Complex Shapes Research Articles

How does urban form explain water cooling effect heterogeneity: A case study in Wuhan, China

Water bodies in urban areas are considered to be natural and effective cooling factors that can help mitigate the urban heat island (UHI) effect. Previous studies highlighted the cooling effect is determined by the size and landscape of the water bodies. However, it is unclear how the urban form surrounding water bodies influences the water cooling effect received by human activity space. Using high resolution data and a multiple linear regression model, the effect of various 2D/3D urban form factors on the average water cooling intensity (AWCI) and water cooling intensity (WCI) at the fine scale were examined in Wuhan City on hot days. We further verified the spatial heterogeneity of the relationship between urban form factors and WCI according to the distance to and size of adjacent water bodies. The AWCI of the entire surrounding area were correlated with building morphology indicators. Urban form indicators effectively explained the variations of WCI at the fine scale, indicating that a mixture of large building volume density (BVD) with small building density (BD), and an aggregated impervious surface area (ISA) with a complex shape were conducive to WCI. Additionally, building morphology had a larger impact on the cooling effect around small water bodies and in the outer buffer area of water bodies. In comparison, the cooling effect of the area surrounding large water bodies was more affected by the landscape of the ISA. We therefore propose a differentiated urban planning strategy to take full use of the limited water cooling effect.

Recent Developments in Mechanical Ultraprecision Machining for Nano/Micro Device Manufacturing.

The production of many components used in MEMS or NEMS devices, especially those with com-plex shapes, requires machining as the best option among manufacturing techniques. Ultraprecision machining is normally employed to achieve the required shapes, dimensional accuracy, or improved surface quality in most of these devices and other areas of application. Compared to conventional machining, ultraprecision machining involves complex phenomenal processes that require extensive investigations for a better understanding of the material removal mechanism. Materials such as semiconductors, composites, steels, ceramics, and polymers are commonly used, particularly in devices designed for harsh environments or applications where alloyed metals may not be suitable. However, unlike alloyed metals, materials like semiconductors (e.g., silicon), ceramics (e.g., silicon carbide), and polymers, which are typically brittle and/or hard, present significant challenges. These challenges include achieving precise surface integrity without post-processing, managing the ductile-brittle transition, and addressing low material removal rates, among others. This review paper examines current research trends in mechanical ultraprecision machining and sustainable ultraprecision machining, along with the adoption of molecular dynamics simulation at the micro and nano scales. The identified challenges are discussed, and potential solutions for addressing these challenges are proposed.

Machine learning for aspherical lens form accuracy improvement in precision molding of infrared chalcogenide glass

Precision glass molding (PGM) is an effective approach to manufacturing infrared chalcogenide glass (ChG) aspherical lens with complex shapes. However, infrared ChG aspherical lens often experiences form error in the designed profile and the final profile obtained by PGM. To reduce the form error of infrared ChG aspherical lens in the PGM process, a form error compensation model based on the random forest (RF) algorithm is proposed. The infrared ChG aspherical lens profile was first machined on an electroless nickel-phosphorus (Ni–P) plating to serve as the mold for PGM. After molding, the profile data of the lens was extracted, and a compensation model based on RF was constructed to optimize the model parameters using the evaluation parameters such as root mean square error (RMSE), coefficient of determination (R2), and out-of-bag (OOB). Finally, the generated compensated profile based on the compensation model was used for the compensation machining of the mold. Through this compensation approach, we have demonstrated a substantial 63.5 % reduction in the form error of the fabricated infrared ChG aspherical lens, decreasing the Peak-to-Valley (PV) value from 1.04 μm to 0.38 μm.

RobotSDF: Implicit Morphology Modeling for the Robotic Arm.

The expression of robot arm morphology is a critical foundation for achieving effective motion planning and collision avoidance in robotic systems. Traditional geometry-based approaches usually suffer from the contradiction between the high demand for computing resources for fine expression and the insufficient detail expression caused by the pursuit of efficiency. The signed distance function addresses these drawbacks due to its ability to handle complex and arbitrary shapes and lower computational requirements. However, conventional robotic morphology methods based on the signed distance function often face challenges when the robot moves dynamically, since robots with different postures are modeled as independent individuals but the postures of robots are infinite. In this paper, we introduce RobotSDF, an implicit morphology modeling approach that can express the robot shape of arbitrary posture precisely. Instead of depicting a whole model of the robot arm, RobotSDF models the robot morphology as integrated implicit joint models driven by joint configurations. In this approach, the dynamic shape change process of the robot is converted into the coordinate transformations of query points within each joint's coordinate system. Experimental results with the Elfin robot demonstrate that RobotSDF can accurately depict robot shapes across different postures up to the millimeter level, which exhibits 38.65% and 66.24% improvement over the Neural-JSDF and configuration space distance field algorithms, respectively, in representing robot morphology. We further verified the efficiency of RobotSDF through collision avoidance in both simulation and actual human-robot collaboration experiments.

