bluuebunny/crossref_metadata_2025_split huggingface dataset:
A Novel Synthesized Thermography (SynTG) Approach for In-Situ Defect Detection During Laser Powder Bed Fusion
Authors: Fu Xianzhe , Son Kwangtae , Fan Zhaoyan 
Published: August 2024

Abstract
Laser Powder Bed Fusion (L-PBF) is one of the most widely applied additive manufacturing processes to fabricate metallic parts with high geometric accuracy. Due to the highly concentrated heating power and fast scanning speed used in the L-PBF process, voids could be produced during printing for multiple reasons. The new method measures the cooling rate at a specific temperature and melt pool temperature of each location on the powder bed and then synthesizes the results into images representing the defect-induced thermal property variation on each printed layer. Analytical models have been built based on a simplified L-PBF process scenario to theoretically prove the relationship between the thermal signatures and the voids-induced conductivity reduction. The relationship is then validated in experiments on a commercial L-PBF platform with a high-speed IR sensor. Ex-situ X-ray CT scanning was employed to validate the detection results of SynTG. The comparison results show a good match between the SynTG methods and the X-ray CT results. The conclusive findings demonstrate the potential of the SynTG method in defect detection, thereby enhancing the quality of the printed parts.
Viscosity Inference of Hybrid Bioink Using Decision Tree-Based Machine Learning Method
Authors: Limon Shah , Sarah Rokeya , Habib Md Ahasan 
Published: August 2024

Abstract
Among various 3D bioprinting methods, the extrusion-based approach stands out for its ability to achieve high cell release rates and construct intricate scaffold structures. However, the use of synthetic semi-solid polymers or natural hydrogels with shear-thinning properties requires ongoing research into rheological properties, especially hydrogel viscosity. Researchers are exploring hybrid hydrogels, a combination of various materials, to ensure scaffold shape fidelity and cell viability. Current practices involve extensive experimentation to achieve the required viscosity for smooth hydrogel release through the nozzle, a process often resource-intensive and time-consuming. Addressing this challenge, computational methods, particularly machine learning, are gaining attention for fine-tuning process parameters and optimizing bio-ink components. This study adopts a decision tree-based machine learning method, demonstrating its efficacy in predicting bioink viscosity for 300 combinations of shear rates and Alginate, Carboxymethyl Cellulose (CMC), and Tempo Mediated Nano-fibrillated Cellulose (TO-NFC) material compositions. The inference model has been trained using 75% of the initial data and tested the model for the rest of the unused 25% of data. The model exhibits excellent accuracy, highlighting its potential to significantly reduce trial-and-error experiments. This approach offers a streamlined and efficient bioprinting process, paving the way for further innovations in the dynamic field of 3D bioprinting.
Dynamic Geometric Modeling for Directed Energy Deposition Process
Authors: Zhang Wenze , Chen Siqi , Dong Boge , Chen Yuanzhi , Deng Xiaoke , Duan Molong , Tang Kai 
Published: August 2024

Abstract
Directed energy deposition (DED) is a prominent additive manufacturing technology for manufacturing metal parts. High-fidelity simulation can reconstruct the DED process but is typically too computationally complex for process control and planning. On the other hand, experimental-based models typically only consider the static relationship between the printed bead geometry and the printing parameters, leading to significant geometry deviations. To address this issue, we propose a dynamic model that correlates the printing parameters, such as energy deposition rate and energy moving speed, with the printed geometry, such as the width and height of the printed bead. A mirrored sigmoid model was developed to fit the geometry profile of the printed bead, and a nonlinear time-invariant system was constructed to simulate the extracted geometry. This system comprises a nonlinear static model and a linear time-invariant system that respectively handles the static relationship and the high-frequency dynamic signal increments decomposed from the whole input signals. Experimental results have verified the effectiveness of the proposed method in predicting the dynamic printed bead geometry and reducing geometry deviations.
Experimental and Computational Study of Transport Phenomena in Laser Melting-Based Metal Additive Manufacturing
Authors: Deb Abhik , Panda Priti Ranjan , Viswanathan Koushik , Dutta Pradip 
Published: August 2024

