Hot-Cracking Mechanism of Laser Welding of Aluminum Alloy 6061 in Lap Joint Configuration.

Laser welding, known for its distinctive advantages, has become significantly valuable in the automotive industry. However, in this context, the frequent occurrence of hot cracking necessitates further investigation into this phenomenon. This research aims to understand the hot-cracking mechanism in aluminum alloy (AA) 6061, welded using a laser beam in a lap joint setup. We used an array of material characterization methods to study the effects of processing parameters on the cracking susceptibility and to elucidate the hot-cracking mechanism. A laser power of 2000 W generated large hot cracks crossing the whole weld zone for all welding speed conditions. Our findings suggest that using a heat input of 30 J/mm significantly mitigates the likelihood of hot cracking. Furthermore, we observed that the concentrations of the alloying elements in the cracked region markedly surpassed the tolerable limits of some elements (silicon: 2.3 times, chromium: 8.1 times, and iron: 2.7 times, on average) in AA6061. The hot-cracking mechanism shows that the crack initiates from the weld root at the interface between the two welded plates and then extends along the columnar dendrite growth direction. Once the crack reaches the central region of the fusion zone, it veers upward, following the cooling direction in this area. Our comprehensive investigation indicates that the onset and propagation of hot cracks are influenced by a combination of factors, such as stress, strain, and the concentration of alloying elements within the intergranular region.

Lipid Bilayer Strengthens the Cooperative Network of a Membrane-Integral Enzyme.

Lipid bilayer provides a two-dimensional hydrophobic solvent milieu for membrane proteins in cells. Although the native bilayer is widely recognized as an optimal environment for folding and function of membrane proteins, the underlying physical basis remains elusive. Here, employing the intramembrane protease GlpG of Escherichia coli as a model, we elucidate how the bilayer stabilizes a membrane protein and engages the protein's residue interaction network compared to the nonnative hydrophobic medium, micelles. We find that the bilayer enhances GlpG stability by promoting residue burial in the protein interior compared to micelles. Strikingly, while the cooperative residue interactions cluster into multiple distinct regions in micelles, the whole packed regions of the protein act as a single cooperative unit in the bilayer. Molecular dynamics (MD) simulation indicates that lipids less efficiently solvate GlpG than detergents. Thus, the bilayerinduced enhancement of stability and cooperativity likely stems from the dominant intraprotein interactions outcompeting the weak lipid solvation. Our findings reveal a foundational mechanism in the folding, function, and quality control of membrane proteins. The enhanced cooperativity benefits function facilitating propagation of local structural perturbation across the membrane. However, the same phenomenon can render the proteins' conformational integrity vulnerable to missense mutations causing conformational diseases1,2.

Unsupervised and supervised AI on molecular dynamics simulations reveals complex characteristics of HLA-A2-peptide immunogenicity.

Immunologic recognition of peptide antigens bound to class I major histocompatibility complex (MHC) molecules is essential to both novel immunotherapeutic development and human health at large. Current methods for predicting antigen peptide immunogenicity rely primarily on simple sequence representations, which allow for some understanding of immunogenic features but provide inadequate consideration of the full scale of molecular mechanisms tied to peptide recognition. We here characterize contributions that unsupervised and supervised artificial intelligence (AI) methods can make toward understanding and predicting MHC(HLA-A2)-peptide complex immunogenicity when applied to large ensembles of molecular dynamics simulations. We first show that an unsupervised AI method allows us to identify subtle features that drive immunogenicity differences between a cancer neoantigen and its wild-type peptide counterpart. Next, we demonstrate that a supervised AI method for class I MHC(HLA-A2)-peptide complex classification significantly outperforms a sequence model on small datasets corrected for trivial sequence correlations. Furthermore, we show that both unsupervised and supervised approaches reveal determinants of immunogenicity based on time-dependent molecular fluctuations and anchor position dynamics outside the MHC binding groove. We discuss implications of these structural and dynamic immunogenicity correlates for the induction of T cell responses and therapeutic T cell receptor design.