A Historical Handwritten French Manuscripts Text Detection Method in Full Pages

Historical handwritten manuscripts pose challenges to automated recognition techniques due to their unique handwriting styles and cultural backgrounds. In order to solve the problems of complex text word misdetection, omission, and insufficient detection of wide-pitch curved text, this study proposes a high-precision text detection method based on improved YOLOv8s. Firstly, the Swin Transformer is used to replace C2f at the end of the backbone network to solve the shortcomings of fine-grained information loss and insufficient learning features in text word detection. Secondly, the Dysample (Dynamic Upsampling Operator) method is used to retain more detailed features of the target and overcome the shortcomings of information loss in traditional upsampling to realize the text detection task for dense targets. Then, the LSK (Large Selective Kernel) module is added to the detection head to dynamically adjust the feature extraction receptive field, which solves the cases of extreme aspect ratio words, unfocused small text, and complex shape text in text detection. Finally, in order to overcome the CIOU (Complete Intersection Over Union) loss in target box regression with unclear aspect ratio, insensitive to size change, and insufficient correlation between target coordinates, Gaussian Wasserstein Distance (GWD) is introduced to modify the regression loss to measure the similarity between the two bounding boxes in order to obtain high-quality bounding boxes. Compared with the State-of-the-Art methods, the proposed method achieves optimal performance in text detection, with the precision and mAP@0.5 reaching 86.3% and 82.4%, which are 8.1% and 6.7% higher than the original method, respectively. The advancement of each module is verified by ablation experiments. The experimental results show that the method proposed in this study can effectively realize complex text detection and provide a powerful technical means for historical manuscript reproduction.

Application of integrated entropy-COPRAS and ANN approaches for maximizing wire EDM machinability attributes of Al6082-T6/GNP/TiB2 composites

Wire Electrical Discharge Machining (WEDM) utilizes electrical sparks to cut conductive materials precisely. It employs a thin, electrically charged wire to erode the material, creating complex shapes with high accuracy, tight tolerance, and minimal material waste. The current study investigates the effect of WEDM process parameters on the various output properties of machining a hybrid Aluminium metal matrix nanocomposite (HAMMNC). A series of experiments were conducted on a composite constructed using Taguchi’s standard L18 Orthogonal Array (OA) design. The acquired responses of Material-Removal-Rate (MRR), Surface-Roughness (SR), and Kerf-Width (KfW) were optimized using integrated Entropy-COPRAS and artificial neural network (ANN) algorithms respectively. The relative significance ( Qi )values obtained for the alternatives are analyzed with the Taguchi method. The outcomes showed that the optimal setting of WEDM process variables is achieved at Servo Voltage: high volts; Pulse-on-time: 60 μs; Pulse-off-time: 16 μs; Peak Current: 6 Amp; Variable frequency: 18 Hz; Speed: 50 RPM; Sim Speed: 30 RPM respectively. The models developed from ANN were adequate and accurate from the results of error histogram and regression plots and they are best suited for the prophecy of future responses. The surface morphology studies confirmed the appearance of pockmarks, voids, and globules of debris on the Wire EDMed surfaces.

Laser-induced protruded bioinspired texturing of Ti-6Al-4V for controlled wettability in biomedical application

