How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers

As a booming research area in the past decade, deep learning technologies have been driven by big data collected and processed on an unprecedented scale. However, privacy concerns arise due to the potential leakage of sensitive information from the training data. Recent research has revealed that deep learning models are vulnerable to various privacy attacks, including membership inference attacks, attribute inference attacks, and gradient inversion attacks. Notably, the efficacy of these attacks varies from model to model. In this paper, we answer a fundamental question: Does model architecture affect model privacy? By investigating representative model architectures from CNNs to Transformers, we demonstrate that Transformers generally exhibit higher vulnerability to privacy attacks compared to CNNs. Additionally, We identify the micro design of activation layers, stem layers, and LN layers, as major factors contributing to the resilience of CNNs against privacy attacks, while the presence of attention modules is another main factor that exacerbates the privacy vulnerability of Transformers. Our discovery reveals valuable insights for deep learning models to defend against privacy attacks and inspires the research community to develop privacy-friendly model architectures.Comment: Under revie

Genomic and Transcriptomic Evidence for Carbohydrate Consumption among Microorganisms in a Cold Seep Brine Pool

The detailed lifestyle of microorganisms in deep-sea brine environments remains largely unexplored. Using a carefully calibrated genome binning approach, we reconstructed partial to nearly-complete genomes of 51 microorganisms in biofilms from the Thuwal cold seep brine pool of the Red Sea. The recovered metagenome-assembled genomes (MAGs) belong to six different phyla: Actinobacteria, Proteobacteria, Candidatus Cloacimonetes, Candidatus Marinimicrobia, Bathyarchaeota and Thaumarchaeota. By comparison with close relatives of these microorganisms, we identified a number of unique genes associated with organic carbon metabolism and energy generation. These genes included various glycoside hydrolases, nitrate and sulfate reductases, putative bacterial microcompartment biosynthetic clusters (BMC), and F420H2 dehydrogenases. Phylogenetic analysis suggested that the acquisition of these genes probably occurred through horizontal gene transfer (HGT). Metatranscriptomics illustrated that glycoside hydrolases are among the most highly expressed genes. Our results suggest that the microbial inhabitants are well adapted to this brine environment, and anaerobic carbohydrate consumption mediated by glycoside hydrolases and electron transport systems (ETSs) is a dominant process performed by microorganisms from various phyla within this ecosystem

Algorithms for Computing Wiener Indices of Acyclic and Unicyclic Graphs

Let $G=(V(G),E(G))$ be a molecular graph, where $V(G)$ and $E(G)$ are the sets of vertices (atoms) and edges (bonds). A topological index of a molecular graph is a numerical quantity which helps to predict the chemical/physical properties of the molecules. The Wiener, Wiener polarity and the terminal Wiener indices are the distance based topological indices. In this paper, we described a linear time algorithm {\bf(LTA)} that computes the Wiener index for acyclic graphs and extended this algorithm for unicyclic graphs. The same algorithms are modified to compute the terminal Wiener index and the Wiener polarity index. All these algorithms compute the indices in time $O(n)$

Transcriptome Profiling of the Whitefly Bemisia tabaci MED in Response to Single Infection of Tomato yellow leaf curl virus, Tomato chlorosis virus, and Their Co-infection