Development of InDel markers for interspecific hybridization between hill pigeons and feral pigeons based on whole-genome re-sequencing.

Interspecific hybridization occurs among birds, and closely related sister taxa tend to hybridize at a high rate. Genomic hybridization markers are useful for understanding the patterns and processes of hybridization and for conserving endangered species in captivity and the wild. In this study, we developed genomic hybridization markers for the F1 progeny of the sister taxa feral pigeons (Columba livia var. domestica) and endangered hill pigeons (Columba rupestris) (family Columbidae). Using whole-genome re-sequencing data, we performed genome-wide analysis for insertion/deletion (InDel) polymorphisms and validated using primers. We conducted polymerase chain reaction (PCR) and agarose gel electrophoresis to identify species-specific InDels. We produced eight F1 hybrids of hill and feral pigeons, and their samples were tested by re-performing analyses and sequencing using 11 species-specific InDel polymorphisms. Eight InDel markers simultaneously amplified two DNA fragments from all F1 hybrids, and there was no abnormality in the sequencing results. The application of genomic tools to detect hybrids can play a crucial role in the assessment of hybridization frequency in the wild. Moreover, systematic captive propagation efforts with hybrids can help control the population decline of hill pigeons.

Deep generative molecular design reshapes drug discovery.

Recent advances and accomplishments of artificial intelligence (AI) and deep generative models have established their usefulness in medicinal applications, especially in drug discovery and development. To correctly apply AI, the developer and user face questions such as which protocols to consider, which factors to scrutinize, and how the deep generative models can integrate the relevant disciplines. This review summarizes classical and newly developed AI approaches, providing an updated and accessible guide to the broad computational drug discovery and development community. We introduce deep generative models from different standpoints and describe the theoretical frameworks for representing chemical and biological structures and their applications. We discuss the data and technical challenges and highlight future directions of multimodal deep generative models for accelerating drug discovery.

Whole-genome sequencing revealed different demographic histories among the Korean endemic hill pigeon (Columba rupestris), rock pigeon (Columba livia var. domestica) and oriental turtle dove (Streptopelia orientalis).

BACKGROUND: The family Columbidae is known as the pigeon family and contains approximately 351 species and 50 genera. Compared to the wealth of biological and genomic information on these Columba livia var. domesteca, information on Columba rupestris and Streptopelia orientalis has been rather limited. The C. rupestris population size is decreasing in Korea. OBJECTIVES: Whole-genome sequencing and identification of population characterization of each species based genome variation on 9 Korean pigeon and dove samples, namely, six hill pigeon (C. rupestris), one rock pigeon (C. livia var. domestica) and two oriental turtle dove (S. orientalis) samples. RESULTS: The whole genome of 9 genotypes were sequenced and mapped to the C. livia reference genome. Sequence alignment showed over 96% identity in C. rupestris and 94% identity in S. orientalis to the reference genome (GenBank assembly accession: GCA_001887795.1). Sequence variations, including single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), and structural variations, revealed that intergenus (Columba vs. Streptopelia) variations were approximately four times higher than intragenus variations (C. livia vs. C. rupestris). Of the two Columba species, C. livia var. domestica is closer to S. orientalis than C. rupestris. Pairwise sequentially Markovian coalescent (PSMC) demographic history analysis revealed that the three species underwent a common population bottleneck between 105 and 120 Kya; since then, the effective population sizes of the rock pigeon and oriental turtle dove have increased. CONCLUSION: The effective population size of the hill pigeon, an Endangered Species of Grade II in Korea, has increased slowly from the second severe bottleneck that occurred approximately 0.5-1.4 × 104 years ago. Our results showed no relationship between copy number variation in the Norrie disease protein (NDP) regulatory regions and plumage color patterns. We report the first comparative analysis of three pigeon genomes.

