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Liping Shen,1,* Linping Chen,1,* Hongbo Chi,1 Lifei Luo,1 Jinsu Ruan,1 Xinzhuan Zhao,1 Yi Jiang,1 Tao-Hsin Tung,2 Hongguo Zhu,1 Kai Zhou,1 Bo Shen,1 Jiaqin Xu1 1Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China; 2Evidence-Based Medicine Center, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jiaqin Xu; Bo Shen, Department of Clinical Laboratory, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Taizhou, People’s Republic of China, Tel +86-13968607148 ; +86 13586121278, Email xujq@enzemed.com; shenb@enzemed.comPurpose: Information about dynamic changes occurring in the parameters and morphology of erythrocytes and platelets during the coronavirus disease 2019 (COVID-19) infection and convalescence is scarce. To explore potential associations between dynamic erythrocyte and platelet parameters, morphological changes, and the course or severity of the disease is essential.Patients and Methods: From January 17th, 2020, to February 20th, 2022, we followed up on 35 patients with non-severe and 11 patients with severe COVID-19 following their discharge. We collected clinical features, dynamic complete blood count (CBC), and peripheral blood smears (PBS) and analyzed parameter and morphological changes of erythrocytes and platelets depending on the course or severity of the disease. The course of the disease included four periods, namely onset (T1), discharge (T2), 1-year follow-up (T3), and 2-year follow-up (T4).Results: Red blood cell (RBC) counts and hemoglobin were the lowest in T2, followed by T1, and lower in T1 and T2 than in T3 and T4. Inversely, the red blood cell distribution width (RDW) was the highest in T2, followed by T1, and higher than in T3 and T4. Compared to non-severe patients, the platelet of severe patients was lower in T1 and T2. In contrast, the mean platelet volume (MPV) and platelet distribution width (PDW) tended to be higher in severe patients. Similarly, anisocytosis was more common in peripheral blood smears at early stages and in severe patients. Finally, large platelets were more common in severe patients.Conclusion: Anisocytosis of erythrocytes and large platelets are found in patients with severe COVID-19, these changes may help primary hospitals to identify patients with a high risk of severe COVID-19 at an early stage.Keywords: erythrocytes, blood platelets, COVID-19

This cross-culture project examines whether thinking about karma allows people to offload punitive intentions and behaviours

Supplementary Material 1

Gravitational Waves (GWs) from coalescing binaries carry crucial information about their component sources, like mass, spin and tidal effects. This implies that the analysis of GW signals from binary neutron star mergers can offer unique opportunities to extract information about the tidal properties of NSs, thereby adding constraints to the NS equation of state. In this work, we use Deep Learning (DL) techniques to overcome the computational challenges confronted in conventional methods of matched-filtering and Bayesian analyses for signal-detection and parameter-estimation. We devise a DL approach to classify GW signals from binary black hole and binary neutron star mergers. We further employ DL to analyze simulated GWs from binary neutron star merger events for parameter estimation, in particular, the regression of mass and tidal deformability of the component objects. The results presented in this work demonstrate the promising potential of DL techniques in GW analysis, paving the way for further advancement in this rapidly evolving field. The proposed approach is an efficient alternative to explore the wealth of information contained within GW signals of binary neutron star mergers, which can further help constrain the NS EoS., Comment: 14 pages, 11 figures

The centrality determination and the estimated fluctuations of number of participant nucleons $N_{part}$ in Au-Au collisions at 1.23 $A$GeV beam kinetic energy suffers from severe model dependencies. Comparing the Glauber Monte Carlo (MC) and UrQMD transport models, it is shown that $N_{part}$ is a strongly model dependant quantity. In addition, for any given centrality class, Glauber MC and UrQMD predicts drastically different $N_{part}$ distributions. The impact parameter $b$ and the number of charged particles $N_{ch}$ on the other hand are much more correlated and give an almost model independent centrality estimator. It is suggested that the total baryon number balance, from integrated rapidity distributions, can be used instead of $N_{part}$ in experiments. Preliminary HADES data show significant differences to both, UrQMD simulations and STAR data in this respect., Comment: 11 pages, 9 figures

We study the momentum and centrality dependence of the non-prompt $J/ψ$ nuclear modification factors ($R_{AA}$), which comes from the $B$ hadrons decay, in Pb-Pb collisions at the Large Hadron Collider. Bottom quarks are produced in the parton hard scatterings and suffer energy loss in the quark-gluon plasma and the hadronic gas, where the spatial and time evolution of the medium is described with the hydrodynamic equations. Medium-induced elastic scatterings and the radiation in bottom quarks are included in the energy loss of bottom quarks. The hadronization process of bottom quarks is described with the instantaneous coalescence model. After considering both cold and hot nuclear matter effects in Pb-Pb collisions at $\sqrt{s_{NN}}=5.02$ TeV, we calculated the $R_{AA}$ and also the elliptic flows of non-prompt $J/ψ$ from the decay of $B$ mesons at different centralities and transverse momentum bins. The $R_{AA}$ and $v_2$ of non-prompt $J/ψ$ sensitive to the hot medium reflect and centrality supply an opportunity to study the bottom quarks energy loss in the hot medium., 7 pages, 6 figures

