Non-Contact Heart Rate Monitoring Method Based on Wi-Fi CSI Signal.

This paper introduces an innovative non-contact heart rate monitoring method based on Wi-Fi Channel State Information (CSI). This approach integrates both amplitude and phase information of the CSI signal through rotational projection, aiming to optimize the accuracy of heart rate estimation in home environments. We develop a frequency domain subcarrier selection algorithm based on Heartbeat to subcomponent ratio (HSR) and design a complete set of signal filtering and subcarrier selection processes to further enhance the accuracy of heart rate estimation. Heart rate estimation is conducted by combining the peak frequencies of multiple subcarriers. Extensive experimental validations demonstrate that our method exhibits exceptional performance under various environmental conditions. The experimental results show that our subcarrier selection method for heart rate estimation achieves an average accuracy of 96.8%, with a median error of only 0.8 bpm, representing an approximately 20% performance improvement over existing technologies.

Per- and polyfluoroalkyl substances induce lipid metabolic impairment in fish: Integration on field investigation and laboratory study.

The biotoxicity of perfluoroalkyl and polyfluoroalkyl substances (PFASs) to aquatic organisms has been widely concerned. However, studies on toxic effects of PFASs are usually evaluated directly by using laboratory exposure rather than laboratory validation based on data obtained in the field. In this study, wild catfish (Silurus meridinalis) was explored on the relationship between PFASs bioaccumulation and lipid disorders. Nine and thirteen lipid metabolites were significantly associated with perfluorooctane sulfonate (PFOS) and 6:2/8:2Cl-PFESA (trade name F-53B) exposures, respectively; and the correlated lipid metabolites were the fatty acid (FA) and conjugates, FA esters, steroids, and glycerophosphate subclasses. The effects of PFASs on lipid metabolism of fish and its mechanism were further analyzed through exposure experiments. Zebrafish (Danio rerio) of different sexes underwent PFOS and F-53B exposures for 21 days at 100 ng/L and 100 µg/L. By determining gene expression levels, hepatic lipid contents, and histopathological change, the adverse effects order on lipid metabolism in male or female was 100 µg/L F-53B > 100 µg/L PFOS > 100 ng/L F-53B > 100 ng/L PFOS; the stress response in male was more intensive than that in female. PFOS and F-53B activated the peroxisome proliferator-activated receptor pathway, promoting the processes of FA and total cholesterol (T-CHO) transport, FA ß-oxidation, FA synthesis, and finally induced FA and T-CHO transportation from blood into liver, then accelerated FA to FA ester transformation, and CHO into steroids. Laboratory experiments confirmed the field analysis. This study innovatively explored the adverse effects of PFOS and F-53B on lipid metabolism and their mechanisms at field and laboratory levels, highlighting concerns regarding PFASs health risks.

Dissecting the chiral recognition of TLR4/MD2 with Neoseptin-3 enantiomers by molecular dynamics simulations.

Toll-like receptor 4 (TLR4) is a pivotal innate immune recognition receptor that regulates intricate signaling pathways within the immune system. Neoseptin-3 (Neo-3), a recently identified small-molecule agonist for mouse TLR4/MD2, exhibits chiral recognition properties. Specifically, the L-enantiomer of Neo-3 (L-Neo-3) effectively activates the TLR4 signaling pathway, while D-Neo-3 fails to induce TLR4 activation. However, the underlying mechanism by which TLR4 enantioselectively recognizes Neo-3 enantiomers remains poorly understood. In this study, in silico simulations were performed to investigate the mechanism of chiral recognition of Neo-3 enantiomers by TLR4/MD2. Two L-Neo-3 molecules stably resided within the cavity of MD2 as a dimer, and the L-Neo-3 binding stabilized the (TLR4/MD2)2 dimerization state. However, the strong electrostatic repulsion between the hydrogen atoms on the chiral carbon of D-Neo-3 molecules caused the relative positions of two D-Neo-3 molecules to continuously shift during the simulation process, thus preventing the formation of D-Neo-3 dimer as well as their stable interactions with the surrounding residues in (TLR4/MD2)2. Considering that L-Neo-3 could not sustain a stable dimeric state in the bulk aqueous environment, it is unlikely that L-Neo-3 entered the cavity of MD2 as a dimeric unit. Umbrella sampling simulations revealed that the second L-Neo-3 molecule entering the cavity of MD2 exhibited a lower binding energy (-25.75 kcal mol-1) than that of the first L-Neo-3 molecule (-14.31 kcal mol-1). These results imply that two L-Neo-3 molecules enter the cavity of MD2 sequentially, with the binding of the first L-Neo-3 molecule facilitating the entry of the second one. This study dissects the binding process of Neo-3 enantiomers, offering a comprehensive understanding of the atomic-level mechanism underlying TLR4's chiral recognition of Neo-3 molecules.

