On the instability of a mechanical system of 2-degree of freedom taking into account the resisting force

Non

Handcrafted histological transformer (H2T):unsupervised representation of whole slide images

Diagnostic, prognostic and therapeutic decision-making of cancer in pathology clinics can now be carried out based on analysis of multi-gigapixel tissue images, also known as whole-slide images (WSIs). Recently, deep convolutional neural networks (CNNs) have been proposed to derive unsupervised WSI representations; these are attractive as they rely less on expert annotation which is cumbersome. However, a major trade-off is that higher predictive power generally comes at the cost of interpretability, posing a challenge to their clinical use where transparency in decision-making is generally expected. To address this challenge, we present a handcrafted framework based on deep CNN for constructing holistic WSI-level representations. Building on recent findings about the internal working of the Transformer in the domain of natural language processing, we break down its processes and handcraft them into a more transparent framework that we term as the Handcrafted Histological Transformer or H2T. Based on our experiments involving various datasets consisting of a total of 10,042 WSIs, the results demonstrate that H2T based holistic WSI-level representations offer competitive performance compared to recent state-of-the-art methods and can be readily utilized for various downstream analysis tasks. Finally, our results demonstrate that the H2T framework can be up to 14 times faster than the Transformer models

One Model is All You Need: Multi-Task Learning Enables Simultaneous Histology Image Segmentation and Classification

The recent surge in performance for image analysis of digitised pathology slides can largely be attributed to the advance of deep learning. Deep models can be used to initially localise various structures in the tissue and hence facilitate the extraction of interpretable features for biomarker discovery. However, these models are typically trained for a single task and therefore scale poorly as we wish to adapt the model for an increasing number of different tasks. Also, supervised deep learning models are very data hungry and therefore rely on large amounts of training data to perform well. In this paper we present a multi-task learning approach for segmentation and classification of nuclei, glands, lumen and different tissue regions that leverages data from multiple independent data sources. While ensuring that our tasks are aligned by the same tissue type and resolution, we enable simultaneous prediction with a single network. As a result of feature sharing, we also show that the learned representation can be used to improve downstream tasks, including nuclear classification and signet ring cell detection. As part of this work, we use a large dataset consisting of over 600K objects for segmentation and 440K patches for classification and make the data publicly available. We use our approach to process the colorectal subset of TCGA, consisting of 599 whole-slide images, to localise 377 million, 900K and 2.1 million nuclei, glands and lumen respectively. We make this resource available to remove a major barrier in the development of explainable models for computational pathology

Chronic scrotal heat stress causes testicular interstitial inflammation and fibrosis: An experimental study in mice

Background: Chronic heat stress is a risk factor that adversely affects the reproduction system. Inflammation and fibrosis are 2 important response processes to damaged tissues. Objective: This study investigates the association of chronic scrotal heat stress with testicular interstitial inflammation and fibrosis in mice. Materials and Methods: For all experiments, 8-10 wk old male Swiss mice (Mus musculus) (20-23 gr) were divided into 3 groups (n = 10/each). The heat-stress groups were submerged in a water bath at 37°C and 40°C, while the control group was treated at 25°C. The testicular tissues underwent hematoxylin and eosin staining, picro sirius red staining, and immunohistochemistry for intercellular adhesion molecule-1, fibroblast-specific protein 1, F4/80, collagen I, and Ki-67 staining to determine the testicular interstitial inflammation and fibrosis. Results: Chronic scrotal heat stress impairs spermatogenesis and reverses testicular histological structure. In this study, heat stress significantly induced increased interstitial cell proliferation and upregulation of intercellular adhesion molecule-1 expression in the interstitial testicular tissue. In the interstitial testicular tissue, the number of F4/80-positive macrophages and the number of fibroblast-specific protein 1- positive fibroblasts were significantly increased in the heat-exposed groups compared to those in the control group. The heat exposed groups had substantially increased extracellular matrix collagen accumulation in their testicular interstitial tissues. Conclusion: Heat stress adversely affects the testicular structure and spermatogenesis, causes inflammation, and leads to testicular interstitial fibrosis. Key words: Heat stress, Testicular, Inflammation, Fibrosis