Though being seemingly disparate and with relatively new intersection, high energy nuclear physics and machine learning have already begun to merge and yield interesting results during the last few years. It's worthy to raise the profile of utilizing this novel mindset from machine learning in high energy nuclear physics, to help more interested readers see the breadth of activities around this intersection. The aim of this mini-review is to introduce to the community the current status and report an overview of applying machine learning for high energy nuclear physics, to present from different aspects and examples how scientific questions involved in high energy nuclear physics can be tackled using machine learning., Comment: 30 pages, 20 figures, mini-review

Based on conjoint survey experiments, we intend to identify discriminatory attitudes against Zainichi Koreans among Japanese citizens. The Zainichi Koreans are ethnic Koreans who have special permanent residency status in Japan. Most of them were born in Japan and speak only Japanese. Nevertheless, they are often discriminated against at times of employment, particularly when they use their ethnic names rather than their unofficial Japanese names.

Additional file 1: Table S1: List of monofocal aspheric intraocular lenses implanted in patients undergoing cataract surgery.

It is shown in Ferrari \cite{Ferrari-1993CMP} that if $[0, T^*)$ is the maximal time interval of existence of a smooth solution of the incompressible Euler equations in a bounded, simply-connected domain in $\mathbb{R}^3$, then $\int_0^{T^*}\|\omega(t,\cdot)\|_{L^\infty}dt=+\infty$, where $\omega$ is the vorticity of the flow. Ferrari's result generalizes the classical Beale-Kato-Majda \cite{BKM-1984CMP}'s breakdown criterion in the case of a bounded fluid domain. In this manuscript, we show a breakdown criterion for a smooth solution of the Euler equations describing the motion of an incompressible fluid in a bounded domain in $\mathbb{R}^3$ with a free surface boundary. The fluid is under the influence of surface tension. In addition, we show that our breakdown criterion reduces to the one proved by Ferrari \cite{Ferrari-1993CMP} when the free surface boundary is fixed. Specifically, the additional control norms on the moving boundary will either become trivial or stop showing up if the kinematic boundary condition on the moving boundary reduces to the slip boundary condition., Comment: Added a new section (Section 5) on an alternative breakdown criterion without loss of regularity. 29 pages. Comments are welcome

Although the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been increasing since the past decade, the proportion of AEG cases in two previous clinical trials (ACTS-GC and CLASSIC) that investigated the efficacy of adjuvant chemotherapy was relatively small. Therefore, whether AEG patients can benefit from adjuvant chemotherapy remains unclear.Patients who were diagnosed with pathological stage II/III, Siewert II/III AEG, and underwent curative surgery at three high-volume institutions were assessed. Clinical outcomes were analyzed by using Kaplan-Meier curves, log-rank test, and Cox regression model. Propensity score matching (PSM) was used to reduce the selection bias.A total of 927 patients were included (the chemotherapy group: 696 patients; the surgery-only group: 231 patients). The median follow-up was 39.0 months. The 5-year overall survival was 63.1% (95% confidence interval [CI]: 59.0-67.6%) for the chemotherapy group and 50.2% in the surgery-only group (hazard ratio [HR] = 0.69, 95% CI: 0.54-0.88; p = 0.003). The 5-year, disease-free survival was 35.4% for the chemotherapy group and 16.6% for the surgery-only group (HR = 0.66, 95% CI: 0.53-0.83; p0.001). After PSM, the survival benefit of adjuvant chemotherapy for AEG was maintained. Multivariate analysis for overall survival and disease-free survival further demonstrated the survival benefit of adjuvant chemotherapy, with HRs of 0.63 (p0.001) and 0.52 (p0.001), respectively.Postoperative adjuvant chemotherapy was associated with improved overall survival and disease-free survival in patients with operable stage II or III AEG after D2 gastrectomy.