Comparison of different organic selenium supplementations on selenium status and serum biomarkers in dairy cows.

The objective of this study was to investigate the effects of two different organic selenium (Se) supplements, selenomethionine (Se-Met) and selenohomolanthionine (Se-Hlan), on the serum biochemical parameters and Se status of dairy cows. Different dietary Se supplementation treatments were set as follows: a control group (CON, adding sodium selenite at 0.3 mg Se/kg dry matter [DM]), 0.3 and 0.5 Se-Met (adding Se-Met at 0.3 and 0.5 mg Se/kg DM, respectively), as well as 0.3 and 0.5 Se-Hlan (adding Se-Hlan at 0.3 and 0.5 mg Se/kg DM, respectively). The experiment lasted 8 weeks. The serum measurements showed that both organic Se treatments resulted in higher uric acid than CON. Se-Met produced higher aspartate aminotransferase, glucose, urea, low-density lipoprotein cholesterol, and lactate dehydrogenase than Se-Hlan. Regarding the Se status, the highest milk Se values appeared in 0.5 Se-Met, with intermediate values in 0.3 Se-Met and 0.5 Se-Hlan, whereas the highest and lowest serum Se levels were presented in 0.5 Se-Met and 0.3 Se-Hlan, respectively. Our results suggest that Se-Hlan was not as efficient in boosting serum or milk Se as Se-Met and differences in serum biomarkers between Se-Met and Se-Hlan may be associated with distinct metabolic pathways for different forms of organic Se.

Per- and polyfluoroalkyl substances in waterbird feathers around Poyang Lake, China: Compound and species-specific bioaccumulation.

As a nondestructive means of environmental monitoring, bird feathers have been used to analyze levels of per- and polyfluoroalkyl substances (PFASs) in specific environments. In this study, feather samples from 10 waterbird species around Poyang Lake were collected, and a pretreatment method for PFASs in feathers was optimized. The results showed that a combined cleaning method using ultrapure water and n-hexane effectively removed external PFASs. Twenty-three legacy and emerging PFASs were identified in the feathers of waterbirds, of which hexafluoropropylene oxides (HFPOs), chlorinated polyfluoroalkyl ether sulfonates (Cl-PFESAs), and sodium p-perfluorinated noneoxybenzene sulfonate (OBS) were reported for the first time, with their concentrations ranging from 0.060-2.4 ng·g-1 dw, 0.046-30 ng·g-1 dw, and lower than the method detection limit to 30 ng·g-1 dw, respectively. Compound- and species-specific bioaccumulation of PFASs was observed in the feathers of different waterbird species, suggesting that different PFAS types can be monitored through the selection of different species. Moreover, the concentrations of most PFCAs (except perfluorobutyric acid), perfluorooctane sulfonate (PFOS), and perfluorooctane sulfonamide (FOSA) were significantly positively correlated with δ15N (p < 0.05), while the concentrations of HFPOs, Cl-PFESAs, and OBS had significant positive correlations with δ13C. This indicates that the bioaccumulation of legacy and emerging PFASs in waterbird feathers is affected by their trophic level, feeding habits, and foraging area.

Numerical modeling of the effects of the shape and aspect ratio of 3D curved fiber on the percolation threshold and electrical conductivity of conductive polymer composites.

