Precise Surface Research Articles

In pursuit of precise Ca II H&K chromospheric surface fluxes

The emission lines of the Ca II H&K doublet present one of the most important channels of radiative cooling for the chromospheres of cool stars. Although most other line emissions (Mg II h&k and numerous iron lines) populate the far-UV and require a very competitive space-born observing time, the Ca II H&K lines in the optical UV are easily accessible by ground-based spectroscopy with relatively cheap instrumentation, and the observational data are plentiful. At the same time, in order to include realistic mechanical and magnetic heating, advanced chromospheric models now require radiative cooling losses in absolute terms and therefore call for a precise surface flux scale, which could be provided by matching a photospheric Ca II H&K line profile computed by photospheric models. However, a major obstacle here is the significant ambiguity in parameter space in the face of a very sensitive dependence of cool stellar optical UV surface fluxes on the effective temperature. Consequently, we have developed a rigorous method by which precise physical parameters, most notably the effective temperature, are first determined by ISPEC tools working on high signal-to-noise spectra and based on a suitable line list and reference continuum. However, crosstalk and navigation of multiple local chi-square minima (best solutions) in parameter space must be considered. Only with the optimal set of parameters is a single PHOENIX model calculated, which defines the spectral surface flux scale in the Ca II H&K line region. In this paper, we discuss the results of the absolute measurements of Ca II K line fluxes for 32 representative cool stars and the accuracy of this approach. Finally, we show a comparison of the Ca II K chromospheric fluxes with line widths, and a relation of chromospheric flux with effective temperature and gravity following the logarithmic form log FCa II = α′ log g + β′ log Teff + C′.

A Comparative Study of Precision Surface Grinding Using Additively Fabricated Acrylonitrile-Butadiene-Styrene (ABS) Wheels with Continuous and Serrated Working Surfaces.

Nowadays, high requirements imposed by mechanical components make it necessary to develop modern production methods. Additive technologies have been dynamically developing in recent years, showing many advantages associated with the fabrication of elements with complex geometries and structures. One of the areas where the potential of additive technologies is exploited is the rapid tooling sector, which is based on the rapid production of tools and components used in various manufacturing methods. Currently, apart from industrial additive fabrication using metal and plastic powders, desktop and low-cost devices for additive manufacturing are gaining more and more importance in the production of functional elements. This paper presents the experimental results obtained from testing the micro-abrasive acrylonitrile-butadiene-styrene ABS tools fabricated by fused filament fabrication (FFF) technology and reinforced with SD 28/20 diamond grains uniformly distributed on the working surface of the tools after they were made. Precision surface grinding operations of 41Cr4 alloy steel were carried out on a portable five-axis CNC milling machine using wheels with continuous and serrated working surfaces. The tool with a serrated working surface enabled a more efficient material removal and produced a better surface finish. In particular, a low wear rate of both FFF-printed tools was confirmed after all experiments. Promising results were obtained, showing the potential for a wider industrial application of the tested tools.

Multiscale Investigation of Liquid Imbibition on an Electrodeposited Rough Surface.

Hydrophilic and superhydrophilic surfaces are often used in various applications, such as biomedical surface modification, heat pipe design, lab-on-chip devices, microelectronic structure design, etc. Deposition of molecules on surfaces and chemical modification of the surface are two of the frequently adopted techniques to fabricate hydrophilic surfaces. However, achieving controlled and precise surface roughness is an expensive process, and the multiscale nature of liquid imbibition on rough surfaces complicates the system's physics. To address this challenge, we propose an alternative approach for creating controlled rough surfaces by electrodeposition of copper ions on copper electrodes, explore the influence of various length scales encountered in roughened surfaces, ranging from micrometers to angstroms, and examine the associated physics. The microscale roughnesses are controlled by adjusting the deposition time. A molecular level investigation is employed to probe the intriguing physics of liquid imbibition on the created rough surface. The molecular analysis of droplet contact line dynamics, including the contact angle and footprint radius, shows qualitative alignment with the real systems. Additionally, this study provides new insights into the flow velocities during imbibition within surface asperities at the molecular level. Directional velocities, such as axially downward and horizontally outward flows, which are otherwise challenging to measure experimentally, are also evaluated on a molecular scale. These findings provide a fundamental understanding of the intricate phenomena of liquid spreading and imbibition on metallic surfaces with randomly distributed rough textures, deepened by molecular-scale insights. The agreement, on a qualitative scale, between the experiments and simulations is successfully established, providing a fundamental understanding of the complex phenomena of water droplet imbibition dynamics on an electrodeposited surface.