In recent years, immune checkpoint inhibitors (ICIs), represented by PD-1/PD-L1 monoclonal antibodies, have become a research hotspot in the field of oncology treatment. Immunotherapy has shown significant survival advantages in a variety of solid tumors. However, the phenomenon of hyperprogressive disease (HPD) in some patients treated with immunotherapy is gradually getting more attention and focus. An early understanding of the characteristics of HPD is crucial to optimize the treatment strategy. We report a patient with unresectable stage III lung adenocarcinoma who developed HPD with metastasis during consolidation therapy with durvalumab after chemoradiation. To further investigate the potential mechanism of HPD after anti-PD-L1 treatment, primary lung baseline tissue, baseline plasma, post-immunotherapy plasma, and liver metastasis samples of the patient were detected via next-generation sequencing (NGS). Then, multiplex immunohistochemistry (mIHC) was performed on primary lung baseline tissue and liver metastasis samples. KRAS and p.G12C were identified as the major driver mutation genes. With a low tumor mutation burden (TMB) value, the patient presented a very high percentage of CD8+PD-L1+ T cells that infiltrated in the baseline tissue, with 95.5% of all CD8+ cells expressing PD-L1 and a low percentage of CD8+ T cells expressing PD-1. After the emergence of HPD from immunotherapy, liver metastases were similarly infiltrated with an extremely high proportion of CD8+PD-L1+ T cells, with 85.6% of all CD8+ cells expressing PD-L1 and almost no CD8+ T cells expressing PD-1. The extreme infiltration of PD-L1+CD8+ T cells in the tumor microenvironment of baseline tissue might be associated with the aggressive tumor growth observed in anti-PD-L1 treatment for related HPD and could be a potential biomarker for HPD development.

The spaceborne synthetic aperture radar (SAR) sparse flight 3-D imaging technology through multiple observations of the cross-track direction is designed to form the cross-track equivalent aperture, and achieve the third dimensionality recognition. In this paper, combined with the actual triple star orbits, a sparse flight spaceborne SAR 3-D imaging method based on the sparse spectrum of interferometry and the principal component analysis (PCA) is presented. Firstly, interferometric processing is utilized to reach an effective sparse representation of radar images in the frequency domain. Secondly, as a method with simple principle and fast calculation, the PCA is introduced to extract the main features of the image spectrum according to its principal characteristics. Finally, the 3-D image can be obtained by inverse transformation of the reconstructed spectrum by the PCA. The simulation results of 4.84 km equivalent cross-track aperture and corresponding 1.78 m cross-track resolution verify the effective suppression of this method on high-frequency sidelobe noise introduced by sparse flight with a sparsity of 49% and random noise introduced by the receiver. Meanwhile, due to the influence of orbit distribution of the actual triple star orbits, the simulation results of the sparse flight with the 7-bit Barker code orbits are given as a comparison and reference to illuminate the significance of orbit distribution for this reconstruction results. This method has prospects for sparse flight 3-D imaging in high latitude areas for its short revisit period.

High-sulfur waste residues (HSWR) is a typical byproduct produced in the printing and dyeing industry that has hazardous properties, such as flammability and reactivity, etc. It is of great significance for the directional and harmless treatment of waste residues in the later stage on the research in-depth of the occurrence characteristics of each component in HSWR. In this paper, the combinatorial analysis method is employed to perform in-depth research on the phase composition, surface chemical situation of element, and the occurrence state of functional groups of the waste residue from multiple perspectives. The results show that the organic and inorganic components in HSWR are intricately interwoven, and exhibit significant thermal instability at high temperatures, with a maximum weight less of 86.66%. Carbon mainly exists in the states of C-H/C-OH/C-C, C-O/C-NH2, and C=O/C-N/C-S/CHx and constitutes the main chain of the carboxylic ring. Sulfur mainly occurs in three forms, namely, amorphous aggregated sulfur, sulfur-containing inorganic salts such as sulfate, and nitrogen-heterocyclic organic compounds containing sulfhydryl groups and methyl sulfur groups. These organic compounds constitute branch chains of the organic phase, and combine with metal cations through hydroxyl or carboxyl groups, and deposit on the surface of inorganic agglomerated sulfur. This wrapping structure increases the stability of volatile compounds in the slag and increases the difficulty of sulfur and chlorine removal. These findings provide a material basis for the later development of safe and effective HSWR disposal techniques.

