Generative Autoencoders as Watermark Attackers: Analyses of Vulnerabilities and Threats

Invisible watermarks safeguard images' copyrights by embedding hidden messages detectable by owners. It also prevents people from misusing images, especially those generated by AI models. Malicious adversaries can violate these rights by removing the watermarks. In order to remove watermarks without damaging the visual quality, the adversary needs to erase them while retaining the essential information in the image. This is analogous to the encoding and decoding process of generative autoencoders, especially variational autoencoders (VAEs) and diffusion models. We propose a framework using generative autoencoders to remove invisible watermarks and test it using VAEs and diffusions. Our results reveal that, even without specific training, off-the-shelf Stable Diffusion effectively removes most watermarks, surpassing all current attackers. The result underscores the vulnerabilities in existing watermarking schemes and calls for more robust methods for copyright protection

Optimize Individualized Energy Delivery for Septic Patients Using Predictive Deep Learning Models: A Real World Study

Background and Objectives: We aim to establish deep learning models to optimize the individualized energy delivery for septic patients. Methods and Study Design: We conducted a study of adult septic patients in Intensive Care Unit (ICU), collecting 47 indicators for 14 days. After data cleaning and preprocessing, we used stats to explore energy delivery in deceased and surviving patients. We filtered out nutrition-related features and divided the data into three metabolic phases: acute early, acute late, and rehabilitation. Models were built using data before September 2020 and validated on the rest. We then established optimal energy target models for each phase using deep learning. Results: A total of 277 patients and 3115 data were included in this study. The models indicated that the optimal energy targets in the three phases were 900kcal/d, 2300kcal/d, and 2000kcal/d, respectively. Excessive energy intake increased mortality rapidly in the early period of the acute phase. Insufficient energy in the late period of the acute phase significantly raised the mortality of septic patients. For the rehabilitation phase, too much or too little energy delivery both associated with high mortality. Conclusion: Our study established time-series prediction models for septic patients to optimize energy delivery in the ICU. This approach indicated the feasibility of developing nutritional tools for critically ill patients. We recommended permissive underfeeding only in the early acute phase. Later, increased energy intake may improve survival and settle energy debts caused by underfeeding

Analysis and Performance Evaluation of a Novel Adjustable Speed Drive with a Homopolar-Type Rotor

The use of a magnetic adjustable speed drive is a popular choice in industrial settings due to its efficient operation, vibration isolation, low maintenance, and overload protection. Most conventional magnetic adjustable speed drives use various forms of the permanent magnets (PMs). Due to the PMs, this type of machine has continuous free-wheeling losses in the form of hysteresis and induced eddy currents. In recent years, the homopolar-type rotor has been widely used in high-speed machines, superconducting machines, and in the application of flywheel energy storage. This study proposes a new application of the homopolar-type rotor. A novel adjustable speed drive with a homopolar-type rotor (HTR-ASD), which has obvious advantages (no brush, no permanent magnet, and no mechanical flux regulation device), is designed and analyzed in this study. Its speed and torque can be adjusted only by adjusting the excitation current. Firstly, in this study, the structure, operation principles, and flux-modulated mechanism of the HTR-ASD are studied. The homopolar-type rotor has a special three-dimensional magnetic circuit structure with the same pole. The 3D-FEM is usually used to calculate its parameters, which is time consuming. In this study, an analytical method is developed to solve this issue. To analytically calculate the torque characteristics, the air gap magnetic flux density, and the winding inductance parameter, the equivalent circuit and the air gap permeance are researched to simplify the analysis. Then, the key parameters of the HTR-ASD are calculated. Finally, the performance of the HTR-ASD is comparatively studied using the analytical method and finite element method, and a comparison of the results is carried out. The comparison indicates that the analytical method is in good agreement with simulation results, and that it is very helpful for designing homopolar-type rotor machines. According to the analysis, the proposed adjustable speed drive displays a great performance in relation to the operating characteristics of a flexible mechanical speed drive

Analysis and Performance Evaluation of a Novel Adjustable Speed Drive with a Homopolar-Type Rotor

