Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling of fluid–solid interaction in granular media with coupled lattice Boltzmann/discrete element methods: application to piping erosion

In this article, we present a numerical method to deal with fluid–solid interactions and simulate particle–fluid systems as encountered in soils. This method is based on a coupling between two methods, now widely used in mechanics of granular media and fluid dynamics respectively: the discrete element (DE) method and the lattice Boltzmann (LB) method. The DE method is employed to model interactions between particles, whereas the LB method is used to describe an interstitial Newtonian fluid flow. The coupling presented here is a full one in the sense that particle motions act on fluid flow and reciprocally. This article presents in details each of the two methods and the principle of the coupling scheme. Determination of hydrodynamic forces and torques is also detailed, and the treatment of boundaries is explained. The coupled method is finally illustrated on a simple example of piping erosion, which puts in evidence that the combined LB–DE scheme constitutes a promising tool to study coupled problems in geomechanics. Copyright © 2011 John Wiley & Sons, Ltd.
Privacy-preserving unknown input observer-based decentralized predictive control of Microgrids

This paper studies the decentralized predictive control problem for microgrids. The proposed constrained control method has the following advantages: (1) it takes into account the privacy protection of the control system, which helps to protect the network transmission data and block the influence of eavesdropping attacks; (2) the observer and the controller are determined by the integrated design, which helps to reduce the influence of the bi-directional interaction error between the estimation error and the control error and improve the robustness of the predictive control. Finally, the validity of the above conclusions obtained in this paper is verified by a numerical example.
Multiple AMR Rigid Formation Control With Collision Avoidance Based On MADDPG

Recently, the formation control of multiple autonomous mobile robots (AMRs) have gained significant attention, and autonomous mobile robots (AMRs) have applied to all aspects of our life. Multi-agent reinforcement learning is used to solve the autonomously sequential decision-making problem of agents in a common environment with competition or cooperation. Therefore, we present a utility function and a reward function to achieve formation control with collision avoidance for a rigid AMRs system, and build a simulation environment to meet environmental requirements based on MPE.
NEUROD1 predicts better prognosis in pancreatic cancer revealed by a TILs-based prognostic signature

It has been well-defined that tumor-infiltrating lymphocytes (TILs) play critical roles in pancreatic cancer (PaCa) progression. This research aimed to comprehensively explore the composition of TILs in PaCa and their potential clinical significance. A total of 178 samples from the TCGA and 63 samples from the GSE57495 dataset were enrolled in our study. ImmuCellAI was applied to calculate the infiltrating abundance of 24 immune cell types in PaCa and further survival analysis revealed the prognostic values of TILs in PaCa. Moreover, the Hallmark enticement analysis of differentially expressed genes (DEGs) between low- and high-risk groups was performed as well. Immunohistochemistry staining was used to evaluate NEUROD1 expression. As result, different kinds of TILs had distinct infiltrating features. In addition, Specific TILs subsets had notable prognostic values in PaCa. We further established a 6-TILs signature to assess the prognosis of PaCa patients. Kaplan-Meier and Cox regression analyses both suggested the significant prognostic value of the signature in PaCa. Based on the prognostic signature, we screened a great deal of potential prognostic biomarkers and successfully validated NEUROD1 as a novel prognostic biomarker in PaCa. Overall, the current study illuminated the immune cells infiltrating the landscape in PaCa and identified a TILs-dependent signature and NEUROD1 for prognostic prediction in PaCa patients.
Therapeutic effects of Fc gamma RIV inhibition are mediated by selectively blocking immune complex-induced neutrophil activation in epidermolysis bullosa acquisita