Abstract
The present study reports an experimentally validated three-dimensional computational model for studying the transport phenomena associated with the molten pool produced by a laser melting based direct energy deposition process. In the present study, the substrate used is SS 316, while the powder feed material is Inconel 718, which is introduced co-spatially with the moving laser beam. The model considers alloy solidification, as the powder material is different from that of the substrate. An enthalpy-based technique is used for modelling the phase change processes so that the solid-liquid interface need not be tracked separately. The reference co-ordinate system is kept moving with the scanning laser beam while solving the mass, momentum, energy, and species conservation equations. The model considers differential melting points of various elements (major elements being nickel, chromium, and iron), their vaporization above the respective boiling points, Marangoni convection arising out of high temperature gradients on the top surface of molten-pool, and the momentum of powder feed particles (being carried by pressurized nitrogen as carrier gas) along with that of the shielding gas (nitrogen). For a fixed laser spot size and constant powder feed rate, other process parameters including the laser scanning speed and laser power have been varied for parametric studies. This transient simulation has been carried out till a steady state of the melt pool is attained, whereafter there is no significant change in the temperature and composition of the molten pool with time. The computational model predicts the velocity distribution, temperature profile with recognition of the melting isotherm, and species distribution in the melt pool, along with the geometry, i.e., width and depth, of the dilution zone. Corresponding experiments have been performed using the same process parameters for depositing IN 718 on a SS 316 substrate. The transient temperature profile in the melt-pool is captured using an IR Camera, whereas the deposited samples are processed and characterized to view the dilution zone. The results obtained from computations with respect to the temperature profile, particularly the melting isotherm, and the dimensions, viz., width and depth, of the dilution zone are validated against the experimental results. This model can then be utilized for designing and optimizing laser melting based direct energy deposition processes. The findings from this model including the local temperature at the solidification front, and concentration of alloying element in the melt-pool region can also serve as inputs for studying the micro-structure evolution of the deposited layers.
Brief Paper: Discrete Element Based Modeling of Powder Spreading Dynamics for Laser Powder Bed Fusion Process
Authors: Tripathi Saurabh , Kumar Cheruvu Siva 
Published: August 2024

Abstract
In the domain of non-conventional manufacturing processes the use of lasers for metal-based additve-manufacturing (AM) processes has got immense push from both industry and academia. And among these processes the use of Laser powder bed fusion (L-PBF) has seen quite interest. But like any other manufacturing process the quality of part produced by l-PBF is a function of raw material characteristics such as size and morphology of the feedstock powder & material-processing conditions throughout the build cycle which includes powder layering and laser melting parameters.Hence, the current study focuses and deals with the study of powder dynamics, especially spreading dynamics in powder-bed based AM systems. This dynamics of powder spreading which can be categorized as bulk phenomenon gets influenced by the particle size distribution, recoater-speed & shape and size of the recoating object employed. The metal powders having approximately spherical shape, with sizes in μm scale, which are used to form a layer of powder and the dynamics associated with them can modeled using Discrete element based approach, which describes the bulk behaviour of powder using a lagrangian approach of tracking the motion of every particle in the bulk medium which is governed by equations of motion & which are differential form of the popular newton’s laws of motion. These equations in terms of force & moment balance laws are then integrated in each time-step to obtain positions & velocities of each particle hence describing their motion in a given domain. The model herein considers the actual size distribution of the Ti6Al4V alloy powder, which was obtained using laser-diffraction analysis. Non-linear force laws were used to model the contact and non-contact interactions among the particles in the bulk. Thus, enabling the model to study how various powder spreading parameters influence the different powder-bed characteristics such as particle segregation and particle packing density.
Brief Paper: Judicious Hybridization of Incremental Forming and Additive Manufacturing to Enhance Product Complexity Through Non-Planar Substrate/Deposition
Authors: Cherukupally Shivaprasad , Nagallapati Vishwanath , Konka Praveen , Simhambhatla Suryakumar , Nallagundla Venkata Reddy 
Published: August 2024

Abstract
Hybrid manufacturing is the combination of two or more different processes to overcome their individual limitations and take advantage of their combined strengths to produce components more efficiently and eco-friendly than existing processes. Double-sided incremental forming (DSIF) and metal additive manufacturing (MAM) using direct energy deposition are the most flexible processes that do not require geometry-specific tooling to produce customized and complex metal parts. However, there is no absolute geometrical freedom, and each process and machine has certain limitations (MAM process has gravity and torch accessibility constraints due to lower surface inclinations and intricate shapes, respectively). Hence, the main objective of the present work is to demonstrate the feasibility thereof from the judicious hybridization of DSIF and MAM processes (termed as HyDAM, Hybrid Deformation aided Additive Manufacturing) in terms of product complexity by exploiting the geometrical freedom offered from both processes. Non-planar substrates are formed using DSIF and deposition is carried out using wire-based direct energy deposition (W-DED). In the present work, two complex geometries which are difficult to fabricate by conventional AM process due to torch accessibility and gravity constraints are considered to demonstrate their feasibility through proposed hybrid process. An appropriate build orientation of the component is chosen, and the corresponding substrate is formed using DSIF. The material deposited on the formed substrate with a suitable deposition path. The feasibility of proposed HyDAM is successfully demonstrated by fabricating complex components using a three-axis machine during deposition. Future work includes the automatic feature recognition for HyDAM, role of process parameters on bead asymmetry, path planning, exploring complex geometries (for example: deposition of non-planar cellular/perforated structures), performing thermo-mechanical analysis, and achieving the good accuracy.
Measurement of Tool Edge Geometry Using Saturated Fluorescence From Cutting Fluid
Authors: Uenohara Tsutomu , Ito Taiyu , Mizutani Yasuhiro , Takaya Yasuhiro 
Published: August 2024

