Role of crystal-field-splitting and longe-range-hoppings on superconducting pairing symmetry of La3_3Ni2_2O7_7

We study the bilayer two-orbital model for superconducting pairing symmetry of La$_3$Ni$_2$O$_7$ under pressure. By combining density-functional-theory (DFT), maximally-localized-Wannier-function, and linearized Eliashberg equation with random-phase-approximation, we find that the superconducting pairing symmetry of La$_3$Ni$_2$O$_7$ is robustly $d_{xy}$ if its DFT band structure is accurately reproduced in the downfolded model. We further show that fine-tuning of crystal-field-splitting between two Ni-$e_g$ orbitals qualitatively affects superconducting pairing symmetry of the bilayer two-orbital model, which changes from $d_{xy}$ to $s_{\pm}$ as the crystal-field-splitting exceeds a critical value. When the model only includes nearest-neighbor and second-nearest-neighbor hoppings, the crystal-field-splitting obtained by fitting to the DFT band structure is larger than the critical value and thus leads to $s_{\pm}$ superconducting pairing symmetry. When all nonzero long-range-hoppings are also included in the model, the fitted crystal-field-splitting is reduced and smaller than the critical value, which makes $d_{xy}$ superconducting pairing symmetry more favorable than $s_{\pm}$ symmetry. Our work demonstrates that in downfolded effective models, the details of band structure can play a crucial role in determining pairing symmetry in multi-orbital unconventional superconductors (such as La$_3$Ni$_2$O$_7$).Comment: 11 pages and 4 figure

Identifiability and Identification of Trace Continuous Pollutant Source

Accidental pollution events often threaten people’s health and lives, and a pollutant source is very necessary so that prompt remedial actions can be taken. In this paper, a trace continuous pollutant source identification method is developed to identify a sudden continuous emission pollutant source in an enclosed space. The location probability model is set up firstly, and then the identification method is realized by searching a global optimal objective value of the location probability. In order to discuss the identifiability performance of the presented method, a conception of a synergy degree of velocity fields is presented in order to quantitatively analyze the impact of velocity field on the identification performance. Based on this conception, some simulation cases were conducted. The application conditions of this method are obtained according to the simulation studies. In order to verify the presented method, we designed an experiment and identified an unknown source appearing in the experimental space. The result showed that the method can identify a sudden trace continuous source when the studied situation satisfies the application conditions

An Electronic Origin of Charge Order in Infinite-Layer Nickelates.

A charge order (CO) with a wavevector [Formula: see text] is observed in infinite-layer nickelates. Here we use first-principles calculations to demonstrate a charge-transfer-driven CO mechanism in infinite-layer nickelates, which leads to a characteristic Ni1+-Ni2+-Ni1+ stripe state. For every three Ni atoms, due to the presence of near-Fermi-level conduction bands, Hubbard interaction on Ni-d orbitals transfers electrons on one Ni atom to conduction bands and leaves electrons on the other two Ni atoms to become more localized. We further derive a low-energy effective model to elucidate that the CO state arises from a delicate competition between Hubbard interaction on Ni-d orbitals and charge transfer energy between Ni-d orbitals and conduction bands. With physically reasonable parameters, [Formula: see text] CO state is more stable than uniform paramagnetic state and usual checkerboard antiferromagnetic state. Our work highlights the multi-band nature of infinite-layer nickelates, which leads to some distinctive correlated properties that are not found in cuprates

Flexible Differentially Private Vertical Federated Learning with Adaptive Feature Embeddings

The emergence of vertical federated learning (VFL) has stimulated concerns about the imperfection in privacy protection, as shared feature embeddings may reveal sensitive information under privacy attacks. This paper studies the delicate equilibrium between data privacy and task utility goals of VFL under differential privacy (DP). To address the generality issue of prior arts, this paper advocates a flexible and generic approach that decouples the two goals and addresses them successively. Specifically, we initially derive a rigorous privacy guarantee by applying norm clipping on shared feature embeddings, which is applicable across various datasets and models. Subsequently, we demonstrate that task utility can be optimized via adaptive adjustments on the scale and distribution of feature embeddings in an accuracy-appreciative way, without compromising established DP mechanisms. We concretize our observation into the proposed VFL-AFE framework, which exhibits effectiveness against privacy attacks and the capacity to retain favorable task utility, as substantiated by extensive experiments

FERM domain-containing unconventional myosin VIIA interacts with integrin β5 subunit and regulates αvβ5-mediated cell adhesion and migration

