LESS: Label-efficient Multi-scale Learning for Cytological Whole Slide Image Screening

In computational pathology, multiple instance learning (MIL) is widely used to circumvent the computational impasse in giga-pixel whole slide image (WSI) analysis. It usually consists of two stages: patch-level feature extraction and slide-level aggregation. Recently, pretrained models or self-supervised learning have been used to extract patch features, but they suffer from low effectiveness or inefficiency due to overlooking the task-specific supervision provided by slide labels. Here we propose a weakly-supervised Label-Efficient WSI Screening method, dubbed LESS, for cytological WSI analysis with only slide-level labels, which can be effectively applied to small datasets. First, we suggest using variational positive-unlabeled (VPU) learning to uncover hidden labels of both benign and malignant patches. We provide appropriate supervision by using slide-level labels to improve the learning of patch-level features. Next, we take into account the sparse and random arrangement of cells in cytological WSIs. To address this, we propose a strategy to crop patches at multiple scales and utilize a cross-attention vision transformer (CrossViT) to combine information from different scales for WSI classification. The combination of our two steps achieves task-alignment, improving effectiveness and efficiency. We validate the proposed label-efficient method on a urine cytology WSI dataset encompassing 130 samples (13,000 patches) and FNAC 2019 dataset with 212 samples (21,200 patches). The experiment shows that the proposed LESS reaches 84.79%, 85.43%, 91.79% and 78.30% on a urine cytology WSI dataset, and 96.88%, 96.86%, 98.95%, 97.06% on FNAC 2019 dataset in terms of accuracy, AUC, sensitivity and specificity. It outperforms state-of-the-art MIL methods on pathology WSIs and realizes automatic cytological WSI cancer screening.Comment: This paper was submitted to Medical Image Analysis. It is under revie

A Provably Secure Signature Scheme based on Factoring and Discrete Logarithms

To make users put much confidence in digital signatures, this paper proposes the first provably secure signature scheme based on both factoring and discrete logarithms. The new scheme incorporates both the Schnorr signature scheme and the PSS-Rabin signature scheme. Unless both the two cryptographic assumptions could be become solved simultaneously, anyone would not forge any signature. The proposed scheme is efficient since the computation requirement and the storage requirement are slightly larger than those for the Schnorr signature scheme and the PSS-Rabin signature scheme

Pollution and health risk assessment of heavy metals in soils of Guizhou, China

Mining of minerals in Guizhou, China, where it is enriched with reserves, may lead to soil contamination with heavy metals. We assessed the risk of eight typical heavy metals in Guizhou soils by collecting province-wide data available in the literature and using the geo-accumulation index method, the ecological risk assessment method, and the USEPA health risk assessment model. The concentrations of eight heavy metals, except for Pb and Cr, were above the background levels. Soil heavy metal pollution evaluation results showed that As, Cu, Zn, Pb, Cr, Cd, and Ni reached the pollution levels, while Hg fell into the category of moderate contamination. As, Cu, Zn, Pb, Cr, and Ni posed low potential ecological risk, while Cd and Hg demonstrated a considerable or a very high potential ecological risk. Totally, the integrated potential ecological risk was ranked “very high” . Regarding to health risk, the non-carcinogenic risks caused by heavy metals were insignificant, but the carcinogenic risk caused by As was significant. Consequently, there appeared serious soil contamination of Hg and As, with the latter also being the greatest potential risk to human health. Both Hg and As should stay at the highest priory for remediation efforts in Guizhou soils

Robust iterative learning control with quadratic performance index

In this paper, a robust iterative learning control (ILC) designed through a linear matrix inequality (LMI) approach is proposed first, based on the worst-case performance index with ellipsoidal uncertainty and polytopic uncertainty, respectively. Since the design based on worst-case performance index is too conservative, a novel ILC design based on nominal performance index is further proposed, and its robust convergence properties are proven. The latter can give better performance when the nominal model is close to the true process. Simulations have demonstrated the effectiveness and excellent performance of the proposed methods. © 2011 American Chemical Society

