Miracle-dz/UniFAR-FTUs huggingface dataset:
Primary Investigation of Deep Learning Models for Japanese “Group Classification” of Whole-Slide Images of Gastric Endoscopic Biopsy

Background Accurate pathological diagnosis of gastric endoscopic biopsy could greatly improve the opportunity of early diagnosis and treatment of gastric cancer. The Japanese “Group classification” of gastric biopsy corresponds well with the endoscopic diagnostic system and can guide clinical treatment. However, severe shortage of pathologists and their heavy workload limit the diagnostic accuracy. This study presents the first attempt to investigate the applicability and effectiveness of AI-aided system for automated Japanese “Group classification” of gastric endoscopic biopsy. Methods In total, 260 whole-slide images of gastric endoscopic biopsy were collected from Dalian Municipal Central Hospital from January 2015 to January 2021. These images were annotated by experienced pathologists according to the Japanese “Group classification. ” Five popular convolutional neural networks, i.e., VGG16, VGG19, ResNet50, Xception, and InceptionV3 were trained and tested. The performance of the models was compared in terms of widely used metrics, namely, AUC (area under the receiver operating characteristic curve, i.e., ROC curve), accuracy, recall, precision, and F1 score. Results Results showed that ResNet50 achieved the best performance with accuracy 93.16% and AUC 0.994. Conclusion Our results demonstrated the applicability and effectiveness of DL-based system for automated Japanese “Group classification” of gastric endoscopic biopsy.
Polyphenolic Composition, Antioxidant, Antiproliferative and Antidiabetic Activities of Coronopus didymus Leaf Extracts

Coronopus didymus (Brassicaceae) commonly known as lesser swine cress has been reported to be used for its pharmacological activities. This study aimed to evaluate the medicinal potential of C. didymus extracts against cancer, diabetes, infectious bacteria and oxidative stress and the identification of bioactive compounds present in these extracts. The effects of using different solvents for the extraction of C. didymus on the contents of major polyphenols and biological activities were investigated. Plant sample was shade dried, ground to a fine powder, and then soaked in pure acetone, ethanol and methanol. The highest contents of major polyphenols were found in methanol-based extract, i.e., chlorogenic acid, HB acid, kaempferol, ferulic acid, quercetin and benzoic acid with 305.02, 12.42, 11.5, 23.33, 975.7 and 428 mg/g of dry weight, respectively, followed by ethanol- and acetone-based extracts. The methanol-based extract also resulted in the highest antioxidant activities (56.76%), whereas the highest antiproliferative (76.36) and alpha glucosidase inhabitation (96.65) were demonstrated in ethanol-based extracts. No antibacterial property of C. didymus was observed against all the tested strains of bacteria. Further studies should be focused on the identification of specific bioactive compounds responsible for pharmacological activities.
Estimation of the Serial Interval and the Effective Reproductive Number of COVID-19 Outbreak Using Contact Data in Burkina Faso, a Sub-Saharan African Country

The COVID-19 outbreak has spread all around the world in less than four months. However, the pattern of the epidemic was different according to the countries. We propose this paper to describe the transmission network and to estimate the serial interval and the reproductive number of the novel coronavirus disease (COVID-19) in Burkina Faso, a Sub-Saharan African country. Data from the COVID-19 response team was analyzed. Information on the 804 first detected cases were pulled together. From contact tracing information, 126 infector-infectee pairs were built. The principal infection clusters with their index cases were observed, principally the two major identified indexes in Burkina. However, the generations of infections were usually short (less than four). The serial interval was estimated to follow a gamma distribution with a shape parameter 1.04 (95% credibility interval: 0.69–1.57) and a scale parameter of 5.69 (95% credibility interval: 3.76–9.11). The basic reproductive number was estimated at 2.36 (95% confidence interval: 1.46–3.26). However, the effective reproductive number decreases very quickly, reaching a minimum value of 0.20 (95% confidence interval: 0.06–0.34). Estimated parameters are made available to monitor the outbreak in Sub-Saharan African countries. These show serial intervals like in the other continents but less infectiousness.
Scaling and universality in coupled driven diffusive models

