Thermally Responsive Fibers for Versatile Thermoactivated Protective Fabrics

Smart textiles with good mechanical adaptability play an important role in personal protection, health monitoring, and aerospace applications. However, most of the reported thermally responsive polymers has long response time and poor processability, comfort, and wearability. Skin-core structures of thermally responsive fibers with multiple commercial fiber cores and temperature-responsive hydrogel skins are designed and fabricated, which exhibit rapid mechanical adaptability, good thermohardening, and thermal insulation. This universal method enables tight bonding between various commercial fiber cores and hydrogel skins via specific covalently anchored networks. At room temperature, prepared fibers show softness, flexibility, and skin compatibility similar to those of ordinary fibers. As temperature rises, smart fibers become hard, rigid, and self-supporting. The modulus of hydrogel skin increases from 304% to 30883%, showing good mechanoadaptability and impact resistance owing to the synergy between hydrophobic interactions and ionic bonding. Moreover, this synergistic effect leads to an increase in heat absorption, and fibers exhibit good thermal insulation, which reduces the contact temperature of the body surface by ≈25 °C under the external temperature of 95 °C, effectively preventing thermal burns. Notably, the active mechanoadaptability of these smart fibers using conductive fibers as cores is demonstrated. This study provides feasibility for fabricating environmentally adaptive intelligent textiles.     

Auxiliary tumour diagnosis image with deep learning technology

The Journal of Supercomputing - In order to analyse the application value of U-Net neural network in reconstruction and diagnosis of computed tomography (CT) scanning image of lung cancer and...     

Prediction of NSCLC recurrence from microarray data with GEP

Lung cancer is one of the deadliest diseases in the world. Non‐small cell lung cancer (NSCLC) is the most common and dangerous type of lung cancer. Despite the fact that NSCLC is preventable and curable for some cases if diagnosed at early stages, the vast majority of patients are diagnosed very late. Furthermore, NSCLC usually recurs sometime after treatment. Therefore, it is of paramount importance to predict NSCLC recurrence, so that specific and suitable treatments can be sought. Nonetheless, conventional methods of predicting cancer recurrence rely solely on histopathology data and predictions are not reliable in many cases. The microarray gene expression (GE) technology provides a promising and reliable way to predict NSCLC recurrence by analysing the GE of sample cells. This study proposes a new model from GE programming to use microarray datasets for NSCLC recurrence prediction. To this end, the authors also propose a hybrid method to rank and select relevant prognostic genes that are related to NSCLC recurrence prediction. The proposed model was evaluated on real NSCLC microarray datasets and compared with other representational models. The results demonstrated the effectiveness of the proposed model.Inspec keywords: lung, cancer, lab‐on‐a‐chip, genetics, patient diagnosisOther keywords: NSCLC recurrence prediction, microarray data, GE programming, nonsmall cell lung cancer, cancer recurrence, histopathology data, microarray gene expression, prognostic genes     

A facile synthesis of supported amorphous iron oxide with high performance for Cr(Ⅵ) removal from aqueous solution under visible light irradiation

A series of supported iron oxide nanoparticles were prepared by impregnation with Fe(NO_3)_3 supported on TiO_2,followed by low-temperature calcination. Scanning electron microscopy(SEM), X-ray diffraction(XRD), X-ray photoelectron spectroscopy(XPS), UV–vis diffuse reflectance spectra and BET have been used to characterize the samples. These iron oxide-impregnated TiO_2 were examined for photocatalytic reduction of Cr(Ⅵ). The experiments demonstrated that Cr(Ⅵ) in aqueous solution was more efficiently reduced using Fe_2O_3/TiO_2 heterogeneous photocatalysts than either pure Fe_2O_3 or TiO_2 under visible light irradiation. All TiO_2 supported samples were somewhat active for visible light photoreduction. With an optimal mole ratio of 0.05-Fe/Ti, the highest rate of Cr(Ⅵ) reduction was achieved under the experimental conditions. We also compared the photoreactivity of TiO_2 supported iron oxide samples with that supported on Al_2O_3 and ZrO_2. It can be noted that iron oxide nanoparticles deposited on high surface area supports to increase the solid-liquid contact area renders it considerably more active. Noticeably,iron oxide cluster size and dispersion are important parameters in synthesizing active, supported Iron oxide nanoparticles. In addition, the interaction between iron oxide and TiO_2 was proposed as the source of photoactivity for Cr(Ⅵ) reduction.     

