Investigations of pressurized Lu-N-H materials by using the hybrid functional

Recently, Lu-N-H materials were reported to have room-temperature superconductivity, and the Hubbard U correction on the Lu's $\textit{f}$-electrons is necessary, and a constant U = 5.5 eV was applied to different Lu-N-H configurations (Nature 615, 244 (2023)). Following simulations indicate that the superconducting transition temperature (T$_{c}$) of LuH$_{3}$ with U = 0 eV is 50 ~ 60 K, while the N-doped LuH$_{3}$ is below 30 K. Quite recently, calculations with U = 5 eV shows that the T$_{c}$ of N-doped LuH$_{3}$ exceeds 100 K. The properties of Lu-N-H are sensitive to the applied U values. Here, the structural and electronic Lu-N-H properties at high-pressure (0 ~ 10 GPa) are systematically investigated based on the hybrid functional. We show that different Lu-N-H configurations should possess different U values varying from 6.4 eV to 7.4 eV. Furthermore, at pressure ranging from 0 GPa to 1 GPa, the $\textit{f}$ and $\textit{d}$ band centers of N-doped LuH$_{3}$ show oscillation or even plateau, and the band gap of insulators also shows a platform near this pressure, this is consistent with the pressure range where room-temperature superconductivity appeared in Lu-N-H. Our work provides insights into the understanding of Lu-N-H materials and other hydrogen-rich superconductors based on the rare-earth elements

Magnetic properties of pressurized CsV3_{3}Sb5_{5} calculated by using a hybrid functional

Based on the hybrid functional, we find that at 0 GPa, the pristine CsV$_{3}$Sb$_{5}$ has local magnetic moment of 0.85 $\mu_B$ /unit cell, which is suppressed at pressure of 2.5 GPa resulting in a spin-crossover. Since the ground sate of CsV$_{3}$Sb$_{5}$ with charge density wave (CDW) distortion is non-magnetic state, the local magnetic moment of pristine CsV$_{3}$Sb$_{5}$ will be suppressed by temperature-induced CDW transition at 94 K. The schematic evolution of magnetic moments as functions of pressure and temperature are presented. At low temperature, CsV$_{3}$Sb$_{5}$ is a rare example of materials hosting pressureinduced local magnetic moment, and we suggeste that the effects of local magnetic moments should be considered for understanding its properties

Deep Joint Source-Channel Coding for DNA Image Storage: A Novel Approach with Enhanced Error Resilience and Biological Constraint Optimization

In the current era, DeoxyriboNucleic Acid (DNA) based data storage emerges as an intriguing approach, garnering substantial academic interest and investigation. This paper introduces a novel deep joint source-channel coding (DJSCC) scheme for DNA image storage, designated as DJSCC-DNA. This paradigm distinguishes itself from conventional DNA storage techniques through three key modifications: 1) it employs advanced deep learning methodologies, employing convolutional neural networks for DNA encoding and decoding processes; 2) it seamlessly integrates DNA polymerase chain reaction (PCR) amplification into the network architecture, thereby augmenting data recovery precision; and 3) it restructures the loss function by targeting biological constraints for optimization. The performance of the proposed model is demonstrated via numerical results from specific channel testing, suggesting that it surpasses conventional deep learning methodologies in terms of peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM). Additionally, the model effectively ensures positive constraints on both homopolymer run-length and GC content

Prompting Large Language Models to Reformulate Queries for Moment Localization

The task of moment localization is to localize a temporal moment in an untrimmed video for a given natural language query. Since untrimmed video contains highly redundant contents, the quality of the query is crucial for accurately localizing moments, i.e., the query should provide precise information about the target moment so that the localization model can understand what to look for in the videos. However, the natural language queries in current datasets may not be easy to understand for existing models. For example, the Ego4D dataset uses question sentences as the query to describe relatively complex moments. While being natural and straightforward for humans, understanding such question sentences are challenging for mainstream moment localization models like 2D-TAN. Inspired by the recent success of large language models, especially their ability of understanding and generating complex natural language contents, in this extended abstract, we make early attempts at reformulating the moment queries into a set of instructions using large language models and making them more friendly to the localization models.Comment: 4 pages, 2 figure

The N-terminal domain of Lhcb proteins is critical for recognition of the LHCII kinase