Analysis of Training and Seed Bias in Small Molecules Generated with a Conditional Graph-Based Variational Autoencoder─Insights for Practical AI-Driven Molecule Generation.

The application of deep learning to generative molecule design has shown early promise for accelerating lead series development. However, questions remain concerning how factors like training, data set, and seed bias impact the technology's utility to medicinal and computational chemists. In this work, we analyze the impact of seed and training bias on the output of an activity-conditioned graph-based variational autoencoder (VAE). Leveraging a massive, labeled data set corresponding to the dopamine D2 receptor, our graph-based generative model is shown to excel in producing desired conditioned activities and favorable unconditioned physical properties in generated molecules. We implement an activity-swapping method that allows for the activation, deactivation, or retention of activity of molecular seeds, and we apply independent deep learning classifiers to verify the generative results. Overall, we uncover relationships between noise, molecular seeds, and training set selection across a range of latent-space sampling procedures, providing important insights for practical AI-driven molecule generation.

Population genetic structure and conservation management of hill pigeons (Columba rupestris) recently endangered in South Korea.

BACKGROUND: Hill pigeons (Columba rupestris) are close to local extinction (ca. less than 100 individuals) in South Korea where a variety of conservation management procedures are urgently required. OBJECTIVE: This study was aimed at determining the conservation direction of captive propagation and reintroduction of hill pigeons using genetic information based on mitochondrial DNA. We also evaluated the extent of hybridization between hill pigeons and cohabiting domestic pigeons. METHODS: We used 51 blood samples of hill pigeons from Goheung (GH), Gurye (GR), and Uiryeong (UR), and domestic pigeons cohabiting with hill pigeon populations. Genetic diversity, pairwise Fst, analysis of molecular variance, and haplotype network analysis were used to examine the genetic structure of hill pigeons. RESULTS: Hill pigeons that inhabited South Korea were not genetically distinct from Mongolian and Russian populations and showed relatively low genetic diversity compared with other endangered species in Columbidae. The GR population that exhibited the largest population size showed lower genetic diversity, compared to the other populations, although the pairwise Fst values of the three populations indicated low genetic differentiation. The GH and GR populations were confirmed to lack hybridization, relatively, whereas the UR population was found to exhibit some degrees of hybridization. CONCLUSION: To conserve hill pigeons with low genetic diversity and differentiation in South Korea, the conservation process of captive propagation and reintroduction may require artificial gene flows among genetically verified populations in captivity and wildness. The introduction of foreign individuals from surrounding countries is also considered an alternative strategy for maintaining genetic diversity.

Simplified, interpretable graph convolutional neural networks for small molecule activity prediction.

We here present a streamlined, explainable graph convolutional neural network (gCNN) architecture for small molecule activity prediction. We first conduct a hyperparameter optimization across nearly 800 protein targets that produces a simplified gCNN QSAR architecture, and we observe that such a model can yield performance improvements over both standard gCNN and RF methods on difficult-to-classify test sets. Additionally, we discuss how reductions in convolutional layer dimensions potentially speak to the "anatomical" needs of gCNNs with respect to radial coarse graining of molecular substructure. We augment this simplified architecture with saliency map technology that highlights molecular substructures relevant to activity, and we perform saliency analysis on nearly 100 data-rich protein targets. We show that resultant substructural clusters are useful visualization tools for understanding substructure-activity relationships. We go on to highlight connections between our models' saliency predictions and observations made in the medicinal chemistry literature, focusing on four case studies of past lead finding and lead optimization campaigns.

CASTELO: clustered atom subtypes aided lead optimization-a combined machine learning and molecular modeling method.

BACKGROUND: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. RESULTS: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. CONCLUSION: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

Photoluminescence Properties of Nano-Sized BaO-TiO2-SiO2 System-Based Glass-Ceramics Doped with Er2O3 and Eu2O3.

