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Abstract We report on the temperature dependent low energy electron diffraction (LEED) studies of 12 nm epitaxial Sr₃Ir₂O₇(001) thin films. The Debye temperature has been extracted from the temperature-dependence of LEED intensity at elevated temperatures and different electron kinetic energies. For the most surface sensitive LEED, obtained at the lowest electron kinetic energies, the extracted surface Debye temperature is 270 ± 22 K, which is much lower than the 488 ± 40 K Debye temperature obtained using higher electron kinetic energies. Surprisingly, the LEED diffraction intensity, at the lowest electron kinetic energies, increases rather than decreases, with increasing sample temperatures up to about 440 K. This anomalous behavior has been attributed to the reduction of the lattice vibrational amplitudes along the surface normal. This damping of the normal mode vibrations with increasing temperature results from the enhanced electronic screening via thermally activated carriers. This scenario is corroborated by the transport measurement, showing that Sr₃Ir₂O₇is a narrow band Mott insulator with a band gap of about 32 meV. We have identified criteria for finding anomalous scattering behavior in other transition metal oxide systems. 

Abstract We report evidence of a finite density of states at the Fermi level at the surface of epitaxial thin films of the narrow bandgap Mott insulator Sr₃Ir₂O₇(001). The Brillouin zone critical points for Sr₃Ir₂O₇(001) thin films have been determined by a comparison of the band mapping from angle-resolved photoemission spectroscopy and low energy electron diffraction. Angle-resolved x-ray photoemission studies reveal the surface termination of Sr₃Ir₂O₇(001) is Sr–O. The absence of dispersion with photon energy, or changing wave vector along the surface normal, indicates the two-dimensional character of the bands contributing to the density of states close to the Fermi level for Sr₃Ir₂O₇(001) thin films. Thus, the finite density of states at the Fermi level is attributed to surface states or surface resonances. The appearance of a finite density of states at the Fermi level is consistent with the increased conductivity with decreasing film thickness for ultrathin Sr₃Ir₂O₇(001) films. 

Ferroelectric tunnel junctions (FTJs) based on epitaxial complex oxide heterostructures are promising building blocks for developing low power nanoelectronics and neuromorphic computing. FTJs consisting of correlated oxide electrodes have distinct advantages in size scaling but only yield moderate electroresistance (ER) at room temperature due to the challenge in imposing asymmetric interfacial screening and large modulation of the tunneling potential profile. Here, we achieve large ER in all-oxide FTJs by paring a correlated metal with a narrow bandgap Mott insulator as electrodes. We fabricate epitaxial FTJs composed of 2.8 and 4 nm PbZr0.2Ti0.8O3 tunnel barriers sandwiched between correlated oxides LaNiO3 and Sr3Ir2O7 electrodes. An ER of 6500% has been observed at room temperature, which increases to over 105% at 100 K. The high ER can be attributed to ferroelectric polarization induced metal–insulator transition in interfacial Sr3Ir2O7, which enhances the potential asymmetry for the tunnel barrier. The temperature dependence of tunneling current shows that direct tunneling dominates in the on state, while the off-state conduction transitions from thermally activated behavior at high temperatures to Glazman–Matveev defect-mediated inelastic tunneling at low temperatures. Our study provides a viable material strategy for designing all-oxide FTJs with high ER, facilitating their implementation in nonvolatile memories and energy-efficient computing devices. 

The prevalent issue in urban trajectory data usage, notably in low-sample rate datasets, revolves around the accuracy of travel time estimations, traffic flow predictions, and trajectory similarity measurements. Conventional methods, often relying on simplistic mixes of static road networks and raw GPS data, fail to adequately integrate both network and trajectory dimensions. Addressing this, the innovative GRFTrajRec framework offers a graph-based solution for trajectory recovery. Its key feature is a trajectory-aware graph representation, enhancing the understanding of trajectory-road network interactions and facilitating the extraction of detailed embedding features for road segments. Additionally, GRFTrajRec's trajectory representation acutely captures spatiotemporal attributes of trajectory points. Central to this framework is a novel spatiotemporal interval-informed seq2seq model, integrating an attention-enhanced transformer and a feature differences-aware decoder. This model specifically excels in handling spatiotemporal intervals, crucial for restoring missing GPS points in low-sample datasets. Validated through extensive experiments on two large real-life trajectory datasets, GRFTrajRec has proven its efficacy in significantly boosting prediction accuracy and spatial consistency. 

Abstract Despite ferritin's critical role in regulating cellular and systemic iron levels, our understanding of the structure and assembly mechanism of isoferritins, discovered over eight decades ago, remains limited. Unveiling how the composition and molecular architecture of hetero‐oligomeric ferritins confer distinct functionality to isoferritins is essential to understanding how the structural intricacies of H and L subunits influence their interactions with cellular machinery. In this study, ferritin heteropolymers with specific H to L subunit ratios were synthesized using a uniquely engineered plasmid design, followed by high‐resolution cryo‐electron microscopy analysis and deep learning‐based amino acid modeling. Our structural examination revealed unique architectural features during the self‐assembly mechanism of heteropolymer ferritins and demonstrated a significant preference for H‐L heterodimer formation over H‐H or L‐L homodimers. Unexpectedly, while dimers seem essential building blocks in the protein self‐assembly process, the overall mechanism of ferritin self‐assembly is observed to proceed randomly through diverse pathways. The physiological significance of these findings is discussed including how ferritin microheterogeneity could represent a tissue‐specific adaptation process that imparts distinctive tissue‐specific functions to isoferritins. 