Laser-Assisted Micropatterned 3D Printed Scaffolds with Customizable Surface Topography and Porosity for Modulation of Cell Function.

The dynamic interaction between cells and their substrate is a cornerstone of biomaterial-based tissue regeneration focused on unraveling the complex factors that govern this crucial relationship. A key challenge is translating physical cues from 2D to 3D due to limitations in current biofabrication techniques. In response, this study introduces an innovative approach that combines additive and subtractive manufacturing for precise surface patterning of 3D printed scaffolds. Using poly(𝜀-caprolactone) as the scaffold material, polymeric fibers are 3D printed and subsequently laser-engraved with femtosecond laser to precisely create controlled microtopographies, including microgrooves (10 and 80µm in width) and micropits (25µm in diameter). Testing shows that the process does not compromise the mechanical properties of the fibers, which is critical for structural applications in tissue engineering. Human mesenchymal stem cells are used to investigate the effects of these topographical features on cell behavior. The 10 µm wide microgrooves notably enhance cell attachment, with cells aligning in elongated forms along the grooves, while micropits and unpatterned surfaces promote polygonal cell shapes. This combined approach demonstrates that precisely engineered microtopographies on 3D printed scaffolds can better mimic the natural extracellular matrix, improving cellular responses and offering a promising strategy for advancing tissue regeneration.

Reproduction of Three-Dimensional Microstructures on Inconel 718 Utilizing Laser-Textured PECM Cathodes

Abstract Pulse electrochemical machining (PECM) is an unconventional material removal process, widely applied to machine or shape difficult-to-machine materials. A new concept of reproducing three-dimensional (3D) microstructures has been developed and elaborated. Picosecond laser was utilized to produce concave or convex patterns on PECM cathodes, and pattern replication was carried out to PECM anodes. The laser achieved high machining precision and excellent surface integrity; both patterns were successfully replicated on the anodes. However, considerable deviations were found in the reproduced concave patterns on the anodes, possibly due to the rounding and widening effects.

Engineering DNA Nanocube SAM Scaffolds for FRET-Based Biosensing: Interfacial Characterization and Sensor Demonstration.

Decorating a gold surface with molecular-level control over the positioning of DNA probes was demonstrated using a self-assembled monolayer (SAM) of wireframe DNA nanocube structures. The DNA nanocubes were specifically adsorbed and oriented using thiol-modified DNA on one face of the cube. The DNA nanocube SAM had a uniform coverage over the gold single crystal bead electrode with a separation of 20-30 nm measured by AFM. The face of the nanocube furthest from the gold surface was designed to hybridize with two different sequences of a 50 base single-stranded DNA probe that was modified with a fluorophore. The first 20 bases were hybridized with the DNA nanocube. One of a pair of FRET fluorophores was used for each probe strand. The dimensions of the nanocube controlled the relative spacing between these fluorophores. When the DNA probes were single-stranded, a FRET signal was observed. FRET decreased to background levels when a complementary DNA target was hybridized to either probe, resulting in a turn-off sensor with little cross-talk between the individual hybridization events. Hybridization isotherms for one target gave KA = 170 pM and a detection limit <50 pM. In addition, the DNA nanocube SAM was configured to be used as a turn-on NeutrAvidin sensor using biotinylated DNA targets hybridized to each probe resulting in an increase in FRET. We show that the wireframe DNA nanocube can be an effective scaffold for preparing biosensors with controlled separation between surface-bound probes facilitating precise sensor surface design and enabling a wide range of sensing modalities with more than one signal available for correlative confirmation of the target binding.