Inspired by the physics of magnetohydrodynamics (MHD) a simplified coupled Burgers-like model in one dimension (1d), a generalization of the Burgers model to coupled degrees of freedom, is proposed to describe 1dMHD. In addition to MHD, this model serves as a 1d reduced model for driven binary fluid mixtures. Here we have performed a comprehensive study of the universal properties of the generalized d-dimensional version of the reduced model. We employ both analytical and numerical approaches. In particular, we determine the scaling exponents and the amplitude ratios of the relevant two-point time-dependent correlation functions in the model. We demonstrate that these quantities vary continuously with the amplitude of the noise cross-correlation. Further our numerical studies corroborate the continuous dependence of long wavelength and long timescale physics of the model on the amplitude of the noise cross-correlations, as found in our analytical studies. We construct and simulate lattice–gas models of coupled degrees of freedom in 1d, belonging to the universality class of our coupled Burgers-like model, which display similar behavior. We use a variety of numerical (Monte Carlo and Pseudo-spectral methods) and analytical (dynamic renormalization group, self-consistent mode coupling theory and functional renormalization group) approaches for our work. The results from our different approaches complement one another. Possible realizations of our results in various non-equilibrium models are discussed.
Aging ef fect of optical properties on low loss antireflection coatings for laser optics

For high precise laser systems like laser gyro, gravitational waves interferometers, the optical components which lie in the cavity or laser path need to control the total loss, scattering, reflection, absorption, and so on. Low loss high-reflection (HR) and antireflection (AR) coating mirrors are their key components and their aging optical properties are the most important performance parameters for long operating lifetime. Low loss AR coatings on quartz substrates for He-Ne laser are designed and manufactured by ion beam sputtering (IBS) technology. Ta2O5 and SiO2 are used as high and low refractive index materials and the obtained total optical loss of AR coating is less than 50 ppm. Aging optical properties of AR coatings are investigated as a function of time placed in the air. When the placed time exceeds 40 days, optical properties tend to be stabilization. The obtained results indicate that the prepared low loss AR coatings have good stability of optical properties and can be applied for high precise laser systems.
Identification of spectrally enhanced Polish vowels

The role of spectral enhancement in identification of Polish vowels is investigated in this study. Identification scores of natural (unprocessed) vowels (Experiment 1) and spectrally enhanced vowels (Experiment 2) were measured for normal-hearing subjects (NHS) and for subjects with hearing impairment of cochlear origin (HIS). The NHS group demonstrated almost 100% vowel-identification scores for natural vowels. Instead, for the HIS group, an overall average identification scores were 85% for natural vowels, 96% for spectrally enhanced vowels. It has been shown that the spectral enhancement applied has improved the average identification score for subjects with sensorineural hearing losses. However, the degree of improvement clearly depended on the subjects, the type of vowel, and the talker.
Entropic approach to local realism and noncontextuality

For any Bell locality scenario (or Kochen-Specker noncontextuality scenario), the joint Shannon entropies of local (or noncontextual) models define a convex cone for which the nontrivial facets are tight entropic Bell (or contextuality) inequalities. In this paper we explore this entropic approach and derive tight entropic inequalities for various scenarios. One advantage of entropic inequalities is that they easily adapt to situations such as bilocality scenarios, which have additional independence requirements that are nonlinear on the level of probabilities, but linear on the level of entropies. Another advantage is that, despite the nonlinearity, taking detection inefficiencies into account turns out to be very simple. When joint measurements are conducted by a single detector only, the detector efficiency for witnessing quantum contextuality can be arbitrarily low.
Inhibition of GABAAR or Application of Lactobacillus casei Zhang Alleviates Ulcerative Colitis in Mice: GABAAR as a Potential Target for Intestinal Epithelial Renewal and Repair