Epidermolysis bullosa acquisita (EBA) is a subepidermal autoimmune bullous disease caused by autoantibodies targeting type VII collagen (COL7). It is characterized by inflammation and subepidermal blistering mainly through immune complex (IC)-mediated activation of neutrophils. In experimental EBA, binding of neutrophils to ICs in the skin and induction of clinical disease depends on the expression of the Fc gamma receptor (FcγR) IV. As activating FcγR mediate both neutrophil extravasation and activation, we used multiphoton imaging to obtain further insights into the mechanistic contribution of FcγRIV in the pathogenesis of EBA. First, we demonstrated that blocking FcγRIV function completely protects LysM-eGFP mice against induction of antibody transfer-induced EBA. To visualize the interactions of anti-COL7 IgG and neutrophils in vivo, fluorescently labeled anti-COL7 IgG was injected into LysM-eGFP mice. Multiphoton microscopy was sequentially performed over a period of 8 days. At all time points, we observed a significantly higher extravasation of neutrophils into the skin of mice treated with anti-FcγRIV antibody compared to controls. However, the percentage of detected neutrophils localized to the target antigen along the dermal-epidermal junction was comparable between both groups. Additionally, reactive oxygen release and migration in vitro assay data demonstrate that FcγRIV antibody treatment inhibits the activation, but not the migration, of neutrophils. Our findings underscore the importance of advanced in vivo imaging techniques to understand the complexity of IC-mediated neutrophil-dependent inflammation, and indicate that the therapeutic utility of FcγRIV blockade is achieved through impairment of IC-mediated neutrophil activation.
Automatic volumetric diagnosis of hepatocellular carcinoma based on four-phase CT scans with minimum extra information

Summary We built a deep-learning based model for diagnosis of HCC with typical images from four-phase CT and MEI, demonstrating high performance and excellent efficiency. Objectives The aim of this study was to develop a deep-learning-based model for the diagnosis of hepatocellular carcinoma. Materials and methods This clinical retrospective study uses CT scans of liver tumors over four phases (non-enhanced phase, arterial phase, portal venous phase, and delayed phase). Tumors were diagnosed as hepatocellular carcinoma (HCC) and non-hepatocellular carcinoma (non-HCC) including cyst, hemangioma (HA), and intrahepatic cholangiocarcinoma (ICC). A total of 601 liver lesions from 479 patients (56 years ± 11 [standard deviation]; 350 men) are evaluated between 2014 and 2017 for a total of 315 HCCs and 286 non-HCCs including 64 cysts, 178 HAs, and 44 ICCs. A total of 481 liver lesions were randomly assigned to the training set, and the remaining 120 liver lesions constituted the validation set. A deep learning model using 3D convolutional neural network (CNN) and multilayer perceptron is trained based on CT scans and minimum extra information (MEI) including text input of patient age and gender as well as automatically extracted lesion location and size from image data. Fivefold cross-validations were performed using randomly split datasets. Diagnosis accuracy and efficiency of the trained model were compared with that of the radiologists using a validation set on which the model showed matched performance to the fivefold average. Student’s t-test (T-test) of accuracy between the model and the two radiologists was performed. Results The accuracy for diagnosing HCCs of the proposed model was 94.17% (113 of 120), significantly higher than those of the radiologists, being 90.83% (109 of 120, p-value = 0.018) and 83.33% (100 of 120, p-value = 0.002). The average time analyzing each lesion by our proposed model on one Graphics Processing Unit was 0.13 s, which was about 250 times faster than that of the two radiologists who needed, on average, 30 s and 37.5 s instead. Conclusion The proposed model trained on a few hundred samples with MEI demonstrates a diagnostic accuracy significantly higher than the two radiologists with a classification runtime about 250 times faster than that of the two radiologists and therefore could be easily incorporated into the clinical workflow to dramatically reduce the workload of radiologists.
The influence of tides on the North West European shelf winter residual circulation