Unreal that feels real: artificial intelligence-enhanced augmented reality for treating social and occupational dysfunction in post-traumatic stress disorder and anxiety disorders

ABSTRACT Background: Fear- and trauma-related conditions, such as post-traumatic stress disorder (PTSD) and social phobia, often manifest as socially avoidant behaviours, which commonly contribute to social and occupational disability transdiagnostically. While gold-standard treatments (i.e. exposure therapy, psychotropic medications) are effective, they are hindered by high dropout rates and limited impact on real-world functioning. Furthermore, most existing interventions only target symptom reduction, with few addressing avoidance-related deficits in social and occupational functioning. Objectives: This methods paper introduces an innovative augmented reality exposure therapy (ARET) technology designed to address the limitations of traditional interventions for anxiety disorders and PTSD, by directly targeting social and occupational dysfunction through exposure to real-life social contexts. Method: We introduce an ARET system, using artificial intelligence (AI)-driven, augmented reality (AR) technology, that enables exposure to realistic scenarios within the patient's real-world environment, fostering contextual generalization and functional improvement. Featuring holographic three-dimensional humans, precise surface mapping, wireless mobility, and telemedicine capabilities, the software provides customizable exposure scenarios to transform an environment into various spaces (e.g. grocery store, house party) with diverse human characters, as well as flexible AI-driven human interactions tailored to individual needs. Results: We share observations and feedback from the treatment of first responders with PTSD. Patients found the technology easy to use, with immersive realism, active engagement, and strong emotional responses needed for effective exposure therapy. Advances in AI-driven character development and AR hardware accessibility support the wider adoption of ARET by clinicians. Conclusion: By bridging the gap between clinical interventions and real-world functioning, ARET offers a transformative approach to addressing the pervasive impact of psychiatric disorders on social and occupational outcomes.

Multifold Topological Point with Quadratic Order in Binary Skutterudite Rhodium Triarsenide.

The exploration of topological nodal point states has recently evolved, moving beyond traditional linear crossings to include higher-order dispersions and multifold degeneracies. This study utilizes first-principles calculations to uncover an ideal multifold nodal point of quadratic order in the binary skutterudite rhodium triarsenide. The band structures around this nodal point show not only simple configuration but also clean distribution. Notably, a type-III dispersion condition has also been identified. When considering the effects of spin-orbit coupling, the nodal point retains both its multiple degeneracy and quadratic characteristics, although the band degeneracy transitions from 3-fold to quadruple. Detailed symmetry argument and model analysis have been provided, and precise band surface distribution has been obtained. Furthermore, the material is characterized by multiple significant arc surface states, as confirmed by the projected topological surface states. The clear separation of these states from the bulk bands facilitates experimental investigation. In summary, the multifold nodal point state identified in this research, along with the corresponding material candidate, presents an exceptional platform for the further study of higher-order topological point states, potentially catalyzing advancements in this emerging field.

Bioinspired Surface Engineering with Dual Covalent Receptors Incorporated via Precise Post-Imprinting Modification to Enhance the Specific Identification of Adenosine 5′-Monophosphate

Expanding the specific surface area of substrates and carrying out precise surface engineering of imprinted nanocavities are crucial methods for enhancing the identification efficiency of molecularly imprinted polymers (MIPs). To implement this synergistic strategy, bioinspired surface engineering was used to incorporate dual covalent receptors via precise post-imprinting modifications (PIMs) onto mesoporous silica nanosheets. The prepared sorbents (denoted as “D-PMIPs”) were utilized to improve the specific identification of adenosine 5′-monophosphate (AMP). Significantly, the mesoporous silica nanosheets possess a high surface area of approximately 498.73 m2∙g–1, which facilitates the formation of abundant specific recognition sites in the D-PMIPs. The dual covalent receptors are valuable for establishing the spatial orientation and arrangement of AMP through multiple cooperative interactions. PIMs enable precise site-specific functionalization within the imprinted cavities, leading to the tailor-made formation of complementary binding sites. The maximum number of high-affinity binding sites (Nmax) of the D-PMIPs is 39.99 μmol∙g–1, which is significantly higher than that of imprinted sorbents with a single receptor (i.e., S-BMIPs or S-PMIPs). The kinetic data of the D-PMIPs can be effectively described by a pseudo-second-order model, indicating that the main binding mechanism involves synergistic chemisorption from boronate affinity and the pyrimidine base. This study suggests that using dual covalent receptors and PIMs is a reliable approach for creating imprinted sorbents with high selectivity, allowing for the controlled engineering of imprinted sites.

