Strengthening-Durable Trade-Off and Self-Healing, Recyclable Shape Memory Polyurethanes Enabled by Dynamic Boron-Urethane Bonds.

Addressing the demand for integrating strength and durability reinforcement in shape memory polyurethane (SMPU) for diverse applications remains a significant challenge. Here a series of SMPUs with ultra-high strength, self-healing and recyclability, and excellent shape memory properties through introducing dynamic boron-urethane bonds are synthesized. The introducing of boric acid (BA) to polyurethane leading to the formation of dynamic covalent bonds (DCB) boron-urethane, that confer a robust cross-linking structure on the SMPUs led to the formation of ordered stable hydrogen-bonding network within the SMPUs. The flexible crosslinking with DCB represents a novel strategy for balancing the trade-off between strength and durability, with their strengths reaching up to 82.2 MPa while also addressing the issue of durability in prolonged usage through the provision of self-healing and recyclability. The self-healing and recyclability of SMPU are demonstrated through rapid dynamic exchange reaction of boron-urethane bonds, systematically investigated by dynamic mechanical analysis (DMA). This study sheds light on the essential role of such PU with self-healing and recyclability, contributing to the extension of the PU's service life. The findings of this work provide a general strategy for overcoming traditional trade-offs in preparing SMPUs with both high strength and good durability.

QNAR modeling of cytotoxicity of mixing nano-TiO2 and heavy metals.

The Quantitative Structure-Activity Relationship (QSAR) has been used to investigate organic mixtures but QSAR in the nanomaterial field (QNAR) is still new. Toxicity is a result of the interaction of many substances. QNAR research focuses on a single nanomaterial in the long-term. It is difficult to find an appropriate descriptor to build a model due to the complexity of the mixture. Here, we attempt to build a QNAR model to predict cell viability for HK-2 cells exposed to a mixture containing nano-TiO2 and heavy metals. HK-2 cells were exposed to four groups of mixtures containing heavy-metals and nanomaterials and CCK8 was added to obtain the number of living cells. At the same time, ROS was investigated to study this mechanism. Each descriptor of the components and mixtures were obtained using the formula Dmix= [Formula: see text] respectively. We used the Multiple Partial Least Squares Regression (PLS) and Random Forest Regression (RF) to build a QNAR model. Both models reliably predict and assess viability of HK-2 cells exposed to the mixture. The RF model showed greater stability and higher precision in toxicity predictability and can be applied to environmental nano-toxicology.

A Distributed Energy-Balanced Topology Control Algorithm Based on a Noncooperative Game for Wireless Sensor Networks.

In wireless sensor networks, nodes may adopt selfish behavior to save their energy resources, which causes energy imbalance among nodes, because of lacking a central controller with the function of making nodes cooperate. Noncooperative game is an effective tool for portraying this kind of selfish behavior. In this paper, we address the problems of transmission power minimization and energy balance using a topology control game. Firstly, we establish a topology control game model and prove that the topology game model is an ordinal potential game with Pareto optimality. Secondly, based on this model, we propose an Energy Balance Topology control Game algorithm (EBTG), in which, by taking the energy efficiency and energy balance of the nodes into account, we design an improved optimization-integrated utility function by introducing the Theil index. Finally, simulation results show that the EBTG algorithm can improve the energy balance and energy efficiency, and can prolong the network lifetime in comparison with other topology control algorithms based on game theory.

Reconfigurable, Solvent-Processable, NIR-Triggerable Shape Memory Cyanate Esters for Smart Molds.