Emerging evidence indicates that the gamma−aminobutyric acid type A receptor (GABAAR) and Lactobacillus casei Zhang regulate colitis in a variety of ways, such as by participating in host immune and inflammatory responses, altering the gut microbiota, and influencing intestinal barrier function. However, not much is known about the mechanisms by which GABAAR and L. casei affect colon epithelial cell renewal and the interaction between GABAAR and L. casei during this process. To elucidate this, we established a dextran sulfate sodium (DSS)−induced model and measured the mouse body weights, colon length, the disease activity index (DAI), and histological scores. Our results indicated that inhibition of GABAAR alleviated the DSS−induced colitis symptoms, resulting in less weight loss and more intact colon tissue. Moreover, treatment with bicuculline (Bic, a GABAAR inhibitor) increased the levels of PCNA, β−catenin, and TCF4 in mice with colitis. Interestingly, open field test performances showed that inhibition of GABAAR also attenuated colitis−related anxiety−like behavior. By 16S RNA gene sequencing analysis, we showed that inhibition of GABAAR partially reversed the gut dysbacteriosis of DSS−induced mice and increased the abundance of beneficial bacteria. Additionally, L. casei Zhang supplementation inhibited the expression of GABAAR in mice with colitis, promoted the proliferation and renewal of colon epithelial cells, and alleviated anxiety−like behavior and intestinal microflora disorder in mice. Thus, GABAAR plays a key role in the beneficial effects of L. casei on DSS−induced colitis in mice.
Preliminary Study on Conducted Emission of a Dynamic Wireless Power Transfer System for Automotive

Aim of this work is an investigation on the conducted emission (CE) of a dynamic wireless power transfer (DWPT) system for automotive applications. The main difference of DWPT systems compared to stationary charging systems is due to the fast transients produced by the on/off and off/on transitions of the transmitting coils during the passage of the vehicle in motion. These transients could represent a significant issue in terms of CE, especially if multiple vehicles are moving along the electrified road. Real components such as coupled inductive coils, compensation networks, converters and battery are suitably modeled by equivalent circuits which are analyzed by SPICE models. The CE is investigated considering different scenarios with single and multiple electric vehicles (EVs) absorbing each 10 kW at 85 kHz in a section of an electrified road with short track architecture. The obtained results demonstrate that higher order harmonics of currents produced by electronic converters are not negligible in both ground and vehicle circuits.
Monte Carlo simulation of Siemens ONCOR linear accelerator with EGSnrc code

Background: The Monte Carlo method is the most accurate method for simulation of radiation therapy equipment. The linear accelerators are currently the most widely used machines in radiation therapy centers. Methods: In this work, a Monte Carlo modelling of the Siemens ONCOR linear accelerator in 6 MV and 18 MV beams was performed. The results of simulation were validated by measurements in water by ionization chamber and EDR 2 film in solid water. The linac’s x-ray particular are so sensitive to the properties of primary electron beam. Square field size of 10 × 10 cm 2 produced by the jaws was compared with ionization chamber and film measurements. Head simulation was performed with BEAMnrc and dose calculation with DOSXYZnrc For film measurements and 3ddose file produced by DOSXYZnrc analyzed used homemade MATLAB program. Results: At 6 MV, the agreement between dose calculated by Monte Carlo modelling and direct measurement was obtained to the least restrictive of 1%, even in the build-up region. At 18 MV, the agreement was obtained 1%, except for in the build-up region. In the build-up region, the difference was 1% at 6 MV and 2% at 18 MV. Conclusions: The mean difference between measurements and Monte Carlo simulation is very small in both of ONCOR x-ray energy. The results are highly accurate and can be used for many applications such as patient dose calculation in treatment planning and in studies that model this linac with small field size such as Intensity Modulated Radiation Therapy technique.
Differential Bacterial Community of Bee Bread and Bee Pollen Revealed by 16s rRNA High-Throughput Sequencing