Optimal Iterative Learning Control Based on a Time-Parametrized Linear Time-Varying Model for Batch Processes

In this paper, an optimal iterative learning control (ILC) algorithm based on a time-parametrized linear time-varying (LTV) model for batch processes is proposed. Utilizing the repetitive nature of batch processes, a time-parametrized LTV model is used to represent the nonlinear behavior, with its consistence and variance properties established. Furthermore, an optimal ILC algorithm based on the time-parametrized LTV model is developed, and its convergence property is analyzed. Simulations have demonstrated the effectiveness and excellent performance of the proposed method

Effect of fly ash microsphere on the rheology and microstructure of alkali-activated fly ash/slag pastes

The highly viscous property of alkali silicate-activated cements is one of the critical challenges that hinder their wide application. The present study focuses on ameliorating the rheological performance of sodium silicate-activated fly ash/slag pastes by using fly ash microsphere (FAM), which are highly spherical particles collected from fly ash with electrostatic adsorption classification technology. The FAM particles work as ‘ball-bearings’ in the pastes to reduce the internal friction between fly ash and slag grains, and meanwhile mitigate the agglomeration of flocs and fragmentation to release the locked water. The interrelationship between the FAM particle geometry and plastic viscosity of the paste is well described by the Krieger-Dougherty equation, which supports the proposed mechanisms of ‘ball-bearings’ effects. FAM can work as an inorganic dispersing agent to improve the workability of alkali-activated cement products for a variety of application aspects

Re-examining the suitability of high magnesium nickel slag as precursors for alkali-activated materials

High-magnesium nickel slag (HMNS) has shown the potential as precursor in the production of alkali-activated materials (AAMs). This study re-examines the suitability of HMNS by comparatively investigating the reactivity of four different sourced HMNSs and analyzing impacts of the magnesium sources in HMNS on the reaction products of AAMs. Results show that the cooling way plays a determinant role of their mineral compositions. The air-cooled HMNSs contain only ∼30 wt% glassy phases, while the water-quenched one is dominantly amorphous. The reactivity of HMNS determined by the dissolution tests correlates well with the calculated depolymerization degree of glasses. HMNS indeed exhibits lower reactivity than the precursors commonly used for AAMs production, such as fly ash and blast furnace slag. In the HMNS samples in the sodium hydroxide solution, M-S-H, C-S-H and hydrotalcite are the main reaction products. The OH− ions in the aqueous system react with Mg2+ to form the brucite, indicating that there is still a volume expansion risk if sodium hydroxide is used as activator. In comparison, only M-S-H and C-S-H gels are coexistent in the samples leached in the sodium silicate solution, because of the kinetic hindrance of soluble silicates for the formation of hydrotalcite and brucite

Sirolimus-tacrolimus Combination Immunosuppression

A series of 32 recipients of liver, kidney, or pancreas transplants who were treated with sirolimus and low-dose tacrolimus experienced a low rate of rejection and excellent graft function without drug-related toxic effects

Effects of calcined dolomite addition on reaction kinetics of one-part sodium carbonate-activated slag cements

In the present study, an environment-friendly one-part alkali-activated cement dry mixture was prepared by using blast furnace slag as the aluminosilicate precursor, solid sodium carbonate as the alkali activator and calcined dolomite (CD) as the reaction kinetics controlling additive. The effects of CD addition on the reaction kinetics and phase evolution of the hydrated cement paste were investigated by using the isothermal conduction calorimetry (ICC), X-ray diffractometry (XRD), thermogravimetric analysis (TGA) and nitrogen adsorption technique. The CD addition promoted the formation of hydrotalcite-like phase in the paste to consume the excess CO32− ions. This is helpful in raising the alkalinity of the pore solution, and consequently enhancing the rate and degree of the alkali-activation. The growth of space-filling C-A-S-H gel phase leads to a more compact pore structure in the paste with higher CD content. The CD addition enables the Na2CO3-activated slag paste to set within 24 h, and improves the compressive strength to an acceptable value of 32.9–41.6 MPa after 28 days of curing at ambient temperature