), dice coefficient (Dice) and accuracy (Acc) are 0.8620, 4.3142, 0.9314 and 0.9987, respectively. Extensive experiments show that RFU-Net effectively improves the segmentation accuracy of the placenta. Boundary de-precision resolves the blurring of placental boundaries, effectively highlighting areas of the placental boundary that may contain blood vessels to aid in the physician's diagnosis.

The dentate gyrus differentially metabolizes glucose and alternative fuels during rest and stimulation.

The metabolic demands of neuronal activity are both temporally and spatially dynamic, and neurons are particularly sensitive to disruptions in fuel and oxygen supply. Glucose is considered an obligate fuel for supporting brain metabolism. Although alternative fuels are often available, the extent of their contribution to central carbon metabolism remains debated. Differential fuel metabolism likely depends on cell type, location, and activity state, complicating its study. While biosensors provide excellent spatial and temporal information, they are limited to observations of only a few metabolites. On the other hand, mass spectrometry is rich in chemical information, but traditionally relies on cell culture or homogenized tissue samples. Here, we use mass spectrometry imaging (MALDI-MSI) to focus on the fuel metabolism of the dentate granule cell (DGC) layer in murine hippocampal slices. Using stable isotopes, we explore labeling dynamics at baseline, as well as in response to brief stimulation or fuel competition. We find that at rest, glucose is the predominant fuel metabolized through glycolysis, with little to no measurable contribution from glycerol or fructose. However, lactate/pyruvate, β-hydroxybutyrate (βHB), octanoate, and glutamine can contribute to TCA metabolism to varying degrees. In response to brief depolarization with 50 mM KCl, glucose metabolism was preferentially increased relative to the metabolism of alternative fuels. With an increased supply of alternative fuels, both lactate/pyruvate and βHB can outcompete glucose for TCA cycle entry. While lactate/pyruvate modestly reduced glucose contribution to glycolysis, βHB caused little change in glycolysis. This approach achieves broad metabolite coverage from a spatially defined region of physiological tissue, in which metabolic states are rapidly preserved following experimental manipulation. Using this powerful methodology, we investigated metabolism within the dentate gyrus not only at rest, but also in response to the energetic demand of activation, and in states of fuel competition.

Vat‐photopolymerization‐based complex ceramic: Optimization of slurry, printing process, and postprocessing parameters

AbstractVat photopolymerization is an effective and economical method for preparing ceramic specimens with complex structures. However, the improper selection of process parameters during the preparation process limits the scope of its application. In this study, the most suitable shear rate was determined based on the solid content and rheological properties of the ceramic slurry. In addition, the specific printing‐process parameters were objectively selected, and the gray correlation method was used to determine the improved weight resolution coefficient through orthogonal experiments combined with the entropy weight method to select the most suitable printing parameters. Finally, the main debinding and sintering parameters that affect the heat treatment performance were considered, and multiple characterization methods were used to detect the specimens and study the impact of parameter changes on specimen performance. The experimental results show that when the laser power is 210 mW, the slice layer thickness is .04 mm, the scanning spacing is .05 mm, and the filling mode is XY, the green bodies have the best forming quality. When the sintering temperature is 1600°C, and the holding time is 4 h, the specimens have the best mechanical properties (the flexural strength reaches 114 MPa).

A non-regularization self-supervised Retinex approach to low-light image enhancement with parameterized illumination estimation

In current Retinex-based low-light image enhancement (LLIE) methods, fine-tuning regularization parameters for Retinex decomposition and illumination estimation can be cumbersome. To address this, we present a novel non-regularization self-supervised Retinex approach for illumination estimation. Our contributions are twofold: First, we introduce a self-supervised method that incorporates edge-aware smoothness properties in bilateral learning, eliminating the need for regularization terms and simplifying parameter adjustments. Second, to enforce smoothness constraints on the estimated bilateral grid, we propose a bilateral grid parameterization network. This network employs a generative encoder to parameterize the bilateral grid of illumination and a trainable slicing layer guided by a map, reconstructing the grid into an illumination map. Despite the absence of regularization terms, our model excels in generating piece-wise smooth illumination, resulting in enhanced naturalness and improved contrast in images. Our model offers exceptional flexibility by eliminating the need for additional regularization terms and parameter fine-tuning. Moreover, it does not depend on external datasets for training, overcoming dataset collection challenges. Extensive experiments, comparing our model with eight state-of-the-art methods across five public available datasets, unequivocally demonstrate our model’s state-of-the-art performance based on key metrics such as NIQE, NIQMC, and CPCQI. These results reaffirm the effectiveness of our approach in low-light image enhancement. Code will be available at: https://github.com/zhaozunjin/NeurBR.