As an important application form of immersive multimedia services, free-viewpoint video(FVV) enables users with great immersive experience by strong interaction. However, the computational complexity of virtual view synthesis algorithms poses a significant challenge to the real-time performance of an FVV system. Furthermore, the individuality of user interaction makes it difficult to serve multiple users simultaneously for a system with conventional architecture. In this paper, we novelly introduce a CNN-based view interpolation algorithm to synthesis dense virtual views in real time. Based on this, we also build an end-to-end live free-viewpoint system with a multi-user oriented streaming strategy. Our system can utilize a single edge server to serve multiple users at the same time without having to bring a large view synthesis load on the client side. We analyze the whole system and show that our approaches give the user a pleasant immersive experience, in terms of both visual quality and latency., Comment: 10 pages, 7 figures

University teachers are the core of university teaching and scientific research construction and an important link of double first-class construction. With the increasingly fierce academic competition among colleges and universities, the resignation behavior of college teachers is increasing, which has brought great impact on the construction of talents and discipline development in colleges and universities. The survey found that the departure of college teachers is not an isolated phenomenon, but a time-consuming process. Although the turnover tendency of college teachers has not evolved into resignation behavior in most cases, the resignation tendency of college teachers is always accompanied by negative psychology, complaints, and perfunctory work. These bad phenomena have brought double negative effects to colleges and universities and teachers themselves. According to this, psychological analysis of the turnover tendency of college teachers is conducive to building a benign flow mechanism for college teachers, thus supporting the long-term development of colleges and universities.

Xiaojie Bi,1,2,&ast; Ying Zhang,2,&ast; Juan Pan,1 Chaochao Chen,2 Yufen Zheng,2 Jing Wang,2 Mengyuan Chen,2 Kai Zhou,2 Tao-Hsin Tung,3 Bo Shen,1,2 Donglian Wang1,2 1Department of Laboratory Medicine, Taizhou Hospital, Zhejiang University, Linhai, 317000, People’s Republic of China; 2Department of Laboratory Medicine, Taizhou Hospital of Zhejiang Province Affiliated to Wenzhou Medical University, Linhai, 317000, People’s Republic of China; 3Evidence-Based Medicine Center, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Linhai, 317000, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Donglian Wang; Bo Shen, Department of Laboratory Medicine, Taizhou Hospital of Zhejiang Province affiliated to Wenzhou Medical University, No. 150, Ximen Street, Taizhou, 317000, People’s Republic of China, Tel +86 13757693182 ; +86 13586121278, Email wangdl@enzemed.com; shenb@enzemed.comPurpose: We evaluated the differences between patients with SARS-CoV-2 Omicron variant infections and Fever outpatients, so that prevention and control measures can be taken in time.Patients and Methods: This study retrospectively analyzed 65 patients with SARS-CoV-2 Omicron variant. Sixty-nine age- and sex-matched Fever outpatients were enrolled during the same period of time. We also reanalyzed data from 81 SARS-CoV-2 Wild-Type-infected patients. We compared the clinical characteristics and initial indexes of routine tests among the 3 groups.Results: A total of 93.8% of the patients with Omicron infections had clinical symptoms, and the major symptoms were cough, fever and pharyngalgia. Pharyngalgia was a specific manifestation in Omicron group compared to Wild-Type group. The white blood cell of the Omicron group was lower than that of the Fever group [5.0 (3.6– 6.1) vs 10.1 (7.6– 12.9) × 109/L, P < 0.001]. The neutrophil count in Omicron group was lower than that in Fever and Wild-Type group [2.6 (1.8– 3.9) vs 8.1 (5.9– 10.9), P < 0.001; 2.6 (1.8– 3.9) vs 3.4 (2.5– 4.7) × 109/L, P < 0.001]. The white blood cell and neutrophil counts were lower in Omicron group than in the Fever group. The top 5 major symptoms were fever, cough, pharyngalgia, headache and expectoration.Conclusion: There are differences between the patients with Omicron infections and Fever outpatients, both in clinical manifestations and initial routine hematology indicators. We hope to provide some clues for early identification combined with a history of living in the epidemic area.Keywords: SARS-CoV-2 Omicron variant, fever outpatient, clinical manifestations, routine hematology indicators

