Toward Feature-Preserving Vector Field Compression

The objective of this work is to develop error-bounded lossy compression methods to preserve topological features in 2D and 3D vector fields. Specifically, we explore the preservation of critical points in piecewise linear and bilinear vector fields. We define the preservation of critical points as, without any false positive, false negative, or false type in the decompressed data, (1) keeping each critical point in its original cell and (2) retaining the type of each critical point (e.g., saddle and attracting node). The key to our method is to adapt a vertex-wise error bound for each grid point and to compress input data together with the error bound field using a modified lossy compressor. Our compression algorithm can be also embarrassingly parallelized for large data handling and in situ processing. We benchmark our method by comparing it with existing lossy compressors in terms of false positive/negative/type rates, compression ratio, and various vector field visualizations with several scientific applications

Characterization of linear viscoelastic, nonlinear viscoelastic and damage stages of asphalt mixtures

It has been demonstrated that asphalt mixtures experienced linear viscoelastic stage, nonlinear viscoelastic stage and damage stage when subjected to controlled-strain repeated direct-tension (RDT) tests with increasing strain levels. However, the linear viscoelastic properties of asphalt mixtures are usually muddled up with their nonlinear viscoelastic properties. These confusions directly lead to the incorrect determination of the pseudostrains and dissipated pseudostrain energies (DPSEs) in the nonlinear viscoelastic stage and damage stage. This study investigated the material properties of fine aggregate mixture (FAM) specimens in all three stages. These three stages were differentiated and characterized in terms of the viscoelastic stress, pseudostrain and DPSE. The definitions of viscoelastic stress, reference modulus and pseudostrain were rigorously established to assure that the material properties in the linear viscoelastic stage were the reference properties and that the sole linear viscoelastic effect was eliminated when determining the pseudostrain and DPSE in the three stages. The characteristics of the DPSE in the three stages were found to be: (1) the DPSE of any loading cycle was zero in the linear viscoelastic stage; (2) in the nonlinear viscoelastic stage, the DPSE of each loading cycle remained approximately the same with the growth of the number of loading cycles, and the DPSE increased to a larger value when the strain level of the RDT test increased to a higher level; (3) in the damage stage, the DPSE of the loading cycle increased as the number of loading cycles increased. This study strictly distinguished the linear viscoelasticity from the nonlinear viscoelasticity of the asphalt mixtures, which is critical for the accurate determination of the DPSE spent in overcoming the nonlinear viscoelasticity and in developing damages, such as cracking and permanent deformation, in the asphalt mixtures

Development and validation of novel immune-inflammation-based clinical predictive nomograms in HER2-negative advanced gastric cancer

PurposeTo explore the predictive value of multiple immune-inflammatory biomarkers including serum VEGFA and systemic immune-inflammation index (SII) in HER2-negative advanced gastric cancer (AGC) and establish nomograms for predicting the first-line chemotherapeutic efficacy, progression-free survival (PFS) and overall survival (OS) of patients with this fatal disease.MethodsFrom November 2017 to April 2022, 102 and 34 patients with a diagnosis of HER2-negative AGC at the First Affiliated Hospital of Bengbu Medical College were enrolled as development and validation cohorts, respectively. Univariate and multivariate analyses were performed to evaluate the clinical value of the candidate indicators. The variables were screened using LASSO regression analysis. Predictive models were developed using significant predictors and are displayed as nomograms.ResultsBaseline VEGFA expression was significantly higher in HER2-negative AGC patients than in nonneoplastic patients and was associated with malignant serous effusion and therapeutic efficacy (all p<0.001). Multivariate analysis indicated that VEGFA was an independent predictor for first-line therapeutic efficacy and PFS (both p<0.01) and SII was an independent predictor for first-line PFS and OS (both p<0.05) in HER2-negative AGC patients. The therapeutic efficacy model had an R2 of 0.37, a Brier score of 0.15, and a Harrell’s C-index of 0.82 in the development cohort and 0.90 in the validation cohort. The decision curve analysis indicated that the model added more net benefits than VEGFA assessment alone. The PFS/OS models had Harrell’s C-indexes of 0.71/0.69 in the development cohort and 0.71/0.62 in the validation cohort.ConclusionThe established nomograms integrating serum VEGFA/SII and commonly available baseline characteristics provided satisfactory performance in predicting the therapeutic efficacy and prognosis of HER2-negative AGC patients

Investigation of kinetic compensation effect in lignocellulosic biomass torrefaction: Kinetic and thermodynamic analyses

The kinetic compensation effect between the activation energy and the pre-exponential factor has extensively existed in the thermochemical conversion processes of lignocellulosic biomass. The research on the kinetic compensation effect in lignocellulosic biomass torrefaction has been insufficient yet. The torrefaction of the pinewood sample was experimentally investigated by thermogravimetric analysis (TGA) at five isothermal temperatures of 220, 250, 265, 280 and 295 °C. The reaction order model was used to analyze the isothermal torrefaction kinetics of lignocellulosic biomass, and the results showed that many sets of activation energy and pre-exponential factor could describe the experimental data at each temperature equally well and they excellently satisfied the kinetic compensation effect relationship. The linear regression lines of the kinetic compensation effect points at different temperatures intersected at one point, whose values corresponded to the obtained optimal kinetic parameters. A kinetic-compensation-effect-based method was developed and verified to determine the kinetic parameters of isothermal biomass torrefaction. Based on the optimal kinetic parameters, the thermodynamic parameters (including Gibbs free energy, enthalpy, and entropy) of biomass torrefaction processes at various temperatures were calculated and analyzed