Simple Summary Gut symbionts play a crucial role in the nutrition provisioning of honeybees. However, the data on the bacterial communities of pollen collected by bees and bee bread are comparatively scarce. Therefore, the present study was designed to explore and identify the bacterial communities from them. The study reports that the bacterial diversity was significantly higher in the bee bread than in bee pollen. The higher bacterial diversity in the bee bread could presumably be due to factors such as storage period, processing of food, fermentation, and high sugar environment. The bacterial communities of bee bread possibly exhibit beneficial roles for honeybees such as polysaccharide degradation and nitrogen fixing. Abstract We investigated the bacterial community of bee bread and bee pollen samples using an approach through 16 s rRNA high-throughput sequencing. The results revealed a higher bacterial diversity in bee bread than in bee pollen as depicted in taxonomic profiling, as well as diversity indices such as the Shannon diversity index (3.7 to 4.8 for bee bread and 1.1 to 1.7 for bee pollen samples) and Simpson’s index (>0.9 for bee bread and 0.4–0.5 for bee pollen). Principal component analysis showed a distinct difference in bacterial communities. The higher bacterial diversity in the bee bread than bee pollen could presumably be due to factors such as storage period, processing of food, fermentation, and high sugar environment. However, no effect of the feed (rapeseed or oak pollen patties or even natural inflow) was indicated on the bacterial composition of bee bread, presumably because of the lack of restriction of foraged pollen inflow in the hive. The diverse bacterial profile of the bee bread could contribute to the nutritional provisioning as well as enhance the detoxification process; however, a thorough investigation of the functional role of individual bacteria genera remains a task for future studies.
Intelligent Mining Method of Audit Data Characteristics under Financial Shared Service Mode

With the development of society, the importance of centralized management and exchange of data has gradually emerged, and large groups have gradually increased their favor for the financial shared service model. There are still some differences between the traditional financial management model and the shared financial model, and internal audit has gradually changed with the change of the management model. Under the financial shared service model, facing the challenge of increasingly quantified data by audited entities, the traditional methods of many domestic accounting firms have been unable to cope with the challenge. How to use data mining technology to effectively discover data in massive data. They are very important for data control. The purpose of this article is to study the intelligent mining of audit data characteristics under the financial shared service mode, and analyze the related technologies of the intelligent mining of audit data characteristics, and combine the professional audit content to study how to use intelligent mining on audit data under the financial shared service mode method, imitating the real situation of auditing data by audit institutions in daily life, comprehensively applying various mining algorithms to analyze the experiment, the experiment proves the accuracy of the intelligent mining method of audit data characteristics in the financial shared service mode in several types of data sets. The highest can reach 86.2%, which proves that the mining model established in this article has certain reference value for actual audit data mining.
Assessing the Coherence Modeling Capabilities of Pretrained Transformer-based Language Models

The task of ordering a shuffled set of sentences 001 into a coherent text is used to evaluate the ca-002 pacity of a model to understand causal and tem-003 poral relations between entities and events. Re-004 cent approaches rely on pretrained Transformer-005 based models, but it remains unknown whether 006 the differences between them, such as size, pre-007 training data and objectives, affect their coher-008 ence modeling capacity. We present a simple 009 architecture for sentence ordering that relies 010 exclusively on pretrained Transformer-based 011 encoder-only models. This allows us to com-012 pare the coherence modeling capabilities of 013 the monolingual and multilingual versions of 014 BERT, RoBERTa, and DistilBERT. We show 015 that RoBERTa-based models outperform BERT-016 based models and are more robust when order-017 ing longer documents with more than 10 sen-018 tences. Thus, the intuitive advantage offered 019 by sentence-based objectives such as Next Sen-020 tence Prediction used in BERT is effectively 021 compensated by the higher amount and diver-022 sity of the training data used in RoBERTa. 023 However, the difference between multilingual 024 versions of BERT and RoBERTa is narrower. 025 This suggests that exposure to different lan-026 guages partially makes up for the benefits of 027 larger and more diverse training data. 028
Lycium barbarum Polysaccharide Regulates the Lipid Metabolism and Alters Gut Microbiota in High-Fat Diet Induced Obese Mice