OBJECTIVE To compare the inhibition of lymphocyte-activation gene 3 (LAG3) plus programmed cell death 1 (PD-1) versus the inhibition of cytotoxic T-lymphocyte antigen 4 (CTLA-4) plus PD-1 in patients with previously untreated advanced melanoma.DESIGN A meta-analysis of individual participant data (IPD).DATA SOURCES PubMed, Web of Science and Embase were searched from January 1, 2015, to January 14, 2022, for eligible studies.ELIGIBILITY CRITERIA FOR STUDY SELECTION Data from randomized controlled trials reporting on the use of dual LAG3-PD1 inhibitors or dual CTLA4-PD1 inhibitors which assigned PD1 inhibitor alone as their control arm and provided corresponding Kaplan-Meier (KM) curves of treatment outcomes for previously untreated advanced melanoma were retrieved. METHODS The IPD data were extracted from the KM plots using a graphical reconstructive algorithm. Log-rank, Cox proportional hazard model, Bayesian hierarchical model with time-varying hazard ratio (HR) effect, and restricted mean survival time (RMST) were performed to estimate survival benefits. The primary endpoint was progression-free survival.RESULTS The CheckMate-067 (N = 630) and RELATIVITY-047 (N = 714) trials were included for analysis. The graphical reconstructive algorithm showed that IPD had similar HRs and log-rank values as the original plots. The HR of nivolumab-relatlimab (LAG3 inhibitor) versus nivolumab-ipilimumab (CTLA4 inhibitor) was 1.19 (95% confidence interval [CI] 0.96 to1.48). The 24-months RMST of nivolumab-relatlimab versus nivolumab alone was 2.35 (95% CI 0.77 to 3.94) months, compared with 1.87 (95% CI 0.25-3.49) months for nivolumab-ipilimumab versus nivolumab. The Bayesian hierarchical model showed that patients treated with nivolumab-relatlimab had earlier PFS benefits than those with nivolumab-ipilimumab. Grade 3 or 4 treatment-related adverse events occurred in 18.9% of patients using nivolumab-relatlimab and 55.0% of patients using nivolumab-ipilimumab.CONCLUSION These findings suggest that the PFS of LAG3-PD1 and CTLA4-PD1 inhibition were similar and that LAG3-PD1 inhibition tended to exhibit earlier survival benefit and lesser TRAEs.

Weakly cemented soft rock has a great influence on the deformation and stability of roadway in the process of roadway excavation. There are different requirements for the excavation and support of ...

The effect of shot peening (SP) on the fatigue life of S42200 steel at room and elevated temperature is investigated. The fatigue test is carried out on a high temperature rotating bending tester. Surface integrity characterization is used to study the effect of SP on surface properties. Furthermore, Finite Element Method (FEM) combined with a fatigue damage model, namely Zheng Equation, is proposed to predict the fatigue life. The results show that SP effectively improves the fatigue life of S42200 steel under all temperatures. However, at lower temperature, higher strength SP leads to higher fatigue resistance, while at higher temperature, lower strength SP leads to higher fatigue resistance. This can be explained by the competitive effect of surface roughness and compressive residual stress (CRS) relaxation on the local stress concentration. This research can be a good guide to the application of SP at different temperatures.

Airway tree segmentation plays a pivotal role in chest computed tomography (CT) analysis tasks such as lesion localization, surgical planning, and intra-operative guidance. The remaining challenge is to identify small bronchi correctly, which facilitates further segmentation of the pulmonary anatomies. A three-dimensional (3D) multi-scale feature aggregation network (MFA-Net) is proposed against the scale difference of substructures in airway tree segmentation. In this model, the multi-scale feature aggregation (MFA) block is used to capture the multi-scale context information, which improves the sensitivity of the small bronchi segmentation and addresses the local discontinuities. Meanwhile, the concept of airway tree partition is introduced to evaluate the segmentation performance at a more granular level. Experiments were conducted on a dataset of 250 CT scans, which were annotated by experienced clinical radiologists. Through the airway partition, we evaluated the segmentation results of the small bronchi compared with the state-of-the-art methods. Experiments show that MFA-Net achieves the best performance in the Dice similarity coefficient (DSC) in the intra-lobar airway and improves the true positive rate (TPR) by 7.59% on average. Besides, in the entire airway, the proposed method achieves the best results in DSC and TPR scores of 86.18% and 79.31%, respectively, with the consequence of higher false positives. The MFA-Net is competitive with the state-of-the-art methods. The experiment results indicate that the MFA block improves the performance of the network by utilizing multi-scale context information. More accurate segmentation results will be more helpful in further clinical analysis.

Rectification is a critical process for speckle projection systems to ensure reliable image matching in producing a depth map. However, few studies have discussed it up to the present. In this article, we present a flexible but robust approach to address this issue. It mainly consists of two steps: calibration and rectification. The calibration step takes one or several pairs of images of the projected speckle pattern on a plane to estimate a unit vector indicating the direction of the line where emitter center lies on. The rectification step virtually rotates the camera based on this vector to obtain rectified images. Given camera intrinsic parameters, this approach only needs a minimum configuration consisting of two freely captured speckle images of a planar surface to complete system rectification, which makes it particularly suited for the case with no access to the internal projected speckle pattern. Elaborate experiments on real speckle images and synthetic images from different camera poses are conducted, demonstrating the effectiveness and robustness of the proposed approach. Furthermore, we also demonstrate that when the internal pattern is recovered from the rectified images, it reaches an accuracy comparable with the ones from the best state-of-the-art methods in performing a stereo matching, but with a much simpler operation to obtain.