Shape memory polymer (SMP)-based smart molds, which could provide high-resolution mold shape and morph in response to external stimuli for readily demolding the complex structure, attract extensive attention. However, the suitable SMP for smart molds is usually confined with low stretchability that likely causes damage during demolding. Herein, we present a cyanate ester smart composite (CESC) with a reconfigurable, solvent-processable, and near-infrared (NIR)-triggerable shape memory effect (SME), which enables the 2D sheet with a variety of morphed complex shapes through deformation in a mild situation. Notably, the reconfigurable SME and the recyclability of the shape memory cyanate ester (SMCE) were addressed for the first time, attributed to the dynamic covalent bonds of transesterification and the novel cyanurate exchange. In addition, we found that the mechanism of solvent-processable SME is attributed to the varied cross-linking density and the mobility of the polymer chain. Integrating the multiple responsive SME and reconfigurable SME, the CESC demonstrated versatile applications as a smart mold. The results demonstrate a wide scope of application of the integrated SME and provide a new design strategy for thermoset cyanate materials.

Synergistic Effects of Graphene and Ammonium Polyphosphate Modified with Vinyltrimethoxysilane on the Properties of High-Impact Polystyrene Composites.

Ammonium polyphosphate (APP) was modified with a silane coupling agent (vinyltrimethoxysilane, Si-171), and then the synergistic flame retarding effect of graphene and surface-modified APP (APP@Si-171) on high-impact polystyrene (HIPS) was investigated. Surface modification and thermal stability characterization of APP were analyzed by Fourier transform infrared spectroscopy (FTIR), energy dispersive spectrometer (EDS), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). The results showed that surface-modified APP (APP@Si-171) exhibited significantly better dispersion and less agglomeration tendencies compared with pure APP. A series of target HIPS composites containing different mass fractions of the two flame retardants were prepared by melt blending. TGA and cone calorimeter tests (CCT) were conducted to quantitatively investigate the thermal and flammability properties of the composites, respectively. Results from TGA and CCT demonstrated that the addition of the flame retardants delayed the onset and peak temperatures in differential thermogravimetry (DTG) curves and weakened the peak heat release rate (PHRR) and total heat release (THR). Moreover, the synergistic effect index (SE) was employed to quantify the synergistic behavior between the two fillers, and the results showed that APP@Si-171 and graphene had a synergistic effect on improving the thermal stability and flame retardancy of HIPS.

Dynamic genetic diversity and population structure of Coreiusguichenoti.

To investigate the genetic effects on the population of Coreiusguichenoti of dam constructions in the upper reaches of the Yangtze River, we analyzed the genetic diversity and population structure of 12 populations collected in 2009 and 2019 using mitochondrial DNA (mtDNA) control regions. There was no significant difference in genetic diversity between 2009 and 2019 (P > 0.05), but the population structure tended to become stronger. Genetic differentiation (FST) among five populations (LX, BB, YB, SF and JA) collected in 2009 was not significant (P > 0.05). However, some populations collected in 2019 were significantly differentiated (P < 0.05), indicating that the population structure has undergone change. A correlation analysis showed that the genetic diversity of the seven populations collected in 2019 was significantly negatively correlated with geographical height (r = -0.808, P = 0.028), indicating that the populations at high elevations were more vulnerable than those at low elevations. In order to prevent the further decrease of genetic diversity and population resources, some conservation and restoration suggestions, such as fish passage and artificial breeding, are put forward.

Artery-venous classification in fluorescein angiograms based on region growing with sequential and structural features.

BACKGROUND AND OBJECTIVES: Fluorescein angiography (FA) is widely used in ophthalmology for examining retinal hemodynamics and vascular morphology. Artery-venous classification is an important step in FA image processing for measurement of feature parameters, such as arterio-venous passage time (AVP) and arterio-venous width ratio (AVR) that are proven useful in clinical assessment of circulation disturbance and vessel abnormalities. However, manual artery-venous classification needs expertise and is rather time consuming, and little effort has been devoted to develop automatic classification methods. In order to solve this problem, we propose a novel artery-venous classification method using region growing strategy with sequential and structural features (RGSS). METHODS: The main procedures of our proposed RGSS method include: (i) registration of FA image sequence by mutual-information method; (ii) extraction of sequential features of the dye perfusion process from the registrated FA images; (iii) extraction of vessel structural features from vascular centerline map; (iv) based on the obtained features, seeds of arteries and veins within initial growing region (here optic disk) are generated and then propagated in the entire vessel network using region growing strategy. The RGSS method was tested on our own dataset and public Duke dataset, and its performance was evaluated quantitatively. RESULTS: Tests show that RGSS method is able to classify arteries and veins from the complicated vessel network in FA images, with high classification accuracy of 0.91 ± 0.04 on Duke dataset and 0.92 ± 0.03 on our dataset. The employed sequential and structural features are demonstrated to be effective in classifying thin arteries and veins at vessel crossings. CONCLUSIONS: Automatic artery-venous classification can be accomplished using our proposed RGSS method with high accuracy. The RGSS method not only emancipates ophthalmologists from hard work of manual marking of arteries and veins, but also helps in measuring important parameters (such as AVP and AVR) for clinical assessment of circulation disturbance and vessel abnormalities.