Bioinspired protruded textures with variable surface morphology and characteristics are getting worldwide popularity due to their wider applications. Among them controlled wettability for different materials through bioinspired textures is very essential to reduce the adhesion, bacterial contamination and growth, and drug delivery application. Even, identification and efficient fabrication of favorable bioinspired protrusions with optimum parameters are comparatively complex from normal textures through any material processing methods due to their complex shapes, form accuracy and dimensions. Therefore, this work targets the fabrication of four different types of protruded bioinspired textures namely, fish scale, protruded square, protruded circular, Python scale (snake) textured surface on biomedical grade Ti-6Al-4V titanium alloy for controlling the wettability using femtosecond laser surface texturing (LST). The optimum process parameters for the machining of Ti-6Al-4V were set as a temporal width of 350 fs, output power of 5.5 W, wavelength of 1030 nm, scanning speed of 100 mm/s and pulse rate of 500 KHz and three repetitions for all the texture types. To examine the effect of texture type, perimeter of all the fabricated textures was kept constant. Further, effect of varying perimeters was also analyzed for perimeter ranges from 300 to 500 µm. Surface morphology and characteristics were also analyzed for the measurement of texture consistency, dimensions and composition which was also related to the wettability results examined by static contact angle of the sessile drop method. Wetting of fish scale texture is decreased with increasing perimeter whereas of all other textures, wettability is going to be improved significantly.

Electroless Deposition of Ni Nanoparticles on Boron Particles: Physicochemical and Oxidation Properties

Elemental boron also has a high volumetric heat of combustion (136 kJ/cm3), the third highest gravimetric heat of combustion (58.5 MJ/kg) and its oxidation is a highly exothermic process. All these features make boron an attractive constituent of propellants, explosives, and high energy density solid fuels for air-breathing propulsion as an energetic material. Given these uses, researchers have worked on the ignition and combustion processes of boron. However, boron has several serious issues that limit its practical use, including large ignition delay, inefficient combustion, and a complex burning process in solid propellants due to the formation of a defensive boron oxide (B2O3) layer on the boron surface. Previous studies have found that the ignition and combustion performance of boron can be improved by coating it with metal particles, metal oxides, or organic materials, as well as by removing the boron oxide layer.In the literature, there are limited studies on metal particle coating of a boron surface using the electroless Ni plating method. The electroless coating has several impressive advantages over conventional electrolytic coating. The prime advantage is that electroless plating does not require any electricity to operate and is a low-cost process. Among other advantages, it provides a uniform coating and can be used with all kinds of substrates with complex shapes. Conductive and non-conductive materials/powders can be coated with constant thickness with good adhesion.The present work investigated Ni nanoparticle coating on irregularly shaped/non-spherical boron particles using the electroless Ni-plating method at room temperature to prevent the oxidation of boron particles. This is preferable since it is very difficult to coat large quantities at relatively high temperatures. The four different simple paths were chosen during the electroless Ni plating to coat Ni on boron particles: no rinsing and no drying (Path A), only drying (Path B), both rinsing and drying (Path C) and only rinsing (Path D). Previous studies have explored the effect of bath concentration, pH, and temperature on the Ni coating. However, the influence of the four different paths mentioned above on Ni coating with boron particles or any other materials has rarely been investigated. Surface morphology confirmed the Ni nanoparticles coating on the surface of boron particles. The size of the Ni nanoparticles varied between 10 and 120 nm concerning the chosen paths used for preparation using TEM. XRD characterization results of the Ni coated boron particles showed the formation of crystalline Ni nanoparticles. EDAX and XPS results showed the presence of the primary B and Ni elements in samples synthesized in the present study. Thermogravimetric analysis conducted in air atmosphere found the boron particles coated with Ni nanoparticles had enhanced oxidation resistance compared to bare boron particles. Also, the Ni coated boron particles showed a shift in exothermic peak to a lower temperature and higher heat evolution than the bare boron particles.Acknowledgements:This work was supported by the National Research Foundation (NRF) of Korea grant funded by the Korea government (MSIT) No. 2019R1A2C1010862, 2022R1A2C2013508

Active shape programming drives Drosophila wing disc eversion.

How complex 3D tissue shape emerges during animal development remains an important open question in biology and biophysics. Here, we discover a mechanism for 3D epithelial shape change based on active, in-plane cellular events that is analogous to inanimate "shape programmable" materials, which undergo blueprinted 3D shape transformations from in-plane gradients of spontaneous strains. We study eversion of the Drosophila wing disc pouch, when the epithelium transforms from a dome into a curved fold, quantifying 3D tissue shape changes and mapping spatial patterns of cellular behaviors on the evolving geometry using cellular topology. Using a physical model inspired by shape programming, we find that active cell rearrangements are the major contributor to pouch eversion and validate this conclusion using a knockdown of MyoVI, which reduces rearrangements and disrupts morphogenesis. This work shows that shape programming is a mechanism for animal tissue morphogenesis and suggests that patterns in nature could present design strategies for shape-programmable materials.