The crystal phase of fresnoite (Ba2TiSi2O8) produced from BaO-TiO2-SiO2 (hereinafter referred to as BTS) has nonlinear optical properties and is capable of emitting ultraviolet light. It can also be utilized in various fields, such as optical communications and optoelectronic devices. In this study, Er and Eu were added to BTS-based glass and a glass-ceramic containing a nano-sized fresnoite crystal phase was prepared through an appropriate heat treatment process. The relationships among the type of crystal phase, the microstructure, the light transmittance capabilities and the PL characteristics of the prepared glass-ceramic were analyzed. In the glass-ceramic of BTS doped with Er, 428 nm light was emitted when excitation light with a 268 nm wavelength was applied, while in the glass-ceramic of BTS doped with Eu, 613 nm red light was emitted when excitation light with a wavelength 394 nm was supplied. The produced fresnoite-based glass-ceramic exhibits transparency and luminescence characteristics due to the nano-sized crystal phase. Therefore, it is likely to find use in various fields in the future.

Study of Anti-Glare Pattern Forming Process by Glass Etching for Improved Image Quality.

In this paper, the anti-glare characteristics of strengthened glass used in the dashboard of automobiles were improved to enhanced the ability of the driver to read the display. To this end, the glass surface was etched with a solution containing HF as a main component. We adjusted the concentration of the etching solution and the etching time as variables, and the transmittance, gloss, haze value, etc. of the etched glass were measured. On the etched glass surface, an irregular pattern mainly containing dioxonium hexa-fluorosilicate crystal phases was generated, and controlling the pattern could improve the anti-glare characteristics of the glass. With higher concentration of the etching solution and longer etching time, the light transmittance, reflectance, and gloss of the etched glass were accordingly lower, while the haze value increased. We discussed the relationship between these property changes and the surface microstructure, pattern components, and roughness of the etched glass.

Nano-Crystallization Behavior and Optical Properties of Diopside: Eu2O3-Based Glass-Ceramic System.

In this study, glass-ceramic was prepared by adding TiO2 as a nucleating agent to induce the internal crystallization behavior of diopside (CaO-MgO-2SiO2)-based glass. The optimum composition for producing a transparent glass-ceramic was a composition of 15 wt% of TiO2 mixed with 85% diopside. The light transmittance of the specimen decreased as the heat treatment temperature increased. When 394 nm excitation light was incident on the glass-ceramic containing 0.05% Eu2O3, red light of 614 nm wavelength emitted. We examined the relationship between the light emission mechanism and the crystal structure of the diopside-based glass-ceramic. We also discussed the applicability of the specimens prepared in this study as light emitting materials in various fields.

Structural cavities are critical to balancing stability and activity of a membrane-integral enzyme.

Packing interaction is a critical driving force in the folding of helical membrane proteins. Despite the importance, packing defects (i.e., cavities including voids, pockets, and pores) are prevalent in membrane-integral enzymes, channels, transporters, and receptors, playing essential roles in function. Then, a question arises regarding how the two competing requirements, packing for stability vs. cavities for function, are reconciled in membrane protein structures. Here, using the intramembrane protease GlpG of Escherichiacoli as a model and cavity-filling mutation as a probe, we tested the impacts of native cavities on the thermodynamic stability and function of a membrane protein. We find several stabilizing mutations which induce substantial activity reduction without distorting the active site. Notably, these mutations are all mapped onto the regions of conformational flexibility and functional importance, indicating that the cavities facilitate functional movement of GlpG while compromising the stability. Experiment and molecular dynamics simulation suggest that the stabilization is induced by the coupling between enhanced protein packing and weakly unfavorable lipid desolvation, or solely by favorable lipid solvation on the cavities. Our result suggests that, stabilized by the relatively weak interactions with lipids, cavities are accommodated in membrane proteins without severe energetic cost, which, in turn, serve as a platform to fine-tune the balance between stability and flexibility for optimal activity.

Crystallization Mechanism and Photoluminescence Properties of CaF2-Al2O3-SiO2: Eu Glass-Ceramics Based on Nano-Scale Phase Separation Phenomenon.