For designing conductive polymer composites (CPCs), understanding how the fiber curvature affects the percolation behavior of curved conductive fibers is essential for determining the effective electrical conductivity σeff of the CPCs. In this work, CPCs were considered as a polymer matrix filled with the random packing of overlapped curved spherocylinders. The geometries of the curved spherocylinders were defined, and inter-curved spherocylinder contact-detecting and system-spanning fiber cluster searching algorithms were developed. The finite-size-scaling method was used to explore how the aspect ratio α and bending central angle θ of a curved spherocylinder affect the percolation threshold ϕc of an overlapped curved spherocylinder system in 3D space. The findings suggest that ϕc decreases as α increases and increases initially before declining as θ increases. An empirical approximation formula was proposed to quantify the effect of the curved spherocylinder's morphology, characterized by the dimensionless excluded volume Vdex of the curved spherocylinder, on ϕc. The new rigorous bound for ϕc of the soft-curved spherocylinder system was further proposed. A random resistor network model was constructed, and the reliability of this model was validated by comparing the simulations and published data. Finally, a fitting formula was developed to assess the impacts of the normalized reduced density (η - ηc)/ηc and Vdex on the σeff of CPCs. A distinct linear correlation between σeff and (η - ηc)/ηc was constructed, denoted as σeff ∼ [(η - ηc)/ηc]t(α,θ). An empirical approximation model was proposed to establish the relationship between the fiber shape and conductivity exponent t. Our study may provide a theoretical hint for the design of CPCs.

Routing Selection Algorithm for Mobile Ad Hoc Networks Based on Neighbor Node Density.

In the process of data transmission in mobile ad hoc networks, it is essential to establish optimal routes from source nodes to destination nodes. However, as network density increases, this process is often accompanied by a significant rise in network overhead. To address this issue, the ND-AODV (neighborhood density AODV) protocol has been introduced, which reduces the probability of transmitting control information in high-density node environments to mitigate network overhead. Nevertheless, this may come at the cost of reduced routing accuracy, potentially leading to unnecessary resource wastage in certain scenarios. Furthermore, ND-AODV does not comprehensively consider the location of the receiving nodes, which limits its ability to reduce network overhead effectively. To overcome these limitations, this paper introduces a novel routing approach, known as CND-AODV (common neighborhood density AODV). In comparison to ND-AODV, CND-AODV offers a more comprehensive solution to the challenges posed by high-density network environments. It intelligently processes control information based on the special positioning of the receiving nodes, thereby significantly reducing unnecessary network overhead. Through simulation experiments comparing performance metrics such as throughput, packet delivery rate, and latency, the results clearly indicate that CND-AODV substantially decreases network overhead, enhancing network performance. Compared to ND-AODV, this innovative routing approach exhibits significant advantages. It provides a more efficient and reliable solution for ad hoc networks in high-density environments.

A new mechanistic insight into the association between environmental perfluorooctane sulfonic acid (PFOS) exposure and attention deficit and hyperactivity disorder (ADHD)-like behavior.

Perfluorooctane sulfonic acid (PFOS) is one of the main residual environmental pollutants that threaten human health. PFOS exposure is positively correlated with the prevalence of attention deficit hyperactivity disorder (ADHD); however, the underlying mechanism is unknown. Given that dopamine (DA) is a crucial target for PFOS and that its dysfunction is a key role in ADHD development, it is speculated that PFOS exposure contributes to the occurrence of ADHD to some extent by disrupting DA homeostasis. To establish the relationship between PFOS exposure, DA dysfunction, and ADHD-like behavior, adult zebrafish were exposed to PFOS for 21 days using PFOS concentrations in the serum of patients with ADHD as the reference exposure dose. Results showed that PFOS caused ADHD-like behaviors, with the presence of the slightly elevated percentage of time spent in movement and prolonged time spent in reaching the target zone in the T-maze. Hyperactivity and cognitive ability impairment were more severe with increasing PFOS concentrations. Further investigation showed that PFOS exposure resulted in a decrease in the DA content, accompanied by a decrease in the number of dopaminergic neurons and a disturbance in the transcription profiles of genes associated with the dopaminergic system. Treatment with Ritalin effectively alleviated PFOS-induced ADHD-like behavior and restored DA levels, number of dopaminergic neurons, and expression of DA metabolism-related genes, suggesting that PFOS exposure induced ADHD-like behavior by triggering DA secretion disorder. This study enriches our understanding of the pathogenic mechanisms underlying ADHD development and emphasizes the importance of focusing on the health risks pertaining to environmental exposure.

Percolation threshold and electrical conductivity of conductive polymer composites filled with curved fibers in two-dimensional space.