The use of a magnetic adjustable speed drive is a popular choice in industrial settings due to its efficient operation, vibration isolation, low maintenance, and overload protection. Most conventional magnetic adjustable speed drives use various forms of the permanent magnets (PMs). Due to the PMs, this type of machine has continuous free-wheeling losses in the form of hysteresis and induced eddy currents. In recent years, the homopolar-type rotor has been widely used in high-speed machines, superconducting machines, and in the application of flywheel energy storage. This study proposes a new application of the homopolar-type rotor. A novel adjustable speed drive with a homopolar-type rotor (HTR-ASD), which has obvious advantages (no brush, no permanent magnet, and no mechanical flux regulation device), is designed and analyzed in this study. Its speed and torque can be adjusted only by adjusting the excitation current. Firstly, in this study, the structure, operation principles, and flux-modulated mechanism of the HTR-ASD are studied. The homopolar-type rotor has a special three-dimensional magnetic circuit structure with the same pole. The 3D-FEM is usually used to calculate its parameters, which is time consuming. In this study, an analytical method is developed to solve this issue. To analytically calculate the torque characteristics, the air gap magnetic flux density, and the winding inductance parameter, the equivalent circuit and the air gap permeance are researched to simplify the analysis. Then, the key parameters of the HTR-ASD are calculated. Finally, the performance of the HTR-ASD is comparatively studied using the analytical method and finite element method, and a comparison of the results is carried out. The comparison indicates that the analytical method is in good agreement with simulation results, and that it is very helpful for designing homopolar-type rotor machines. According to the analysis, the proposed adjustable speed drive displays a great performance in relation to the operating characteristics of a flexible mechanical speed drive

Transmembrane protein 176B regulates amino acid metabolism through the PI3K-Akt-mTOR signaling pathway and promotes gastric cancer progression

Abstract Background The present study aimed to investigate the expression level, biological function, and underlying mechanism of transmembrane protein 176B (TMEM176B) in gastric cancer (GC). Methods TMEM176B expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting (WB). The function of TMEM176B was determined by various in vitro assays including colony formation, 5-ethynyl-2ʹ-deoxyuridine (EdU), Transwell, and flow cytometry. Bioinformatics techniques were then used to elucidate the signaling pathways associated with TMEM176B activity. Tumor formation experiments were conducted on nude mice for in vivo validation of the preceding findings. TMEM176B expression was cross-referenced to clinicopathological parameters and survival outcomes. Results It was observed that TMEM176B was overexpressed in GC cells and tissues. Targeted TMEM176B abrogation inhibited colony formation, proliferation, migration, and invasion but promoted apoptosis in GC cell lines while TMEM176B overexpression had the opposite effects. Subsequent experimental validation disclosed an association between TMEM176B and the phosphatidylinositol 3-carboxykinase (PI3K)-protein kinase B (Akt)-mammalian target of rapamycin (mTOR) signaling axis. Moreover, TMEM176B affects GC cancer progression by regulating asparagine synthetase (ASNS). The in vivo assays confirmed that TMEM176B is oncogenic and the clinical data revealed a connection between TMEM176B expression and the clinicopathological determinants of GC. Conclusion The foregoing results suggest that TMEM176B significantly promotes the development of gastric cancer and is an independent prognostic factor of it

Charged Particle (Negative Ion)-Based Cloud Seeding and Rain Enhancement Trial Design and Implementation

China has been suffering from water shortage for a long time. Weather modification and rainfall enhancement via cloud seeding has been proved to be effective to alleviate the problem. Current cloud seeding methods mostly rely on solid carbon dioxide and chemicals such as silver iodide and hygroscopic salts, which may have negative impacts on the environment and are expensive to operate. Lab experiments have proved the efficiency of ion-based cloud seeding compared with traditional methods. Moreover, it is also more environmentally friendly and more economical to operate at a large scale. Thus, it is necessary to carry out a field experiment to further investigate the characteristics and feasibility of the method. This paper provides the design and implementation of the ion-based cloud seeding and rain enhancement trial currently running in Northwest China. It introduces the basic principle of the trial and the devices developed for it, as well as the installation of the bases and the evaluation method design for the trial

DataSheet1_Identification pyroptosis-related gene signature to predict prognosis and associated regulation axis in colon cancer.docx

Background: Pyroptosis is an important component of the tumor microenvironment and associated with the occurrence and progression of cancer. As the expression of pyroptosis-related genes and its impact on the prognosis of colon cancer (CC) remains unclear, we constructed and validated a pyroptosis-related genes signature to predict the prognosis of patients with CC.Methods: Microarray datasets and the follow-up clinical information of CC patients were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases. Candidate genes were screened out for further analysis. Various methods were combined to construct a robust pyroptosis-related genes signature for predicting the prognosis of patients with CC. Based on the gene signature and clinical features, a decision tree and nomogram were developed to improve risk stratification and quantify risk assessment for individual patients.Results: The pyroptosis-related genes signature successfully discriminated CC patients with high-risk in the training cohorts. The prognostic value of this signature was further confirmed in independent validation cohort. Multivariable Cox regression and stratified survival analysis revealed this signature was an independent prognostic factor for CC patients. The decision tree identified risk subgroups powerfully, and the nomogram incorporating the gene signature and clinical risk factors performed well in the calibration plots.Conclusion: Pyroptosis-related genes signature was an independent prognostic factor, and can be used to predict the prognosis of patients with CC.</p