Recyclable Ni-Containing Coordination Polymer as an Efficient Catalyst for the Synthesis of Oxindole and Quinoline Derivatives through the Borrowing Hydrogen Strategy

A coordination polymer Ni-CIA has been designed, synthesized, and characterized via Fourier transform infrared spectroscopy (FT-IR), powder X-ray diffraction (XRD), scanning electron microscopy (SEM), X-ray photoelectron spectrometry (XPS), energy-dispersive X-ray spectroscopy (EDS), and thermal gravimetric analysis (TGA). The resulting polymer reveals a slice layer stacked combination structure and good stability. Importantly, this polymer exhibited high catalytic activity for the synthesis of oxindole and quinoline derivatives via borrowing hydrogen and dehydrogenation reactions. Meanwhile, several control reactions were carried out to investigate the possible mechanisms of this transformation. Finally, the results of the recycling experiment indicate that the coordination polymer Ni-CIA could be recovered and reused at least five times.

Digital light processing 4D printing multilayer polymers with tunable mechanical properties and shape memory behavior

Four-dimensional (4D) printing has currently been renowned as a world-changing technology which has recently gained significant attention amongst researchers. It enables 3D printed objects to alter its shape, properties and functions through the application of external stimuli. However, the development of 4D printing has been impeded by the overexposure effect, which has made it difficult for photocuring to print gradient structures. In this paper, we propose a novel photocuring 4D printing strategy of gradient structures with tunable properties. Multi-walled carbon nanotubes (MWCNTs) are added to the intermediate layer (Fast Layer, FL) of multilayer shape memory polymers (SMPs) to reduce curing degree and absorb overexposure. The mechanical properties and shape memory behavior of multilayer SMPs can be tuned by adjusting the layer ratio of FL with low curing degree. Outcome of microscopic images, interlayer bonding force, and shore hardness originating from this study indicates that the printed multilayer SMPs possessed excellent interlayer bonding properties as well as obvious modulus differences between each layer. The average shape recovery speed (Sa) of multilayer SMPs was almost linearly related to the slice layer number of FL. The strategy was successfully demonstrated in the fabrication of multilayer SMPs with sequential recovery and multiple deformation behavior. An electrically responsive shape memory effect was also achieved by using embedded graphite electrothermal layer to exhibit its application in time-delay devices. The proposed strategy enables the application of multilayer SMPs gradient structures in soft robotics and flexible electronics.

Authentication of video based on concatenated plane slicing layers approach

Authentication of video based on concatenated plane slicing layers approach

Bamboo-Inspired Renewable, High-Strength, Vibration-Damping Composites for Structural Applications

Renewable structural materials derived from natural biological materials can potentially replace non-renewable synthetic materials for civil engineering and transportation applications. Here, inspired by the functional gradient structure of bamboo, we propose a simple and efficient two-step preparation strategy to convert natural bamboo into a lightweight, high-strength, damping, and sound-insulating structural engineering material called densified bundle-laminated veneer lumber (DBLVL). DBLVL was prepared by finely grading and thinning three layers of bamboo slices and removing the lignin and hemicelluloses from the surface of bamboo bundles. This was followed by penetrating the phenol formaldehyde resin and then solidifying and densifying it in situ. DBLVL had superior mechanical properties due to its bamboo-like gradient laminated structure, three-dimensional network distribution of adhesive under high temperature and high pressure, in situ curing, and solid interfacial bonding. It had a specific tensile strength of 297 MPa cm3 g–1, which was superior to those of many other construction materials. The tensile strength of DBLVL reached 363 MPa, and the bending strength reached 219 MPa, which were 97.28 and 92.11% higher than those of natural bamboo, respectively. The impact toughness reached 15.4 J/cm2. DBLVL also showed excellent damping and vibration reduction (the first three damping ratios were 2.35, 1.81, and 2.40%) and dimensional stability (the thickness expansion rate after 24 h of water absorption was 4.43%). Because of its excellent mechanical properties and hygrothermal stability, DBLVL is expected to replace non-renewable synthetic materials as a green and sustainable structural material for engineering applications.

Three-dimensional biofabrication of nanosecond laser micromachined nanofibre meshes for tissue engineered scaffolds.