In this paper, CaF2-Al2O3-SiO2 glass containing nano-sized CaF2 crystals were fabricated using phase separation phenomenon and the effects of rare earth ion (Eu) addition on the optical properties were investigated. The formation conditions for nano-sized CaF2 crystal phase were confirmed using non-isothermal analysis and X-ray diffraction (XRD) measurement, while inhibiting anorthite or wollastonite crystal formation. The phase separation phenomenon in the mother glass and the nano-sized crystals generated by heat treatment were observed through the microstructure analysis using scanning electron microscopy (SEM). In addition, photoluminescence (PL) spectra and decay time analysis were performed to confirm the emission characteristics of Eu-doped glass-ceramics. The Eu-doped glass-ceramics produced in this study showed strong red light. The overall luminescence properties according to the heat treatment temperatures were found to shift from red to blue as indicated in the Commission International de l'Eclairage (CIE) color coordinate system.

Crystal Growth Behavior, Nanometer Microstructure, and Mechanical Properties of Diopside-Based Glass-Ceramics.

In this study, to increase the light transmittance of diopside type crystallized glass, crystals with size of less than 100 nm, which is smaller than the visible light wavelength, were generated in the specimen. For this purpose, the so-called two-step process encompassing heat treatment at the nucleation temperature followed by heating the crystal at the crystal growth temperature was employed. The crystallization behavior of the prepared specimen was studied and the optical and mechanical properties were investigated according to the heat treatment conditions. The glass used in the experiment was CaO-MgO-2SiO2, which is a stoichiometric composition of diopside crystals. Heat-treating temperatures for nucleation and crystal growth were determined by a nonisothermal thermal analysis using Differential Thermal Analysis (DTA). The most suitable heattreating conditions were nucleation at 761 °C/6 h and crystal growth at 880 °C/1 h. The generated diopside crystal size was below 100 nm on average and the light transmittance was as high as ~75% for most of the specimens and the parent glass specimen showed higher light transmittance than that of conventional commercialized semitransparent crystallized glass products. The bending strength of diopside-based glass-ceramics was 30 MPa and the fracture energy was 1.56 N/mm. The Avrami constant calculated from the Kissinger equation and the Augis-Bennett equation was 1.38 and the activation energy was 355.63 kJ/mol, and these value indicate surface crystallization behavior.

Nanometer Scale Microstructure and Optical Properties of BaO-TiO2-SiO2 System-Based Glass-Ceramics.

The fresnoite phase, one of the crystals obtainable in the BaO-TiO2-SiO2 (BTS) system, is a material with excellent nonlinear optical properties. In this study, glass-ceramic containing nanometer scale fresnoite crystal was prepared by controlling the heat-treatment process from a BTS system, and its properties were analyzed. BTS glasses were prepared by conventional melting and quenching method. The heat treatment conditions were investigated by the non-isothermal analysis method using DTA. The formation of fresnoite crystals and the change of crystallinity according to heat treatment temperature were investigated by a XRD analysis. The glass-ceramics prepared in this study had fine crystal grains less than 100 nm in size and showed surface crystallization behavior growing from the surface to the inside. The transmittance of the prepared specimen in the range of visible light was measured up to 77%. The photoluminescence (PL) intensity of specimen was remarkably high at 470 nm and the emitted light has a blue and white light characteristic as displayed in the CIE coordinates.

Study on Crystallization of the Glaze for Tiles by Substitution of TiO2, Al2O3 and ZrO2 Nucleating Agents.