Numerical study of the multi-dimensional Galilei invariant fractional advection–diffusion equation using direct mesh-less local Petrov–Galerkin method

This article presents a local mesh-less procedure for simulating the Galilei invariant fractional advection–diffusion (GI-FAD) equations in one, two, and three-dimensional spaces. The proposed method combines a second-order Crank–Nicolson scheme for time discretization and the second-order weighted and shifted Grünwald difference (WSGD) formula. This time discretization scheme ensures unconditional stability and convergence with an order of O(τ2). In the spatial domain, a mesh-less weak form is employed based on the direct mesh-less local Petrov–Galerkin (DMLPG) method. The DMLPG method employs the generalized moving least-square (GMLS) approximation in conjunction with the local weak form of the equation. By utilizing simple polynomials as shape functions in the GMLS approximation, the necessity for complex shape function construction in the MLS approximation is eliminated. To validate and demonstrate the effectiveness of the proposed algorithm, a variety of problems in one, two, and three dimensions are investigated on both regular and irregular computational domains. The numerical results obtained from these investigations confirm the accuracy and reliability of the developed approach in simulating GI-FAD equations.

Cold sintering of complex-shaped ceramic materials

The present work explores for the first time the production of ceramic bodies with complex shape through the cold sintering process. Inspired by previous works on spark plasma sintering, a spacer accessory was designed to act as a removable mold. This proof-of-concept was tested with four different ceramic systems: biogenic hydroxyapatite, zinc oxide, diatomaceous earth and construction/demolition waste materials. In all cases, the density is comparable to that obtained by cold sintering of simpler disks. Moreover, the microstructure of the complex-shaped materials is substantially homogeneous in the entire component. Some distortions can be detected when comparing the spacer and sample shape, their control and modeling being a key challenge for future works.

Optimizing the separation process for improved zirconia molding through liquid crystal display 3D printing

Mask stereolithography 3D printing for zirconia ceramics has attracted increasing attention in the industrial manufacturing due to their advantages of complex shapes, precisely controlled internal structures and fine surface effects. However, high refractive index and expensive equipment cost have always affected its development. Herein, we combine liquid crystal display (LCD) light curing 3D printing with zirconia molding, which is free from environmental and price limitations. In the conventional method of operation, the cured layer is bonded to the bottom and cannot be manufactured. We put forward a strategy for optimizing separation process and investigate the mechanism of the separation process in depth for high-quality zirconia ceramics LCD 3D printing. The results show that the controlled adjustment of the surface free energy can achieve a great reduction in the separation force, which enabled the successful printing of zirconia ceramics based on LCD. The effect of physical properties of the separation membrane on the separation process was studied and the solid content and 3D printing parameters of ceramic paste were optimized. When the solid content is 72.5 wt%, high quality zirconia ceramic parts with flexural strength of 255 MPa and relative density of 98.1 % can be obtained. This work provides new ideas for the convenient customization of zirconia ceramics in many fields.

Tunable bending characteristics of bamboo by regulating moisture content for bamboo curved component manufacturing

Traditional applications of mechanically robust bamboo are mostly confined to flat and straight components. Here, we investigated the tunable bending characteristics of bamboo strips by regulating the moisture content as a means to achieve efficient fabrication of single-layer and multi-layer bamboo curved components (SBCCs and MBCCs). Under the two opposite radial bending modes, the bending strength of bamboo strips decreased while their ductility and toughness increased as the moisture content increased from 0 % to 35 %, and the asymmetry of the bending properties became more pronounced. Moisture in bamboo strips was a double-edged sword for curved component manufacturing. Bamboo strips with high moisture content had higher bendability, which was conducive to improving the bending pass rate of SBCCs. At a bending radius of 70 mm, the total bending pass rate of SBCCs made from bamboo strips with 35 % moisture content was 85.9 % higher than that of SBCCs made from bamboo strips with 0 % moisture content. However, excessive moisture content could easily reduce the bending stability of the SBCCs and affect the bonding properties of the MBCCs. The optimal moisture content of bamboo strips for manufacturing curved components was 10–18 %, and increasing the moisture content of bamboo strips could produce components with complex shapes. The results can provide more possibilities for innovative bamboo product design and engineering applications, thereby promoting the utilization of sustainable and eco-friendly bamboo.