AbstractThe light-harvesting chlorophyll (Chl) a/b complex of photosystem (PS) II (LHCII) plays important roles in the distribution of the excitation energy between the two PSs in the thylakoid membrane during state transitions. In this process, LHCII, homo- or heterotrimers composed of Lhcb1–3, migrate between PSII and PSI depending on the phosphorylation status of Lhcb1 and Lhcb2. We have studied the mechanisms of the substrate recognition of a thylakoid threonine kinase using reconstituted site-directed trimeric Lhcb protein–pigment complex mutants. Mutants lacking the positively charged residues R/K upstream of phosphorylation site (Thr) in the N-terminal domain of Lhcb1 were no longer phosphorylated. Besides, the length of the peptide upstream of the phosphorylated site (Thr) is also crucial for Lhcb phosphorylation in vitro. Furthermore, the two N-terminal residues of Lhcb appear to play a key role in the phosphorylation kinetics because Lhcb with N-terminal RR was phosphorylated much faster than with RK. Therefore, we conclude that the substrate recognition of the LHCII kinase is determined to a large extent by the N-terminal sequence of the Lhcb proteins. The study provides new insights into the interactions of the Lhcb proteins with the LHCII kinase

A Novel Prognostic Predictor of Immune Micro-environment and Therapeutic Response in Kidney Renal Clear Cell Carcinoma based on Necroptosis-related Gene Signature

Background: Necroptosis, a cell death of caspase-independence, plays a pivotal role in cancer biological regulation. Although necroptosis is closely associated with oncogenesis, cancer metastasis, and immunity, there remains a lack of studies determining the role of necroptosis-related genes (NRGs) in the highly immunogenic cancer type, kidney renal clear cell carcinoma (KIRC). Methods: The information of clinicopathology and transcriptome was extracted from TCGA database. Following the division into the train and test cohorts, a three-NRGs (TLR3, FASLG, ZBP1) risk model was identified in train cohort by LASSO regression. The overall survival (OS) comparison was conducted between different risk groups through Kaplan-Meier analysis, which was further validated in test cohort. The Cox proportional hazards regression model was introduced to assess its impact of clinicopathological factors and risk score on survival. ESTIMATE and CIBERSORT algorithms were introduced to evaluate immune microenvironment, while enrichment analysis was conducted to explore the biological significance. Correlation analysis was applied for the correlation assessment between checkpoint gene expression and risk score, between gene expression and therapeutic response. Gene expressions from TCGA were verified by GEO datasets and immunohistochemistry (IHC) analysis. Results: This NRGs-related signature predicted poorer OS in high-risk group, which was also verified in test cohort. Risk score could also independently predict survival outcome of KIRC. Significant changes were also found in immune microenvironment and checkpoint gene expressions between different risk groups, with immune functional enrichment in high-risk group. Interestingly, therapeutic response was correlated with the expressions of NRGs. The expressions of NRGs from TCGA were consistent with those from GEO datasets and IHC analysis. Conclusion: The NRGs-related signature functions as a novel prognostic predictor of immune microenvironment and therapeutic response in KIRC

The role of edge-based and surface-based information in natural scene categorization: evidence from behavior and event-related potentials

A fundamental question in vision research is whether visual recognition is determined by edge-based information (e.g., edge, line, and conjunction) or surface-based information (e.g., color, brightness, and texture). To investigate this question, we manipulated the stimulus onset asynchrony (SOA) between the scene and the mask in a backward masking task of natural scene categorization. The behavioral results showed that correct classification was higher for line-drawings than for color photographs when the SOA was 13ms, but lower when the SOA was longer. The ERP results revealed that most latencies of early components were shorter for the line-drawings than for the color photographs, and the latencies gradually increased with the SOA for the color photographs but not for the line-drawings. The results provide new evidence that edge-based information is the primary determinant of natural scene categorization, receiving priority processing; by contrast, surface information takes longer to facilitate natural scene categorization

A Tutorial on Coding Methods for DNA-based Molecular Communications and Storage

Exponential increase of data has motivated advances of data storage technologies. As a promising storage media, DeoxyriboNucleic Acid (DNA) storage provides a much higher data density and superior durability, compared with state-of-the-art media. In this paper, we provide a tutorial on DNA storage and its role in molecular communications. Firstly, we introduce fundamentals of DNA-based molecular communications and storage (MCS), discussing the basic process of performing DNA storage in MCS. Furthermore, we provide tutorials on how conventional coding schemes that are used in wireless communications can be applied to DNA-based MCS, along with numerical results. Finally, promising research directions on DNA-based data storage in molecular communications are introduced and discussed in this paper