The contribution of histone mark redistribution to the age-induced decline of endogenous neuroprotection remains unclear. In this study, we used an intracerebral hemorrhage (ICH)-induced acute brain injury rat model to study the transcriptional and chromatin responses in 13- and 22-month-old rats. Transcriptome analysis (RNA-seq) revealed that the expression of neuroinflammation-associated genes was systematically upregulated in ICH rat brains, irrespective of age. Further, we found that interferon-γ (IFN-γ) response genes were activated in both 13- and 22-month-old rats. Anti-IFN-γ treatment markedly reduced ICH-induced acute brain injury in 22-month-old rats. At the chromatin level, ICH induced the redistribution of histone modifications in the promoter regions, especially H3K4me3 and H3K27me3, in neuroinflammation-associated genes in 13- and 22-month-old rats, respectively. Moreover, ICH-induced histone mark redistribution and gene expression were found to be correlated. Collectively, these findings demonstrate that histone modifications related to gene expression are extensively regulated in 13- and 22-month-old rats and that anti-IFN-γ is effective for ICH treatment, highlighting the potential of developing therapies targeting histone modifications to cure age-related diseases, including brain injury and neuroinflammation.

Within substations installed with flexible ac transmission systems, the magnetic flux leakage (MFL) generated by air core reactors in static var compensator (SVC) can be very high. To reduce the influence of the high magnetic field, an optimal suppression method is selected based on fuzzy comprehensive evaluation. First, a series of onsite measurements are performed around the reactors in the SVC. From the measurement results, the low-voltage cables, dc system, grounding grid, and magnetic flux density around the air core reactors are seriously affected by the MFL generated by the air core reactors with currents of a few kiloamperes. Then, according to the actual parameters of the air core reactors, a three-dimensional simulation model is constructed using the finite-element method (FEM) to calculate the magnetic flux density and some parameters related to the magnetic field. Moreover, four different suppression methods are proposed to suppress the MFL influence. Due to the multiple aspects affected by MFL, it is always difficult to make a quantitative comparison for the suppression methods based on previous research. For this reason, a fuzzy comprehensive evaluation method based on a linear evaluation model is proposed to quantitatively compare the suppression methods by using the suppression effect value δ. In a comparison of different suppression methods, the aluminum plate shielding with proper parameters has prove to be an optimal method for achieving a comprehensive suppression effect. The modeling and evaluation methods presented in this article are both valuable to solve the complex MFL influence problem in different SVC-based substations.

It is critical to learn and obtain a good distance metric that can precisely measure the distance between samples in imbalanced data. However, traditional metric learning algorithms, e.g. large margin nearest neighbour (LMNN), information-theoretic metric learning, neighbourhood component analysis, do not take imbalanced distributions of classes into consideration. The traditional methods are apt to be affected by the majority samples, so those important minority samples are often ignored during the learning phase of distance metrics matrix, this may gravely confuse decision-making systems on classifying samples. In order to resolve this problem, the authors propose a novel metric-learning method named balancing large margin nearest neighbour (BLMNN) for imbalanced data. BLMNN can improve the objective function according to the distribution of classes, which treats the minority and majority classes equally during the optimisation process. Thus, the contribution of minority class is taken into full consideration, which can greatly improve the accuracy of classification. Substantial experiments were performed on real-world imbalanced datasets. The experiments results in various evaluation indexes of the proposed method comparing it with other metric-learning methods show the advantages of the proposed method.

Background & Aim: Optimal approaches for video-assisted thoracoscopic surgery (VATS) resection of anterior mediastinal diseases remain controversial. The present study was designed to compare subxiphoid approach with lateral intercostal approach, together with perioperative indices.Methods: Patients diagnosed with anterior mediastinal diseases between January 1, 2018 and October 31, 2019 were prospectively randomly assigned to two groups, to receive lateral intercostal approach vs. subxiphoid approach for VATS resection. Intraoperation PaCO2, SaO2, PaO2 and circulation changes were recorded. Perioperative outcomes, including clinical and surgical parameters such as operation time and blood loss, postoperative complication, neutrophil-to-lymphocyte ratio, and postoperative pain scores were compared. Results: A total 59 patients diagnosed with anterior mediastinal tumors or myasthenia gravis underwent VATS resection. 31 patients treated with subxiphoid approach and 28 patients treated with lateral intercostal approach had comparable baseline characteristics. Intraoperation PaCO2 was increased significantly whereas SaO2 remained stable in subxiphoid group. By contrast, PaCO2 was increased significantly whereas SaO2 was decreased in lateral intercostal group, and operations were more frequently interrupted due to hypoxia or circulation disturbance during thymus dissection in the lateral intercostal approach. Compared with lateral intercostal group, patients in subxiphoid group experienced less inflammation reaction, while yielded lower pain scores and shorter postoperative hospital stay. There were no significant differences in postoperative complications between the two groups. All these patients recovered well when discharged. There were no perioperative deaths. Conclusion: Subxiphoid approach may influence pulmonary and circulation lesser than lateral intercostal approach. Procedure may be safer and easier for subxiphoid approach, as an ideal choice for anterior mediastinal diseases.