Application of the image‐well method for transient borehole thermal energy storage systems with complex boundaries

AbstractThis study introduces a new analytical framework that employs the image‐well method to simulate the spatial and temporal temperature distribution in vertical borehole thermal energy storage (BTES) systems. The model accommodates complex boundary shapes and conditions, including insulation, convection, and constant temperature, without requiring iterative solutions at each time step. The model's accuracy and utility are demonstrated through an application to a borehole heat exchanger cluster arranged in an octagonal shape with insulating boundaries, based on a BTES site in Drake Landing (Canada). Model predictions are validated against a finite element model, showing a root‐mean‐square error of 0.012°C. A global sensitivity analysis highlights the influence of thermal parameters on system performance, identifying the heat flux of the borehole heat exchanger as the most sensitive parameter. Overall, this approach combines the advantages of analytical and numerical techniques to provide a clear and efficient tool for evaluating BTES systems, offering significant potential for advancing sustainable energy solutions.

Study on ultra-precision diamond cutting of polymers: Factors affecting dimensional accuracy and material removal mechanism

Polymers with surface microstructure have promising prospects for applications in the domains of aerospace, integrated circuits, and optical engineering. Ultra-precision cutting has unique advantages in the preparation of microstructure with high precision and complex shape. However, the inherent characteristics of polymers such as high elasticity, strong toughness, and poor thermal conductivity bring ultra-precision cutting a great challenge. In this study, the rectangular groove microstructures on polymers were fabricated by ultra-precision diamond cutting, and the influence of matrix material, feedrate and cutting depth on cutting performance and dimensional accuracy was quantitatively evaluated. The results indicate that the polyimide (PI) exhibits a good machinability compared with polyetheretherketone (PEEK) and polytetrafluoroethylene (PTFE). In addition, the feedrate have a negligible influence on the morphologies and dimensional accuracy of groove structure, while the groove width decreases and the ridge width increases as the cutting depth increases from 10 μm to 100 μm. The groove structure has the best dimensional accuracy when the cutting depth is 10 μm. Furthermore, the material removal mechanism of PI was discussed detailedly based on the results of numerical simulation and experiment.

Coordinate system setting for post-machining of impeller shape by wire arc DED and evaluation of processing efficiency

Wire arc additive manufacturing (WAAM) is a direct energy deposition (DED) process that uses arc welding. It is a method of stacking beads made by melting metal wires with an arc heat source generated by a short-circuit current. Compared to other metal additive manufacturing methods, this process can be used to quickly produce large and complex-shaped metal parts. However, due to the multi-bead stacking method, the surface is highly curved and the dimensional errors are large; therefore, post-processing of the surface by cutting is required. Impellers, which are widely used in various industries, have complex shapes and high material consumption during cutting; therefore, the WAAM process can improve the manufacturing efficiency. In this study, a manufacturing process for an impeller with a diameter of 160 mm was developed by using the WAAM process. A 6-bladed fan-type impeller used for high-pressure fluid delivery was similarly modeled, and the product was additively manufactured using an Inconel 625 alloy wire. Manufacturing conditions that ensure productivity and quality or the product were determined through experimentation. Considering the post-processing of the WAAM-fabricated structure, the robot and tool paths of the impeller model were designed, and the error in the process coordinate system caused by attaching and detaching the workpiece between the two processes was reduced. Through the post-processing of the WAAM-fabricated structure, the production efficiency and process reliability were verified when the conventional manufacturing method and WAAM process were applied.

A novel framework for low-contrast and random multi-scale blade casting defect detection by an adaptive global dynamic detection transformer

The radiographic inspection plays a crucial role in ensuring the casting quality for improving the service life under harsh environments. However, due to the low-contrast between the defects and the image background, the random spatial position distribution, random shapes and aspect ratios of the defects, the development of an accurate defect automatic detection system is still challenging. To address these issues, this paper proposes a novel framework for low-contrast and random multi-scale casting defect detection, which is referred to as adaptive global dynamic detection transformer (AGD-DETR). A novel defect-aware data augmentation method is first proposed to adaptively highlight the feature of the low-contrast defect boundary. A multi-attentional pyramid feature refinement (MPFR) module is then established to refine and fuse the multi-scale defect features of random sizes. Afterwards, a novel global dynamic receptive fusion-transformer (GDRF-Transformer) detection scheme is designed to perform the global perception and feature dynamic extraction of complex internal casting defects. It includes 4D-anchor query and cross-layer box update strategy, query rectification by prior information of defect aspect ratio, and global adaptive-feed forward network (GA-FFN). A dataset comprising turbine blade casting defect radiographic (TBCDR) images, is used to demonstrate the high efficiency of the proposed AGD-DETR. The obtained results show that the proposed method can accurately capture the spatial position distributions and complex defect shapes. Furthermore, it outperforms existing state-of-the-art defect detection methods.