Abstract
Tool edge wear has a significant effect on machining accuracy. Therefore, to obtain high machining accuracy, the tool edge geometry must be measured with high accuracy. On-machine measurement of tool edge geometry is desirable to reduce re-installation errors and improve throughput. Although conventional optical measurement methods can generally achieve high measurement accuracy in a clean measurement environment, on-machine measurement is difficult because the cutting fluid adhering to the tool interferes with the measurement. We have proposed a tool edge profile measurement method based on confocal detection of fluorescence generated by laser excitation of cutting fluid, and have demonstrated its validity. In this study, we focused on the phenomenon of saturated fluorescence to further improve the measurement accuracy. The intensity of fluorescence from the cutting fluid depends on the intensity of the excitation laser. When the intensity of the excitation laser is relatively low, the fluorescence intensity is proportional to the intensity of the excitation laser. At higher excitation laser intensities, however, the fluorescence intensity saturates due to the limited number of fluorescent molecules that can be excited. In other words, when a focused laser beam is used to excite the cutting fluid, the fluorescence intensity saturates only in a localized region in the vicinity of the focal spot. Therefore, detecting only the saturated fluorescence improves the spatial resolution of tool edge geometry measurement. In this study, the excitation laser was time-modulated to detect the saturated fluorescence. When the excitation laser is modulated at frequency f, fluorescence is also emitted at frequency f when the fluorescence is not saturated. On the other hand, when the fluorescence saturates, it is known that a frequency component twice the modulation frequency of the excitation laser appears in the fluorescence intensity. In other words, by modulating the excitation laser at frequency f and extracting only the 2f frequency component of the emitted fluorescence intensity using a lock-in amplifier, only the saturated fluorescence can be detected. In this study, the geometry of a worn throw-away tip was measured to validate the proposed method. Compared to the conventional method that detects non-saturated fluorescence, the proposed method has a steeper rise in fluorescence intensity when the focal spot is scanned from the air to the cutting fluid and a steeper fall in fluorescence intensity when the focal spot is scanned from the cutting fluid to the tool. This experimentally confirmed that the measurement resolution of the tool surface was improved. The tool edge geometry was measured by scanning the focal spot at many points on the tool. As a result, wear of a few micrometers to several tens of micrometers could be measured with high accuracy. The proposed method is expected to be implemented on machine tools.
Structural basis of paramyxo- and pneumovirus polymerase inhibition by non-nucleoside small-molecule antivirals
Authors: Wolf Josef D. , Sirrine Michael R. , Cox Robert M. , Plemper Richard K. 
Published: August 2024

ABSTRACT

Small-molecule antivirals can be used as chemical probes to stabilize transitory conformational stages of viral target proteins, facilitating structural analyses. Here, we evaluate allosteric pneumo- and paramyxovirus polymerase inhibitors that have the potential to serve as chemical probes and aid the structural characterization of short-lived intermediate conformations of the polymerase complex. Of multiple inhibitor classes evaluated, we discuss in-depth distinct scaffolds that were selected based on well-understood structure-activity relationships, insight into resistance profiles, biochemical characterization of the mechanism of action, and photoaffinity-based target mapping. Each class is thought to block structural rearrangements of polymerase domains albeit target sites and docking poses are distinct. This review highlights validated druggable targets in the paramyxo- and pneumovirus polymerase proteins and discusses discrete structural stages of the polymerase complexes required for bioactivity.
A time-course analysis of
Aspergillus terreus
secretomes reveals the importance of pectin-degrading enzymes to increase the digestibility of soybean meal
Authors: Plouhinec Lauriane , Bonnin Estelle , Kielbasa Mélodie , Armengaud Jean , Neugnot Virginie , Berrin Jean-Guy , Lafond Mickael 
Published: August 2024

ABSTRACT

Considering an ever-growing global population, which hit 8 billion people in the fall of 2022, it is essential to find solutions to avoid croplands competition between human food and animal feed. Agricultural co-products such as soybean meals have become important components of the circular economy thanks to their use in animal feed. Their implementation was made possible by the addition of exogenous enzymes in the diet of monogastric animals, especially fungal carbohydrate-active enzymes (CAZymes). Here, we describe a time-course production and analysis of
Aspergillus terreus
secretomes for the identification of CAZymes able to enhance the digestibility of soybean meals. Functional assays revealed that the release of nutrients and the degradation of pectins in soybean meals can be tightly interconnected. Using a comparative proteomics approach, we identified several fungal pectin-degrading enzymes leading to increased assimilable nutrients in the soluble fraction of soybean meals. Our results reinforce the importance of deconstructing pectic polysaccharides in feedstuffs and contribute to sharpen our understanding of the fungal enzymatic interplays involved in pectin hydrolysis.

