Projection-Free Methods for Stochastic Simple Bilevel Optimization with Convex Lower-level Problem

In this paper, we study a class of stochastic bilevel optimization problems, also known as stochastic simple bilevel optimization, where we minimize a smooth stochastic objective function over the optimal solution set of another stochastic convex optimization problem. We introduce novel stochastic bilevel optimization methods that locally approximate the solution set of the lower-level problem via a stochastic cutting plane, and then run a conditional gradient update with variance reduction techniques to control the error induced by using stochastic gradients. For the case that the upper-level function is convex, our method requires $\tilde{\mathcal{O}}(\max\{1/\epsilon_f^{2},1/\epsilon_g^{2}\})$ stochastic oracle queries to obtain a solution that is $\epsilon_f$-optimal for the upper-level and $\epsilon_g$-optimal for the lower-level. This guarantee improves the previous best-known complexity of $\mathcal{O}(\max\{1/\epsilon_f^{4},1/\epsilon_g^{4}\})$. Moreover, for the case that the upper-level function is non-convex, our method requires at most $\tilde{\mathcal{O}}(\max\{1/\epsilon_f^{3},1/\epsilon_g^{3}\})$ stochastic oracle queries to find an $(\epsilon_f, \epsilon_g)$-stationary point. In the finite-sum setting, we show that the number of stochastic oracle calls required by our method are $\tilde{\mathcal{O}}(\sqrt{n}/\epsilon)$ and $\tilde{\mathcal{O}}(\sqrt{n}/\epsilon^{2})$ for the convex and non-convex settings, respectively, where $\epsilon=\min \{\epsilon_f,\epsilon_g\}$

Internal Wasserstein Distance for Adversarial Attack and Defense

Deep neural networks (DNNs) are vulnerable to adversarial examples that can trigger misclassification of DNNs but may be imperceptible to human perception. Adversarial attack has been an important way to evaluate the robustness of DNNs. Existing attack methods on the construction of adversarial examples use such $\ell_p$ distance as a similarity metric to perturb samples. However, this kind of metric is incompatible with the underlying real-world image formation and human visual perception. In this paper, we first propose an internal Wasserstein distance (IWD) to measure image similarity between a sample and its adversarial example. We apply IWD to perform adversarial attack and defense. Specifically, we develop a novel attack method by capturing the distribution of patches in original samples. In this case, our approach is able to generate semantically similar but diverse adversarial examples that are more difficult to defend by existing defense methods. Relying on IWD, we also build a new defense method that seeks to learn robust models to defend against unseen adversarial examples. We provide both thorough theoretical and empirical evidence to support our methods

LWS: A Framework for Log-based Workload Simulation in Session-based SUT

Microservice-based applications and cloud-native systems have been widely applied in large IT enterprises. The operation and management of microservice-based applications and cloud-native systems have become the focus of research. Essential and real workloads are the premise and basis of prominent research topics including performance testing, dynamic resource provisioning and scheduling, and AIOps. Due to the privacy restriction, the complexity and variety of workloads, and the requirements for reasonable intervention, it is difficult to copy or generate real workloads directly. In this paper, we formulate the task of workload simulation and propose a framework for Log-based Workload Simulation (LWS) in session-based application systems. First, LWS collects session logs and transforms them into grouped and well-organized sessions. Then LWS extracts the user behavior abstraction based on a relational model and the intervenable workload intensity by three methods from different perspectives. LWS combines the user behavior abstraction and the workload intensity for simulated workload generation and designs a domain-specific language for better execution. The experimental evaluation is performed on an open-source cloud-native application and a public real-world e-commerce workload. The experimental results show that the simulated workload generated by LWS is effective and intervenable

Non-invasive methods to evaluate liver fibrosis in patients with non-alcoholic fatty liver disease