Characterization of micro-wire electrical discharge machining surface texture by empirical mode decomposition

Surface roughness is a critical factor for the operational efficacy and lifespan of the manufactured components, often serving as a key metric for evaluating manufacturing processes and determining acceptance of a component. Traditional surface roughness measurements are highly sensitive to the fixed standard cut-off length, influencing the scale at which surface texture features are analyzed. Thus, developing techniques with more reliable filtering of surface features is essential for accurate surface metrology. This research proposes a novel method that combines Empirical Mode Decomposition (EMD) and Fast Fourier Transform (FFT) for surface roughness characterization. We applied our method to Nitinol shape memory alloy (equal atomic proportions of nickel and titanium) surfaces processed using micro-Wire Electrical Discharge Machining (μ-WEDM). Our results demonstrate that the EMD-FFT method significantly outperforms traditional filtering, especially for surfaces without distinct patterns like μ-WEDM. This improvement is particularly valuable for materials like Nitinol, which is widely used in critical applications where precise surface roughness control is essential. By accurately assessing the effects of μ-WEDM parameters on surface roughness, the proposed method reveals that for a constant pulse on time and a constant discharge current, the variation of pulse off time is more important than servo voltage. Thus, this method can contribute to optimizing manufacturing processes and producing higher-quality components with improved performance and durability.

Surface Tension of Two Near-Ideal Binary Liquid Mixtures and the Influence of Adjacent Vapors.

The measured surface tension of a binary liquid is found to depend strongly on the constituents of the adjacent vapor and on whether equilibrium has been achieved, giving insight into the complex interfacial configuration. This dependence is quantified by three techniques that offer complementary insights: surface tension measurements with a constrained sessile drop surrounded by different vapors, surface tension measurements by surface light scattering spectroscopy in a sealed cell at equilibrium, and molecular dynamics simulations of the equilibrium surface tension and excess surface concentration. Ensuring homogeneity of the binary liquid, which is essential for surface light scattering, was found to be nontrivial and was assured by high-sensitivity Schlieren imaging. Two pairs of liquids, n-pentane with 2-methylpentane and n-pentane with n-hexane, were investigated. The first pair was motivated by the observed improvement in the effectiveness of binary fluids versus a single constituent in wickless heat pipes studied in microgravity. The second pair was used for comparison. Experimental evaluation of different volume fractions of the two liquids showed strong dependence of surface tension on the relative concentration of different molecules near the interfacial region. For the above pairs of liquids, which appear to form ideal mixtures in bulk, we present sufficiently precise surface tension measurements to indicate unexpectedly complex behaviors at interfaces.

Close-to-Atomic Precision Surface Achieved through a Neutral and Eco-friendly Slurry in Chemical Mechanical Polishing of TC4 Alloy

Close-to-Atomic Precision Surface Achieved through a Neutral and Eco-friendly Slurry in Chemical Mechanical Polishing of TC4 Alloy

Intaglio surface of CNC milled versus 3D printed maxillary complete denture bases – An in vitro investigation of the accuracy of seven systems

ObjectivesThe accuracy of the intaglio surface of maxillary complete dentures produced with a variety of digital manufacturing systems have been comprehensively investigated, however, not for multiple systems in the same study. This in vitro study endeavors to measure and compare the accuracy of the intaglio surface of maxillary complete denture bases constructed with different photopolymerization-based 3D printing and CNC milling systems. Materials and MethodsTwo subtractive manufacturing machines and five additive manufacturing machines were used to manufacture a maxillary denture bases (n = 10) for analysis. The samples were stored in artificial saliva at 37 °C for 7 days to mimic intraoral use before they were air dried for 5 min, and then scanned with an E3 dental laboratory scanner to generate STL files. A 3D metrology software program was used to analyze the data against the original CAD design. Statistical differences were determined with 1-way analysis of variance (ANOVA) and the Kruskal Wallis test (α=0.05). Color deviation heat maps were used to interpret areas of clinical significance. ResultsThe results indicated that the subtractive manufacturing method delivers the truest and most precise intaglio surface of maxillary complete denture bases. The additive manufacturing technique delivers less true and less precise results with inconsistency observed between the different systems as opposed to the subtractive manufacturing groups which showed no significant differences. ConclusionsWhen manufacturing a complete maxillary denture base subtractive manufacturing will deliver the most consistent and true results.