Bioactive compounds provide new insights into the prevention and treatment of obesity. Lycium barbarum polysaccharide (LBP), a biological macromolecule extracted from Goji berry, has displayed potential for regulating lipid metabolism. However, the relationship between gut microbiota regulation and lipid metabolism is not entirely clear. In the present study, 50, 100, and 150 mg/kg LBP were intragastrically administered to C57BL/6J male mice fed with a high-fat diet simultaneously lasting for twelve weeks. The results showed that 150 mg/kg LBP showed significant results and all doses of LBP feeding (50, 100, 150 mg/kg) remarkably decreased both serum and liver total cholesterol (TC) and triglyceride (TG) levels. Treatment of 150 mg/kg LBP seems to be more effective in weight loss, lowering free fatty acid (FFA) levels in serum and liver tissues of mice. LBP feeding increased the gene expression of adiponectin and decreased the gene expression of peroxisome proliferator-activated receptor γ, Cluster of Differentiation 36, acetyl-coA carboxylase, and fatty acid synthase in a dose-dependent manner. In addition, the 16s rDNA Sequencing analysis showed that 150 mg/kg LBP feeding may significantly increase the richness of gut microbiota by up-regulation of the ACE and Chao1 index and altered β-diversity among groups. Treatment of 150 mg/kg LBP feeding significantly regulated the microbial distribution by decreasing the relative abundance of Firmicutes and increasing the relative abundance of Bacteroidetes at the phylum level. Furthermore, the relative abundance of Faecalibaculum, Pantoea, and uncultured_bacterium_f_Muribaculaceae at the genus level was significantly affected by LBP feeding. A significant correlation was observed between body weight, TC, TG, FFA and bile acid and phyla at the genus level. The above results indicate that LBP plays a vital role in preventing obesity by co-regulating lipid metabolism and gut microbiota, but its effects vary with the dose.
Active vs. Passive: A Comparison of Automata Learning Paradigms for Network Protocols

Active automata learning became a popular tool for the behavioral analysis of communication protocols. The main advantage is that no manual modeling effort is required since a behavioral model is automatically inferred from a black-box system. However, several real-world applications of this technique show that the overhead for the establishment of an active interface might hamper the practical applicability. Our recent work on the active learning of Bluetooth Low Energy (BLE) protocol found that the active interaction creates a bottleneck during learning. Considering the automata learning toolset, passive learning techniques appear as a promising solution since they do not require an active interface to the system under learning. Instead, models are learned based on a given data set. In this paper, we evaluate passive learning for two network protocols: BLE and Message Queuing Telemetry Transport (MQTT). Our results show that passive techniques can correctly learn with less data than required by active learning. However, a general random data generation for passive learning is more expensive compared to the costs of active learning.
Automatic terminal guidance for small fixed‐wing unmanned aerial vehicles

The research presented in this article focuses on expanding and deepening the prior research of a low‐cost terminal guidance system in a previous paper entitled “Design, implementation and verification of a low‐cost terminal guidance system for small fixed‐wing UAVs. ” An automatic terminal guidance workflow is specially designed for an individual in a small fixed‐wing unmanned aerial vehicle (SUAV) swarm. The extended work around the proposed workflow primarily involves upgrading onboard hardware modules to improve sensor accuracy and environmental adaptability, the imaging performance of the seeker, as well as the computational capability of the image processor, applying object detection to replace the human‐in‐the‐loop function and adopting the integral proportional guidance law in the vertical direction to reduce the required overload and obtain a larger impact angle. Furthermore, we conducted several field tests on two types of SUAV against a stationary target on the ground in a field scenario. The experiments have generated valuable onboard image data and SUAV status information, all of which are aligned in the time domain. The only remaining data sets that support the findings of this study are available from the corresponding author. Our study into automatic terminal guidance has yielded a solution of the automatic strap‐down monocular terminal guidance problem of individual SUAVs. The field trials of a single SUAV demonstrate the robustness and efficiency of the proposed automatic terminal guidance methodology and lays a foundation for the future SUAVs' cooperative attack test.