CTRP3 induces an intermediate switch of CD14++CD16+ monocyte subset with anti-inflammatory phenotype.

Acute myocardial infarction (AMI) evokes a temporally coordinated immune response, in which monocytes are critically involved in the clearance of cell debris; however, excessive inflammation induced by the classical sub-population of monocytes frequently limits the endogenous reparative process. In the present study, the potential of the anti-inflammatory adipokine complement C1q tumor necrosis factor (TNF)-related protein-3 (CTRP3) to induce intermediate switch of monocytes to an anti-inflammatory phenotype was explored. Circulating monocytes were isolated from patients with AMI at various time-points (3-5 h, 3 days and 7 days) and categorized by flow cytometry/immunostaining into three sub-divisions based on the expression of CD14 and CD16 epitopes: Classical (CD14++/CD16-), non-classical (CD14+/CD16++) and intermediate populations (CD14++/CD16+). The phagocytic activity was evaluated by the ingestion of FITC-Zymosan and 19F-nanoemulsion and the migratory activity using Thin Cert™ Transwell assay. Monocytes were cultured using autologous serum in the presence of CTRP3 (1 µg/ml) for 24 h and the expression of interleukin 6 (IL-6) and TNF-α was quantified by reverse-transcription quantitative PCR. In addition, SB203580, a p38 mitogen-activated protein kinase (MAPK)/ERK inhibitor, was used to examine the downstream pathways of CTRP3. AMI evoked a transient increase in monocyte counts of the classical subset after onset of the ischemic insult, while the non-classical and intermediate subsets persistently expanded (P<0.01). The monocytes from patients at 3 days after AMI displayed enhanced phagocytic and migratory activities in comparison with those from healthy volunteers (P<0.01). Of note, addition of CTRP3 induced an intermediate switch of monocyte subsets and antagonized the enhanced expression of cytokines, particularly IL-6, in monocytes stressed by lipopolysaccharides, likely by blunting the ERK1/2 and P38 MAPK signaling pathway. In conclusion, the present study demonstrated a dynamic fluctuation of monocyte subsets and enhanced phagocytic and migratory activities in patients with AMI. Furthermore, the 'proof-of-concept' evidence pinpoints CTRP3 as an alternative candidate to modulate the 'uncontrolled' inflammatory response and thus to augment cardiac reparative processes in patients with AMI.

Sensitive and multiplexed detection of antibiotics using a suspension array platform based on silica-agarose hybrid microbeads.

A multiplex suspension array detection platform of antibiotics has been developed based on silica-agarose hybrid microbeads (SAHMs). Chloramphenicol (CAP), sulfamethoxazole (SMX), metronidazole (MTZ) and amoxicillin (AMX) were employed as model analytes. The antigens (the antibiotics conjugated with BSA) were immobilized on the surface of four different types of SAHMs. Based on an indirect competition immunoassay, the selected antibiotics are detected through the competition of the specific monoclonal antibodies between the multiple antibiotics and the antigens. Due to high resistance to nonspecific protein absorption of SAHMs, the proposed method exhibited wide linear ranges (0.4˜72.9 ng/mL for CAP, 2.0˜108.5 ng/mL for SMX, 2.6˜142.2 ng/mL for MTZ, 1.0˜63.3 ng/mL for AMX) and low detection limits of 0.09˜0.8 ng/mL. Recoveries for spiked tap water samples were from 82% to 113%, with relative standard deviation lower than 14%, demonstrating the accuracy of the measurements performed with the developed method. This work offered a high-throughput, flexible and accurate tool, which provides a good platform for simultaneous detection of antibiotics.