Quantifying the influence of fiber curvature on the percolation behavior of flexible conductive fiber and further on the electrical conductivity of conductive polymer composites (CPCs) is crucial for the design of CPCs. This study considers CPCs as a random packing of soft curved discorectangles (CDCRs) in a polymer matrix. The geometry of CDCR is developed, and an inter-CDCR contact detection algorithm is used to generate a random packing structure of CDCRs. The effects of aspect ratio α and bending central angles θ of CDCR on the percolation threshold ϕc of the overlapped CDCR system in a two-dimensional plane are then investigated using the finite-size scaling method. The result reveals that ϕc decreases monotonically as α grows and increases monotonically as θ rises. A shape-independent power law formula, denoted as ϕc = 2.2015 A-0.8172dex is developed to quantify the relationship between the Adex and ϕc. A comparison of our numerical simulations, published data, and predictions verifies the reliability and universality of the fitting model. Subsequently, a resistor network searching algorithm (RNSA) is proposed to construct the random resistor network model (RRNM). A power law model, denoted as is developed to evaluate the effects of the normalized reduced density (η - ηc)/ηc on the effective conductivity σeff of CPC. Comparing our predictions with data from the literature and our simulation verifies the reliability of our RNSA and the fitting model. This paper's methodology and findings may provide a theoretical hint for the CPC's design.

Novel PFOS alternative OBS inhibits body growth of developing zebrafish by triggering thyroid function disorder and osteoclast differentiation.

The extensive use of the perfluorooctane sulfonate (PFOS) alternative sodium p-perfluorous nonenoxybenzene sulfonate (OBS) has resulted in its widespread detection in the environment and enrichment in wildlife and humans. However, little is known about its potential toxicity, particularly in terms of body development. In this study, zebrafish embryos were acutely exposed to PFOS and OBS for a comparative developmental toxicity assessment. Both PFOS and OBS led to lower body weight and shorter body length, and the damaging effects of PFOS were more severe than those of OBS at the same exposure concentration. Biochemical assays of THs and transcription profiles correlated to the HPT axis demonstrated that OBS-induced body development inhibition resulted mainly from interference in THs synthesis, transfer, coupling with receptors, and conversion from T4 to T3, which was similar to the case of PFOS, except that the disruptive effects of OBS on thyroid function were more intense. Further transcriptome analysis showed that PFOS and OBS also promoted osteoclast differentiation, aggravating the inhibitory effects on body growth, and that PFOS had more obvious inhibitory effects than OBS. This study systematically explored the inhibitory effects of PFOS and OBS exposure on body development and tightly linked the toxic effects to thyroid function disorder and osteoclast differentiation. Our findings highlight that the health risks associated with OBS, an emerging substitute for PFOS, should not be ignored.

Automatic Myocardial Contrast Echocardiography Image Quality Assessment Using Deep Learning: Impact on Myocardial Perfusion Evaluation.

OBJECTIVE: The image quality of myocardial contrast echocardiography (MCE) is critical for precise myocardial perfusion evaluation but challenging for echocardiographers. Differences in quality may lead to diagnostic heterogeneity. This study was aimed at achieving automatic MCE image quality assessment using a deep neural network (DNN) and investigating its impact on myocardial perfusion evaluation. METHODS: The Resnet-18 model was used for training and testing on internal and external data sets. Quality assessment involved three aspects: left ventricular opacification (LVO), shadowing, and flash adequacy; the quality score was calculated based on image quality. This study explored the impact of the DNN-based quality score on perfusion evaluation (normal, delay or obstruction) by echocardiographers (two seniors, one junior and one novice). Additionally, the effect of the score difference between re-scans on perfusion evaluation was investigated. RESULTS: The time cost for DNN prediction was 0.045 s/frame. In internal validation and external testing, the DNN achieved F1 and macro F1 scores >90% for quality assessment and had high intraclass correlation coefficients (0.954 and 0.892, respectively) in sequence quality scores. The proportion of segments deemed uninterpretable increased as the DNN-based quality score decreased. The agreement of perfusion assessment between one senior and others decreased as the quality score decreased. And the greater the score difference between the re-scans, the lower was the agreement on perfusion assessment by the same echocardiographer. CONCLUSION: This study determined the effectiveness of DNN for real-time automatic MCE quality assessment. It has the potential to reduce the variability in perfusion evaluation among echocardiographers.