Simulation study of turning-ultrasonic rolling compound processing for 42CrMo steel

The ultrasonic rolling processing technology has been shown to significantly reduce surface roughness and enhance the residual stress of parts, thereby improving their surface properties and extending their service life. This technology is particularly effective for the precision machining and surface strengthening of ultra-high-strength steel 42CrMo. This study aims to investigate the impact of turning pre-processing on the distribution of residual stress during ultrasonic rolling, a simulation model incorporating turning pre-processing was developed and used to conduct ultrasonic rolling simulation experiments, enabling the analysis of residual stress distribution patterns. Concurrently, ultrasonic rolling strengthening experiments were performed to validate the accuracy of the simulation model. The results confirm that with increasing rotational speed and feed rate, residual stress decreases, whereas with increasing static pressure and amplitude, residual stress increases. The residual stress variation obtained from the simulation of combined turning and ultrasonic rolling closely matched the results of experimental ultrasonic rolling tests. This consistency validates the accuracy of the simulation model. This study offers a novel approach for simulating and experimentally validating ultrasonic rolling processes, particularly for shaft-like parts that undergo turning as a pre-processing step.

Enhancing the anodic dissolution uniformity of dendritic-structured refractory high entropy alloys using a split electrolytic cell with a deep eutectic solvent

The attainment of uniform anodic dissolution in dendritic-structured refractory high entropy alloys (RHEAs) during the electropolishing process is essential for their utilization in high-precision components. Nevertheless, the intricate microstructures of these materials impede uniform dissolution, resulting in suboptimal surface quality. In this work, based on a choline chloride-based deep eutectic solvent and suitable polarization parameters selected by linear scanning voltammetry, a split electrolytic cell (SEC) was proposed to alter the traditional integrated electrolytic cell (IEC) to enhance the anodic dissolution uniformity of dendritic-structured RHEAs. A much smoother surface with Ra of 0.233 μm and a smaller height discrepancy of 0.8 μm was obtained, compared to those processed in IEC at the same condition. The non-uniform anodic dissolution was mainly attributed to the cathode-forming (hydroxide ion (OH−), dissolution of tungsten (W) in the dendrite region under the attack by OH−, and the formation of by-product, i.e., the water molecule. The positive impact of SEC on dissolution uniformity could be ascribed to its role in inhibiting OH− from interacting with the anode, as well as to the enhancement of solution acidity on the anode side, which facilitated the dissolution of metal oxides. The suggested reaction pathway was subsequently validated through experiments with controlled water concentration and assessing of electrochemical kinetics. Finally, the effects of SEC under different parameters were demonstrated. This work provides valuable insight into the precise, micro/nanoscale manufacturing and green electrochemical surface finishing of RHEAs in the future.

Anchoring Frustrated Lewis Pair Active Sites on Copper Nanoclusters for Regioselective Hydrogenation.

In recent years, the concept of Frustrated Lewis Pairs (FLPs), which consist of a combination of Lewis acid (LA) and Lewis base (LB) active sites arranged in a suitable geometric configuration, has been widely utilized in homogeneous catalytic reactions. This concept has also been extended to solid supports such as zeolites, metal oxide surfaces, and metal/covalent organic frameworks, resulting in a diverse range of heterogeneous FLP catalysts that have demonstrated notable efficiency and recyclability in activating small molecules. This study presents the successful immobilization of FLP active sites onto the surface of ligand-stabilized copper nanoclusters with atomic precision, leading to the development of copper nanocluster FLP catalysts characterized by high reactivity, stability, and selectivity. Specifically, thiol ligands containing 2-methoxyl groups were strategically designed to stabilize the surface of [Cu34S7(RS)18(PPh3)4]2+ (where RSH = 2-methoxybenzenethiol), facilitating the formation of FLPs between the surface copper atoms (LA) and ligand oxygen atoms (LB). Experimental and theoretical investigations have demonstrated that these FLPs on the cluster surface can efficiently activate H2 through a heterolytic pathway, resulting in superior catalytic performance in the hydrogenation of alkenes under mild conditions. Notably, the intricate yet precise surface coordination structures of the cluster, reminiscent of enzyme catalysts, enable the hydrogenation process to proceed with nearly 100% selectivity. This research offers valuable insights into the design of FLP catalysts with enhanced activity and selectivity by leveraging surface/interface coordination chemistry of ligand-stabilized atomically precise metal nanoclusters.