Tomato yellow leaf curl virus (TYLCV) and Tomato chlorosis virus (ToCV) are two of the most devastating cultivated tomato viruses, causing significant crop losses worldwide. As the vector of both TYLCV and ToCV, the whitefly Bemisia tabaci Mediterranean (MED) is mainly responsible for the rapid spread and mixed infection of TYLCV and ToCV in China. However, little is known concerning B. tabaci MED's molecular response to TYLCV and ToCV infection or their co-infection. We determined the transcriptional responses of the whitefly MED to TYLCV infection, ToCV infection, and TYLCV&ToCV co-infection using Illumina sequencing. In all, 78, 221, and 60 differentially expressed genes (DEGs) were identified in TYLCV-infected, ToCV-infected, and TYLCV&ToCV co-infected whiteflies, respectively, compared with non-viruliferous whiteflies. Differentially regulated genes were sorted according to their roles in detoxification, stress response, immune response, transport, primary metabolism, cell function, and total fitness in whiteflies after feeding on virus-infected tomato plants. Alterations in the transcription profiles of genes involved in transport and energy metabolism occurred between TYLCV&ToCV co-infection and single infection with TYLCV or ToCV; this may be associated with the adaptation of the insect vector upon co-infection of the two viruses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses demonstrated that the single infection with TYLCV or ToCV and the TYLCV&ToCV co-infection could perturb metabolic processes and metabolic pathways. Taken together, our results provide basis for further exploration of the molecular mechanisms of the response to TYLCV, ToCV single infection, and TYLCV&ToCV co-infection in B. tabaci MED, which will add to our knowledge of the interactions between plant viruses and insect vectors

Note on the Algebra of Screening Currents for the Quantum Deformed W-Algebra

With slight modifications in the zero modes contributions, the positive and negative screening currents for the quantum deformed W-algebra W_{q,p}(g) can be put together to form a single algebra which can be regarded as an elliptic deformation of the universal enveloping algebra of \hat{g}, where g is any classical simply-laced Lie algebra.Comment: LaTeX file, 9 pages. Errors in Serre relation corrected. Two references to Awata,H. et al adde

A Reconfigurable Active Huygens' Metalens

Metasurfaces enable a new paradigm of controlling electromagnetic waves by manipulating subwavelength artificial structures within just a fraction of wavelength. Despite the rapid growth, simultaneously achieving low-dimensionality, high transmission efficiency, real-time continuous reconfigurability, and a wide variety of re-programmable functions are still very challenging, forcing researchers to realize just one or few of the aforementioned features in one design. In this study, we report a subwavelength reconfigurable Huygens' metasurface realized by loading it with controllable active elements. Our proposed design provides a unified solution to the aforementioned challenges of real-time local reconfigurability of efficient Huygens' metasurfaces. As one exemplary demonstration, we experimentally realized a reconfigurable metalens at the microwave frequencies which, to our best knowledge, demonstrates for the first time that multiple and complex focal spots can be controlled simultaneously at distinct spatial positions and re-programmable in any desired fashion, with fast response time and high efficiency. The presented active Huygens' metalens may offer unprecedented potentials for real-time, fast, and sophisticated electromagnetic wave manipulation such as dynamic holography, focusing, beam shaping/steering, imaging and active emission control.Comment: 20 pages, 4 figures, accepted for publication in Advanced Material

Diagnostic accuracy and reproducibility of optical flow ratio for functional evaluation of coronary stenosis in a prospective series

Background: Evaluating prospectively the feasibility, accuracy and reproducibility of optical flow ratio (OFR), a novel method of computational physiology based on optical coherence tomography (OCT).Methods and results: Sixty consecutive patients (76 vessels) underwent prospectively OCT, angiography- based quantitative flow ratio (QFR) and fractional flow ratio (FFR). OFR was computed offline in a central core-lab by analysts blinded to FFR. OFR was feasible in 98.7% of the lesions and showed excellent agreement with FFR (ICCa = 0.83, r = 0.83, slope = 0.80, intercept = 0.17, kappa = 0.84). The area under curve to predict an FFR ≤ 0.80 was 0.95, higher than for QFR (0.91, p = 0.115) and for minimal lumen area (0.64, p < 0.001). Diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio were 93%, 92%, 93%, 88%, 96%, 13.8, 0.1, respectively. Median time to obtain OFR was 1.07 (IQR: 0.98–1.16) min, with excellent intraobserver and interobserver reproducibility (0.97 and 0.95, respectively). Pullback speed had negligible impact on OFR, provided the same coronary segment were imaged (ICCa = 0.90, kappa = 0.697).Conclusions: The prospective computation of OFR is feasible and reproducible in a real-world series,resulting in excellent agreement with FFR, superior to other image-based methods