Abstract Analysis of factors that lead to the functionality of transcriptional activation domains remains a crucial and yet challenging task owing to the significant diversity in their sequences and their intrinsically disordered nature. Almost all existing methods that have aimed to predict activation domains have involved traditional machine learning approaches, such as logistic regression, that are unable to capture complex patterns in data or plain convolutional neural networks and have been limited in exploration of structural features. However, there is a tremendous potential in the inspection of the structural properties of activation domains, and an opportunity to investigate complex relationships between features of residues in the sequence. To address these, we have utilized the power of graph neural networks which can represent structural data in the form of nodes and edges, allowing nodes to exchange information among themselves. We have experimented with two kinds of graph formulations, one involving residues as nodes and the other assigning atoms to be the nodes. A logistic regression model was also developed to analyze feature importance. For all the models, several feature combinations were experimented with. The residue-level GNN model with amino acid type, residue position, acidic/basic/aromatic property and secondary structure feature combination gave the best performing model with accuracy, F1 score and AUROC of 97.9%, 71% and 97.1% respectively which outperformed other existing methods in the literature when applied on the dataset we used. Among the other structure-based features that were analyzed, the amphipathic property of helices also proved to be an important feature for classification. Logistic regression results showed that the most dominant feature that makes a sequence functional is the frequency of different types of amino acids in the sequence. Our results consistent have shown that functional sequences have more acidic and aromatic residues whereas basic residues are seen more in non-functional sequences. 

Abstract The Ruddlesden‐Popper 5diridate Sr₂IrO₄is an antiferromagnetic Mott insulator with the electronic, magnetic, and structural properties highly intertwined. Voltage control of its magnetic state is of intense fundmenatal and technological interest but remains to be demonstrated. Here, the tuning of magnetotransport properties in 5.2 nm Sr₂IrO₄via interfacial ferroelectric PbZr_0.2Ti_0.8O₃is reported. The conductance of the epitaxial PbZr_0.2Ti_0.8O₃/Sr₂IrO₄heterostructure exhibits ln(T) behavior that is characteristic of 2D correlated metal, in sharp contrast to the thermally activated behavior followed by 3D variable range hopping observed in single‐layer Sr₂IrO₄films. Switching PbZr_0.2Ti_0.8O₃polarization induces nonvolatile, reversible resistance modulation in Sr₂IrO₄. At low temperatures, the in‐plane magnetoresisance in the heterostructure transitions from positive to negative at high magnetic fields, opposite to the field dependence in single‐layer Sr₂IrO₄. In the polarization down state, the out‐of‐plane anisotropic magnetoresistanceR_AMRexhibits sinusoidal angular dependence, with a 90° phase shift below 20 K. For the polarization up state, unusual multi‐level resistance pinning appears inR_AMRbelow 30 K, pointing to enhanced magnetocrystalline anisotropy. The work sheds new light on the intriguing interplay of interface lattice coupling, charge doping, magnetoelastic effect, and possible incipient ferromagnetism in Sr₂IrO₄, facilitating the functional design of its electronic and material properties. 

ABSTRACT Microorganisms play a central role in sustaining soil ecosystems and agriculture, and these functions are usually associated with their complex life history. Yet, the regulation and evolution of life history have remained enigmatic and poorly understood, especially in protozoa, the third most abundant group of organisms in the soil. Here, we explore the life history of a cosmopolitan species—Colpoda steinii. Our analysis has yielded a high-quality macronuclear genome forC. steinii, with size of 155 Mbp and 37,123 protein-coding genes, as well as mean intron length of ~93 bp, longer than most other studied ciliates. Notably, we identify two possible whole-genome duplication events inC. steinii, which may account for its genome being about twice the size ofC. inflata’s, another co-existing species. We further resolve the gene expression profiles in diverse life stages ofC. steinii, which are also corroborated inC. inflata. During the resting cyst stage, genes associated with cell death and vacuole formation are upregulated, and translation-related genes are downregulated. While the translation-related genes are upregulated during the excystment of resting cysts. Reproductive cysts exhibit a significant reduction in cell adhesion. We also demonstrate that most genes expressed in specific life stages are under strong purifying selection. This study offers a deeper understanding of the life history evolution that underpins the extraordinary success and ecological functions of microorganisms in soil ecosystems.IMPORTANCEColpodaspecies, as a prominent group among the most widely distributed and abundant soil microorganisms, play a crucial role in sustaining soil ecosystems and promoting plant growth. This investigation reveals their exceptional macronuclear genomic features, including significantly large genome size, long introns, and numerous gene duplications. The gene expression profiles and the specific biological functions associated with the transitions between various life stages are also elucidated. The vast majority of genes linked to life stage transitions are subject to strong purifying selection, as inferred from multiple natural strains newly isolated and deeply sequenced. This substantiates the enduring and conservative nature ofColpoda’s life history, which has persisted throughout the extensive evolutionary history of these highly successful protozoa in soil. These findings shed light on the evolutionary dynamics of microbial eukaryotes in the ever-fluctuating soil environments. This integrative research represents a significant advancement in understanding the life histories of these understudied single-celled eukaryotes. 

Colpoda, one of the most widespread ciliated protozoa in soil, are poorly understood in regard to their genetics and evolution. Our research revealed extreme mitochondrial gene rearrangements dominated by gene loss events, potentially leading to the streamlining ofColpodamitogenomes. Surprisingly, while interspecific rearrangements abound, our population-level mitogenomic study revealed a conserved gene order within species, offering a potential new identification criterion. Phylogenomic analysis traced their lineage over 326 million years, revealing two distinct groups. Substantial genomic divergence might be associated with the lack of extended collinear blocks and relaxed purifying selection. This study systematically revealsColpodaciliate mitogenome structures and evolution, providing insights into the survival and evolution of these vital soil microorganisms.