Non-alcoholic Fatty Liver Disease (NAFLD) is a chronic liver disease that is strongly related to insulin resistance and metabolic syndrome, and it has become the most common liver disorder in developed countries. NAFLD embraces the full pathological process of three conditions: steatosis, non-alcoholic steatohepatitis, and finally, cirrhosis. As NAFLD progresses, symptoms will become increasingly severe as fibrosis develops. Therefore, evaluating the fibrosis stage is crucial for patients with NAFLD. A liver biopsy is currently considered the gold standard for staging fibrosis. However, due to the limitations of liver biopsy, non-invasive alternatives were extensively studied and validated in patients with NAFLD. The advantages of non-invasive methods include their high safety and convenience compared with other invasive approaches. This review introduces the non-invasive methods, summarizes their benefits and limitations, and assesses their diagnostic performance for NAFLD-induced fibrosis

The expression and role of protein kinase C (PKC) epsilon in clear cell renal cell carcinoma

Protein kinase C epsilon (PKCε), an oncogene overexpressed in several human cancers, is involved in cell proliferation, migration, invasion, and survival. However, its roles in clear cell renal cell carcinoma (RCC) are unclear. This study aimed to investigate the functions of PKCε in RCC, especially in clear cell RCC, to determine the possibility of using it as a therapeutic target. By immunohistochemistry, we found that the expression of PKCε was up-regulated in RCCs and was associated with tumor Fuhrman grade and T stage in clear cell RCCs. Clone formation, wound healing, and Borden assays showed that down-regulating PKCε by RNA interference resulted in inhibition of the growth, migration, and invasion of clear cell RCC cell line 769P and, more importantly, sensitized cells to chemotherapeutic drugs as indicated by enhanced activity of caspase-3 in PKCε siRNA-transfected cells. These results indicate that the overexpression of PKCε is associated with an aggressive phenotype of clear cell RCC and may be a potential therapeutic target for this disease

Transparent Power-Generating Windows Based on Solar-Thermal-Electric Conversion

Zhang Q, Huang A, Ai X, et al. Transparent Power-Generating Windows Based on Solar-Thermal-Electric Conversion. Advanced Energy Materials . 2021: 2101213.Integrating transparent solar-harvesting systems into windows can provide renewable on-site energy supply without altering building aesthetics or imposing further design constraints. Transparent photovoltaics have shown great potential, but the increased transparency comes at the expense of reduced power-conversion efficiency. Here, a new technology that overcomes this limitation by combining solar-thermal-electric conversion with a material's wavelength-selective absorption is presented. A wavelength-selective film consisting of Cs0.33WO3 and resin facilitates high visible-light transmittance (up to 88%) and outstanding ultraviolet and infrared absorbance, thereby converting absorbed light into heat without sacrificing transparency. A prototype that couples the film with thermoelectric power generation produces an extraordinary output voltage of approximate to 4 V within an area of 0.01 m(2) exposed to sunshine. Further optimization design and experimental verification demonstrate high conversion efficiency comparable to state-of-the-art transparent photovoltaics, enriching the library of on-site energy-saving and transparent power generation

Optimal Regimens and Cutoff Evaluation of Tildipirosin Against Pasteurella multocida

Pasteurella multocida (PM) can invade the upper respiratory tract of the body and cause death and high morbidity. Tildipirosin, a new 16-membered-ring macrolide antimicrobial, has been recommended for the treatment of respiratory diseases. The objective of this research was to improve the dose regimes of tildipirosin to PM for reducing the macrolides resistance development with the pharmacokinetic/pharmacodynamic (PK/PD) modeling approach and to establish an alternate cutoff for tildipirosin against PM. A single dose (4 mg/kg body weight) of tildipirosin was administered via intramuscular (i.m.) and intravenous (i.v.) injection to the pigs. The minimum inhibitory concentration (MIC) values of clinical isolates (112) were measured in the range of 0.0625–32 μg/ml, and the MIC50 and MIC90 values were 0.5 and 2 μg/ml, respectively. The MIC of the selected PM04 was 2 and 0.5 μg/ml in the tryptic soy broth (TSB) and serum, respectively. The main pharmacokinetic (PK) parameters including the area under the curve at 24 h (AUC24 h), AUC, terminal half-life (T1/2), the time to peak concentration (Tmax), peak concentration (Cmax), relative total systemic clearance (CLb), and the last mean residence time (MRTlast) were calculated to be 7.10, 7.94 μg∗h/ml, 24.02, NA h, NA μg/ml, 0.46 L/h∗kg, 8.06 h and 3.94, 6.79 μg∗h/ml, 44.04, 0.25 h, 0.98 μg/ml, 0.43 L/h∗kg, 22.85 h after i.v. and i.m. induction, respectively. Moreover, the bioavailability of i.m. route was 85.5%, and the unbinding of tildipirosin to serum protein was 78%. The parameters AUC24 h/MIC in serum for bacteriostatic, bactericidal, and elimination activities were calculated as 18.91, 29.13, and 34.03 h based on the inhibitory sigmoid Emax modeling. According to the Monte Carlo simulation, the optimum doses for bacteriostatic, bactericidal, and elimination activities were 6.10, 9.41, and 10.96 mg/kg for 50% target and 7.86, 12.17, and 14.57 mg/kg for 90% target, respectively. The epidemiological cutoff value (ECV) was calculated to be 4 μg/ml which could cover 95% wild-type clinical isolates distribution. The PK-PD cutoff (COPD) was analyzed to be 0.25 μg/ml in vitro for tildipirosin against PM based on the Monte Carlo simulation. Compared with these two cutoff values, the finial susceptible breakpoint was defined as 4 μg/ml. The data presented now provides the optimal regimens (12.17 mg/kg) and susceptible breakpoint (4 μg/ml) for clinical use, but these predicted data should be validated in the clinical practice