Unique role of non-mercapto groups in thiol-pinning-mediated Ag growth on Au nanoparticles

Owing to the strong affinity of thiols to Au and Ag, they are often employed to modify the surfaces of nanoparticles (NPs). Recently, these strong ligand-interface interactions have been employed to control NP growth, and this technique has emerged as a unique modulation strategy for creating unconventional plasmonic hybrid nanostructures. In these systems, the roles of the non-mercapto components of the thiol molecules and their structures are still unknown. Therefore, we herein present our investigation into this phenomenon. Primary amino (–NH₂) groups in thiols are found to play a key role in regulating growth kinetics, i.e., in accelerating Ag deposition on Au NPs. The–NH₂ groups are thought to bring Ag ions to the particle surface by coordinating to them, and thereby assist their reduction. The effect of molecular structure is non-trivial and thus provides the possibility of selective thiol detection. Based on the dependence of kinetic modulation on the non-mercapto components and molecular structures of molecules, we demonstrate the highly sensitive and specific detection of cysteine (limit of detection: 6 nM) in a mixture of 19 natural amino acids based on Ag growth on Au nanospheres. In addition, based on this modulation effect, we reveal the entrapping of chiral thiols within the growth layer through their plasmonic circular dichroism (PCD) responses. We believe that thiol-based growth regulation has great potential for creating plasmonic nanostructures with novel functionalities.

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智能耳诊机的软、硬件设计

本文从实际应用出发,详尽论述了“智能耳诊机”软、硬件设计的方法。对从事单片机开发应用的工程技术人员有较高的参考价值。     

Further results of recursive evaluation for compound distribution with the severity distribution of mixed type

Yang et al. [J.P. Yang, S.H. Cheng, Q. Wu, Recursive equations for compound distribution with the severity distribution of the mixed type, Science in China Series A 48 (2005) 594-609] investigated a recursive procedure for a kind of compound distributions with the number of claims belonging to (a,b)-family and the severity distribution of the mixed type. In this paper, we extend their results by assuming that the claim number belongs to a larger class. As applications, the excess-of-loss reinsurance treaty is discussed and concrete examples are considered in some detail.     

Stable local dimensionality reduction approaches

Dimensionality reduction is a big challenge in many areas. A large number of local approaches, stemming from statistics or geometry, have been developed. However, in practice these local approaches are often in lack of robustness, since in contrast to maximum variance unfolding (MVU), which explicitly unfolds the manifold, they merely characterize local geometry structure. Moreover, the eigenproblems that they encounter, are hard to solve. We propose a unified framework that explicitly unfolds the manifold and reformulate local approaches as the semi-definite programs instead of the above-mentioned eigenproblems. Three well-known algorithms, locally linear embedding (LLE), laplacian eigenmaps (LE) and local tangent space alignment (LTSA) are reinterpreted and improved within this framework. Several experiments are presented to demonstrate the potential of our framework and the improvements of these local algorithms.     

A controllable and accountable state-oriented Card-Aided Firewall

This paper proposes a new approach, named Card-Aided Firewall (CAF) that combines the simplified firewall and the state-oriented smart card technologies to construct a controllable and accountable Internet access framework. The idea suggests that a client computer, protected by a light-weight firewall, could establish diversified authenticated communication channels, controlled and accounted by “legal” states of the smart card.The program of a smart card is state-oriented or a state machine, which defines a chain of events involving various state transitions. The “legal” states of a smart card program are defined to be legal to communicate with surfing targets. A predefined Access Control List (ACL), stored in the same card, is necessary. An ACL is a sequential list of permit or deny statements that apply to addresses or upper-layer protocols. The proposed firewall decides acceptance or rejection messages by matching the current state of the card program and the ACL. In addition, a complete surfing account for tracing back is recorded. It is a by-product of the smart card authentication.The proposed Card-Aided Firewall framework is implemented to demonstrate its effectiveness. The implementation is done at the driver level. It keeps up with the high line speed. The driver takes 39K bytes and works well with other firewalls. The average packet processing time of the CAF driver is 31.74 μs. On the premise of secure authentication within the smart card, the Card-Aided Firewall would facilitate various rapidly growing applications in campus cards, family cards, and employee cards, etc. that require accurate controllability and accountability in the surfing boundary.