Tides contribute to the large-scale residual circulation and mixing of shelf seas. However, tides are typically excluded from global circulation models (GCMs) so their modelled residual circulation (and mixing) in shelf seas may be systematically wrong. We focus on circulation as it is relatively unexplored, and affects shelf temperature and salinity, potentially biasing climate impact studies. Using a validated model of the North West European Shelf Seas (NWS), we show the essential role of tides in driving the residual circulation, and how this affects the NWS temperature and salinity distribution. Over most of the NWS, removing the tides increases the magnitude of residual circulation while in some regions (such as the Irish Sea) it leads to a reduction. Furthermore, we show that modelling the NWS without tides leads to a cold fresh bias in the Celtic Sea and English Channel (of >0.5°C, and >0.5 psu). This shows that NWS tidal dynamics are essential in the transport of heat and matter, and so must be included in GCMs. We explore two processes by which the tides impact the residual circulation and investigate whether these could be parameterised within non-tidal GCMs: (1) Enhancing the seabed friction to mimic the equivalent energy loss from an oscillating tidal flow; (2) Tidal Phase-driven Transport (TPT), whereby tidal asymmetry drives a net transport due to the phase between tidal-elevation and velocities (equivalent to the bolus term in oceanographic literature). To parameterise TPT, we calculate a climatology of this transport from a harmonic analysis from the tidal model and add it as an additional force in the Navier Stokes equations in the non-tidal model. We also modify the bed drag coefficient to balance the bed stress between the simulations – hypothesising that using this modified drag coefficient will simulate the effect of the tides. This tends to improve the mean and variability of the residual circulation, while the TPT improves the spatial distribution and temporal variability of the temperature and salinity. We show that our proof-of-concept parameterisation can replicate the tidally-driven impact on the residual circulation without direct simulation, thus reducing computational effort.
The P300 event related potential predicts phonological working memory skills in school-aged children

The P300 event related potential (ERP) has been cited as a marker of phonological working memory (PWM); however, little is known regarding its relationship to behavioral PWM skills in early school-aged children. The current study investigates the P300 ERP recorded in response to native and non-native (English and Spanish) phoneme contrasts as a predictor of PWM skills in monolingual English-speaking first and second grade children. Thirty-three typically developing children, ages 6–9, completed a battery of phonological processing, language, and cognitive assessments. ERPs were recorded within an auditory oddball paradigm in response to both English phoneme contrasts (/ta/, /pa/) and Spanish contrasts (/t̪a/, /d̪a/). The P300 ERP recorded in response to English phoneme contrasts significantly predicted standard scores on the Nonword Repetition subtest of the Comprehensive Test of Phonological Processing, Second Edition. Spanish contrasts did not elicit a P300 response, nor were amplitude or latency values within the P300 timeframe (250–500 ms) recorded in response to Spanish contrasts related to English nonword repetition performance. This study provides further evidence that the P300 ERP in response to native phonemic contrasts indexes PWM skills, specifically nonword repetition performance, in monolingual children. Further work is necessary to determine the extent to which the P300 response to changing phonological stimuli reflects PWM skills in other populations.
Application of SMILES-based molecular generative model in new drug design

Drugs are playing an increasingly important role in the long struggle between man and disease. Drug discovery is the process of identifying potential new therapeutic entities and drug design is the process of finding new medications based on knowledge of biological targets involving the design of molecules (Zhou and Zhong, 2017). Drug discovery and design has been facing obstacles due to the large human, material and financial resources required. With the success of artificial intelligence in the fields of image processing, pattern recognition and natural language processing (Xie et al., 2022), deep generative model has attracted wide attention in the field of drug discovery, and it also shows a promising application prospect in the field of molecular design optimization. When a generative model is used to generate molecules, its essence is to learn the distribution of molecules in the training set, and then generate molecules similar to but different from those in the training set. Combined with evolutionary algorithm or reinforcement learning, the properties of the generated molecules can be further optimized (Tong et al., 2021; Tan et al., 2022a). The molecular representation in the generative model can be in many forms, including Simplified Molecular Input Line Entry System (SMILES), molecular graph, etc. Generative models can be roughly divided into five categories, including recurrent neural network, RNN, autoencoder, AE, generative aggressive network, GAN, Transformer and generative model combined with reinforcement learning, RL (Bhisetti and Fang, 2022) as shown in Figure 1A. Among them, the molecular generative model based on the text sequence (SMILES) is the most widely used. This paper simply introduces the basic principle and application of deep generative model based on the latest molecular design of the text sequence (SMILES), so that readers can understand deep generative model and use it better in drug molecular design. OPEN ACCESS
CRISPR/Cas9-mediated genome editing of RsGL1a and RsGL1b in radish (Raphanus sativus L.)