The success of graph neural networks stimulates the prosperity of graph mining and the corresponding downstream tasks including graph anomaly detection (GAD). However, it has been explored that those graph mining methods are vulnerable to structural manipulations on relational data. That is, the attacker can maliciously perturb the graph structures to assist the target nodes to evade anomaly detection. In this paper, we explore the structural vulnerability of two typical GAD systems: unsupervised FeXtra-based GAD and supervised GCN-based GAD. Specifically, structural poisoning attacks against GAD are formulated as complex bi-level optimization problems. Our first major contribution is then to transform the bi-level problem into one-level leveraging different regression methods. Furthermore, we propose a new way of utilizing gradient information to optimize the one-level optimization problem in the discrete domain. Comprehensive experiments demonstrate the effectiveness of our proposed attack algorithm BinarizedAttack., Comment: arXiv admin note: substantial text overlap with arXiv:2106.09989

The robustness of recommender systems under node injection attacks has garnered significant attention. Recently, GraphRfi, a GNN-based recommender system, was proposed and shown to effectively mitigate the impact of injected fake users. However, we demonstrate that GraphRfi remains vulnerable to attacks due to the supervised nature of its fraudster detection component, where obtaining clean labels is challenging in practice. In particular, we propose a powerful poisoning attack, MetaC, against both GNN-based and MF-based recommender systems. Furthermore, we analyze why GraphRfi fails under such an attack. Then, based on our insights obtained from vulnerability analysis, we design an adaptive fraudster detection module that explicitly considers label uncertainty. This module can serve as a plug-in for different recommender systems, resulting in a robust framework named PDR. Comprehensive experiments show that our defense approach outperforms other benchmark methods under attacks. Overall, our research presents an effective framework for integrating fraudster detection into recommendation systems to achieve adversarial robustness.

Graph Neural Networks (GNNs) are vulnerable to data poisoning attacks, which will generate a poisoned graph as the input to the GNN models. We present FocusedCleaner as a poisoned graph sanitizer to effectively identify the poison injected by attackers. Specifically, FocusedCleaner provides a sanitation framework consisting of two modules: bi-level structural learning and victim node detection. In particular, the structural learning module will reverse the attack process to steadily sanitize the graph while the detection module provides ``the focus" -- a narrowed and more accurate search region -- to structural learning. These two modules will operate in iterations and reinforce each other to sanitize a poisoned graph step by step. As an important application, we show that the adversarial robustness of GNNs trained over the sanitized graph for the node classification task is significantly improved. Extensive experiments demonstrate that FocusedCleaner outperforms the state-of-the-art baselines both on poisoned graph sanitation and improving robustness.

Additional file 1: Figure S1. Additional data related to Fig. 1. A Representative 8 sections of Hoechst staining of Cx3cr1CreER-Eyfp/wt mouse brain sequential sagittal slices, the numbers representing the location and number of EYFP��� microglia in that location, each color represents one mouse, n = 6. Figure S2. Morphology analysis. A The process to prepare topological skeleton from the original photomicrographs. The full-size maximum intensity projection images (top) were processed into binary images (middle) and then skeletonized (bottom) following the ImageJ plugin protocol. Cropped images (right) from the original full-size images (left) were shown to improve the visualization. Scale bar, 50 ��m. B The Analyze Skeleton plugin was applied, and skeletonized endpoints were tagged purple, the slab is orange, and the junction is pink. The tagged data are summarized as total length (sum of endpoints, slab, and junction) and the total number of endpoints. C The process area is represented as the convex hull area by connecting the process ends using the ImageJ polygon tool. Figure S3. Additional data related to Fig. 1. A Gating strategies of flow cytometry analyses. B EYFP��� microglia ratio of total microglia at 3 weeks, 4 weeks, 6 weeks, 9 weeks and 15 weeks old mice, n = 4, 4, 6, 4, respectively, mean �� s.d. No significant difference by one-way ANOVA. C UMAP plots from single-cell sequencing, each dot represents one cell, the color represents the expression levels of Cx3cr1. D Histogram plot of Cx3cr1. The x-axis represents Cx3cr1 expression read counts; the y-axis represents cell numbers. Figure S4. Additional data related to Fig. 2. A Graph showing relative Iba-1+ microglia at 1 day, 3 days and 7 days after the final Tam injection, respectively; n = 3���4, mean �� s.d. *p