The Effects Analysis of Contact Stiffness of Double-Row Tapered Roller Bearing under Composite Loads.

Double-row tapered roller bearings have been widely used in various equipment recently due to their compact structure and ability to withstand large loads. The dynamic stiffness is composed of contact stiffness, oil film stiffness and support stiffness, and the contact stiffness has the most significant influence on the dynamic performance of the bearing. There are few studies on the contact stiffness of double-row tapered roller bearings. Firstly, the contact mechanics calculation model of double-row tapered roller bearing under composite loads has been established. On this basis, the influence of load distribution of double-row tapered roller bearing is analyzed, and the calculation model of contact stiffness of double-row tapered roller bearing is obtained according to the relationship between overall stiffness and local stiffness of bearing. Based on the established stiffness model, the influence of different working conditions on the contact stiffness of the bearing is simulated and analyzed, and the effects of radial load, axial load, bending moment load, speed, preload, and deflection angle on the contact stiffness of double row tapered roller bearings have been revealed. Finally, by comparing the results with Adams simulation results, the error is within 8%, which verifies the validity and accuracy of the proposed model and method. The research content of this paper provides theoretical support for the design of double-row tapered roller bearings and the identification of bearing performance parameters under complex loads.

Application of Deep Learning Algorithm to Monitor Upper Extremity Task Practice.

Upper extremity hemiplegia is a serious problem affecting the lives of many people post-stroke. Motor recovery requires high repetitions and quality of task-specific practice. Sufficient practice cannot be completed during therapy sessions, requiring patients to perform additional task practices at home on their own. Adherence to and quality of these home task practices are often limited, which is likely a factor reducing rehabilitation effectiveness post-stroke. However, home adherence is typically measured by self-reports that are known to be inconsistent with objective measurement. The objective of this study was to develop algorithms to enable the objective identification of task type and quality. Twenty neurotypical participants wore an IMU sensor on the wrist and performed four representative tasks in prescribed fashions that mimicked correct, compensatory, and incomplete movement qualities typically seen in stroke survivors. LSTM classifiers were trained to identify the task being performed and its movement quality. Our models achieved an accuracy of 90.8% for task identification and 84.9%, 81.1%, 58.4%, and 73.2% for movement quality classification for the four tasks for unseen participants. The results warrant further investigation to determine the classification performance for stroke survivors and if quantity and quality feedback from objective monitoring facilitates effective task practice at home, thereby improving motor recovery.

Synthesis of Sb-pyromellitic acid metal-organic framework material and its sodium storage properties.

Developing electrode materials with high capacity and low cost is crucial for promoting the application of sodium-ion batteries. In this paper, a new Sb-PMA-300 metal-organic framework (MOF) material is synthesized by chelation of Sb3+ and pyromellitic acid (PMA) followed by a heat treatment at 300 °C. As anodes for sodium-ion batteries, the Sb-PMA-300 composite exhibits a stable capacity of 443 mA h g-1 at a current density of 0.1 A g-1. At a current density of 1 A g-1, the discharge capacity is maintained at 326.4 mA h g-1 after 200 cycles. The electrode process dynamics of this material are mainly controlled by diffusion. The values of the diffusion coefficient of Na+ are between 10-12 and 3.0 × 10-10 cm2 s-1 during discharging, while they are between 10-12 and 5.0 × 10-11 cm2 s-1 during charging. The excellent cycle stability is attributed to the special structure of the MOF material, where the organic ligand prevents the aggregation of Sb alloy particles and buffers the tension resulting from volume variation.

A novel risk stratification model for STEMI after primary PCI: global longitudinal strain and deep neural network assisted myocardial contrast echocardiography quantitative analysis.