Enhanced electrochemical performance of ZrTe-Mn2O3 nanocomposite electrocatalyst for HER and OER in alkaline medium

Electrochemical energy conversion in renewable-energy technologies relies on the OER and HER towards next-generation fuels. Herein, we have coupled zirconia telluride (ZrTe) and manganese oxide (Mn2O3) nanosheets heterointerfaces by a facile hydrothermal method, which are engineered on stainless steel substrate (ZrTe-Mn2O3/SS). The physical properties, including crystallinity, phase purity, morphology, conductivity, and chemical interacted states of the developed composite, are systematically investigated by XRD, HRTEM, I-V, and XPS. The XPS observation showed unique redox properties of hydrogen peroxide species on the ZrTe-Mn2O3 catalyst and the oxidation state of Zr and Mn that was more easily changed in the ZrTe-Mn2O3 electrocatalyst compared with the pristine catalysts. The very decent electrochemical performance of the catalyst activation step (Mn3+→Mn4+ and Zr2+→Zr4+ oxidations) observed from electrochemical cyclic voltammetry (CV) and linear sweep voltammetry (LSV) studies that are tested in the alkaline environment. Concerning higher bifunctional activity for ZrTe-Mn2O3, the current density of 10 mA cm−2 is revealed only at a lower overpotential of 244 mV and Tafel slope of 48 mV/dec toward better OER. At the same time, composite material also exhibited a minimal overpotential of 61 mV toward HER to attain 100 mA/cm2. It was also found that introducing a connection of ZrTe with Mn2O3 improves the precise surface area and exposes more multi-active sites for easy transfer of electrons. In addition, it maintains excellent long-term stability for almost 110 hrs through chronoamperometry, which leads to no activity loss and further represents higher OER/HER activity in industrial applications. We conclusively demonstrate that the first-time reported research provides valuable insights attributed to the defective structure, porous nature, and covalently bridging between atomic-level heterogeneous interfaces, favouring rapid electron transfer process activation for continuously produced O2 and H2 gas bubbles.

Orthogonal cutting of 3D printed multi-material workpiece: numerical investigation of machining forces, stress, and temperature distribution

AbstractWith the development of 3D metal printers for rapid prototyping and industrial component production, heightened attention was directed towards post-processing operations for achieving precise surface quality and geometrical tolerances for these components. This paper investigated the orthogonal cutting of multi-material 3D printed workpieces using a coated cutting tool through finite element simulation. The workpieces featured different horizontal and vertical arrangements of layers composed of aluminum 7075-T6 alloy (Al), stainless steel 316 low alloy (SS), and Ti6Al4V alloy (Ti). The study explored the impacts of multi-material composition, coating thickness, and the rake angle of the cutting tool on machining forces, stress distribution, temperature distribution, and chip formation geometry. The results revealed a bimodal chip morphology in the machining process of horizontally arranged SS layers combined with other alloys. The SS layer resulted in a relatively uniform chip formation, while layers with two other materials exhibited a serrated chip formation. In contrast, a discontinuous chip formed when combining Al and Ti materials, as well as in the horizontally arranged layers made of Al, SS, and Ti alloys. The cutting force increased by 2.26 times when cutting workpieces with the horizontal arrangement of SS and Al layers compared to those with a single Al material. For the horizontal and vertical arrangement of layers made of Al and SS, von Mises stress values over the edge of the coated cutting tool significantly increased where the tool contacted the SS layer. Additionally, the horizontal arrangement of layers made of Al and SS materials caused the coated cutting tool to exhibit an extensive temperature distribution, with the maximum recorded temperature reaching 1448 °K. Increasing coating thickness led to a decrease in maximum principal stress at the surface of the tool and a rise in temperature at the cutting edge of the insert.