The large area detector onboard the eXTP mission

The Large Area Detector (LAD) is the high-throughput, spectral-timing instrument onboard the eXTP mission, a flagship mission of the Chinese Academy of Sciences and the China National Space Administration, with a large European participation coordinated by Italy and Spain. The eXTP mission is currently performing its phase B study, with a target launch at the end-2027. The eXTP scientific payload includes four instruments (SFA, PFA, LAD and WFM) offering unprecedented simultaneous wide-band X-ray timing and polarimetry sensitivity. The LAD instrument is based on the design originally proposed for the LOFT mission. It envisages a deployed 3.2 m2 effective area in the 2-30 keV energy range, achieved through the technology of the large-area Silicon Drift Detectors - offering a spectral resolution of up to 200 eV FWHM at 6 keV - and of capillary plate collimators - limiting the field of view to about 1 degree. In this paper we will provide an overview of the LAD instrument design, its current status of development and anticipated performance

Global Trends of Lipid Metabolism Research in Epigenetics Field: A Bibliometric Analysis from 2012–2021

Most common diseases are characterized by metabolic changes, among which lipid metabolism is a hotspot. Numerous studies have demonstrated a strong correlation between epigenetics and lipid metabolism. This study of publications on the epigenetics of lipid metabolism searched in the Web of Science Core Collection from 2012 to 2022, and a total of 3685 publications were retrieved. Much of our work focused on collecting the data of annual outputs, high-yielding countries and authors, vital journals, keywords and citations for qualitative and quantitative analysis. In the past decade, the overall number of publications has shown an upward trend. China (1382, 26.69%), the United States (1049, 20.26%) and Italy (206, 3.98%) were the main contributors of outputs. The Chinese Academy of Sciences and Yale University were significant potential cooperation institutions. Articles were mainly published in the “International Journal of Molecular Sciences”. In addition to typical liver-related diseases, “ferroptosis”, “diabetes” and “atherosclerosis” were identified as potential research topics. “NF-κB” and “oxidative stress” were referred to frequently in publications. METTL3 and ALKBH5 were the most discussed m6A-related enzymes in 2022. Our study revealed research hotspots and new trends in the epigenetics of lipid metabolism, hoping to provide significant information and inspiration for researchers to further explore new directions

FMDL: Federated Mutual Distillation Learning for Defending Backdoor Attacks

Federated learning is a distributed machine learning algorithm that enables collaborative training among multiple clients without sharing sensitive information. Unlike centralized learning, it emphasizes the distinctive benefits of safeguarding data privacy. However, two challenging issues, namely heterogeneity and backdoor attacks, pose severe challenges to standardizing federated learning algorithms. Data heterogeneity affects model accuracy, target heterogeneity fragments model applicability, and model heterogeneity compromises model individuality. Backdoor attacks inject trigger patterns into data to deceive the model during training, thereby undermining the performance of federated learning. In this work, we propose an advanced federated learning paradigm called Federated Mutual Distillation Learning (FMDL). FMDL allows clients to collaboratively train a global model while independently training their private models, subject to server requirements. Continuous bidirectional knowledge transfer is performed between local models and private models to achieve model personalization. FMDL utilizes the technique of attention distillation, conducting mutual distillation during the local update phase and fine-tuning on clean data subsets to effectively erase the backdoor triggers. Our experiments demonstrate that FMDL benefits clients from different data, tasks, and models, effectively defends against six types of backdoor attacks, and validates the effectiveness and efficiency of our proposed approach

Distribution Characteristics of Microplastics in Surface Seawater off the Yangtze River Estuary Section and Analysis of Ecological Risk Assessment

Microplastics are widespread in the oceans as a new type of pollutant. Due to the special geographical environment characteristics, the Yangtze River estuary region become hotspot for microplastics research. In 2017 and 2019, surface seawater microplastics samples were collected from five stations off the Yangtze River estuary during four seasons (spring, summer, autumn, and winter). The abundance and characteristics of microplastics in seawater were researched. The results showed that microplastics widely existed in surface seawater; the average abundance of microplastics in seawater was (0.17 ± 0.14) items/m3 (0.00561 ± 0.00462) mg/m3; and accounting for 80% of the total plastic debris, the abundance of microplastics was at moderately low levels compared to national and international studies. The particle size of most microplastics was between 1 mm to 2 mm, accounting for 36.1% of the total microplastics. The main shapes of microplastics were fiber, flake, and line, accounting for 39.5%, 28.4%, and 20.8%, respectively. Polypropylene, polyethylene terephthalate, and polyethylene were the main components of microplastics, accounting for 41.0%, 25.1%, and 24.9%, respectively. Yellow, green, black, and transparent were the most common colors, accounting for 21.9%, 19.6%, 16.5%, and 15.7%, respectively. This study shows that the spatial distribution of microplastics in the surface waters off the Yangtze River estuary shows a decreasing trend from nearshore to farshore due to the influence of land-based inputs, hydrodynamics, and human activities; the distribution of microplastics has obvious seasonal changes, and the level of microplastic pollution is higher in summer. The potential ecological risk of microplastics in the surface waters off the Yangtze River estuary is relatively small