There is a high demand for bespoke grafts to replace damaged or malformed bone and cartilage tissue. Three-dimensional (3D) printing offers a method of fabricating complex anatomical features of clinically relevant sizes. However, the construction of a scaffold to replicate the complex hierarchical structure of natural tissues remains challenging. This paper reports a novel biofabrication method that is capable of creating intricately designed structures of anatomically relevant dimensions. The beneficial properties of the electrospun fibre meshes can finally be realised in 3D rather than the current promising breakthroughs in two-dimensional (2D). The 3D model was created from commercially available computer-aided design software packages in order to slice the model down into many layers of slices, which were arrayed. These 2D slices with each layer of a defined pattern were laser cut, and then successfully assembled with varying thicknesses of 100 μm or 200 μm. It is demonstrated in this study that this new biofabrication technique can be used to reproduce very complex computer-aided design models into hierarchical constructs with micro and nano resolutions, where the clinically relevant sizes ranging from a simple cube of 20 mm dimension, to a more complex, 50 mm-tall human ears were created. In-vitro cell-contact studies were also carried out to investigate the biocompatibility of this hierarchal structure. The cell viability on a micromachined electrospun polylactic-co-glycolic acid fibre mesh slice, where a range of hole diameters from 200 μm to 500 μm were laser cut in an array where cell confluence values of at least 85% were found at three weeks. Cells were also seeded onto a simpler stacked construct, albeit made with micromachined poly fibre mesh, where cells can be found to migrate through the stack better with collagen as bioadhesives. This new method for biofabricating hierarchical constructs can be further developed for tissue repair applications such as maxillofacial bone injury or nose/ear cartilage replacement in the future.

GABAB receptor outward currents are transiently disclosed by the convulsant 4-aminopyridine in vitro

The K+ channel blocker 4-aminopyridine (4AP) has been extensively used to investigate the mechanisms underlying neuronal network synchronization in both in vitro and in vivo animal models of focal epilepsy. 4AP-induced effects are paralleled by an increase in both excitatory and inhibitory neurotransmitter release, but the mechanisms of action of 4AP on neuronal networks remain unclear. By employing simultaneous whole-cell patch clamp and field potential recordings from hippocampal CA3/4 pyramidal layer of acute brain slices obtained from mice (n = 30), we found that the appearance of epileptiform discharges induced by 4AP (100 μM) is consistently preceded by the transient recurrence of presumptive GABAB outward currents, which are not mirrored by any field activity. These GABAB outward currents still occurred during application of ionotropic glutamatergic antagonists (n = 12 cells) but were blocked by the GABAB receptor antagonist CGP55845 (n = 7). Our findings show that the transient occurrence of distinct GABAB outward currents precedes the appearance of 4AP-induced neuronal network synchronization leading to epileptiform activity in the rodent hippocampus in vitro.

Optimizing Manufacturing Parameters of DLP Machine by Taguchi Method and Desirability Approach

With less manufacturing time and less photosensitive resin consumed, Digital Light Processing of the bottom-up process is more forward-looking than the top-down one in terms of 3D printing technology. In view of differences in the optimization of machine printing parameters for objectives with different quality requirements, this paper discusses how the control factors consisting of machine printing parameters can obtain objects with a high quality through an experimental design with full considerations of the separation force and dimensional tolerance. By taking the titling separation mechanism as an example, the importance, contribution, and best calculation results of the control factors in forming a separation force and four dimensional tolerances are obtained using the Taguchi method and an analysis of variance, and then the optimal solution for multiple objectives is obtained via the desirability approach. It was found from this study that the rising speed of the forming platform is the most important parameter affecting the dimensional tolerance and separation force. The slice layer thickness has an inverse characteristic for optimizing the dimensional tolerance of the aperture and the face width. Regarding multi-objective optimization, it will not change the optimal printing parameters considering the minimum separation force and overall dimensional tolerance, regardless of the weight of the separation force.