AbstractUnconventional myosin VIIA (Myo7a) has been known to associate with hereditary deafness. Here we present a novel function of Myo7a by identifying that Myo7a directly interacts with integrin β5 subunit and regulates cell adhesion and motility in an integrin-dependent manner. We found that Myo7a bound to the cytoplasmic tail of integrin β5. Further, we pinpointed an integrin-binding domain at F3 of the first FERM domain and F1 of the second FERM domain. Functionally, Myo7a-induced cell adhesion and migration were mediated by integrin αvβ5. These findings indicated that Myo7a interacts with integrin β5 and selectively promotes integrin αvβ5-mediated cell migration

Transcription of AAT•ATT Triplet Repeats in Escherichia coli Is Silenced by H-NS and IS1E Transposition

The trinucleotide repeats AAT•ATT are simple DNA sequences that potentially form different types of non-B DNA secondary structures and cause genomic instabilities in vivo.The molecular mechanism underlying the maintenance of a 24-triplet AAT•ATT repeat was examined in E. coli by cloning the repeats into the EcoRI site in plasmid pUC18 and into the attB site on the E. coli genome. Either the AAT or the ATT strand acted as lagging strand template in a replication fork. Propagations of the repeats in either orientation on plasmids did not affect colony morphology when triplet repeat transcription using the lacZ promoter was repressed either by supplementing LacI(Q)in trans or by adding glucose into the medium. In contrast, transparent colonies were formed by inducing transcription of the repeats, suggesting that transcription of AAT•ATT repeats was toxic to cell growth. Meanwhile, significant IS1E transposition events were observed both into the triplet repeats region proximal to the promoter side, the promoter region of the lacZ gene, and into the AAT•ATT region itself. Transposition reversed the transparent colony phenotype back into healthy, convex colonies. In contrast, transcription of an 8-triplet AAT•ATT repeat in either orientation on plasmids did not produce significant changes in cell morphology and did not promote IS1E transposition events. We further found that a role of IS1E transposition into plasmids was to inhibit transcription through the repeats, which was influenced by the presence of the H-NS protein, but not of its paralogue StpA.Our findings thus suggest that the longer AAT•ATT triplet repeats in E. coli become vulnerable after transcription. H-NS and its facilitated IS1E transposition can silence long triplet repeats transcription and preserve cell growth and survival

DuetFace: Collaborative Privacy-Preserving Face Recognition via Channel Splitting in the Frequency Domain

With the wide application of face recognition systems, there is rising concern that original face images could be exposed to malicious intents and consequently cause personal privacy breaches. This paper presents DuetFace, a novel privacy-preserving face recognition method that employs collaborative inference in the frequency domain. Starting from a counterintuitive discovery that face recognition can achieve surprisingly good performance with only visually indistinguishable high-frequency channels, this method designs a credible split of frequency channels by their cruciality for visualization and operates the server-side model on non-crucial channels. However, the model degrades in its attention to facial features due to the missing visual information. To compensate, the method introduces a plug-in interactive block to allow attention transfer from the client-side by producing a feature mask. The mask is further refined by deriving and overlaying a facial region of interest (ROI). Extensive experiments on multiple datasets validate the effectiveness of the proposed method in protecting face images from undesired visual inspection, reconstruction, and identification while maintaining high task availability and performance. Results show that the proposed method achieves a comparable recognition accuracy and computation cost to the unprotected ArcFace and outperforms the state-of-the-art privacy-preserving methods. The source code is available at https://github.com/Tencent/TFace/tree/master/recognition/tasks/duetface.Comment: Accepted to ACM Multimedia 202

Approach to Identifying Raindrop Vibration Signal Detected by Optical Fiber

Optical Fiber Vibration pre-Warning System (OFVWS) is widely applied to pipeline transportation, defense boundary and military base. One of its key technologies is signal feature extraction and vibration source identification. However, some harmless vibration signals often affect the reliability of this identification process due to the false alarms. Therefore, it is very important to identify various harmless vibration signals effectively. In this paper, we analyze the energy distribution feature of nature raindrop vibration signal detected by optical fiber. Based on this analysis, we develop an energy information entropy model and an approach to identify the harmless raindrop vibration signal. Study shows that the nature raindrop vibration signal can be detected and identified automatically by extracting the energy information entropy value and combining with the statistical detection method. The field tests result also showed that this approach based on energy information entropy model is able to effectively identify harmless raindrop vibration signal. Its identification probability is high and its false alarm and false recognition probability is low, hence the working performance of the OFVWS can be improved by using the presented approach