Background: In ST-segment elevation myocardial infarction (STEMI) with the restoration of TIMI 3 flow by percutaneous coronary intervention (PCI), visually defined microvascular obstruction (MVO) was shown to be the predictor of poor prognosis, but not an ideal risk stratification method. We intend to introduce deep neural network (DNN) assisted myocardial contrast echocardiography (MCE) quantitative analysis and propose a better risk stratification model. Methods: 194 STEMI patients with successful primary PCI with at least 6 months follow-up were included. MCE was performed within 48 h after PCI. The major adverse cardiovascular events (MACE) were defined as cardiac death, congestive heart failure, reinfarction, stroke, and recurrent angina. The perfusion parameters were derived from a DNN-based myocardial segmentation framework. Three patterns of visual microvascular perfusion (MVP) qualitative analysis: normal, delay, and MVO. Clinical markers and imaging features, including global longitudinal strain (GLS) were analyzed. A calculator for risk was constructed and validated with bootstrap resampling. Results: The time-cost for processing 7,403 MCE frames is 773 s. The correlation coefficients of microvascular blood flow (MBF) were 0.99 to 0.97 for intra-observer and inter-observer variability. 38 patients met MACE in 6-month follow-up. We proposed A risk prediction model based on MBF [HR: 0.93 (0.91-0.95)] in culprit lesion areas and GLS [HR: 0.80 (0.73-0.88)]. At the best risk threshold of 40%, the AUC was 0.95 (sensitivity: 0.84, specificity: 0.94), better than visual MVP method (AUC: 0.70, Sensitivity: 0.89, Specificity: 0.40, IDI: -0.49). The Kaplan-Meier curves showed that the proposed risk prediction model allowed for better risk stratification. Conclusion: The MBF + GLS model allowed more accurate risk stratification of STEMI after PCI than visual qualitative analysis. The DNN-assisted MCE quantitative analysis is an objective, efficient and reproducible method to evaluate microvascular perfusion.

Design, synthesis and evaluation of monoketene compounds as novel potential Parkinson's disease agents by suppressing ER stress via AKT.

Curcumin is identified that it has the potential to treat Parkinson's disease (PD), but its instability limits its further application in clinic. The mono-carbonyl analogs of curcumin (MACs) with diketene structure can effectively improve its stability, but it is highly toxic. In the present study, a less cytotoxic and more stable monoketene MACs skeleton S2 was obtained, and a series of monoketene MACs were synthesized by combining 4-hydroxy-3­methoxy groups of curcumin. In the 6-OHDA-induced PD's model in-vitro, some compounds exhibited significant neurotherapeutic effect. The quantitative structure-activity relationship (QSAR) model established by the random forest algorithm (RF) for the cell viability rate of above compounds showed that the statistical results are good (R2 = 0.883507), with strong reliability. Among all compounds, the most active compound A4 played an important role in neuroprotection in the PD models both in vitro and in vivo by activating AKT pathway, and then inhibiting the apoptosis of cells caused by endoplasmic reticulum (ER) stress. In the PD model in-vivo, compound A4 significantly improved survival of dopaminergic neurons and the contents of neurotransmitters. It also enhanced the retention of nigrostriatal function which was better than the effect in the mice treated by Madopar, a classical clinical drug for PD. In summary, we screened out the compound A4 with high stability, less cytotoxic monoketene compounds. And these founding provide evidence that the compound A4 can protect dopaminergic neurons via activating AKT and subsequently suppressing ER stress in PD.

Popularity Status Insecurity as a Risk Factor for Adolescents' Maladaptive Weight-Related Cognitions and Behaviors: Examining a Moderated Mediation Model.

Previous studies have identified popularity as a risk factor for adolescents' body image concerns and disordered eating behaviors, yet little is known about how adolescents' insecure feelings about their popularity status may be associated with these outcomes. To address this gap, this study examined whether popularity status insecurity was linked to weight-related cognitions and behaviors one year later and whether these links were mediated by body dissatisfaction and moderated by popularity status. A total of 233 Chinese 10th and 11th grade adolescents (41% girls; Mage = 15.81 years, SD = 0.68) participated in the study. The results showed that adolescents' popularity status insecurity was positively and indirectly related to greater future drive for thinness and restrained eating through the mediation of dissatisfied feelings about their own body shape only among those with average and low popularity, and these indirect effects were strengthened as adolescents' popularity decreased. Implications for prevention and intervention of eating disturbances for adolescents are discussed.

Denoising Generalization Performance of Channel Estimation in Multipath Time-Varying OFDM Systems.