An initial feasibility study into ray-based slicing for revolving thin-wall parts using a rotary 3D printer

PurposeWith the development of 3D printing or additive manufacturing (AM), curved layer fused deposition modeling (CLFDM) has been researched to cope with the flat layer AM inherited problems, such as stair-step error, anisotropy and the time-cost and material-cost problems from the supporting structures. As one type of CLFDM, cylindrical slicing has obtained some research attention. However, it can only deal with rotationally symmetrical parts with a circular slicing layer, limiting its application. This paper aims to propose a ray-based slicing method to increase the inter-layer strength of flat layer-based AM parts to deal with more general revolving parts.Design/methodology/approachSpecifically, the detailed algorithm and implementation steps are given with several examples to enable readers to understand it better. The combination of ray-based slicing and helical path planning has been proposed to consider the nonuniform path spacing between the adjacent paths in the same curved layer. A brief introduction of the printing system is given, mainly including a 3D printer and the graphical user interface.FindingsThe preliminary experiments are successfully conducted to verify the feasibility and versatility of the proposed and improved slicing method for the revolving thin-wall parts based on a rotary 3D printer.Originality/valueThis research is early-stage work, and the authors are intended to explore the process and show the initial feasibility of ray-based slicing for revolving thin-wall parts using a rotary 3D printer. In general, this research provides a novel and feasible slicing method for multiaxis rotary 3D printers, making manufacturing revolving thin-wall and complex parts possible.

Prenatal alcohol exposure affects developmental differentiation of interictal discharges in septal and temporal hippocampus.

Prenatal alcohol exposure (PAE) provokes lifelong CNS dysfunction, including an increased susceptibility to seizure disorders. We investigated hippocampal excitability in vitro in the offspring of dams exposed to a mild ethanol concentration throughout pregnancy (ethanol 15%v/v in drinking water). Hippocampal slices were prepared from the offspring at a young (Y, 21-30 postnatal days, PND) or adult (A, 60 PND) age, with controls from same age normal rats (N). Synchronous spontaneous interictal-type epileptiform discharges (IEDs) were induced by bathing the slices in Mg2+-free ACSF or in 4-Aminopyridine (4-AP, 50µΜ) and were recorded from CA1 pyramidal layer of temporal (T) and septal slices (S). Hippocampal slices readily generated IEDs following NMDA receptor activation or K+ conductance block, with frequency and duration depending on location (septal or temporal), age, the activating mechanism, and prior conditioning (N or PAE). From the two media, 4-AP induced higher frequency (always), shorter duration (mostly) IEDs compared to Mg 2+-free ACSF. Temporal IED frequency increased with age, whereas septal was stable, indicating an earlier maturation of the latter part. The hippocampal "T to S" (high to low) excitability gradient appeared at/later than the end of the first postnatal month and mostly concerned discharge frequency. Discharge duration generally decreased with maturation but appeared to depend on many factors, including conditioning. Prenatal alcohol exposure differentiated the control of synchronous discharges by NMDA receptors and K+ conductances, and their developmental evolution, thus suggesting potential mechanisms for aberrant hippocampal neuronal network function.

Additive remanufacturing of coupler knuckle based on robotic gas metal arc welding

Take the wear parts of coupler knuckle as an example, the “Modeling—Slicing — Stacking” mode remanufacturing process is studied. First, the 3D model of the of the worn coupler knuckle surface is acquired by structured light 3D detection. The remanufacturing model of the failure part is built by Boolean operation between the original model and the acquired 3D model. Second, the user can slice layer of the remanufacturing model according to the remanufacturing stacking parameters. The zone that surrounded by the contour of each sliced layer is the robotic GMAW remanufacturing stack region. Third, the robotic GMAW remanufacturing path is planed within the region mentioned above and the executable program is generated to carry out the remanufacturing task layer by layer. Moreover, the worn coupler knuckle was repaired by adopting Robotic GMAW Process. The mechanical performances of component were tested, the results indicate that the remanufactured coupler knuckle satisfying the operating requirements.

Self-Organized Criticality in the Brain

Self-organized criticality (SOC) refers to the ability of complex systems to evolve toward a second-order phase transition at which interactions between system components lead to scale-invariant events that are beneficial for system performance. For the last two decades, considerable experimental evidence has accumulated that the mammalian cortex with its diversity in cell types, interconnectivity, and plasticity might exhibit SOC. Here, we review the experimental findings of isolated, layered cortex preparations to self-organize toward four dynamical motifs presently identified in the intact cortex in vivo: up-states, oscillations, neuronal avalanches, and coherence potentials. During up-states, the synchronization observed for nested theta/gamma oscillations embeds scale-invariant neuronal avalanches, which can be identified by robust power law scaling in avalanche sizes with a slope of −3/2 and a critical branching parameter of 1. This precise dynamical coordination, tracked in the negative transients of the local field potential (nLFP) and spiking activity of pyramidal neurons using two-photon imaging, emerges autonomously in superficial layers of organotypic cortex cultures and acute cortex slices, is homeostatically regulated, exhibits separation of time scales, and reveals unique size vs. quiet time dependencies. A subclass of avalanches, the coherence potentials, exhibits precise maintenance of the time course in propagated local synchrony. Avalanches emerge in superficial layers of the cortex under conditions of strong external drive. The balance of excitation and inhibition (E/I), as well as neuromodulators such as dopamine, establishes powerful control parameters for avalanche dynamics. This rich dynamical repertoire is not observed in dissociated cortex cultures, which lack the differentiation into cortical layers and exhibit a dynamical phenotype expected for a first-order phase transition. The precise interactions between up-states, nested oscillations, and avalanches in superficial layers of the cortex provide compelling evidence for SOC in the brain.

