Gradient-based iterative parameter estimation for bilinear-in-parameter systems using the model decomposition technique

The parameter estimation issues of a block-oriented non-linear system that is bilinear in the parameters are studied, i.e. the bilinear-in-parameter system. Using the model decomposition technique, the bilinear-in-parameter model is decomposed into two fictitious submodels: one containing the unknown parameters in the non-linear block and the other containing the unknown parameters in the linear dynamic one and the noise model. Then a gradient-based iterative algorithm is proposed to estimate all the unknown parameters by formulating and minimising two criterion functions. The stochastic gradient algorithms are provided for comparison. The simulation results indicate that the proposed iterative algorithm can give higher parameter estimation accuracy than the stochastic gradient algorithms

Reduction in the Number of Fault Injections for Blind Fault Attack on SPN Block Ciphers

In 2014, a new fault analysis called blind fault attack (BFA) was proposed, in which attackers can only obtain the number of different faulty outputs without knowing the public data. The original BFA requires 480,000 fault injections to recover a 128-bit AES key. This work attempts to reduce the number of fault injections under the same attack assumptions. We analyze BFA from an information theoretical perspective and introduce a new probability-based distinguisher. Three approaches are proposed for different attack scenarios. The best one realized a 66.8% reduction of the number of fault injections on AES

A preliminary study of in vitro and in vivo synergistic effects of ciprofloxacin and D-tyrosine against Pseudomonas aeruginosa isolates

Purpose: To investigate the synergistic antimicrobial effects of ciprofloxacin and D-tyrosine against drug-resistant bacteria.Method: The antimicrobial effects of ciprofloxacin and D-tyrosine on clinical isolates of multidrugresistant (MDR) Pseudomonas aeruginosa (P. aeruginosa) no. 3556 were determined in vitro based on time-kill curve, and in vivo in P. aeruginosa-zebrafish infection model. Furthermore, 30 clinical isolates of multidrug-resistant P. aeruginosa were used in vitro to ascertain the synergistic effect of the two agents.Results: Combined use of ciprofloxacin and D-tyrosine produced synergistic effects against the clinical isolate of P. aeruginosa no. 3556 in vitro and in vivo. Synergism occurred in 96.67 % (95 % CI, range 83.33 - 99.41 %) of the clinical isolates, and ciprofloxacin dose was reduced in 90 % (95 % CI, range 74.38 - 96.54 %) of the clinical isolates in vitro.Conclusion: These preliminary results suggest that the combination of ciprofloxacin and D-tyrosine is a promising therapeutic strategy against MDR P. aeruginosa infections. Keywords: Ciprofloxacin, D-tyrosine, Synergistic, P. aeruginosa, Zebrafish infection model, Time-killing curv

Changes in clinical and CT manifestations related to liver abscesses in patients with vs. without basic diabetes mellitus before and after CT-guided interventional therapy: An observational study

Purpose: To explore differences in the changes of clinical and CT manifestations related to liver abscess before and after CT-guided interventional therapy between patients with and without Diabetes Mellitus (DM). Materials and methods: Fifty-eight consecutive patients with liver abscesses were retrospectively enrolled in this study. All patients underwent upper abdominal contrast-enhanced CT scans before and after CT-guided interventional therapy. They were divided into two groups including the DM group (n=30) and the Non-DM group (n=28) if the liver abscess occurred in patients with and without DM, respectively. The changes in the clinical and CT manifestations related to liver abscess after CT-guided interventional therapy in both groups were statistically analyzed. Results: After CT-guided interventional therapy, the length of hospital stay, white blood cell recovery time and drainage tube removal time in the DM group were longer than in the Non-DM group (all p-values < 0.05). The incidence of postoperative complications in the DM group was higher than in the Non-DM group (p < 0.05). As shown on CT, the postoperative reduced percentage of maximum diameter of abscess cavity and the reduction rate of edema band surrounding the liver abscess in the DM group were smaller than in the Non-DM group (both p-values < 0.05). The time intervals of the previous characteristic changes on CT before and after interventional therapy in the DM group were longer than in the Non-DM group (all p-values < 0.05). Conclusions: The liver abscesses patients with DM could not have a faster recovery and better therapeutic effect than those without DM after the CT-guided interventional therapy

Genomic instability, inflammatory signaling and response to cancer immunotherapy

Genomic and chromosomal instability are hallmarks of cancer and shape the genomic composition of cancer cells, thereby determining their behavior and response to treatment. Various genetic and epigenetic alterations in cancer have been linked to genomic instability, including DNA repair defects, oncogene-induced replication stress, and spindle assembly checkpoint malfunction. A consequence of genomic and chromosomal instability is the leakage of DNA from the nucleus into the cytoplasm, either directly or through the formation and subsequent rupture of micronuclei. Cytoplasmic DNA subsequently activates cytoplasmic DNA sensors, triggering downstream pathways, including a type I interferon response. This inflammatory signaling has pleiotropic effects, including enhanced anti-tumor immunity and potentially results in sensitization of cancer cells to immune checkpoint inhibitors. However, cancers frequently evolve mechanisms to avoid immune clearance, including suppression of inflammatory signaling. In this review, we summarize inflammatory signaling pathways induced by various sources of genomic instability, adaptation mechanisms that suppress inflammatory signaling, and implications for cancer immunotherapy

LivePhoto: Real Image Animation with Text-guided Motion Control

Despite the recent progress in text-to-video generation, existing studies usually overlook the issue that only spatial contents but not temporal motions in synthesized videos are under the control of text. Towards such a challenge, this work presents a practical system, named LivePhoto, which allows users to animate an image of their interest with text descriptions. We first establish a strong baseline that helps a well-learned text-to-image generator (i.e., Stable Diffusion) take an image as a further input. We then equip the improved generator with a motion module for temporal modeling and propose a carefully designed training pipeline to better link texts and motions. In particular, considering the facts that (1) text can only describe motions roughly (e.g., regardless of the moving speed) and (2) text may include both content and motion descriptions, we introduce a motion intensity estimation module as well as a text re-weighting module to reduce the ambiguity of text-to-motion mapping. Empirical evidence suggests that our approach is capable of well decoding motion-related textual instructions into videos, such as actions, camera movements, or even conjuring new contents from thin air (e.g., pouring water into an empty glass). Interestingly, thanks to the proposed intensity learning mechanism, our system offers users an additional control signal (i.e., the motion intensity) besides text for video customization.Comment: Project page: https://xavierchen34.github.io/LivePhoto-Page