Gut microbiome-based noninvasive diagnostic model to predict acute coronary syndromes

BackgroundPrevious studies have shown that alterations in the gut microbiota are closely associated with Acute Coronary Syndrome (ACS) development. However, the value of gut microbiota for early diagnosis of ACS remains understudied.MethodsWe recruited 66 volunteers, including 29 patients with a first diagnosis of ACS and 37 healthy volunteers during the same period, collected their fecal samples, and sequenced the V4 region of the 16S rRNA gene. Functional prediction of the microbiota was performed using PICRUSt2. Subsequently, we constructed a nomogram and corresponding webpage based on microbial markers to assist in the diagnosis of ACS. The diagnostic performance and usefulness of the model were analyzed using boostrap internal validation, calibration curves, and decision curve analysis (DCA).ResultsCompared to that of healthy controls, the diversity and composition of microbial community of patients with ACS was markedly abnormal. Potentially pathogenic genera such as Streptococcus and Acinetobacter were significantly increased in the ACS group, whereas certain SCFA-producing genera such as Blautia and Agathobacter were depleted. In addition, in the correlation analysis with clinical indicators, the microbiota was observed to be associated with the level of inflammation and severity of coronary atherosclerosis. Finally, a diagnostic model for ACS based on gut microbiota and clinical variables was developed with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.963 (95% CI: 0.925–1) and an AUC value of 0.948 (95% CI: 0.549–0.641) for bootstrap internal validation. The calibration curves of the model show good consistency between the actual and predicted probabilities. The DCA showed that the model had a high net clinical benefit for clinical applications.ConclusionOur study is the first to characterize the composition and function of the gut microbiota in patients with ACS and healthy populations in Southwest China and demonstrates the potential effect of the microbiota as a non-invasive marker for the early diagnosis of ACS

Distribution and Supply of Antimony Resources in China and Abroad and Development Status of Antimony Industry Chain

Antimony is an important raw material for industrial production which is widely used and irreplaceable. With the development of lead battery, flame retardant, alloy, semiconductor, catalyst, microcrystalline glass, chemical, military and other industries, coupled with the impact of the new crown epidemic on the global social and economic and international environmental uncertainty, strategic position of antimonyis highlighted. This paper systematically summarizes the distribution and supply, industry chain status and future development trend of antimony in China and abroad. The research shows that China's antimony resources occupy a dominant position, China's antimony has high production and consumption, the proportion of high-end products in China's antimony industry chain is not high, the demand for antimony resources has a strong growth space, and worldwide demand for antimony will remain stable over the next decade. Suggestions on strengthening domestic antimony prospecting, strengthening foreign resources development, increasing technology research and development, promoting green development of antimony industry, trengthening industrial chain integration, promoting high-quality development of application end, formulating strategic reserve system, implementing strategic reserve of antimony resources are put forward