Dual Temporal and Spatial Sparse Representation for Inferring Group-Wise Brain Networks From Resting-State fMRI Dataset.

Recently, sparse representation has been successfully used to identify brain networks from task-based fMRI dataset. However, when using the strategy to analyze resting-state fMRI dataset, it is still a challenge to automatically infer the group-wise brain networks under consideration of group commonalities and subject-specific characteristics. In the paper, a novel method based on dual temporal and spatial sparse representation (DTSSR) is proposed to meet this challenge. First, the brain functional networks with subject-specific characteristics are obtained via sparse representation with online dictionary learning for the fMRI time series (temporal domain) of each subject. Next, based on the current brain science knowledge, a simple mathematical model is proposed to describe the complex nonlinear dynamic coupling mechanism of the brain networks, with which the group-wise intrinsic connectivity networks (ICNs) can be inferred by sparse representation for these brain functional networks (spatial domain) of all subjects. Experiments on Leiden_2180 dataset show that most group-wise ICNs obtained by the proposed DTSSR are interpretable by current brain science knowledge and are consistent with previous literature reports. The robustness of DTSSR and the reproducibility of the results are demonstrated by experiments on three different datasets (Leiden_2180, Leiden_2200, and our own dataset). The present work also shed new light on exploring the coupling mechanism of brain networks from perspective of information science.

Experimental Study of Thermal Runaway Process of 18650 Lithium-Ion Battery.

This study addresses the effects of the SOC (State of Charge) and the charging-discharging process on the thermal runaway of 18650 lithium-ion batteries. A series of experiments were conducted on an electric heating and testing apparatus. The experimental results indicate that 6 W is the critical heating power for 40% SOC. With a 20 W constant heating rate, the thermal runaway initial temperature of the lithium-ion battery decreases with the increasing SOC. The final thermal runaway temperature increases with the SOC when the SOC is lower than 80%. However, a contrary conclusion was obtained when the SOC was higher than 80%. Significant mass loss, accompanied by an intense exothermic reaction, took place under a higher SOC. The critical charging current, beyond which the thermal runaway occurs, was found to be 2.6 A. The thermal runaway initial temperature decreases with the increasing charging current, while the intensity of the exothermic reaction varies inversely. Mass ejection of gas and electrolytes exists during thermal runaway when the charging current is higher than 10.4 A, below which only a large amount of gas is released. The thermal runaway initial temperature of discharging is higher than that of non-discharging.

Effects of Combined Surface and In-Depth Absorption on Ignition of PMMA.

A one-dimensional numerical model and theoretical analysis involving both surface and in-depth radiative heat flux absorption are utilized to investigate the influence of their combination on ignition of PMMA (Polymethyl Methacrylate). Ignition time, transient temperature in a solid and optimized combination of these two absorption modes of black and clear PMMA are examined to understand the ignition mechanism. Based on the comparison, it is found that the selection of constant or variable thermal parameters of PMMA barely affects the ignition time of simulation results. The linearity between tig-0.5 and heat flux does not exist anymore for high heat flux. Both analytical and numerical models underestimate the surface temperature and overestimate the temperature in a solid beneath the heat penetration layer for pure in-depth absorption. Unlike surface absorption circumstances, the peak value of temperature is in the vicinity of the surface but not on the surface for in-depth absorption. The numerical model predicts the ignition time better than the analytical model due to the more reasonable ignition criterion selected. The surface temperature increases with increasing incident heat flux. Furthermore, it also increases with the fraction of surface absorption and the radiative extinction coefficient for fixed heat flux. Finally, the combination is optimized by ignition time, temperature distribution in a solid and mass loss rate.