Induction heating simulation for aircraft RTM toolings

Aircraft CFRP parts as sharklets are produced in resin transfer molding (RTM) tooling. The parts need to be heated up homogenously over the whole area with a constant temperature. The complex shape and accessibility of the tooling make it hard to introduce a common heating system. In addition, the heat must be transferred through the Invar metal tooling structure onto the CFRP. Infrared lamp, air fan and microwave heating are concepts in development. Electrical heating layer mats and cages are laborious in applying. Induction has the advantage of contact-less, efficient, and fast heating. Induction heating was tested for the structural bonding of CFRP frames and stringers showing high bonding strengths. To apply this technology for the RTM tooling, the placement and distance of the induction coils is important. Simulation can help to find the right adjustments and power needed for induction heating. With the program COMSOL the surface and the coils are modeled, and the numerically structured net is divided in small tetrahedron and quadratic sub elements. Since there is no magnetic streamline in the middle of the coil-section, a symmetric halving of the structure is applied as a boundary condition. The temperature-time development and the distance of the coils are simulated in 2D and 3D. Due to the material properties of the magnetic flux concentrator (MFC), higher flux concentration of the magnetic field occurred only in 2D. The results are validated by experiments and are in good agreement.

A new corrective method for the Tanzer’s group IIB constricted ear: Helical expansion using V-Y advancement flap combined with concha cartilage graft

BackgroundThe complexity of the constricted ear's shape renders a uniform surgical method unattainable, thus posing an ongoing challenge in its correction. The Tanzer’s group IIB constricted ear is characterized by a prominent downward folding, an underdeveloped antihelix, and the absence of sacpha. The present study utilized a V-Y advancement flap combined with concha cartilage for the repair of Tanzer’s group IIB constricted ear. MethodFrom September 2016 to September 2022, a total of 16 patients diagnosed with type IIB ear constriction were enrolled in this retrospective study. The correction procedure for constricted ear involved the utilization of a V-Y advancement flap combined with concha cartilage graft. The auricle shape data of the patients, as well as their VAS satisfaction score and auricle aesthetic score, were examined both preoperatively and 12 months postoperatively. ResultThe mean duration of follow-up in this study was 18 months. The postoperative measurements of ear length, ear width, bilateral differences in ear length, and bilateral differences in ear width exhibited significant improvement compared to preoperative values. The mean preoperative AOS score was 1.12±0.34, while the mean postoperative AOS score increased to 3.81±0.40. The preoperative VAS satisfaction score was recorded as 2.31±0.70, while the postoperative VAS score significantly increased to 8.00±0.89. The follow-up period did not present any cases of flap necrosis, hematoma, infection, or wound dehiscence. ConclusionThe combination of V-Y advancement flap and concha cartilage transplantation for the correction of Tanzer’s group IIB constricted ear can achieve a natural and aesthetically pleasing auricle shape, resulting in high patient satisfaction.

Convergent direct and indirect cortical streams shape avoidance decisions in mice via the midline thalamus

Current concepts of corticothalamic organization in the mammalian brain are mainly based on sensory systems, with less focus on circuits for higher-order cognitive functions. In sensory systems, first-order thalamic relays are driven by subcortical inputs and modulated by cortical feedback, while higher-order relays receive strong excitatory cortical inputs. The applicability of these principles beyond sensory systems is uncertain. We investigated mouse prefronto-thalamic projections to the midline thalamus, revealing distinct top-down control. Unlike sensory systems, this pathway relies on indirect modulation via the thalamic reticular nucleus (TRN). Specifically, the prelimbic area, which influences emotional and motivated behaviors, impacts instrumental avoidance responses through direct and indirect projections to the paraventricular thalamus. Both pathways promote defensive states, but the indirect pathway via the TRN is essential for organizing avoidance decisions through disinhibition. Our findings highlight intra-thalamic circuit dynamics that integrate cortical cognitive signals and their role in shaping complex behaviors.