Additional file 1. The main results of QTL identification based on Substitution lines (S1–S6; D1–D2) and recipient Xihui 18 by one way ANOVA and LSD multiple comparisons. Between groups represent the variations among all SSSLs (S1–S6), DSSLs (D1 and D2) and recipient Xihui18 comparison for each trait as grain length, chalkiness degree, panicle length, grain width, 1000-grain weight, ratio of length to width. Within groups represent variation for errors. LSD represents least significant difference multiple comparison, in which I VAR0001 is Xihui 18, J VAR0001 is substitution lines (S1–S6 and D1–D2), respectively, Mean difference (I–J) is the difference value between Xihui 18 and each substitution line. Sig. represent probability value (P) for each trait difference between each substitution line and Xihui 18. When Sig. < 0.05 represents a QTL for a certain trait existed in a SSSL (S1–S6) or DSSL.

Additional file 2. The main results of epistatic interaction between Q1 (located in i substitution segment) and Q2 (located in j substitution segment) in DSSLs (D1–D2) by two-way ANOVA. Tests of between subjects effects represent Q1, Q2 and Q1× Q2 test using DSSL containing both the i and j substitution segments and the responding SSSLi and SSSLj by two-way ANOVA, in which sig. < 0.05 for Q1 or Q2 indicate additive effects of Q1 or Q2 existed; sig. > 0.05 for Q1 or Q2 indicate no significant additive effects of Q1 or Q2 existed and “-“ was showed; sig. < 0.05 for Q1 × Q2 indicate epistatic effect of Q1 and Q2 interaction existed in the DSSL; sig. >0.05 for Q1 × Q2 indicate independent inheritance of Q1 and Q2 in the DSSL.

With the rapid development of smart manufacturing, data-driven machinery health management has been of growing attention. In situations where some classes are more difficult to be distinguished compared to others and where classes might be organised in a hierarchy of categories, current DL methods can not work well. In this study, a novel hierarchical cavitation intensity recognition framework using Sub-Main Transfer Network, termed SMTNet, is proposed to classify acoustic signals of valve cavitation. SMTNet model outputs multiple predictions ordered from coarse to fine along a network corresponding to a hierarchy of target cavitation states. Firstly, a data augmentation method based on Sliding Window with Fast Fourier Transform (Swin-FFT) is developed to solve few-shot problem. Secondly, a 1-D double hierarchical residual block (1-D DHRB) is presented to capture sensitive features of the frequency domain valve acoustic signals. Thirdly, hierarchical multi-label tree is proposed to assist the embedding of the semantic structure of target cavitation states into SMTNet. Fourthly, experience filtering mechanism is proposed to fully learn a prior knowledge of cavitation detection model. Finally, SMTNet has been evaluated on two cavitation datasets without noise (Dataset 1 and Dataset 2), and one cavitation dataset with real noise (Dataset 3) provided by SAMSON AG (Frankfurt). The prediction accurcies of SMTNet for cavitation intensity recognition are as high as 95.32%, 97.16% and 100%, respectively. At the same time, the testing accuracies of SMTNet for cavitation detection are as high as 97.02%, 97.64% and 100%. In addition, SMTNet has also been tested for different frequencies of samples and has achieved excellent results of the highest frequency of samples of mobile phones., Comment: we need update this paper

Based on the Spatial Durbin Model (SDM), this study evaluates the spatial spillover effect of PM2.5 concentration in Beijing–Tianjin–Hebei (BTH) and its surrounding areas from 2000 to 2016, analyzes its main influencing factors and verifies the Environmental Kuznets Curve (EKC). In addition, Social Network Analysis (SNA) is used to measure the regional air pollution transmission network. The results are as follows: (1) A significant inverted U-shaped EKC with spatial spillover effect between the sampled 48 cities was verified. (2) Industrial structure had both local and spillover effects on air pollution with a U-shaped curve; technological progress exerted a negative spillover effect on air pollution, while traffic evidenced positive local and spillover effects; meteorological conditions showed different impacts on air pollution. (3) Heze, Tianjin, Xingtai, Shijiazhuang and Liaocheng are the top five cities in the centrality of the air pollution correlation network, indicating air pollution in these cities have significant impacts on other cities within the network; while Sanmenxia, Weihai, Yuncheng, Langfang and Zhumadian are the bottom five cities, which indicates that the air pollution of these cities has the least correlation with other cities. The policy suggestions for 48 cities involve: building up a regional joint prevention and control mechanism, enhancing the supervision of cities located in the centrality of the air pollution correlation network, accelerating high-tech and service-oriented industrialization, encouraging technological innovation in energy conservation and environmental protection and implementing vehicle regulation.