A path planning method of lattice structural components for additive manufacturing

Compared with traditional structures, lattice structures show more excellent mechanical properties, e.g., higher rigidity and lighter weight. The additive manufacturing (AM) technology enables complex lattice structure to be realized. The path planning problem of AM for lattice structures faces new challenges that have been barely explored before now, because the lattice structures have unique characteristics of complex geometrical features and high-precision processing requirements. Despite many efforts toward path generation, the printing efficiency problem of the lattice structures is more than one single printing path can resolve. Using machine learning method based on a support vector machine (SVM) system, the goal of this paper is to automatically determine a suitable filling path for each sub-domain of the slicing layer of the lattice structures. Moreover, a route is found to traverse every scattered sub-domain by solving a traveling salesman problem (TSP). We demonstrate various testing examples and the experimental results to show the superiority and effectiveness of our method in terms of classification accuracy, filling effects, and linking path length.

End-to-end network slice architecture and distribution across 5G micro-operator leveraging multi-domain and multi-tenancy

Local 5G networks are emerging as a new form for 5G deployment, targeting service delivery for vertical-specific purposes and other local users. These networks are also known as micro-operator networks for which prior work has established different deployment scenarios, namely Closed, Open and Mixed Networks. To achieve network flexibility, customization and privacy required by various vertical sectors, such as industry, health and energy, it is essential to have a well-defined network slicing architecture and adequate implementation procedure. In this paper, a sophisticated end-to-end network slicing architecture is proposed for different deployment scenarios of the local 5G micro-operator concept. The proposed architecture incorporates a broad four-layer concept, leveraging a multi-tenancy layer for different tenants and their end users, a descriptive service layer, a multi-domain slicing management and orchestration layer, and a resource layer. We further propose a network slice instance (NSI) communication service distribution technique for local 5G micro-operators. This is achieved by expanding/leveraging the communication service management function in the multi-tenant layer into a multi-tenant manager and an orchestrator of communication services. In addition, we describe how the communication service orchestrator will address all the possible multitenant-slice situations during the distribution of a network slice instance to multiple tenants. The novel methods described in the paper present a solution for not only network slice communication service distribution across different micro-operator’s tenants but also for future use cases, especially, when the allocated slice is responsible for multiple tenants or when a tenant requests multiple NSIs.

An automatic compensation method for improving forming precision of multi-layer multi-bead component

Wire and arc additive manufacturing (WAAM) is a promising technology for manufacturing large-sized metal components. However, the material shortage region (MSR) at the edge of each slicing layer can influence the forming precision and surface flatness of components. To solve these problems, this paper proposes a shape follow-up edge cycle compensation (SECC) method and model for predicting the weld width and weld height to improve the efficiency of the WAAM process. First, the prediction model was used to determine the weld width and weld height for various welding parameters. The predicted width was then used to obtain the optimal overlap distance, and the filling path of each layer was generated. The same weld height was used for slicing of the 3D model and the tool path compensation cycle was generated. Second, the influence of the MSR on the morphology of multi-layer multi-bead (MLMB) components was analyzed. The MSR results in a height difference between the edge height and the middle height of every deposited layer, and the height difference increases as more layers are added and the height of the component increases. Furthermore, the influence of the MSR gradually extends from the edge to the middle, such that the upper surface presents a parabolic shape. Finally, a mathematical model was established to determine the height difference based on the area of the MSR. When the height difference reaches the weld height, an edge compensation weld is added to eliminate the height difference. Our experimental results show that the proposed forming control strategy improves forming precision and surface flatness. The method is highly feasible and can be applied to a wide range of WAAM applications.