IMPORTANCE
In the present study, we developed a strategy to identify the key fungal enzymatic activities involved in the improvement of soybean meal (SBM) digestibility. Our data unravel the importance of pectin degradation for the release of nutrients from SBM and provide some insights regarding the degradation of rhamnogalacturonan-I (RG-I) by ascomycetes. Indeed, the hydrolysis of pectins and RG-I by human microbiota is well documented in the literature, but our knowledge of the fungal CAZymes at play for the degradation of soybean pectins remains hitherto underexplored. Due to its wide use in animal feed, improving the digestibility of SBM by enzymatic treatments is a current challenge for feed additive suppliers. Since non-starch polysaccharides and pectins have often been reported for their anti-nutritional role in SBM, we believe this study will provide new avenues toward the improvement of enzymatic cocktails for animal nutrition and health.
Demystifying anaerobic respiration: a problem-solving exercise
Authors: Linder Tomas 
Published: August 2024

ABSTRACT

Anaerobic respiration reactions are of fundamental importance to global biogeochemical cycling of elements. Yet, the idea that cellular respiration can occur not only in the absence of oxygen but also involve the oxidation of inorganic substrates (e.g., AsO
3
3–
, Fe
2+
, H
2
, H
2
S, Mn
2+
, NH
3
, and S
0
) is often foreign to many undergraduate students. This article describes a problem-solving exercise where students are introduced to the thermodynamic fundamentals of respiration with a particular focus on the role of redox (reduction-oxidation) potentials (

E
0
´

). In the exercise, the students investigate how the difference in redox potential (

ΔE
0
´

) between different pairs of reductants and oxidants affects the range of permissible microbial metabolic reactions in natural environments when oxygen is absent.
Incompatible packaging signals and impaired protein functions hinder reassortment of bat H17N10 or H18N11 segment 7 with human H1N1 influenza A viruses
Authors: Wang Liping , Shi Lei , Liu Heidi , Zhang Jialin , Yang Wenyu , Schountz Tony , Ma Wenjun 
Published: August 2024

ABSTRACT

Novel bat H17N10 and H18N11 influenza A viruses (IAVs) are incapable of reassortment with conventional IAVs during co-infection. To date, the underlying mechanisms that inhibit bat and conventional IAV reassortment remain poorly understood. Herein, we used the bat influenza M gene in the PR8 H1N1 virus genetic background to determine the molecular basis that restricts reassortment of segment 7. Our results showed that NEP and M1 from bat H17N10 and H18N11 can interact with PR8 M1 and NEP, resulting in mediating PR8 viral ribonucleoprotein (vRNP) nuclear export and formation of virus-like particles with single vRNP. Further studies demonstrated that the incompatible packaging signals (PSs) of H17N10 or H18N11 M segment led to the failure to rescue recombinant viruses in the PR8 genetic background. Recombinant PR8 viruses (rPR8psH18M and rPR8psH17M) containing bat influenza M coding region flanked with the PR8 M PSs were rescued but displayed lower replication in contrast to the parental PR8 virus, which is due to a low efficiency of recombinant virus uncoating correlating with the functions of the bat M2. Our studies reveal molecular mechanisms of the M gene that hinder reassortment between bat and conventional IAVs, which will help to understand the biology of novel bat IAVs.

IMPORTANCE
Reassortment is one of the mechanisms in fast evolution of influenza A viruses (IAVs) and responsible for generating pandemic strains. To date, why novel bat IAVs are incapable of reassorting with conventional IAVs remains completely understood. Here, we attempted to rescue recombinant PR8 viruses with M segment from bat IAVs to understand the molecular mechanisms in hindering their reassortment. Results showed that bat influenza NEP and M1 have similar functions as respective counterparts of PR8 to medicating viral ribonucleoprotein nuclear export. Moreover, the incompatible packaging signals of M genes from bat and conventional IAVs and impaired bat M2 functions are the major reasons to hinder their reassortment. Recombinant PR8 viruses with bat influenza M open reading frames were generated but showed attenuation, which correlated with the functions of the bat M2 protein. Our studies provide novel insights into the molecular mechanisms that restrict reassortment between bat and conventional IAVs.