Although Orthogonal Frequency Division Multiplexing (OFDM) technology is still the key transmission waveform technology in 5G, traditional channel estimation algorithms are no longer sufficient for the high-speed multipath time-varying channels faced by both existing 5G and future 6G. In addition, the existing Deep Learning (DL) based OFDM channel estimators are only applicable to Signal-to-Noise Ratios (SNRs) in a small range, and the estimation performance of the existing algorithms is greatly limited when the channel model or the mobile speed at the receiver does not match. To solve this problem, this paper proposes a novel network model NDR-Net that can be used for channel estimation under unknown noise levels. NDR-Net consists of a Noise Level Estimate subnet (NLE), a Denoising Convolutional Neural Network subnet (DnCNN), and a Residual Learning cascade. Firstly, a rough channel estimation matrix value is obtained using the conventional channel estimation algorithm. Then it is modeled as an image and input to the NLE subnet for noise level estimation to obtain the noise interval. Then it is input to the DnCNN subnet together with the initial noisy channel image for noise reduction to obtain the pure noisy image. Finally, the residual learning is added to obtain the noiseless channel image. The simulation results show that NDR-Net can obtain better estimation results than traditional channel estimation, and it can be well adapted when the SNR, channel model, and movement speed do not match, which indicates its superior engineering practicability.

A Numerical Study of ITZ Percolation in Polyphase Concrete Systems Considering the Synergetic Effect of Aggregate Shape- and Size-Diversities.

The percolation of the interfacial transition zone (ITZ) is generally regarded as an important factor that may accelerate the penetration of aggressive agents in concrete materials, and its threshold is largely determined by the features of aggregates. In most numerical studies about ITZ percolation, both fine aggregates and coarse aggregates are assumed to be the particles of uniform shape, and their size distributions are generally strung together by a single function, which is quite different from reality. To quantify the ITZ percolation associated with the polydispersity of aggregate shapes and size gradations in a more realistic way, the two-dimensional (2D) meso-scale model of concrete is generated by simplifying coarse aggregates and fine aggregates as polygons and ovals, respectively. Moreover, the size gradations of them are also represented by two separate expressions. By combining these models with percolation theory, the percolation of ITZ in the 2D case is explicitly simulated, and the influence of aggregate shape- and size-diversities on the critical threshold ϕagg,c is studied in detail. Based on the simulated results of ϕagg,c, an empirically analytical expression is further proposed to fast predict the ITZ percolation, and its reliability is verified. The results show that the ITZ thickness, average aggregate fineness, coarse aggregate shape, and fine aggregate shapes are the four main contributing factors to the ITZ percolation. Compared with the existing literature, the proposed model here has a broader range of applications (e.g., mortar, concrete, and other granular systems) in the 2D case and can provide the larger predicted results, which may be closer to reality.

Dynamic differentiation of F4/80+ tumor-associated macrophage and its role in tumor vascularization in a syngeneic mouse model of colorectal liver metastasis.

Tumor-associated macrophages (TAMs) are highly heterogeneous and play vital roles in tumor progression. Here we adopted a C57BL/6 mouse model imitating the late-stage colorectal liver metastasis (CRLM) by Mc38 colorectal cancer cell injection via the portal vein. With serial sections of CRLM biopsies, we defined 7-9 days post-injection as the critical period for tumor neovascularization, which was initiated from the innate liver vessels via vessel cooption and extended by vascular mimicry and thereof growth of CD34+cells. In samples with increasing-sized liver metastases, the infiltrated Ly6C+ CD11b+ F4/80- monocytes steadily gained the expression of F4/80, a Kupffer cell marker, before transformed into Ly6C- CD11bint F4/80+ cells, which, the same phenotype was also adapted by Ly6C- CD11b- F4/80+ Kupffer cells. F4/80+ TAMs showed proximity to neovascularization and tumor vessels, functionally angiogenic in vivo; and greatly promoted the activation of a few key angiogenic markers such as VEGFA, Ki67, etc. in endothelial cells in vitro. Depletion of macrophages or diversion of macrophage polarization during neovascularization impeded tumor growth and vascularization and resulted in greatly reduced F4/80+ TAMs, yet increased CD11b+ cells due to inhibition of TAM differentiation. In summary, our results showed dynamic and spatial-temporal F4/80+ TAM transformation within the tumor microenvironment and strengthened its role as perivascular and angiogenic TAMs in CRLM.