zk-SNARKs from Codes with Rank Metrics

Succinct non-interactive zero-knowledge arguments of knowledge (zk-SNARKs) are a type of non-interactive proof system enabling efficient privacy-preserving proofs of membership for NP languages. A great deal of works has studied candidate constructions that are secure against quantum attackers, which are based on either lattice assumptions, or post-quantum collision-resistant hash functions. In this paper, we propose a code-based zk-SNARK scheme, whose security is based on the rank support learning (RSL) problem, a variant of the random linear code decoding problem in the rank metric. Our construction follows the general framework of Gennaro et al. (CCS\u2718), which is based on square span programs (SSPs). Due to the fundamental differences between the hardness assumptions, our proof of security cannot apply the techniques from the lattice-based constructions, and indeed, it distinguishes itself by the use of techniques from coding theory. We also provide the scheme with a set of concrete parameters

A THEORETICAL STUDY ON CHEMICAL BONDING AND INFRARED SPECTRA OF SinM (M = Sc, Y; n = 1-10) CLUSTERS

In this paper, we applied the B3P86 method and DGDZVP basis set to investigate electronic properties and infrared (IR) spectra for SinM (M = Sc, Y; n = 1-10) clusters. The NBO analyses show that electron transfers from the dopant atoms to silicon frame of the SinM clusters. It is remarkable that the Si-M bond is mainly formed by the overlaps of the 3s-AOs and 3p-AOs of Si atoms, and 3d-AOs and 4s-AOs of Sc (or 4d-AOs and AO-5s of Y). The chemical bonds in the SiM and Si2M clusters are dominated by the covalent character including sigma and pi bonds. In addition, the analysis of the IR spectra suggests that the vibrational modes of SinM clusters are delocalized over the whole cluster. Moreover, the high-frequency and strong-intensity modes usually involve the vibrations of the dopant atoms. The results of this work provide fundamental information for experimental studies on transition-metal doped silicon clusters

An Assessment of the Values of French Colonial Townhouses in Hanoi Towards A More Sustainable Conservation

As the capital city of French Indochina, Hanoi was well planned by the French and immensely invested in the construction of public buildings as well as houses. In addition to public buildings and villas designed in French colonial styles that shaped the so-called distinctive architectural heritage in Hanoi throughout the colonial years, a large number of townhouses built during 1920 - 1950 which formed the cityscape of Hanoi in the first half of the 20th century should be noted. After nearly 70 years since the French army withdrew from the city, the number of French townhouses has considerably decreased. The remaining houses have shown that this is a real “treasure” that needs to be conserved because of their important values, not only in terms of urban architecture but also in cultural and historical aspects. However, a fact requiring special attention is that French townhouses in Hanoi - unlike French public buildings and villas - have not yet been recognised as heritage so that they can be kept to avoid the risk of deterioration or demolition under the impact of rapid urbanisation in the market economy. One of the main reasons for this negative urban development is that there has been no concrete or comprehensive rating system to assess the values of those townhouses which will closely correspond to their characteristics and contexts. Therefore, the authors - based on site surveys and by applying some appropriate methods such as expert consultations and case studies - have developed a full set of criteria to help evaluate those remaining townhouses as accurately as possible. This system can be used as a basis for a systematic assessment and classification towards a more effective conservation and even promoting the values of those townhouses with regard to the development of a modern society and in consideration of sustainable heritage conservation as a mainstream in the world.

An Aquaculture Water Checker--design and Manufacture

A real-time, mobile aquaculture water checker is presented. The configuration of double integrating spheres is developed for simultaneously measuring backward scattering $R_d$, forward scattering $T_d$  and transmitted light $T_c$. Based on Kubelka-Munk model, a set of optical parameters including absorption coefficient $\mu _a$, scattering coefficient $\mu_s$ and anisotropy  $g$  are calculated. The obtained results for diluted milk standard samples with different milk concentrations and aquaculture water samples with different densities of Psexdo-Nitzschia-delicatissium algae are also reported