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) is a powerful tool widely used for genome editing in various organisms, including plants. It introduces and facilitates the study of rare genetic mutations in a short time and is a potent tool to assist in plant molecular breeding. Radish (Raphanus sativus L.) is an important Brassicaceae vegetable cultivated and consumed worldwide. However, the application of the CRISPR/Cas9 system is limited by the absence of an efficient transformation system in radish. This study aimed to establish a CRISPR/Cas9 system in radish employing the Agrobacterium-mediated genetic transformation system reported recently. For this purpose, we performed genome editing using the CRISPR/Cas9 system targeting the GLABRA1 (GL1) orthologs, RsGL1a and RsGL1b, that induces leaf trichome formation in radish. A Cas9/single guide RNA (sgRNA) vector with a common sgRNA corresponding to RsGL1a and RsGL1b was transferred. A total of eight T0 plants were analyzed, of which six (editing efficiency 75%) had a mutated RsGL1a, five (62.5%) had a mutated RsGL1b, and five showed mutations in both RsGL1a and RsGL1b. Most mutations in T0 plants were short (<3 bp) deletions or insertions, causing frameshift mutations that might produce non-functional proteins. Chimeric mutations were detected in several T0 generation plants. In the T1 generation, the hairless phenotype was observed only in plants with knockout mutations in both RsGL1a and RsGL1b. The majority of mutant alleles in T0 plants, with the exception of the chimeric mutant plants detected, were stably inherited in the T1 generation. In conclusion, we successfully knocked out RsGL1a and RsGL1b using the CRISPR/Cas9 system and demonstrated that both RsGL1a and RsGL1b independently contribute to the induction of leaf trichome formation in radish. In this study, genome-edited plants without T-DNA, which are useful as breeding material, were obtained. The findings prove the feasibility of genome editing in radish using a CRISPR/Cas9 system that could accelerate its molecular breeding to improve agronomically desirable traits.
The validity of animal models to explore the pathogenic role of the complement system in multiple sclerosis: A review

Animal models of multiple sclerosis (MS) have been extensively used to characterize the disease mechanisms in MS, as well as to identify potential pharmacologic targets for this condition. In recent years, the immune complement system has gained increased attention as an important effector in the pathogenesis of MS. Evidence from histological, serum, and CSF studies of patients supports an involvement of complement in both relapsing-remitting and progressive MS. In this review, we discuss the history and advances made on the use of MS animal models to profile the effects of the complement system in this condition. The first studies that explored the complement system in the context of MS used cobra venom factor (CVF) as a complement depleting agent in experimental autoimmune encephalomyelitis (EAE) Lewis rats. Since then, multiple mice and rat models of MS have revealed a role of C3 and the alternative complement cascade in the opsonization and phagocytosis of myelin by microglia and myeloid cells. Studies using viral vectors, genetic knockouts and pharmacologic complement inhibitors have also shown an effect of complement in synaptic loss. Antibody-mediated EAE models have revealed an involvement of the C1 complex and the classical complement as an effector of the humoral response in this disease. C1q itself may also be involved in modulating microglia activation and oligodendrocyte differentiation in these animals. In addition, animal and in vitro models have revealed that multiple complement factors may act as modulators of both the innate and adaptive immune responses. Finally, evidence gathered from mice models suggests that the membrane attack complex (MAC) may even exert protective roles in the chronic stages of EAE. Overall, this review summarizes the importance of MS animal models to better characterize the role of the complement system and guide future therapeutic approaches in this condition.
Survivorship of the retained femoral component after revision total hip arthroplasty: A systematic review and meta-analysis