Zero-shot image segmentation for monitoring thermal conditions of individual cage-free laying hens

Body temperature is a critical indicator of the health and productivity of egg-laying chickens and other domesticated animals. Recent advancements in thermography allow for precise surface temperature measurement without physical contact with animals, reducing animal stress from human handling. Gold standard temperature analysis via thermography requires manual selection of limited points for an object of interest, which could be time-consuming and inadequate for representing the comprehensive thermal profile of a chicken’s body. The objective of this study was to leverage and optimize a zero-shot artificial intelligence technology for the automatic segmentation of individual cage-free laying hens within thermal images, providing insights into their overall thermal conditions. A zero-shot image segmentation model (Segment Anything, “SAM”) was modified by replacing manual selections of target points with automatic selection of the initial point using pre-processing techniques (e.g., thresholding) in each thermal image. The model was also incorporated with post-processing techniques integrated with a machine learning classifier to improve segmentation accuracy. Three versions of modified SAM models (i.e., SAM, FastSAM, and MobileSAM), two common instance segmentation algorithms (i.e., YOLOv8 and Mask R-CNN), and two foundation segmentation models (i.e., U2-Net and ISNet) were comparatively evaluated to determine the optimal one for bird segmentation from thermal images. A total of 1,917 thermal images were collected from cage-free laying hens (Hy-Line W-36) at 77–80 weeks of age. The image dataset exhibited considerable variations such as feathers, bird movement, body gestures, and the specific conditions of cage-free facilities. The experimental results demonstrate that the modified SAM did not only surpass the six zero-shot models—YOLOv8, Mask R-CNN, FastSAM, MobileSAM, U2Net, and ISNet—but also outperformed other modified SAM-based models (Modified FastSAM and Modified MobileSAM) in terms of hen detection performance, achieving a success rate of 84.4 %, and in segmentation performance, with an intersection over union of 85.5 %, recall of 91.0 %, and an F1 score of 92.3 %. The optimal model, modified SAM, was pipelined to extract statistics including the averages (°C) of mean (27.03, 27.04, 28.53, 26.68), median (26.27, 26.84, 28.28, 26.78), 25th percentile (25.33, 25.61, 27.26, 25.53), and 75th percentile (28.04, 27.95, 29.22, 27.55) of surface body temperature of individual laying hens in thermal images for each week. More statistics of hen body surface temperature can be extracted based on the segmentation results. The developed pipeline is a useful tool for automatically evaluating the thermal conditions of individual birds.

Study on the efficacy of 3D printing technology combined with customized plates for the treatment of complex tibial plateau fractures

BackgroundAnatomical reduction and stable fixation of complex tibial plateau fractures remain challenging in clinical practice. This study examines the efficacy of using 3D printing technology combined with customized plates for treating these fractures.MethodsWe retrospectively analyzed 22 patients treated with 3D printing and customized plates at the Orthopedic Department of the Central Hospital affiliated with Shenyang Medical College from September 2020 to January 2023. These patients were matched with 22 patients treated with traditional plates with similar baseline characteristics. Patients were divided into an experimental group (3D-printed models and customized plates) and a control group (traditional plates). The control group underwent traditional surgical methods, while the experimental group had a preoperative 3D model and customized plates for surgical planning. We compared baseline characteristics and recorded various indicators, including preoperative preparation time, surgical time, intraoperative blood loss, number of intraoperative fluoroscopies, hospital stay duration, fracture healing time, complications, knee joint range of motion (ROM), Rasmussen anatomical and functional scores, and HSS scores.ResultsAll surgeries were successful with effective follow-up. The experimental group had shorter surgical time, less intraoperative blood loss, and fewer intraoperative fluoroscopies (P < 0.05). At 6 months and 1 year postoperatively, the experimental group had better knee joint HSS scores than the control group. Preoperative preparation time and total hospital stay were shorter in the control group (P < 0.05). There were no significant differences in fracture healing time and follow-up duration between groups. The experimental group showed better knee joint flexion angles (P < 0.05). Rasmussen scores showed no statistical difference between groups (P > 0.05). The incidence of complications was slightly lower in the experimental group but not significantly different.Conclusion3D printing technology combined with customized plates for complex tibial plateau fractures enables precise articular surface reduction, significantly shortens surgical time, and reduces intraoperative blood loss. This method improves knee joint function, offering a more effective treatment option.