A crystalline glaze is more chemically stable than a general glaze because it forms a fine and regular crystalline grain in vitreous matrix, and they are mainly used for floor or wall tiles because the surface of the glaze is smooth and has excellent abrasion resistance. In this paper, high hardness crystallized glazes with nano-sized crystal grains were prepared by substituting the nucleating agents TiO2, Al2O3 and ZrO2 in the glaze. The crystal glazes were obtained by preparing a glaze frit based on the composition SiO2-ZrO2-ZnO-CaO, according to the substitution amounts of TiO2, Al2O3 and ZrO2, and firing at 1100 °C and 1150 °C. X-ray diffraction (XRD) analysis was performed to observe the resulting crystal phase depending on the nucleating agent. The crystal size of the crystallized glaze produced was confirmed to be nano-sized through field emission scanning electron microscope (FE-SEM) analysis. The hardness of the crystallized glazes prepared by adding the nucleating agent was tested using the Vickers hardness measurement method, and was found to be slightly higher than that of the crystallized glaze made of ordinary glaze frit. Thus, nano-crystalline glazes of high hardness were prepared by controlling the nucleating agent and substitution amount.

Modeling and Structural Characterization of the Sweet Taste Receptor Heterodimer.

Sweet taste receptor, a heterodimer belonging to the class C G-protein coupled receptor (GPCR) family and composed of the T1R2 and T1R3 subunits, is responsible for the perception of natural sugars, sweet proteins, various d-amino acids, as well as artificial sweeteners. Despite the critical importance of the sweet receptor not only in mediating gustation but also in its role in the food industry, the architecture of the T1R2-T1R3 complex and the mechanism by which extracellular stimuli induce conformational changes that are propagated to the intracellular milieu, i.e., the signal transduction pathway, remain largely unknown. Here, we constructed and characterized a full-length structural model of the T1R2-T1R3 receptor, including both the transmembrane (TM) and extracellular (EC) domains of the heterodimer, using comparative modeling and extensive all-atom molecular dynamics simulations. Several heterodimer interfaces were first examined for the TM domain, and conformational changes occurring at the intracellular side and associated with the receptor's activation were characterized. From the analysis on the simulated data, putative allosteric binding sites for ligands, ions, and cholesterol were proposed. Also, insights into the protein interface of the TM domain upon activation are provided. The EC domain of the heterodimer, including both the Venus flytrap and cysteine-rich domains, was also investigated. Several important intersubunit interactions located at regions responsible for the receptor's proper function were observed, which resemble those recently identified in other class C GPCR members. Integration of the results from the TM and EC domains facilitates the generation of a full-length T1R2-T1R3 receptor. These findings along with the full-length structural model of the T1R2-T1R3 receptor provide a structural framework that may assist in understanding the mechanistic details associated with the receptor activation process for the sweet T1R2-T1R3 receptor as well as other members of the same family.

Raptor genomes reveal evolutionary signatures of predatory and nocturnal lifestyles.

BACKGROUND: Birds of prey (raptors) are dominant apex predators in terrestrial communities, with hawks (Accipitriformes) and falcons (Falconiformes) hunting by day and owls (Strigiformes) hunting by night. RESULTS: Here, we report new genomes and transcriptomes for 20 species of birds, including 16 species of birds of prey, and high-quality reference genomes for the Eurasian eagle-owl (Bubo bubo), oriental scops owl (Otus sunia), eastern buzzard (Buteo japonicus), and common kestrel (Falco tinnunculus). Our extensive genomic analysis and comparisons with non-raptor genomes identify common molecular signatures that underpin anatomical structure and sensory, muscle, circulatory, and respiratory systems related to a predatory lifestyle. Compared with diurnal birds, owls exhibit striking adaptations to the nocturnal environment, including functional trade-offs in the sensory systems, such as loss of color vision genes and selection for enhancement of nocturnal vision and other sensory systems that are convergent with other nocturnal avian orders. Additionally, we find that a suite of genes associated with vision and circadian rhythm are differentially expressed in blood tissue between nocturnal and diurnal raptors, possibly indicating adaptive expression change during the transition to nocturnality. CONCLUSIONS: Overall, raptor genomes show genomic signatures associated with the origin and maintenance of several specialized physiological and morphological features essential to be apex predators.