Objective This systematic review and meta-analysis aimed to estimate re-revision rates of retained femoral components after revision of total hip arthroplasty (THA). Methods Papers were searched in the PubMed, Embase, Web of Science, and Cochrane Library databases with predetermined keywords from January 2000 to January 2022. The studies reporting the re-revision rates of retained stems after revision THA were identified. Pooled rates of re-revision for any reason and aseptic loosening were calculated using a random-effects model or a fixed-effects model based on the results of heterogeneity assessment after the Freeman–Tukey double-arcsine transformation. A meta-regression was performed to explore potential sources of heterogeneity. Results There were 20 studies with 1,484 hips that received the isolated cup revision with the femoral component retained. The pooled re-revision rate of retained stems was 1.75% [95% confidence interval (CI) 0.43%–3.65%]. The re-revision rate of retained stems due to aseptic loosening was 0.62% (95% CI, 0.06%–1.55%). The meta-regression showed that the fixation type (cemented or cementless) was related to the re-revision rate for any reason and the re-revision rate for aseptic loosening. Conclusion Based on the existing evidence, the isolated cup revision with a stable stem in situ yields low re-revision rates. The cement status of retained stems may influence the survivorship of stems.
Cryptococcus escapes host immunity: What do we know?

Cryptococcus is an invasive fungus that seriously endangers human life and health, with a complex and well-established immune-escaping mechanism that interferes with the function of the host immune system. Cryptococcus can attenuate the host’s correct recognition of the fungal antigen and escape the immune response mediated by host phagocytes, innate lymphoid cells, T lymphocytes, B lymphocytes with antibodies, and peripheral cytokines. In addition, the capsule, melanin, dormancy, Titan cells, biofilm, and other related structures of Cryptococcus are also involved in the process of escaping the host’s immunity, as well as enhancing the ability of Cryptococcus to infect the host.
THE CONNECTIONS BETWEEN THE UV AND OPTICAL Fe ii EMISSION LINES IN TYPE 1 AGNs

We investigate the spectral properties of the UV (λλ2650–3050 Å) and optical (λλ4000–5500 Å) Fe ii emission features in a sample of 293 Type 1 active galactic nuclei (AGNs) from the Sloan Digital Sky Survey database. We explore different correlations between their emission line properties, as well as the correlations with other emission lines from the spectral range. We find several interesting correlations and outline the most interesting results as follows. (i) There is a kinematical connection between the UV and optical Fe ii lines, indicating that the UV and optical Fe ii lines originate from the outer part of the broad line region, the so-called intermediate line region. (ii) The unexplained anticorrelations of the optical Fe ii equivalent width (EW Fe iiopt) versus EW [O iii] 5007 Å and EW Fe iiopt versus FWHM Hβ have not been detected for the UV Fe ii lines. (iii) The significant averaged redshift in the UV Fe ii lines, which is not present in optical Fe ii, indicates an inflow in the UV Fe ii emitting clouds, and probably their asymmetric distribution. (iv) Also, we confirm the anticorrelation between the intensity ratio of the optical and UV Fe ii lines and the FWHM of Hβ, and we find the anticorrelations of this ratio with the widths of Mg ii 2800 Å, optical Fe ii, and UV Fe ii. This indicates a very important role for the column density and microturbulence in the emitting gas. We discuss the starburst activity in high-density regions of young AGNs as a possible explanation of the detected optical Fe ii correlations and intensity line ratios of the UV and optical Fe ii lines.
In-person school reopening and the spread of SARS-CoV-2 during the second wave in Spain

We investigate the effects of school reopening on the evolution of COVID-19 infections during the second wave in Spain studying both regional and age-group variation within an interrupted time-series design. Spain's 17 Autonomous Communities reopened schools at different moments in time during September 2020. We find that in-person school reopening correlates with a burst in infections in almost all those regions. Data from Spanish regions gives a further leverage: in some cases, pre-secondary and secondary education started at different dates. The analysis of those cases does not allow to conclude whether reopening one educational stage had an overall stronger impact than the other. To provide a plausible mechanism connecting school reopening with the burst in contagion, we study the Catalan case in more detail, scrutinizing the interrupted time-series patterns of infections among age-groups and the possible connections between them. The stark and sudden increase in contagion among older children (10–19) just after in-person school reopening appears to drag the evolution of other age-groups according to Granger causality. This might be taken as an indirect indication of household transmission from offspring to parents with important societal implications for the aggregate dynamics of infections.